Notebook 1 of 5: Identification of nPOD Donors and Matching Process

The entire nPOD biobank collection was screened for eligible study donors and then matched in trios, as described in the main text. Each step and the corresponding code is provided below.

Dependencies

Set the file location for created data files.

In [1]:
libname files "/mnt/hgfs/myfolders"
Out[1]:

11   ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
12
13 libname files "/mnt/hgfs/myfolders"
14 ;
NOTE: Libref FILES was successfully assigned as follows:
Engine: V9
Physical Name: /mnt/hgfs/myfolders
14 ! *';*";*/;ods html5 close;ods listing;

15

The following macros were used to perform the 1:1:1 matching. The Pharmacoepidemiology Toolbox was developed by Rassen JA and colleagues, is documented and downloadable here. Running the below code chunk for the first time will create a classpath warning message that can be ignored. Re-running the code will resolve this particular error, but not neccessary for execution of this notebook.

In [2]:
%INCLUDE "macros/java_utils.sas";
%INCLUDE "macros/matching.sas";
%toolbox_Start(%QUOTE (macros/pharmacoepi.jar));

PROC javainfo classpaths;
run;
Out[2]:

17   ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
18
19 %INCLUDE "macros/java_utils.sas";
109 %INCLUDE "macros/matching.sas";
374 %toolbox_Start(%QUOTE (macros/pharmacoepi.jar));
WARNING: Could not initialize classpath. Classpath variable is not set.
NOTE: Invalid argument to function SYSGET('CLASSPATH') at line 374 column 221.
NOTE: Due to SAS limitations, ignore any classpath-related messages from the prior or next statement(s)
path_separator=: orig_classpath= _ERROR_=1 _N_=1
NOTE: DATA statement used (Total process time):
real time 1.04 seconds
cpu time 0.01 seconds

NOTE: Invalid argument to function SYSGET('CLASSPATH') at line 374 column 119.
NOTE: Ignore any messages from the next statement(s)
current_classpath= new_classpath=macros/pharmacoepi.jar _ERROR_=1 _N_=1
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

NOTE: Setting Java classpath to macros/pharmacoepi.jar
375
376 PROC javainfo classpaths;
377 run;
java.class.path = /opt/sasinside/SASHome/SASVersionedJarRepository/eclipse/plugins/sas.launcher.jar
java.ext.dirs = /opt/sasinside/SASHome/SASPrivateJavaRuntimeEnvironment/9.4/jre/lib/ext:/usr/java/packages/lib/ext
java.library.path =
/opt/sasinside/SASHome/SASODBCDriversfortheWebInfrastructurePlatformDataServer/9.4/Driver:/opt/sasinside/SASHome/SASPrivateJavaRunti
meEnvironment/9.4/jre/lib/amd64/server:/opt/sasinside/SASHome/SASPrivateJavaRuntimeEnvironment/9.4/jre/lib/amd64:/opt/sasinside/SASH
ome/SASFoundation/9.4/sasexe:/usr/java/packages/lib/amd64:/usr/lib64:/lib64:/lib:/usr/lib
sas.app.class.path = /opt/sasinside/SASHome/SASVersionedJarRepository/eclipse/plugins/tkjava.jar
sun.boot.class.path =
/opt/sasinside/SASHome/SASPrivateJavaRuntimeEnvironment/9.4/jre/lib/resources.jar:/opt/sasinside/SASHome/SASPrivateJavaRuntimeEnviro
nment/9.4/jre/lib/rt.jar:/opt/sasinside/SASHome/SASPrivateJavaRuntimeEnvironment/9.4/jre/lib/sunrsasign.jar:/opt/sasinside/SASHome/S
ASPrivateJavaRuntimeEnvironment/9.4/jre/lib/jsse.jar:/opt/sasinside/SASHome/SASPrivateJavaRuntimeEnvironment/9.4/jre/lib/jce.jar:/op
t/sasinside/SASHome/SASPrivateJavaRuntimeEnvironment/9.4/jre/lib/charsets.jar:/opt/sasinside/SASHome/SASPrivateJavaRuntimeEnvironmen
t/9.4/jre/lib/jfr.jar:/opt/sasinside/SASHome/SASPrivateJavaRuntimeEnvironment/9.4/jre/classes
sun.boot.library.path = /opt/sasinside/SASHome/SASPrivateJavaRuntimeEnvironment/9.4/jre/lib/amd64

NOTE: PROCEDURE JAVAINFO used (Total process time):
real time 0.01 seconds
cpu time 0.00 seconds

378 ods html5 close;ods listing;

379

Data Import & Coding of Needed Variables

Obtain all nPOD case records with with donor timeline data from nPOD DataShare.

In [3]:
PROC import out = icu datafile = 
            "Donor_TimeLine.xlsx"
     dbms = xlsx replace;
     options validvarname = V7;
run;
Out[3]:

381  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
382
383 PROC import out = icu datafile =
384 "Donor_TimeLine.xlsx"
385 dbms = xlsx replace;
386 options validvarname = V7;
387 run;
NOTE: Variable Name Change. nPOD CaseID -> nPOD_CaseID
NOTE: Variable Name Change. Donor Type -> Donor_Type
NOTE: Variable Name Change. Organ Received Datetime Flag -> Organ_Received_Datetime_Flag
NOTE: Variable Name Change. Organ Frozen Datetime Flag -> Organ_Frozen_Datetime_Flag
NOTE: Variable Name Change. Admit Datetime Flag -> Admit_Datetime_Flag
NOTE: Variable Name Change. Braindeath Datetime Flag -> Braindeath_Datetime_Flag
NOTE: Variable Name Change. Xclamp Datetime Flag -> Xclamp_Datetime_Flag
NOTE: Variable Name Change. Hospitalization Stay Minutes -> Hospitalization_Stay_Minutes
NOTE: Variable Name Change. Transport Duration Minutes -> Transport_Duration_Minutes
NOTE: Variable Name Change. Processing Time Minutes -> Processing_Time_Minutes
NOTE: The import data set has 301 observations and 10 variables.
NOTE: WORK.ICU data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
real time 0.18 seconds
cpu time 0.05 seconds

388
389 ods html5 close;ods listing;

390

Flags represent potential issues with the timeline and are therefore exlcuded from consideration.

In [4]:
DATA icu1 (drop = npod_caseid);
     set icu;
     ptid = npod_caseid * 1;
     if Admit_Datetime_Flag          = 1 then 
        Hospitalization_Stay_Minutes = .;
     if Xclamp_Datetime_Flag         = 1 then 
        Hospitalization_Stay_Minutes = .;
     if Xclamp_Datetime_Flag         = 1 then 
        Transport_Duration_Minutes   = .;
     if Organ_Received_Datetime_Flag = 1 then 
        Transport_Duration_Minutes   = .;
     if Organ_Received_Datetime_Flag = 1 then 
        Processing_Time_Minutes      = .;
     if Organ_Frozen_Datetime_Flag   = 1 then 
        Processing_Time_Minutes      = .;
     Hospitalization_Stay_Days = Hospitalization_Stay_minutes / 1440;
     Processing_Time_Minutes1 = Processing_Time_Minutes * 1;
     transport_duration_hours=Transport_Duration_Minutes / 60;
 run;
Out[4]:

392  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
393
394 DATA icu1 (drop = npod_caseid);
395 set icu;
396 ptid = npod_caseid * 1;
397 if Admit_Datetime_Flag = 1 then
398 Hospitalization_Stay_Minutes = .;
399 if Xclamp_Datetime_Flag = 1 then
400 Hospitalization_Stay_Minutes = .;
401 if Xclamp_Datetime_Flag = 1 then
402 Transport_Duration_Minutes = .;
403 if Organ_Received_Datetime_Flag = 1 then
404 Transport_Duration_Minutes = .;
405 if Organ_Received_Datetime_Flag = 1 then
406 Processing_Time_Minutes = .;
407 if Organ_Frozen_Datetime_Flag = 1 then
408 Processing_Time_Minutes = .;
409 Hospitalization_Stay_Days = Hospitalization_Stay_minutes / 1440;
410 Processing_Time_Minutes1 = Processing_Time_Minutes * 1;
411 transport_duration_hours=Transport_Duration_Minutes / 60;
412 run;
NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column).
396:13 397:9 399:9 401:9 403:9 405:9 407:9
NOTE: Missing values were generated as a result of performing an operation on missing values.
Each place is given by: (Number of times) at (Line):(Column).
43 at 409:63 20 at 410:57 24 at 411:58
NOTE: There were 301 observations read from the data set WORK.ICU.
NOTE: The data set WORK.ICU1 has 301 observations and 13 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

413 ods html5 close;ods listing;

414

Download demographics data from nPOD DataShare. An ERROR message may appear, but safe to ignore.

In [5]:
PROC import datafile = 'demographics.tsv' 
            out      = demographics 
            dbms     = dlm replace;
            delimiter = '09'x;
            getnames  = yes;
            guessingrows = 1000;
run;
quit;
Out[5]:

416  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
417
418 PROC import datafile = 'demographics.tsv'
419 out = demographics
420 dbms = dlm replace;
421 delimiter = '09'x;
422 getnames = yes;
423 guessingrows = 1000;
424 run;
ERROR: Expecting page 1, got page -1 instead.
ERROR: Page validation error while reading SASUSER.PROFILE.CATALOG.
NOTE: Unable to open SASUSER.PROFILE. WORK.PROFILE will be opened instead.
NOTE: All profile changes will be lost at the end of the session.
425 /**********************************************************************
426 * PRODUCT: SAS
427 * VERSION: 9.4
428 * CREATOR: External File Interface
429 * DATE: 11SEP17
430 * DESC: Generated SAS Datastep Code
431 * TEMPLATE SOURCE: (None Specified.)
432 ***********************************************************************/
433 data WORK.DEMOGRAPHICS ;
434 %let _EFIERR_ = 0; /* set the ERROR detection macro variable */
435 infile 'demographics.tsv' delimiter='09'x MISSOVER DSD lrecl=32767 firstobs=2 ;
436 informat DonorType $24. ;
437 informat abo_subtype $3. ;
438 informat ptid best32. ;
439 informat oppc_PancreasWT best32. ;
440 informat oppc_Gender $6. ;
441 informat oppc_Ethnicity $29. ;
442 informat oppc_ABO $3. ;
443 informat multi_organ_donor $3. ;
444 informat non_hrt_beat_donor $7. ;
445 informat oppc_ageR best32. ;
446 informat oppc_heightR best32. ;
447 informat oppc_weightR best32. ;
448 informat oppc_bmiR best32. ;
449 informat cod_final $50. ;
450 informat death_mech_final $30. ;
451 informat replace $4. ;
452 format DonorType $24. ;
453 format abo_subtype $3. ;
454 format ptid best12. ;
455 format oppc_PancreasWT best12. ;
456 format oppc_Gender $6. ;
457 format oppc_Ethnicity $29. ;
458 format oppc_ABO $3. ;
459 format multi_organ_donor $3. ;
460 format non_hrt_beat_donor $7. ;
461 format oppc_ageR best12. ;
462 format oppc_heightR best12. ;
463 format oppc_weightR best12. ;
464 format oppc_bmiR best12. ;
465 format cod_final $50. ;
466 format death_mech_final $30. ;
467 format replace $4. ;
468 input
469 DonorType $
470 abo_subtype $
471 ptid
472 oppc_PancreasWT
473 oppc_Gender $
474 oppc_Ethnicity $
475 oppc_ABO $
476 multi_organ_donor $
477 non_hrt_beat_donor $
478 oppc_ageR
479 oppc_heightR
480 oppc_weightR
481 oppc_bmiR
482 cod_final $
483 death_mech_final $
484 replace $
485 ;
486 if _ERROR_ then call symputx('_EFIERR_',1); /* set ERROR detection macro variable */
487 run;
NOTE: The infile 'demographics.tsv' is:
Filename=/mnt/hgfs/myfolders/demographics.tsv,
Owner Name=root,Group Name=vboxsf,
Access Permission=-rwxrwx---,
Last Modified=22Dec2016:19:49:35,
File Size (bytes)=30668

NOTE: 306 records were read from the infile 'demographics.tsv'.
The minimum record length was 32.
The maximum record length was 136.
NOTE: The data set WORK.DEMOGRAPHICS has 306 observations and 16 variables.
NOTE: DATA statement used (Total process time):
real time 0.03 seconds
cpu time 0.00 seconds

306 rows created in WORK.DEMOGRAPHICS from demographics.tsv.



NOTE: WORK.DEMOGRAPHICS data set was successfully created.
NOTE: The data set WORK.DEMOGRAPHICS has 306 observations and 16 variables.
NOTE: PROCEDURE IMPORT used (Total process time):
real time 0.63 seconds
cpu time 0.20 seconds

488 quit;
489 ods html5 close;ods listing;

490

Join timeline and demographics data tables together

In [6]:
PROC sort data = icu1;
     by ptid;
run;
 
PROC sort data = demographics;
     by ptid;
run;
 
DATA all;
     merge icu1 (in = a) demographics (in = b);
     by ptid;
     if a;
run;
Out[6]:

492  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
493
494 PROC sort data = icu1;
495 by ptid;
496 run;
NOTE: There were 301 observations read from the data set WORK.ICU1.
NOTE: The data set WORK.ICU1 has 301 observations and 13 variables.
NOTE: PROCEDURE SORT used (Total process time):
real time 0.01 seconds
cpu time 0.00 seconds

497
498 PROC sort data = demographics;
499 by ptid;
500 run;
NOTE: There were 306 observations read from the data set WORK.DEMOGRAPHICS.
NOTE: The data set WORK.DEMOGRAPHICS has 306 observations and 16 variables.
NOTE: PROCEDURE SORT used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

501
502 DATA all;
503 merge icu1 (in = a) demographics (in = b);
504 by ptid;
505 if a;
506 run;
NOTE: There were 301 observations read from the data set WORK.ICU1.
NOTE: There were 306 observations read from the data set WORK.DEMOGRAPHICS.
NOTE: The data set WORK.ALL has 301 observations and 28 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.01 seconds

507 ods html5 close;ods listing;

508

Explore hospitalization stay time (in days). It can be seen below that values are normally distributed across all nPOD samples.

In [7]:
PROC univariate data = ALL noprint;
     histogram Hospitalization_Stay_minutes / kernel 
               (k = normal
                c = 0.8
                w = 2.5
                color = green)
     normal (mu = est
             sigma = est
             color = red
             w = 2.5 )
     midpoints = 0 to 40000 by 60;
run;
 
PROC univariate data = ALL noprint;
     histogram Hospitalization_Stay_Days / kernel 
               (k = normal
                c = 0.8
                w = 2.5
                color = green)
     normal (mu = est
             sigma = est
             color = red
             w = 2.5)
     midpoints = 0 to 30 by 1;
run;
Out[7]:
SAS Output

The SAS System

The UNIVARIATE Procedure

Histogram for Hospitalization_Stay_Minutes

The SAS System

The UNIVARIATE Procedure

Fitted Normal Distribution for Hospitalization_Stay_Minutes (Hospitalization Stay Minutes)

Parameters for Normal Distribution
Parameter Symbol Estimate
Mean Mu 6788.519
Std Dev Sigma 5509.989
Goodness-of-Fit Tests for Normal Distribution
Test Statistic p Value
Kolmogorov-Smirnov D 0.1810677 Pr > D <0.010
Cramer-von Mises W-Sq 2.9069783 Pr > W-Sq <0.005
Anderson-Darling A-Sq 16.1773878 Pr > A-Sq <0.005
Quantiles for Normal Distribution
Percent Quantile
Observed Estimated
1.0 686.000 -6029.633
5.0 1788.000 -2274.607
10.0 2450.000 -272.816
25.0 3527.000 3072.088
50.0 5206.500 6788.519
75.0 8440.000 10504.951
90.0 13363.000 13849.855
95.0 16117.000 15851.646
99.0 31266.000 19606.672

The SAS System

The UNIVARIATE Procedure

Histogram for Hospitalization_Stay_Days

The SAS System

The UNIVARIATE Procedure

Fitted Normal Distribution for Hospitalization_Stay_Days

Parameters for Normal Distribution
Parameter Symbol Estimate
Mean Mu 4.71425
Std Dev Sigma 3.826382
Goodness-of-Fit Tests for Normal Distribution
Test Statistic p Value
Kolmogorov-Smirnov D 0.1810677 Pr > D <0.010
Cramer-von Mises W-Sq 2.9069783 Pr > W-Sq <0.005
Anderson-Darling A-Sq 16.1773878 Pr > A-Sq <0.005
Quantiles for Normal Distribution
Percent Quantile
Observed Estimated
1.0 0.47639 -4.18725
5.0 1.24167 -1.57959
10.0 1.70139 -0.18946
25.0 2.44931 2.13339
50.0 3.61563 4.71425
75.0 5.86111 7.29510
90.0 9.27986 9.61795
95.0 11.19236 11.00809
99.0 21.71250 13.61574

Hospitalization stay time (in days) will be binned based on the definition used by In't Veld and colleagues (2010, Diabetes), and consistent with our previous work. Other coding performed to re-format the data.

In [8]:
DATA all1;
     set all;
     hospbin =.;
     if Hospitalization_Stay_Days^ =. and Hospitalization_Stay_Days < 3 then 
        hospbin = 3;
     if Hospitalization_Stay_Days >=3 and Hospitalization_Stay_Days < 6 then 
        hospbin = 6;
     if Hospitalization_Stay_Days >= 6 then 
        hospbin = 9;
     *if Hospitalization_Stay_Days>=9 then hospbin=12;
     if donor_type = "Autoab Pos" then 
        donor = 3;
     if donor_type = "T1D" then 
        donor = 1;
     if donor_type = "T1D Medalist" then 
        donor = 1;
     if donor_type = "T2D" then 
        donor = 2;
     if donor_type = "No diabetes" then
        donor = 0;
     if donor_type = "Gestational diabetes" then
        donor = 99;
     if donor_type = "Pregnancy" then 
        donor = 99;
     if donor_type = "Other" then 
        donor = 99;
     if donor_type = "Pending" then 
        donor = 99;
     if donor_type = "Autoab Pos by screening" then 
        donor = 3;
     if donor_type = "Preclinical T2D" then 
        donor = 99;
     if donor_type = "Cystic fibrosis" then 
        donor = 99;
     if donor_type = "Fulminant" then 
        donor = 99;
     if donor_type = "Transplant" then 
        donor = 99;
     if donor_type = "Virus infected cell line" then 
        donor = 99;
     if donor_type = "MODY" then 
        donor = 99;
     if donor_type = "CMA" then 
        donor = 99;
     if donor_type = "T2D+Incretin" then 
        donor = 2;
     if donor_type = "TMA" then 
        donor = 99;
     if donor_type = "Gastric Bypass" then 
        donor = 99;
     * coding for sex and ethnicity so as to be used for matching;
     sex = .;
     if oppc_gender = "Male" then 
        sex = 1;
     if oppc_gender = "Female" then 
        sex = 2;
     ethnicity = .;
     if oppc_ethnicity = "Caucasian" then 
        ethnicity = 1;
     if oppc_ethnicity = "Hispanic/Latino" then 
        ethnicity = 2;
     if oppc_ethnicity = "African Am" then 
        ethnicity = 3;
     if oppc_ethnicity = "Asian" then 
        ethnicity = 4;
     if oppc_ethnicity = "American Indian/Alaska Native" then 
        ethnicity = 5;
 run;
Out[8]:

540  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
541
542 DATA all1;
543 set all;
544 hospbin =.;
545 if Hospitalization_Stay_Days^ =. and Hospitalization_Stay_Days < 3 then
546 hospbin = 3;
547 if Hospitalization_Stay_Days >=3 and Hospitalization_Stay_Days < 6 then
548 hospbin = 6;
549 if Hospitalization_Stay_Days >= 6 then
550 hospbin = 9;
551 *if Hospitalization_Stay_Days>=9 then hospbin=12;
552 if donor_type = "Autoab Pos" then
553 donor = 3;
554 if donor_type = "T1D" then
555 donor = 1;
556 if donor_type = "T1D Medalist" then
557 donor = 1;
558 if donor_type = "T2D" then
559 donor = 2;
560 if donor_type = "No diabetes" then
561 donor = 0;
562 if donor_type = "Gestational diabetes" then
563 donor = 99;
564 if donor_type = "Pregnancy" then
565 donor = 99;
566 if donor_type = "Other" then
567 donor = 99;
568 if donor_type = "Pending" then
569 donor = 99;
570 if donor_type = "Autoab Pos by screening" then
571 donor = 3;
572 if donor_type = "Preclinical T2D" then
573 donor = 99;
574 if donor_type = "Cystic fibrosis" then
575 donor = 99;
576 if donor_type = "Fulminant" then
577 donor = 99;
578 if donor_type = "Transplant" then
579 donor = 99;
580 if donor_type = "Virus infected cell line" then
581 donor = 99;
582 if donor_type = "MODY" then
583 donor = 99;
584 if donor_type = "CMA" then
585 donor = 99;
586 if donor_type = "T2D+Incretin" then
587 donor = 2;
588 if donor_type = "TMA" then
589 donor = 99;
590 if donor_type = "Gastric Bypass" then
591 donor = 99;
592 * coding for sex and ethnicity so as to be used for matching;
593 sex = .;
594 if oppc_gender = "Male" then
595 sex = 1;
596 if oppc_gender = "Female" then
597 sex = 2;
598 ethnicity = .;
599 if oppc_ethnicity = "Caucasian" then
600 ethnicity = 1;
601 if oppc_ethnicity = "Hispanic/Latino" then
602 ethnicity = 2;
603 if oppc_ethnicity = "African Am" then
604 ethnicity = 3;
605 if oppc_ethnicity = "Asian" then
606 ethnicity = 4;
607 if oppc_ethnicity = "American Indian/Alaska Native" then
608 ethnicity = 5;
609 run;
NOTE: There were 301 observations read from the data set WORK.ALL.
NOTE: The data set WORK.ALL1 has 301 observations and 32 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

610 ods html5 close;ods listing;

611

Case Exclusion

Limiting donors to only nPOD cases, i.e. excluding donors from other collections stored at nPOD. Calculated age for donor with pre-term births.

In [9]:
DATA all1;
     set all1;
     if ptid < 6000 then 
        delete;
     if ptid > 6999 then 
        delete;
    *for those donors born pre-term, age was based on numbe of lived days after birth (i.e. number of days after gestational age);
    if ptid = 6120 then 
       oppc_ageR = 1 / 365;
    if ptid = 6164 then 
       oppc_ageR = 13.75 / 365;
    if ptid = 6192 then 
       oppc_ageR = 1 / 365;
    if ptid = 6200 then 
       oppc_ageR = 2.4 / 365;
    if ptid = 6201 then 
       oppc_ageR = 1 / 365;
    if ptid = 6210 then 
       oppc_ageR = 5.48 / 365;
    if ptid = 6214 then 
       oppc_ageR = 5.95 / 365;
run;
Out[9]:

613  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
614
615 DATA all1;
616 set all1;
617 if ptid < 6000 then
618 delete;
619 if ptid > 6999 then
620 delete;
621 *for those donors born pre-term, age was based on numbe of lived days after birth (i.e. number of days after gestational
621! age);
622 if ptid = 6120 then
623 oppc_ageR = 1 / 365;
624 if ptid = 6164 then
625 oppc_ageR = 13.75 / 365;
626 if ptid = 6192 then
627 oppc_ageR = 1 / 365;
628 if ptid = 6200 then
629 oppc_ageR = 2.4 / 365;
630 if ptid = 6201 then
631 oppc_ageR = 1 / 365;
632 if ptid = 6210 then
633 oppc_ageR = 5.48 / 365;
634 if ptid = 6214 then
635 oppc_ageR = 5.95 / 365;
636 run;
NOTE: There were 301 observations read from the data set WORK.ALL1.
NOTE: The data set WORK.ALL1 has 293 observations and 32 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

637 ods html5 close;ods listing;

638

Further limiting donors to only control cases.

In [10]:
DATA all2;
     set all1;
     * only looking at controls;
     if donor^ = 0 then 
        delete; 
     if hospbin = . then 
        delete;
     if (Organ_Received_Datetime_Flag^ = 0 and 
         Organ_Frozen_Datetime_Flag ^= 0   and
         Admit_Datetime_Flag^ = 0          and 
         Braindeath_Datetime_Flag^ = 0     and
         clamp_Datetime_Flag^ = 0) then 
         delete;
run;
Out[10]:

640  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
641
642 DATA all2;
643 set all1;
644 * only looking at controls;
645 if donor^ = 0 then
646 delete;
647 if hospbin = . then
648 delete;
649 if (Organ_Received_Datetime_Flag^ = 0 and
650 Organ_Frozen_Datetime_Flag ^= 0 and
651 Admit_Datetime_Flag^ = 0 and
652 Braindeath_Datetime_Flag^ = 0 and
653 clamp_Datetime_Flag^ = 0) then
654 delete;
655 run;
NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column).
649:10 650:10 651:10 652:10
NOTE: Variable clamp_Datetime_Flag is uninitialized.
NOTE: There were 293 observations read from the data set WORK.ALL1.
NOTE: The data set WORK.ALL2 has 96 observations and 33 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

656 ods html5 close;ods listing;

657

Preparation for Donor Matching

For all donors, estimate 3-group propensity score using polytomous logistic regression

In [11]:
PROC logistic data = all2 
     order = data DESCENDING;
     class hospbin sex ethnicity;
     model hospbin(ref="3") = oppc_ager sex oppc_bmiR ethnicity /LINK=glogit;
     output out  = input_3way_cohort_long(KEEP = ptid hospbin prob) PRED = prob;
run;
quit
Out[11]:
SAS Output

The SAS System

The LOGISTIC Procedure

Model Information
Data Set WORK.ALL2
Response Variable hospbin
Number of Response Levels 3
Model generalized logit
Optimization Technique Newton-Raphson
Number of Observations Read 96
Number of Observations Used 92
Response Profile
Ordered
Value
hospbin Total
Frequency
1 6 32
2 9 26
3 3 34

Logits modeled use hospbin=3 as the reference category.

Note:4 observations were deleted due to missing values for the response or explanatory variables.

Class Level Information
Class Value Design Variables
sex 1 1    
  2 -1    
ethnicity 1 1 0 0
  2 0 1 0
  3 0 0 1
  5 -1 -1 -1
Model Convergence Status
Quasi-complete separation of data points detected.

Model Fit Statistics
Criterion Intercept Only Intercept and Covariates
AIC 204.988 218.123
SC 210.032 253.428
-2 Log L 200.988 190.123
Testing Global Null Hypothesis: BETA=0
Test Chi-Square DF Pr > ChiSq
Likelihood Ratio 10.8653 12 0.5405
Score 10.0906 12 0.6080
Wald 7.6438 12 0.8123
Type 3 Analysis of Effects
Effect DF Wald
Chi-Square
Pr > ChiSq
oppc_ageR 2 0.6342 0.7283
sex 2 0.3810 0.8266
oppc_bmiR 2 4.0468 0.1322
ethnicity 6 1.7377 0.9422
Analysis of Maximum Likelihood Estimates
Parameter   hospbin DF Estimate Standard
Error
Wald
Chi-Square
Pr > ChiSq
Intercept   6 1 5.1878 164.2 0.0010 0.9748
Intercept   9 1 -0.0921 249.4 0.0000 0.9997
oppc_ageR   6 1 -0.00121 0.0162 0.0056 0.9404
oppc_ageR   9 1 -0.0121 0.0160 0.5785 0.4469
sex 1 6 1 0.1383 0.2823 0.2401 0.6242
sex 1 9 1 -0.0366 0.2766 0.0175 0.8947
oppc_bmiR   6 1 -0.0988 0.0538 3.3704 0.0664
oppc_bmiR   9 1 0.00400 0.0464 0.0074 0.9313
ethnicity 1 6 1 -2.9156 164.2 0.0003 0.9858
ethnicity 1 9 1 0.0200 249.4 0.0000 0.9999
ethnicity 2 6 1 -3.8612 164.2 0.0006 0.9812
ethnicity 2 9 1 0.2798 249.4 0.0000 0.9991
ethnicity 3 6 1 -2.9303 164.2 0.0003 0.9858
ethnicity 3 9 1 -0.0951 249.4 0.0000 0.9997
Odds Ratio Estimates
Effect hospbin Point Estimate 95% Wald
Confidence Limits
oppc_ageR 6 0.999 0.968 1.031
oppc_ageR 9 0.988 0.958 1.019
sex 1 vs 2 6 1.319 0.436 3.988
sex 1 vs 2 9 0.929 0.314 2.749
oppc_bmiR 6 0.906 0.815 1.007
oppc_bmiR 9 1.004 0.917 1.100
ethnicity 1 vs 5 6 <0.001 <0.001 >999.999
ethnicity 1 vs 5 9 1.252 <0.001 >999.999
ethnicity 2 vs 5 6 <0.001 <0.001 >999.999
ethnicity 2 vs 5 9 1.623 <0.001 >999.999
ethnicity 3 vs 5 6 <0.001 <0.001 >999.999
ethnicity 3 vs 5 9 1.116 <0.001 >999.999

If propensity score not generated for a donor (because of unavailable/missing data), then delete case. Calculate logit of propensity score.

In [12]:
DATA input_3way_cohort_long;
     set input_3way_cohort_long;
     if prob = . then
        delete;
     logitpr = log(prob / (1 - prob));
     drop prob ;
     rename logitpr = prob;
run;
Out[12]:

671  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
672
673 DATA input_3way_cohort_long;
674 set input_3way_cohort_long;
675 if prob = . then
676 delete;
677 logitpr = log(prob / (1 - prob));
678 drop prob ;
679 rename logitpr = prob;
680 run;
NOTE: There were 288 observations read from the data set WORK.INPUT_3WAY_COHORT_LONG.
NOTE: The data set WORK.INPUT_3WAY_COHORT_LONG has 276 observations and 3 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

681 ods html5 close;ods listing;

682

SD of logit is 1.4180436, .2 of that is .2836087, but that caliper width is recommended for 1:1 matching. No studies have been done on optimal caliper width for 1:1:1 matching. We therefore conservatively doubled the 1:1 caliper width allowing .5672174; authors of the Pharmacoepidemiology Toolbox recommend 3 times the 1:1.

In [13]:
PROC means data = input_3way_cohort_long 
     n 
     mean 
     std;
     var prob;
run;
Out[13]:
SAS Output

The SAS System

The MEANS Procedure

Analysis Variable : prob
N Mean Std Dev
276 -0.7793156 1.4180436

Need to transform the data from one row per donor per level to one row per donor with one variable per level.

In [14]:
PROC transpose data = input_3way_cohort_long OUT = input_3way_cohort
     prefix = prob;
     by ptid hospbin;
run;
 
data input_3way_cohort (drop=_name_);
     set input_3way_cohort;
     ptid1 = put(ptid, 7.);
     drop ptid ;
     rename ptid1 = ptid;
run;
Out[14]:

695  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
696
697 PROC transpose data = input_3way_cohort_long OUT = input_3way_cohort
698 prefix = prob;
699 by ptid hospbin;
700 run;
NOTE: There were 276 observations read from the data set WORK.INPUT_3WAY_COHORT_LONG.
NOTE: The data set WORK.INPUT_3WAY_COHORT has 92 observations and 6 variables.
NOTE: PROCEDURE TRANSPOSE used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds

701
702 data input_3way_cohort (drop=_name_);
703 set input_3way_cohort;
704 ptid1 = put(ptid, 7.);
705 drop ptid ;
706 rename ptid1 = ptid;
707 run;
NOTE: There were 92 observations read from the data set WORK.INPUT_3WAY_COHORT.
NOTE: The data set WORK.INPUT_3WAY_COHORT has 92 observations and 5 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

708 ods html5 close;ods listing;

709

A priori to running the matching macros, case 6210 was identified as having some sample quality issues for this experiment, therefore is being removed as a candidate.

In [15]:
DATA input_3way_cohort1;
     set input_3way_cohort;
     if ptid = 6210 then 
        delete;
run;
Out[15]:

711  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
712
713 DATA input_3way_cohort1;
714 set input_3way_cohort;
715 if ptid = 6210 then
716 delete;
717 run;
NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column).
715:9
NOTE: There were 92 observations read from the data set WORK.INPUT_3WAY_COHORT.
NOTE: The data set WORK.INPUT_3WAY_COHORT1 has 91 observations and 5 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

718 ods html5 close;ods listing;

719

Macro Matching

Use of the matching macro needs the location of the path to a temp directory. This temp directory changes file path from one session to another. The %LET statement stores the session path, and it is then used below when running the macro. If problems arise, an alternative solution is to run %put %sysfunc(getoption(work)); then copy the file path and paste it after the %QUOTE in the macro below (in particular, you need all the numbers and letters that appear after SAS_work).

In [19]:
* Run 1:1:1 nearest neighbor match;

%match_NearestNeighborMatch    (input_3way_cohort1,
                             output_3way_cohort,
                             %QUOTE(&file_path),
                             var_patient_id = ptid,
                             var_exposure   = hospbin,
                             var_ps         = prob1 prob2 prob3,
                             exp_groups     = 3 6 9,
                             caliper        = .5672174,
                             ratio          = 1);
 
DATA match_import1 (keep = pat_id ptid SET_NUM);
     set match_import;
     ptid = pat_id * 1;
run;
 
DATA match_import1 (keep = ptid set_num);
     set match_import1;
run;
 
PROC sort data = match_import1;
     by ptid;
run;
 
PROC sort data = all2;
     by ptid;
run;
 
DATA study;
     merge match_import1 (in = a) all2 (in = b);
     by ptid;
     if a;
run;
 
PROC freq data = study;
     tables hospbin;
run;
Out[19]:
SAS Output

The SAS System

The FREQ Procedure

hospbin Frequency Percent Cumulative
Frequency
Cumulative
Percent
3 15 33.33 15 33.33
6 15 33.33 30 66.67
9 15 33.33 45 100.00

Verification of Results

Need to determine if there are any differences in age, sex, BMI, and ethnicity between the three groups, as these variables were used for matching. Here, distribution of variables is examined.

In [20]:
PROC univariate data = study;
     var oppc_ager 
     oppc_bmir 
     Transport_Duration_Minutes 
     Processing_Time_Minutes1;
run;
 
PROC univariate data = study noprint;
     histogram Transport_Duration_Minutes / kernel 
               (k     = normal
                c     = 0.8 
                w     = 2.5 
                color = green)
     normal (mu    = est 
             sigma = est 
             color = red 
             w     = 2.5 )
     midpoints = 0 to 2880 by 60; 
run;
 
PROC univariate data = study noprint;
     histogram Processing_Time_Minutes1 / kernel 
               (k     = normal
                c     = 0.8 
                w     = 2.5 
                color = green)
     normal (mu    = est 
             sigma = est 
             color = red 
             w     = 2.5)
     midpoints = 0 to 400 by 5;
run;
Out[20]:
SAS Output

The SAS System

The UNIVARIATE Procedure

Variable: oppc_ageR

Moments
N 45 Sum Weights 45
Mean 24.1774795 Sum Observations 1087.98658
Std Deviation 16.3125239 Variance 266.098436
Skewness 0.5133685 Kurtosis 0.23193307
Uncorrected SS 38013.1042 Corrected SS 11708.3312
Coeff Variation 67.4699111 Std Error Mean 2.43172749
Basic Statistical Measures
Location Variability
Mean 24.17748 Std Deviation 16.31252
Median 22.70000 Variance 266.09844
Mode 0.33000 Range 71.99342
    Interquartile Range 24.00000

Note: The mode displayed is the smallest of 6 modes with a count of 2.

Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 9.942512 Pr > |t| <.0001
Sign M 22.5 Pr >= |M| <.0001
Signed Rank S 517.5 Pr >= |S| <.0001
Quantiles (Definition 5)
Level Quantile
100% Max 72.00000000
99% 72.00000000
95% 50.00000000
90% 45.80000000
75% Q3 38.00000000
50% Median 22.70000000
25% Q1 14.00000000
10% 0.50000000
5% 0.33000000
1% 0.00657534
0% Min 0.00657534
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.00657534 35 45.8 28
0.33000000 34 46.0 6
0.33000000 20 50.0 5
0.42000000 19 51.0 29
0.50000000 36 72.0 9

The SAS System

The UNIVARIATE Procedure

Variable: oppc_bmiR

Moments
N 45 Sum Weights 45
Mean 24.06 Sum Observations 1082.7
Std Deviation 5.45316422 Variance 29.737
Skewness 0.26293153 Kurtosis -0.796331
Uncorrected SS 27358.19 Corrected SS 1308.428
Coeff Variation 22.6648554 Std Error Mean 0.81290973
Basic Statistical Measures
Location Variability
Mean 24.06000 Std Deviation 5.45316
Median 24.20000 Variance 29.73700
Mode 17.10000 Range 21.50000
    Interquartile Range 7.90000

Note: The mode displayed is the smallest of 2 modes with a count of 2.

Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 29.59738 Pr > |t| <.0001
Sign M 22.5 Pr >= |M| <.0001
Signed Rank S 517.5 Pr >= |S| <.0001
Quantiles (Definition 5)
Level Quantile
100% Max 36.0
99% 36.0
95% 32.7
90% 32.2
75% Q3 27.9
50% Median 24.2
25% Q1 20.0
10% 17.1
5% 16.3
1% 14.5
0% Min 14.5
Extreme Observations
Lowest Highest
Value Obs Value Obs
14.5 35 32.2 7
15.7 3 32.4 30
16.3 26 32.7 13
17.0 36 34.0 45
17.1 34 36.0 14

The SAS System

The UNIVARIATE Procedure

Variable: Transport_Duration_Minutes (Transport Duration Minutes)

Moments
N 45 Sum Weights 45
Mean 808.377778 Sum Observations 36377
Std Deviation 493.579195 Variance 243620.422
Skewness 1.09542492 Kurtosis 3.65355162
Uncorrected SS 40125657 Corrected SS 10719298.6
Coeff Variation 61.0579866 Std Error Mean 73.5784422
Basic Statistical Measures
Location Variability
Mean 808.3778 Std Deviation 493.57920
Median 835.0000 Variance 243620
Mode 835.0000 Range 2656
    Interquartile Range 728.00000

Note: The mode displayed is the smallest of 2 modes with a count of 2.

Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 10.98661 Pr > |t| <.0001
Sign M 22.5 Pr >= |M| <.0001
Signed Rank S 517.5 Pr >= |S| <.0001
Quantiles (Definition 5)
Level Quantile
100% Max 2715
99% 2715
95% 1464
90% 1248
75% Q3 1124
50% Median 835
25% Q1 396
10% 178
5% 105
1% 59
0% Min 59
Extreme Observations
Lowest Highest
Value Obs Value Obs
59 6 1248 43
84 2 1456 35
105 1 1464 33
112 5 1496 3
178 9 2715 45

The SAS System

The UNIVARIATE Procedure

Variable: Processing_Time_Minutes1

Moments
N 42 Sum Weights 42
Mean 94.2619048 Sum Observations 3959
Std Deviation 68.911417 Variance 4748.78339
Skewness 1.55090872 Kurtosis 3.03309837
Uncorrected SS 567883 Corrected SS 194700.119
Coeff Variation 73.1063277 Std Error Mean 10.6332625
Basic Statistical Measures
Location Variability
Mean 94.26190 Std Deviation 68.91142
Median 77.50000 Variance 4749
Mode 30.00000 Range 325.00000
    Interquartile Range 78.00000
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 8.864815 Pr > |t| <.0001
Sign M 21 Pr >= |M| <.0001
Signed Rank S 451.5 Pr >= |S| <.0001
Quantiles (Definition 5)
Level Quantile
100% Max 340.0
99% 340.0
95% 215.0
90% 195.0
75% Q3 120.0
50% Median 77.5
25% Q1 42.0
10% 30.0
5% 25.0
1% 15.0
0% Min 15.0
Extreme Observations
Lowest Highest
Value Obs Value Obs
15 9 195 25
20 4 200 29
25 41 215 13
30 35 255 12
30 10 340 21
Missing Values
Missing
Value
Count Percent Of
All Obs Missing Obs
. 3 6.67 100.00

The SAS System

The UNIVARIATE Procedure

Histogram for Transport_Duration_Minutes

The SAS System

The UNIVARIATE Procedure

Fitted Normal Distribution for Transport_Duration_Minutes (Transport Duration Minutes)

Parameters for Normal Distribution
Parameter Symbol Estimate
Mean Mu 808.3778
Std Dev Sigma 493.5792
Goodness-of-Fit Tests for Normal Distribution
Test Statistic p Value
Kolmogorov-Smirnov D 0.10088584 Pr > D >0.150
Cramer-von Mises W-Sq 0.07117205 Pr > W-Sq >0.250
Anderson-Darling A-Sq 0.64243467 Pr > A-Sq 0.091
Quantiles for Normal Distribution
Percent Quantile
Observed Estimated
1.0 59.0000 -339.85913
5.0 105.0000 -3.48775
10.0 178.0000 175.83059
25.0 396.0000 475.46367
50.0 835.0000 808.37778
75.0 1124.0000 1141.29189
90.0 1248.0000 1440.92497
95.0 1464.0000 1620.24331
99.0 2715.0000 1956.61469

The SAS System

The UNIVARIATE Procedure

Histogram for Processing_Time_Minutes1

The SAS System

The UNIVARIATE Procedure

Fitted Normal Distribution for Processing_Time_Minutes1

Parameters for Normal Distribution
Parameter Symbol Estimate
Mean Mu 94.2619
Std Dev Sigma 68.91142
Goodness-of-Fit Tests for Normal Distribution
Test Statistic p Value
Kolmogorov-Smirnov D 0.12503077 Pr > D 0.096
Cramer-von Mises W-Sq 0.22008976 Pr > W-Sq <0.005
Anderson-Darling A-Sq 1.48109231 Pr > A-Sq <0.005
Quantiles for Normal Distribution
Percent Quantile
Observed Estimated
1.0 15.0000 -66.05002
5.0 25.0000 -19.08729
10.0 30.0000 5.94837
25.0 42.0000 47.78186
50.0 77.5000 94.26190
75.0 120.0000 140.74195
90.0 195.0000 182.57544
95.0 215.0000 207.61110
99.0 340.0000 254.57383

After matching completed, list of donors was reviewed. It was determined that tissue was not available for 6001 and 6021, so all blocks that contain these samples were removed from consideration of this experiment and matching verification proceeded.

In [21]:
DATA study1;
     set study;
     if set_num = 2  then 
        delete;
     if set_num = 12 then 
        delete;
run;

DATA grouping_list (keep = case match_group oppc_ageR);
     set study1;
     rename ptid=case;
     rename set_num=match_group;
run;
Out[21]:

1108  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
1109
1110 DATA study1;
1111 set study;
1112 if set_num = 2 then
1113 delete;
1114 if set_num = 12 then
1115 delete;
1116 run;
NOTE: There were 45 observations read from the data set WORK.STUDY.
NOTE: The data set WORK.STUDY1 has 39 observations and 34 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

1117
1118 DATA grouping_list (keep = case match_group oppc_ageR);
1119 set study1;
1120 rename ptid=case;
1121 rename set_num=match_group;
1122 run;
NOTE: There were 39 observations read from the data set WORK.STUDY1.
NOTE: The data set WORK.GROUPING_LIST has 39 observations and 3 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

1123 ods html5 close;ods listing;

1124

continuous parametric: ANOVA for multi-group comparisons

In [22]:
%macro anova (X); 
PROC anova data = study1;
     class hospbin;
     model &X = hospbin;
run;

%mend anova;
%anova (oppc_ageR); 
run;
%anova (oppc_bmiR); 
run;
*transport duration was not formally matched, but checked anyway;
%anova (Transport_Duration_Minutes); 
run;
Out[22]:
SAS Output

The SAS System

The ANOVA Procedure

Class Level Information
Class Levels Values
hospbin 3 3 6 9
Number of Observations Read 39
Number of Observations Used 39

The SAS System

The ANOVA Procedure

Dependent Variable: oppc_ageR

Source DF Sum of Squares Mean Square F Value Pr > F
Model 2 90.855584 45.427792 0.20 0.8180
Error 36 8094.286253 224.841285    
Corrected Total 38 8185.141836      
R-Square Coeff Var Root MSE oppc_ageR Mean
0.011100 66.91105 14.99471 22.40991
Source DF Anova SS Mean Square F Value Pr > F
hospbin 2 90.85558353 45.42779177 0.20 0.8180
Distribution of oppc_ageR by hospbin

The SAS System

The ANOVA Procedure

Class Level Information
Class Levels Values
hospbin 3 3 6 9
Number of Observations Read 39
Number of Observations Used 39

The SAS System

The ANOVA Procedure

Dependent Variable: oppc_bmiR

Source DF Sum of Squares Mean Square F Value Pr > F
Model 2 1.626667 0.813333 0.02 0.9760
Error 36 1202.049231 33.390256    
Corrected Total 38 1203.675897      
R-Square Coeff Var Root MSE oppc_bmiR Mean
0.001351 24.02033 5.778430 24.05641
Source DF Anova SS Mean Square F Value Pr > F
hospbin 2 1.62666667 0.81333333 0.02 0.9760
Distribution of oppc_bmiR by hospbin

The SAS System

The ANOVA Procedure

Class Level Information
Class Levels Values
hospbin 3 3 6 9
Number of Observations Read 39
Number of Observations Used 39

The SAS System

The ANOVA Procedure

Dependent Variable: Transport_Duration_Minutes Transport Duration Minutes

Source DF Sum of Squares Mean Square F Value Pr > F
Model 2 688024.667 344012.333 1.45 0.2491
Error 36 8569701.231 238047.256    
Corrected Total 38 9257725.897      
R-Square Coeff Var Root MSE Transport_Duration_Minutes Mean
0.074319 57.99492 487.9009 841.2821
Source DF Anova SS Mean Square F Value Pr > F
hospbin 2 688024.6667 344012.3333 1.45 0.2491
Distribution of Transport_Duration_Minutes by hospbin

continuous non-parametric: wilcoxon rank sum

In [23]:
%macro npar1way (X);
PROC npar1way data = study1 wilcoxon;
     class hospbin;
     var &X;
     title "wilcoxon rank sum for &X on group1";
     %mend npar1way;
     *processing time was not formally matched, but checked anyway;
     %npar1way (Processing_Time_Minutes1);
run;
Out[23]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The NPAR1WAY Procedure

Wilcoxon Scores (Rank Sums) for Variable Processing_Time_Minutes1
Classified by Variable hospbin
hospbin N Sum of
Scores
Expected
Under H0
Std Dev
Under H0
Mean
Score
Average scores were used for ties.
3 12 191.0 228.0 30.754403 15.916667
9 13 254.0 247.0 31.363461 19.538462
6 12 258.0 228.0 30.754403 21.500000
Kruskal-Wallis Test
Chi-Square 1.6532
DF 2
Pr > Chi-Square 0.4375
Box Plot of Wilcoxon Scores for Processing_Time_Minutes1 Classified by hospbin

p-values were calculated for both 2- and multi-class categorical nominal data. Fisher's exact test was used when values from 1 or more cells in a contingency table (2 x 2 or R x C) were less than 5. Pearson's chi square was used where values in all cells exceeded 5. If values from 2 or more cells in any table were equal to 0, p-values were not generated.

In [24]:
%macro freq (X);
PROC freq data = study1;
     tables &X * hospbin / measures chisq;
     %mend freq;
run;
 
%macro freq1 (X);
PROC freq data = study1;
     tables &X * hospbin / measures fisher;
     %mend freq1;
     %freq1(ethnicity); run;
     %freq1 (sex);
run;
Out[24]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

Frequency
Percent
Row Pct
Col Pct
Table of ethnicity by hospbin
ethnicity hospbin
3 6 9 Total
1
10
25.64
31.25
76.92
12
30.77
37.50
92.31
10
25.64
31.25
76.92
32
82.05
 
 
2
1
2.56
33.33
7.69
1
2.56
33.33
7.69
1
2.56
33.33
7.69
3
7.69
 
 
3
2
5.13
50.00
15.38
0
0.00
0.00
0.00
2
5.13
50.00
15.38
4
10.26
 
 
Total
13
33.33
13
33.33
13
33.33
39
100.00

Statistics for Table of ethnicity by hospbin

Statistic DF Value Prob
WARNING: 67% of the cells have expected counts less
than 5. Chi-Square may not be a valid test.
Chi-Square 4 2.2500 0.6899
Likelihood Ratio Chi-Square 4 3.4890 0.4796
Mantel-Haenszel Chi-Square 1 0.0000 1.0000
Phi Coefficient   0.2402  
Contingency Coefficient   0.2335  
Cramer's V   0.1698  
Fisher's Exact Test
Table Probability (P) 0.0178
Pr <= P 0.7673
Statistic Value ASE
Gamma 0.0000 0.3657
Kendall's Tau-b 0.0000 0.1692
Stuart's Tau-c 0.0000 0.1154
Somers' D C|R 0.0000 0.2479
Somers' D R|C 0.0000 0.1154
Pearson Correlation -0.0000 0.1868
Spearman Correlation 0.0000 0.1820
Lambda Asymmetric C|R 0.0769 0.1733
Lambda Asymmetric R|C 0.0000 0.0000
Lambda Symmetric 0.0606 0.1379
Uncertainty Coefficient C|R 0.0407 0.0213
Uncertainty Coefficient R|C 0.0754 0.0330
Uncertainty Coefficient Symmetric 0.0529 0.0255

Sample Size = 39


wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

Frequency
Percent
Row Pct
Col Pct
Table of sex by hospbin
sex hospbin
3 6 9 Total
1
10
25.64
40.00
76.92
9
23.08
36.00
69.23
6
15.38
24.00
46.15
25
64.10
 
 
2
3
7.69
21.43
23.08
4
10.26
28.57
30.77
7
17.95
50.00
53.85
14
35.90
 
 
Total
13
33.33
13
33.33
13
33.33
39
100.00

Statistics for Table of sex by hospbin

Statistic DF Value Prob
WARNING: 50% of the cells have expected counts less
than 5. Chi-Square may not be a valid test.
Chi-Square 2 2.8971 0.2349
Likelihood Ratio Chi-Square 2 2.8820 0.2367
Mantel-Haenszel Chi-Square 1 2.6057 0.1065
Phi Coefficient   0.2726  
Contingency Coefficient   0.2630  
Cramer's V   0.2726  
Fisher's Exact Test
Table Probability (P) 0.0233
Pr <= P 0.3388
Statistic Value ASE
Gamma 0.4298 0.2348
Kendall's Tau-b 0.2469 0.1450
Stuart's Tau-c 0.2735 0.1622
Somers' D C|R 0.2971 0.1740
Somers' D R|C 0.2051 0.1217
Pearson Correlation 0.2619 0.1536
Spearman Correlation 0.2619 0.1538
Lambda Asymmetric C|R 0.1538 0.1119
Lambda Asymmetric R|C 0.0714 0.2482
Lambda Symmetric 0.1250 0.1441
Uncertainty Coefficient C|R 0.0336 0.0391
Uncertainty Coefficient R|C 0.0566 0.0657
Uncertainty Coefficient Symmetric 0.0422 0.0490

Sample Size = 39

Additional Grouping

An additional factor is created to specifically test whether differences in the analysis are seen based on age. Groupings based on papers by Gregg et al, J Clin Endocrinol Metab, 2012 (examines Ki67/insulin staining by age groups) and Cole TJ, 2009, Adv Exp Med Biol, 639:1-13 (examines organ development by age).

In [25]:
DATA study1;
    set study1;
    if oppc_ageR<1 then age_group=1;                     /*developmental and neonates*/
    if oppc_ageR>=1 and oppc_ageR<12 then age_group=1;   /*child*/
    if oppc_ageR>=12 and oppc_ageR<20 then age_group=2;  /*adolescent*/
    if oppc_ageR>=20 then age_group=3;                   /*adult*/
run;

PROC sort data=study1;
     by hospbin;
run;

PROC freq data=study1;
     tables age_group;
run;

PROC freq data=study1;
     tables age_group;
     by hospbin;
run;

proc print data=study1;
run;
Out[25]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

age_group Frequency Percent Cumulative
Frequency
Cumulative
Percent
1 11 28.21 11 28.21
2 5 12.82 16 41.03
3 23 58.97 39 100.00

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

age_group Frequency Percent Cumulative
Frequency
Cumulative
Percent
1 3 23.08 3 23.08
2 2 15.38 5 38.46
3 8 61.54 13 100.00

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

age_group Frequency Percent Cumulative
Frequency
Cumulative
Percent
1 4 30.77 4 30.77
2 2 15.38 6 46.15
3 7 53.85 13 100.00

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

age_group Frequency Percent Cumulative
Frequency
Cumulative
Percent
1 4 30.77 4 30.77
2 1 7.69 5 38.46
3 8 61.54 13 100.00

wilcoxon rank sum for Processing_Time_Minutes1 on group1

Obs set_num ptid Donor_Type Organ_Received_Datetime_Flag Organ_Frozen_Datetime_Flag Admit_Datetime_Flag Braindeath_Datetime_Flag Xclamp_Datetime_Flag Hospitalization_Stay_Minutes Transport_Duration_Minutes Processing_Time_Minutes Hospitalization_Stay_Days Processing_Time_Minutes1 transport_duration_hours DonorType abo_subtype oppc_PancreasWT oppc_Gender oppc_Ethnicity oppc_ABO multi_organ_donor non_hrt_beat_donor oppc_ageR oppc_heightR oppc_weightR oppc_bmiR cod_final death_mech_final replace hospbin donor sex ethnicity clamp_Datetime_Flag age_group
1 6 6003 No diabetes 0 0 0 0 0 3994 84 30 2.7736 30 1.4000 No diabetes O . Female Caucasian O+ Yes No 23 160 75 29.3 HEAD TRAUMA blunt injury TRUE 3 0 2 1 . 3
2 11 6048 No diabetes 0 0 0 0 0 1927 368 55 1.3382 55 6.1333 No diabetes O 139 Male Caucasian O- Yes No 30 165.1 56 20.6 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 3 0 1 1 . 3
3 14 6073 No diabetes 0 0 0 0 0 3560 754 50 2.4722 50 12.5667 No diabetes O 66.5 Male Caucasian O+ Yes No 19.2 165.1 98 36 ANOXIA cardiovascular TRUE 3 0 1 1 . 2
4 8 6099 No diabetes 0 1 0 0 0 2945 890 . 2.0451 . 14.8333 No diabetes A2B 85.56 Male Caucasian AB+ Yes No 14.2 175.3 92 30 HEAD TRAUMA blunt injury TRUE 3 0 1 1 . 2
5 1 6106 No diabetes 0 0 0 0 0 4164 1131 45 2.8917 45 18.8500 No diabetes A1 16.32 Male Caucasian A+ Yes No 2.9 94 16 18.1 ANOXIA drowning TRUE 3 0 1 1 . 1
6 4 6131 No diabetes 0 0 0 0 0 2743 1127 120 1.9049 120 18.7833 No diabetes B 108.92 Male Caucasian B+ Yes Yes 24.2 182.9 83 24.8 ANOXIA drug intoxication TRUE 3 0 1 1 . 3
7 13 6134 No diabetes 0 0 0 0 0 2905 1010 75 2.0174 75 16.8333 No diabetes O 82.42 Male Caucasian O+ Yes No 26.7 180.3 65 20.1 ANOXIA drug intoxication TRUE 3 0 1 1 . 3
8 9 6162 No diabetes 0 0 0 0 0 2193 1203 115 1.5229 115 20.0500 No diabetes B 81.5 Male African Am B+ Yes No 22.7 188 102 28.9 HEAD TRAUMA gunshot wound TRUE 3 0 1 3 . 3
9 3 6174 No diabetes 0 0 0 0 0 1181 604 135 0.8201 135 10.0667 No diabetes O 79.3 Male Caucasian O+ Yes No 20.8 196 75 19.5 CEREBROVASCULAR/STROKE blunt injury TRUE 3 0 1 1 . 3
10 15 6200 No diabetes 0 0 0 0 0 3449 1456 30 2.3951 30 24.2667 No diabetes   4.29 Female Hispanic/Latino O+ No Unknown 0.0065753425 41 2.2 14.5 Pulmonary hypoplasia respiratory TRUE 3 0 2 2 . 1
11 7 6235 No diabetes 0 0 0 0 0 3690 1020 120 2.5625 120 17.0000 No diabetes O 102.31 Male Caucasian O+ Yes No 30 172.7 76 25.4 HEAD TRAUMA gunshot wound TRUE 3 0 1 1 . 3
12 5 6250 No diabetes 0 0 0 0 0 2732 1081 25 1.8972 25 18.0167 No diabetes O . Male Caucasian O+ Yes No 40 180.3 90.7 27.9 HEAD TRAUMA blunt injury TRUE 3 0 1 1 . 3
13 10 6278 No diabetes 0 0 0 0 0 2653 895 87 1.8424 87 14.9167 No diabetes   33.6 Female African Am A No Unknown 10 157.5 52.4 21.3 ANOXIA cardiovascular TRUE 3 0 2 3 . 1
14 10 6047 No diabetes 0 0 0 0 0 4851 737 30 3.3688 30 12.2833 No diabetes O 53.02 Male Caucasian O- Yes No 7.8 111.8 30 23.9 ANOXIA drowning TRUE 6 0 1 1 . 1
15 11 6104 No diabetes 0 1 0 0 0 4703 352 . 3.2660 . 5.8667 No diabetes O 55.2 Male Caucasian O+ Yes No 41 190.5 74 20.5 ANOXIA drug intoxication TRUE 6 0 1 1 . 3
16 1 6117 No diabetes 0 0 0 0 0 4785 940 65 3.3229 65 15.6667 No diabetes B 5.4 Male Caucasian B- Yes No 0.33 66 8.5 18.4 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 1
17 4 6126 No diabetes 0 0 0 0 0 7024 673 340 4.8778 340 11.2167 No diabetes O 80.2 Male Caucasian O+ Yes No 25.2 175.3 77 25.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 3
18 7 6129 No diabetes 0 0 0 0 0 6058 1132 75 4.2069 75 18.8667 No diabetes O 58.84 Female Caucasian O- Yes No 42.9 152.4 54 23.4 ANOXIA intracranial hemorrhage/stroke TRUE 6 0 2 1 . 3
19 5 6165 No diabetes 0 0 0 0 0 6815 985 120 4.7326 120 16.4167 No diabetes O 97.41 Female Caucasian O+ Yes No 45.8 165.1 68 25 CEREBROVASCULAR/STROKE   TRUE 6 0 2 1 . 3
20 13 6187 No diabetes 0 0 0 0 0 5485 625 60 3.8090 60 10.4167 No diabetes O 5.8 Male Caucasian O+ Yes Yes 0.33 63.5 6.7 17.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 1
21 15 6219 No diabetes 0 0 0 0 0 6322 1124 90 4.3903 90 18.7333 No diabetes AB 4.99 Male Hispanic/Latino AB+ Yes No 0.5 66 7.4 17 HEAD TRAUMA blunt injury TRUE 6 0 1 2 . 1
22 8 6229 No diabetes 0 0 0 0 0 4489 835 100 3.1174 100 13.9167 No diabetes O 45.6 Female Caucasian O+ Yes No 31 156 65.5 26.9 HEAD TRAUMA blunt injury TRUE 6 0 2 1 . 3
23 3 6230 No diabetes 0 0 0 0 0 4368 947 130 3.0333 130 15.7833 No diabetes B 66.27 Male Caucasian B+ Yes No 16 173 56.7 18.9 HEAD TRAUMA gunshot wound TRUE 6 0 1 1 . 2
24 6 6251 No diabetes 0 0 0 0 0 5366 310 75 3.7264 75 5.1667 No diabetes A1 77.8 Female Caucasian A- Yes Yes 33 154.9 70 29.5 HEAD TRAUMA   TRUE 6 0 2 1 . 3
25 9 6254 No diabetes 0 0 0 0 0 4677 1248 105 3.2479 105 20.8000 No diabetes A1B 69.9 Male Caucasian AB+ Yes Yes 38 167.6 86 30.5 ANOXIA asphyxiation TRUE 6 0 1 1 . 3
26 14 6279 No diabetes 0 0 0 0 0 4860 2715 140 3.3750 140 45.2500 No diabetes   80.17 Male Caucasian O+ No Unknown 19 180.3 110.2 34 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 2
27 1 6005 No diabetes 0 0 0 0 0 9184 1496 30 6.3778 30 24.9333 No diabetes A1 . Female Caucasian A- Yes No 5 104 17 15.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1 . 1
28 3 6007 No diabetes 0 0 0 0 0 9985 264 20 6.9340 20 4.4000 No diabetes O . Male African Am O+ Yes No 9 143 41 20 ANOXIA   TRUE 9 0 1 3 . 1
29 7 6008 No diabetes 0 0 0 0 0 15058 112 30 10.4569 30 1.8667 No diabetes O . Female Caucasian O+ Yes Yes 50 160 62 24.2 HEAD TRAUMA blunt injury TRUE 9 0 2 1 . 3
30 5 6011 No diabetes 0 0 0 0 0 40531 59 42 28.1465 42 0.9833 No diabetes O . Female African Am O+ Yes No 46 163 70 26.3 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 3 . 3
31 9 6019 No diabetes 0 0 0 0 0 11642 215 40 8.0847 40 3.5833 No diabetes O . Male Caucasian O- Yes No 42 175 95 31 HEAD TRAUMA intracranial hemorrhage/stroke TRUE 9 0 1 1 . 3
32 10 6057 No diabetes 0 0 0 0 0 12416 709 255 8.6222 255 11.8167 No diabetes O 104.36 Male Caucasian O+ Yes No 22 188 92 26 HEAD TRAUMA blunt injury TRUE 9 0 1 1 . 3
33 6 6060 No diabetes 0 0 0 0 0 13119 396 215 9.1104 215 6.6000 No diabetes A1 104 Male Caucasian A+ Yes No 24 175.3 100 32.7 HEAD TRAUMA blunt injury TRUE 9 0 1 1 . 3
34 13 6115 No diabetes 0 0 0 0 0 16117 848 45 11.1924 45 14.1333 No diabetes A 3.9 Male Caucasian A1- Yes No 0.42 64 7 17.1 ANOXIA sids TRUE 9 0 1 1 . 1
35 11 6140 No diabetes 0 0 0 0 0 11767 835 195 8.1715 195 13.9167 No diabetes A1 65.1 Male Caucasian A+ Yes No 38 170.2 59 21.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 1 1 . 3
36 15 6144 No diabetes 0 0 0 0 0 34014 426 90 23.6208 90 7.1000 No diabetes B 45 Female Hispanic/Latino B+ Yes Yes 7.5 124.5 25 16.3 Respiratory Distress/Failure natural causes TRUE 9 0 2 2 . 1
37 14 6172 No diabetes 0 0 0 0 0 10358 999 135 7.1931 135 16.6500 No diabetes A1 59.7 Female Caucasian A+ Yes No 19.2 172.7 97 32.4 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1 . 2
38 8 6178 No diabetes 0 0 0 0 0 9414 741 145 6.5375 145 12.3500 No diabetes A1 72.7 Female Caucasian A+ Yes No 24.5 182 92 27.5 ANOXIA cardiovascular TRUE 9 0 2 1 . 3
39 4 6179 No diabetes 0 0 0 0 0 20106 1464 120 13.9625 120 24.4000 No diabetes O 72.4 Female Caucasian O- Yes Yes 21.8 157.5 51 20.7 HEAD TRAUMA blunt injury TRUE 9 0 2 1 . 3

Need to test for collinearity of age group with hospitalization time group, since both will be included in the model.

In [26]:
%macro freq (X, Y);

PROC freq data=study1;
     tables &X*&Y/measures chisq exact;

%mend freq;

/*ORDINAL VS ORDINAL or 2-class nominal vs. ordinal Tau-b if equal r x c, and tau-c if unequal r x c*/
%freq (hospbin,age_group); run;
Out[26]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

Frequency
Percent
Row Pct
Col Pct
Table of hospbin by age_group
hospbin age_group
1 2 3 Total
3
3
7.69
23.08
27.27
2
5.13
15.38
40.00
8
20.51
61.54
34.78
13
33.33
 
 
6
4
10.26
30.77
36.36
2
5.13
15.38
40.00
7
17.95
53.85
30.43
13
33.33
 
 
9
4
10.26
30.77
36.36
1
2.56
7.69
20.00
8
20.51
61.54
34.78
13
33.33
 
 
Total
11
28.21
5
12.82
23
58.97
39
100.00

Statistics for Table of hospbin by age_group

Statistic DF Value Prob
WARNING: 67% of the cells have expected counts less
than 5. Chi-Square may not be a valid test.
Chi-Square 4 0.6688 0.9551
Likelihood Ratio Chi-Square 4 0.7134 0.9497
Mantel-Haenszel Chi-Square 1 0.0482 0.8262
Phi Coefficient   0.1310  
Contingency Coefficient   0.1298  
Cramer's V   0.0926  
Fisher's Exact Test
Table Probability (P) 0.0129
Pr <= P 1.0000
Statistic Value ASE
Gamma -0.0389 0.2370
Kendall's Tau-b -0.0238 0.1449
Stuart's Tau-c -0.0217 0.1324
Somers' D C|R -0.0217 0.1324
Somers' D R|C -0.0260 0.1586
Pearson Correlation -0.0356 0.1587
Spearman Correlation -0.0254 0.1594
Lambda Asymmetric C|R 0.0000 0.0000
Lambda Asymmetric R|C 0.0385 0.0998
Lambda Symmetric 0.0238 0.0621
Uncertainty Coefficient C|R 0.0098 0.0223
Uncertainty Coefficient R|C 0.0083 0.0189
Uncertainty Coefficient Symmetric 0.0090 0.0205

Sample Size = 39

Matching Schema Save

The final verified matching scheme is saved for later reference.

In [27]:
libname files "/mnt/hgfs/myfolders";

DATA files.grouping_list (keep = case match_group age_group oppc_ageR);
     set study1;
     rename ptid=case;
     rename set_num=match_group;
run;
Out[27]:

1219  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
1220
1221 libname files "/mnt/hgfs/myfolders";
NOTE: Libref FILES was successfully assigned as follows:
Engine: V9
Physical Name: /mnt/hgfs/myfolders
1222
1223 DATA files.grouping_list (keep = case match_group age_group oppc_ageR);
1224 set study1;
1225 rename ptid=case;
1226 rename set_num=match_group;
1227 run;
NOTE: There were 39 observations read from the data set WORK.STUDY1.
NOTE: The data set FILES.GROUPING_LIST has 39 observations and 4 variables.
NOTE: DATA statement used (Total process time):
real time 0.20 seconds
cpu time 0.02 seconds

1228 ods html5 close;ods listing;

1229

Table 1 - Demographics

Additional data files needed

The study1 data file does not have info on c-peptide. Downloaded that dataset from nPOD DataShare and merged it.

In [28]:
PROC import datafile = 'Diabetes Information.tsv' 
            out      = diabetesinfo 
            dbms     = dlm replace;
            delimiter = '09'x;
            getnames  = yes;
            guessingrows = 1000;
run;
quit;


data diabetesinfo1;
     set diabetesinfo;
     npodcaseID1=npodcaseid*1;
     rename nPODCaseID1=ptid;
     cpeptide=oppc_c_peptideR*1;
 run;

PROC sort data=diabetesinfo1;
     by ptid;
run;

PROC sort data=study1;
     by ptid;
run;

data study2;
     merge study1 (in=a) diabetesinfo1 (in=b);
     by ptid;
     if a;
run;

proc print data=study2;
run;
Out[28]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

Obs set_num ptid Donor_Type Organ_Received_Datetime_Flag Organ_Frozen_Datetime_Flag Admit_Datetime_Flag Braindeath_Datetime_Flag Xclamp_Datetime_Flag Hospitalization_Stay_Minutes Transport_Duration_Minutes Processing_Time_Minutes Hospitalization_Stay_Days Processing_Time_Minutes1 transport_duration_hours DonorType abo_subtype oppc_PancreasWT oppc_Gender oppc_Ethnicity oppc_ABO multi_organ_donor non_hrt_beat_donor oppc_ageR oppc_heightR oppc_weightR oppc_bmiR cod_final death_mech_final replace hospbin donor sex ethnicity clamp_Datetime_Flag age_group nPODCaseID diabetes_Duration_yrs oppc_C_peptideR oppc_HbA1cR diabetes_history insulin_depd insulin_meds_taken cpeptide
1 6 6003 No diabetes 0 0 0 0 0 3994 84 30 2.7736 30 1.4000 No diabetes O . Female Caucasian O+ Yes No 23 160 75 29.3 HEAD TRAUMA blunt injury TRUE 3 0 2 1 . 3 6003 .   . No   None .
2 1 6005 No diabetes 0 0 0 0 0 9184 1496 30 6.3778 30 24.9333 No diabetes A1 . Female Caucasian A- Yes No 5 104 17 15.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1 . 1 6005 .   . No   None .
3 3 6007 No diabetes 0 0 0 0 0 9985 264 20 6.9340 20 4.4000 No diabetes O . Male African Am O+ Yes No 9 143 41 20 ANOXIA   TRUE 9 0 1 3 . 1 6007 .   . No   None .
4 7 6008 No diabetes 0 0 0 0 0 15058 112 30 10.4569 30 1.8667 No diabetes O . Female Caucasian O+ Yes Yes 50 160 62 24.2 HEAD TRAUMA blunt injury TRUE 9 0 2 1 . 3 6008 .   . No   None .
5 5 6011 No diabetes 0 0 0 0 0 40531 59 42 28.1465 42 0.9833 No diabetes O . Female African Am O+ Yes No 46 163 70 26.3 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 3 . 3 6011 .   . No   None .
6 9 6019 No diabetes 0 0 0 0 0 11642 215 40 8.0847 40 3.5833 No diabetes O . Male Caucasian O- Yes No 42 175 95 31 HEAD TRAUMA intracranial hemorrhage/stroke TRUE 9 0 1 1 . 3 6019 . 0.47 5.6 No   None 0.47
7 10 6047 No diabetes 0 0 0 0 0 4851 737 30 3.3688 30 12.2833 No diabetes O 53.02 Male Caucasian O- Yes No 7.8 111.8 30 23.9 ANOXIA drowning TRUE 6 0 1 1 . 1 6047 . 0.65 5.5 No   No 0.65
8 11 6048 No diabetes 0 0 0 0 0 1927 368 55 1.3382 55 6.1333 No diabetes O 139 Male Caucasian O- Yes No 30 165.1 56 20.6 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 3 0 1 1 . 3 6048 . 17.91 . No   No 17.91
9 10 6057 No diabetes 0 0 0 0 0 12416 709 255 8.6222 255 11.8167 No diabetes O 104.36 Male Caucasian O+ Yes No 22 188 92 26 HEAD TRAUMA blunt injury TRUE 9 0 1 1 . 3 6057 . 16.23 . No   No 16.23
10 6 6060 No diabetes 0 0 0 0 0 13119 396 215 9.1104 215 6.6000 No diabetes A1 104 Male Caucasian A+ Yes No 24 175.3 100 32.7 HEAD TRAUMA blunt injury TRUE 9 0 1 1 . 3 6060 . 13.63 . No   No 13.63
11 14 6073 No diabetes 0 0 0 0 0 3560 754 50 2.4722 50 12.5667 No diabetes O 66.5 Male Caucasian O+ Yes No 19.2 165.1 98 36 ANOXIA cardiovascular TRUE 3 0 1 1 . 2 6073 . 0.69 . Unknown   No 0.69
12 8 6099 No diabetes 0 1 0 0 0 2945 890 . 2.0451 . 14.8333 No diabetes A2B 85.56 Male Caucasian AB+ Yes No 14.2 175.3 92 30 HEAD TRAUMA blunt injury TRUE 3 0 1 1 . 2 6099 . 5.37 . No   No 5.37
13 11 6104 No diabetes 0 1 0 0 0 4703 352 . 3.2660 . 5.8667 No diabetes O 55.2 Male Caucasian O+ Yes No 41 190.5 74 20.5 ANOXIA drug intoxication TRUE 6 0 1 1 . 3 6104 . 20.55 . No   No 20.55
14 1 6106 No diabetes 0 0 0 0 0 4164 1131 45 2.8917 45 18.8500 No diabetes A1 16.32 Male Caucasian A+ Yes No 2.9 94 16 18.1 ANOXIA drowning TRUE 3 0 1 1 . 1 6106 . 7.36 . No   None 7.36
15 13 6115 No diabetes 0 0 0 0 0 16117 848 45 11.1924 45 14.1333 No diabetes A 3.9 Male Caucasian A1- Yes No 0.42 64 7 17.1 ANOXIA sids TRUE 9 0 1 1 . 1 6115 . 4.59 . No   No 4.59
16 1 6117 No diabetes 0 0 0 0 0 4785 940 65 3.3229 65 15.6667 No diabetes B 5.4 Male Caucasian B- Yes No 0.33 66 8.5 18.4 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 1 6117 . 3.27 . No   No 3.27
17 4 6126 No diabetes 0 0 0 0 0 7024 673 340 4.8778 340 11.2167 No diabetes O 80.2 Male Caucasian O+ Yes No 25.2 175.3 77 25.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 3 6126 . 0.88 . No   No 0.88
18 7 6129 No diabetes 0 0 0 0 0 6058 1132 75 4.2069 75 18.8667 No diabetes O 58.84 Female Caucasian O- Yes No 42.9 152.4 54 23.4 ANOXIA intracranial hemorrhage/stroke TRUE 6 0 2 1 . 3 6129 . 0.51 5.2 No   No 0.51
19 4 6131 No diabetes 0 0 0 0 0 2743 1127 120 1.9049 120 18.7833 No diabetes B 108.92 Male Caucasian B+ Yes Yes 24.2 182.9 83 24.8 ANOXIA drug intoxication TRUE 3 0 1 1 . 3 6131 . 1.01 . No   No 1.01
20 13 6134 No diabetes 0 0 0 0 0 2905 1010 75 2.0174 75 16.8333 No diabetes O 82.42 Male Caucasian O+ Yes No 26.7 180.3 65 20.1 ANOXIA drug intoxication TRUE 3 0 1 1 . 3 6134 . 3.59 . No   No 3.59
21 11 6140 No diabetes 0 0 0 0 0 11767 835 195 8.1715 195 13.9167 No diabetes A1 65.1 Male Caucasian A+ Yes No 38 170.2 59 21.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 1 1 . 3 6140 . 11.1 6 No   No 11.10
22 15 6144 No diabetes 0 0 0 0 0 34014 426 90 23.6208 90 7.1000 No diabetes B 45 Female Hispanic/Latino B+ Yes Yes 7.5 124.5 25 16.3 Respiratory Distress/Failure natural causes TRUE 9 0 2 2 . 1 6144 . 1.27 . No   No 1.27
23 9 6162 No diabetes 0 0 0 0 0 2193 1203 115 1.5229 115 20.0500 No diabetes B 81.5 Male African Am B+ Yes No 22.7 188 102 28.9 HEAD TRAUMA gunshot wound TRUE 3 0 1 3 . 3 6162 . 7.61 . No   No 7.61
24 5 6165 No diabetes 0 0 0 0 0 6815 985 120 4.7326 120 16.4167 No diabetes O 97.41 Female Caucasian O+ Yes No 45.8 165.1 68 25 CEREBROVASCULAR/STROKE   TRUE 6 0 2 1 . 3 6165 . 4.45 5.6 No   No 4.45
25 14 6172 No diabetes 0 0 0 0 0 10358 999 135 7.1931 135 16.6500 No diabetes A1 59.7 Female Caucasian A+ Yes No 19.2 172.7 97 32.4 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1 . 2 6172 . 8.02 5.4 No     8.02
26 3 6174 No diabetes 0 0 0 0 0 1181 604 135 0.8201 135 10.0667 No diabetes O 79.3 Male Caucasian O+ Yes No 20.8 196 75 19.5 CEREBROVASCULAR/STROKE blunt injury TRUE 3 0 1 1 . 3 6174 . 3 . No     3.00
27 8 6178 No diabetes 0 0 0 0 0 9414 741 145 6.5375 145 12.3500 No diabetes A1 72.7 Female Caucasian A+ Yes No 24.5 182 92 27.5 ANOXIA cardiovascular TRUE 9 0 2 1 . 3 6178 . 4.55 5 No     4.55
28 4 6179 No diabetes 0 0 0 0 0 20106 1464 120 13.9625 120 24.4000 No diabetes O 72.4 Female Caucasian O- Yes Yes 21.8 157.5 51 20.7 HEAD TRAUMA blunt injury TRUE 9 0 2 1 . 3 6179 . 2.74 . No     2.74
29 13 6187 No diabetes 0 0 0 0 0 5485 625 60 3.8090 60 10.4167 No diabetes O 5.8 Male Caucasian O+ Yes Yes 0.33 63.5 6.7 17.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 1 6187 . 0.72 . No   None 0.72
30 15 6200 No diabetes 0 0 0 0 0 3449 1456 30 2.3951 30 24.2667 No diabetes   4.29 Female Hispanic/Latino O+ No Unknown 0.0065753425 41 2.2 14.5 Pulmonary hypoplasia respiratory TRUE 3 0 2 2 . 1 6200 . 0.2 .     None 0.20
31 15 6219 No diabetes 0 0 0 0 0 6322 1124 90 4.3903 90 18.7333 No diabetes AB 4.99 Male Hispanic/Latino AB+ Yes No 0.5 66 7.4 17 HEAD TRAUMA blunt injury TRUE 6 0 1 2 . 1 6219 . 1.53 . No   None 1.53
32 8 6229 No diabetes 0 0 0 0 0 4489 835 100 3.1174 100 13.9167 No diabetes O 45.6 Female Caucasian O+ Yes No 31 156 65.5 26.9 HEAD TRAUMA blunt injury TRUE 6 0 2 1 . 3 6229 . 6.23 5.5 No   None 6.23
33 3 6230 No diabetes 0 0 0 0 0 4368 947 130 3.0333 130 15.7833 No diabetes B 66.27 Male Caucasian B+ Yes No 16 173 56.7 18.9 HEAD TRAUMA gunshot wound TRUE 6 0 1 1 . 2 6230 . 5.22 5.3 No   None 5.22
34 7 6235 No diabetes 0 0 0 0 0 3690 1020 120 2.5625 120 17.0000 No diabetes O 102.31 Male Caucasian O+ Yes No 30 172.7 76 25.4 HEAD TRAUMA gunshot wound TRUE 3 0 1 1 . 3 6235 . 8.1 . No   None 8.10
35 5 6250 No diabetes 0 0 0 0 0 2732 1081 25 1.8972 25 18.0167 No diabetes O . Male Caucasian O+ Yes No 40 180.3 90.7 27.9 HEAD TRAUMA blunt injury TRUE 3 0 1 1 . 3 6250 . 7.31 . No   None 7.31
36 6 6251 No diabetes 0 0 0 0 0 5366 310 75 3.7264 75 5.1667 No diabetes A1 77.8 Female Caucasian A- Yes Yes 33 154.9 70 29.5 HEAD TRAUMA   TRUE 6 0 2 1 . 3 6251 . 1.92 5.3 No   None 1.92
37 9 6254 No diabetes 0 0 0 0 0 4677 1248 105 3.2479 105 20.8000 No diabetes A1B 69.9 Male Caucasian AB+ Yes Yes 38 167.6 86 30.5 ANOXIA asphyxiation TRUE 6 0 1 1 . 3 6254 . 6.43 5.3 No   None 6.43
38 10 6278 No diabetes 0 0 0 0 0 2653 895 87 1.8424 87 14.9167 No diabetes   33.6 Female African Am A No Unknown 10 157.5 52.4 21.3 ANOXIA cardiovascular TRUE 3 0 2 3 . 1 6278 . 4.54 6.3 No   None 4.54
39 14 6279 No diabetes 0 0 0 0 0 4860 2715 140 3.3750 140 45.2500 No diabetes   80.17 Male Caucasian O+ No Unknown 19 180.3 110.2 34 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 2 6279 . 8.01 . No   None 8.01

Data on medications adminstered within 24 hours prior to organ recovery. Downloaded from nPOD DataShare and merged it.

In [37]:
PROC import datafile = 'meds.tsv' 
            out      = meds 
            dbms     = dlm replace;
            delimiter = '09'x;
            getnames  = yes;
            guessingrows = 1000;
run;
quit;

data meds1 (drop=npodcaseid);
     set meds;
     npodcaseID1=npodcaseid*1;
     rename nPODCaseID1=ptid;
run;

PROC sort data=meds1;
     by ptid;
run;

PROC sort data=study2;
     by ptid;
run;

data study3;
     merge study2 (in=a) meds1 (in=b);
     by ptid;
     if a;
run;

proc print data=study3;
run;
Out[37]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

Obs set_num ptid Donor_Type Organ_Received_Datetime_Flag Organ_Frozen_Datetime_Flag Admit_Datetime_Flag Braindeath_Datetime_Flag Xclamp_Datetime_Flag Hospitalization_Stay_Minutes Transport_Duration_Minutes Processing_Time_Minutes Hospitalization_Stay_Days Processing_Time_Minutes1 transport_duration_hours DonorType abo_subtype oppc_PancreasWT oppc_Gender oppc_Ethnicity oppc_ABO multi_organ_donor non_hrt_beat_donor oppc_ageR oppc_heightR oppc_weightR oppc_bmiR cod_final death_mech_final replace hospbin donor sex ethnicity clamp_Datetime_Flag age_group nPODCaseID diabetes_Duration_yrs oppc_C_peptideR oppc_HbA1cR diabetes_history insulin_depd insulin_meds_taken cpeptide dataSetsDemographicsDonorType pt_steroids pt_diuretics pt_t3 pt_t4 anticonv antihype vasodil ddavp heparin arginine insulin other_meds1 other_meds2 other_meds3
1 6 6003 No diabetes 0 0 0 0 0 3994 84 30 2.7736 30 1.4000 No diabetes O . Female Caucasian O+ Yes No 23 160 75 29.3 HEAD TRAUMA blunt injury TRUE 3 0 2 1 . 3 6003 .   . No   None . No diabetes Y Y N Y Y N N N Y N N CEFEPIME DOPAMINE CLINDAMYCIN
2 1 6005 No diabetes 0 0 0 0 0 9184 1496 30 6.3778 30 24.9333 No diabetes A1 . Female Caucasian A- Yes No 5 104 17 15.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1 . 1 6005 .   . No   None . No diabetes Y Y N N N N N N Y N Y MYCAMINE NARCAN REGATINE
3 3 6007 No diabetes 0 0 0 0 0 9985 264 20 6.9340 20 4.4000 No diabetes O . Male African Am O+ Yes No 9 143 41 20 ANOXIA   TRUE 9 0 1 3 . 1 6007 .   . No   None . No diabetes Y Y N Y Y N Y N Y N Y ANCEF    
4 7 6008 No diabetes 0 0 0 0 0 15058 112 30 10.4569 30 1.8667 No diabetes O . Female Caucasian O+ Yes Yes 50 160 62 24.2 HEAD TRAUMA blunt injury TRUE 9 0 2 1 . 3 6008 .   . No   None . No diabetes N N N N Y N N N N N Y CEFEPINE ANCF KCL
5 5 6011 No diabetes 0 0 0 0 0 40531 59 42 28.1465 42 0.9833 No diabetes O . Female African Am O+ Yes No 46 163 70 26.3 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 3 . 3 6011 .   . No   None . No diabetes Y Y N N N N N N Y N N PROPOFOL PENTOBARB VANC
6 9 6019 No diabetes 0 0 0 0 0 11642 215 40 8.0847 40 3.5833 No diabetes O . Male Caucasian O- Yes No 42 175 95 31 HEAD TRAUMA intracranial hemorrhage/stroke TRUE 9 0 1 1 . 3 6019 . 0.47 5.6 No   None 0.47 No diabetes Y Y N Y Y Y N N Y N Y NARCAN FACTOR 7 D5D
7 10 6047 No diabetes 0 0 0 0 0 4851 737 30 3.3688 30 12.2833 No diabetes O 53.02 Male Caucasian O- Yes No 7.8 111.8 30 23.9 ANOXIA drowning TRUE 6 0 1 1 . 1 6047 . 0.65 5.5 No   No 0.65 No diabetes Y Y N Y Y N Y N Y Y Y CLEOCIN    
8 11 6048 No diabetes 0 0 0 0 0 1927 368 55 1.3382 55 6.1333 No diabetes O 139 Male Caucasian O- Yes No 30 165.1 56 20.6 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 3 0 1 1 . 3 6048 . 17.91 . No   No 17.91 No diabetes Y Y N N N N Y Y Y Y N CEFEPIME VANCOMYCIN PROTONIX
9 10 6057 No diabetes 0 0 0 0 0 12416 709 255 8.6222 255 11.8167 No diabetes O 104.36 Male Caucasian O+ Yes No 22 188 92 26 HEAD TRAUMA blunt injury TRUE 9 0 1 1 . 3 6057 . 16.23 . No   No 16.23 No diabetes N Y N N N N Y N Y N N      
10 6 6060 No diabetes 0 0 0 0 0 13119 396 215 9.1104 215 6.6000 No diabetes A1 104 Male Caucasian A+ Yes No 24 175.3 100 32.7 HEAD TRAUMA blunt injury TRUE 9 0 1 1 . 3 6060 . 13.63 . No   No 13.63 No diabetes N Y N Y N N Y N Y N N COLACE, PROTONIX, PROPOFOL CLOACIN, LEVAQUIN, MORPHINE VANCOMYCIN, AMINOPHLLINE
11 14 6073 No diabetes 0 0 0 0 0 3560 754 50 2.4722 50 12.5667 No diabetes O 66.5 Male Caucasian O+ Yes No 19.2 165.1 98 36 ANOXIA cardiovascular TRUE 3 0 1 1 . 2 6073 . 0.69 . Unknown   No 0.69 No diabetes Y Y Y N N N N Y Y Y Y Invanz 1 gram Magnesium 1 gram potassium chloride 20 meq
12 8 6099 No diabetes 0 1 0 0 0 2945 890 . 2.0451 . 14.8333 No diabetes A2B 85.56 Male Caucasian AB+ Yes No 14.2 175.3 92 30 HEAD TRAUMA blunt injury TRUE 3 0 1 1 . 2 6099 . 5.37 . No   No 5.37 No diabetes Y Y N Y N N N N Y Y Y neosynephrine merrem, KCL flolan
13 11 6104 No diabetes 0 1 0 0 0 4703 352 . 3.2660 . 5.8667 No diabetes O 55.2 Male Caucasian O+ Yes No 41 190.5 74 20.5 ANOXIA drug intoxication TRUE 6 0 1 1 . 3 6104 . 20.55 . No   No 20.55 No diabetes Y Y N N N N Y N Y N N NARCAN (Naloxone) CEFEPIME  
14 1 6106 No diabetes 0 0 0 0 0 4164 1131 45 2.8917 45 18.8500 No diabetes A1 16.32 Male Caucasian A+ Yes No 2.9 94 16 18.1 ANOXIA drowning TRUE 3 0 1 1 . 1 6106 . 7.36 . No   None 7.36 No diabetes Y Y N Y N N N N Y Y Y Albuterol, Atrovent, Nystatin Unasyn, Mag, Vit K Na Bicarb, KCl, Pavulon
15 13 6115 No diabetes 0 0 0 0 0 16117 848 45 11.1924 45 14.1333 No diabetes A 3.9 Male Caucasian A1- Yes No 0.42 64 7 17.1 ANOXIA sids TRUE 9 0 1 1 . 1 6115 . 4.59 . No   No 4.59 No diabetes Y Y N N N N N N Y Y N CEFEPIME GENTAMYCIN vancomycin
16 1 6117 No diabetes 0 0 0 0 0 4785 940 65 3.3229 65 15.6667 No diabetes B 5.4 Male Caucasian B- Yes No 0.33 66 8.5 18.4 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 1 6117 . 3.27 . No   No 3.27 No diabetes N Y N Y N N N Y Y N Y Dopamine, KCL, Zosyn Dextrose  
17 4 6126 No diabetes 0 0 0 0 0 7024 673 340 4.8778 340 11.2167 No diabetes O 80.2 Male Caucasian O+ Yes No 25.2 175.3 77 25.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 3 6126 . 0.88 . No   No 0.88 No diabetes Y Y N Y N N N N Y Y N ANCEF    
18 7 6129 No diabetes 0 0 0 0 0 6058 1132 75 4.2069 75 18.8667 No diabetes O 58.84 Female Caucasian O- Yes No 42.9 152.4 54 23.4 ANOXIA intracranial hemorrhage/stroke TRUE 6 0 2 1 . 3 6129 . 0.51 5.2 No   No 0.51 No diabetes Y Y N N N Y N N Y N Y zosyn   vecuronium
19 4 6131 No diabetes 0 0 0 0 0 2743 1127 120 1.9049 120 18.7833 No diabetes B 108.92 Male Caucasian B+ Yes Yes 24.2 182.9 83 24.8 ANOXIA drug intoxication TRUE 3 0 1 1 . 3 6131 . 1.01 . No   No 1.01 No diabetes Y N N Y N N N N Y Y N dopamine, neo levophed ancef, vonco, zoayn
20 13 6134 No diabetes 0 0 0 0 0 2905 1010 75 2.0174 75 16.8333 No diabetes O 82.42 Male Caucasian O+ Yes No 26.7 180.3 65 20.1 ANOXIA drug intoxication TRUE 3 0 1 1 . 3 6134 . 3.59 . No   No 3.59 No diabetes Y Y N Y N Y N N Y Y N NEO/BICARB MILRINONE/CARDEINE ANCEF
21 11 6140 No diabetes 0 0 0 0 0 11767 835 195 8.1715 195 13.9167 No diabetes A1 65.1 Male Caucasian A+ Yes No 38 170.2 59 21.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 1 1 . 3 6140 . 11.1 6 No   No 11.10 No diabetes Y Y N Y N Y N N Y Y Y ROCEPHIN/VANCOMYCIN NIMBEX BENADRYL
22 15 6144 No diabetes 0 0 0 0 0 34014 426 90 23.6208 90 7.1000 No diabetes B 45 Female Hispanic/Latino B+ Yes Yes 7.5 124.5 25 16.3 Respiratory Distress/Failure natural causes TRUE 9 0 2 2 . 1 6144 . 1.27 . No   No 1.27 No diabetes N N N N N N N N Y N N      
23 9 6162 No diabetes 0 0 0 0 0 2193 1203 115 1.5229 115 20.0500 No diabetes B 81.5 Male African Am B+ Yes No 22.7 188 102 28.9 HEAD TRAUMA gunshot wound TRUE 3 0 1 3 . 3 6162 . 7.61 . No   No 7.61 No diabetes N Y N Y N N N N Y Y N unasyn    
24 5 6165 No diabetes 0 0 0 0 0 6815 985 120 4.7326 120 16.4167 No diabetes O 97.41 Female Caucasian O+ Yes No 45.8 165.1 68 25 CEREBROVASCULAR/STROKE   TRUE 6 0 2 1 . 3 6165 . 4.45 5.6 No   No 4.45 No diabetes N Y N N N Y N N Y N N NIMBEX/NARCAN/FENTANYL ALBUTEROL/ATROVENT ZOSYN/TOBRAMYCIN/CISATRACURIUM
25 14 6172 No diabetes 0 0 0 0 0 10358 999 135 7.1931 135 16.6500 No diabetes A1 59.7 Female Caucasian A+ Yes No 19.2 172.7 97 32.4 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1 . 2 6172 . 8.02 5.4 No     8.02 No diabetes Y Y N Y N N N Y Y Y Y      
26 3 6174 No diabetes 0 0 0 0 0 1181 604 135 0.8201 135 10.0667 No diabetes O 79.3 Male Caucasian O+ Yes No 20.8 196 75 19.5 CEREBROVASCULAR/STROKE blunt injury TRUE 3 0 1 1 . 3 6174 . 3 . No     3.00 No diabetes Y N N Y N N N N Y Y Y dobutamine, levophed, neosynephrine Ancef
27 8 6178 No diabetes 0 0 0 0 0 9414 741 145 6.5375 145 12.3500 No diabetes A1 72.7 Female Caucasian A+ Yes No 24.5 182 92 27.5 ANOXIA cardiovascular TRUE 9 0 2 1 . 3 6178 . 4.55 5 No     4.55 No diabetes Y Y N Y N N N N Y Y Y Fentanyl,KCL, Calcium Gluconate    
28 4 6179 No diabetes 0 0 0 0 0 20106 1464 120 13.9625 120 24.4000 No diabetes O 72.4 Female Caucasian O- Yes Yes 21.8 157.5 51 20.7 HEAD TRAUMA blunt injury TRUE 9 0 2 1 . 3 6179 . 2.74 . No     2.74 No diabetes Y N N N N N N N Y Y N Lacrilube, NaHCO3    
29 13 6187 No diabetes 0 0 0 0 0 5485 625 60 3.8090 60 10.4167 No diabetes O 5.8 Male Caucasian O+ Yes Yes 0.33 63.5 6.7 17.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 1 6187 . 0.72 . No   None 0.72 No diabetes N N N N N N Y N Y N N Rocephin Vancomycin  
30 15 6200 No diabetes 0 0 0 0 0 3449 1456 30 2.3951 30 24.2667 No diabetes   4.29 Female Hispanic/Latino O+ No Unknown 0.0065753425 41 2.2 14.5 Pulmonary hypoplasia respiratory TRUE 3 0 2 2 . 1 6200 . 0.2 .     None 0.20 No diabetes                            
31 15 6219 No diabetes 0 0 0 0 0 6322 1124 90 4.3903 90 18.7333 No diabetes AB 4.99 Male Hispanic/Latino AB+ Yes No 0.5 66 7.4 17 HEAD TRAUMA blunt injury TRUE 6 0 1 2 . 1 6219 . 1.53 . No   None 1.53 No diabetes N Y N N N Y Y N Y Y N Versed, Rocuronium Fentanyl Ancef
32 8 6229 No diabetes 0 0 0 0 0 4489 835 100 3.1174 100 13.9167 No diabetes O 45.6 Female Caucasian O+ Yes No 31 156 65.5 26.9 HEAD TRAUMA blunt injury TRUE 6 0 2 1 . 3 6229 . 6.23 5.5 No   None 6.23 No diabetes Y Y N Y N N N N Y N Y Zosyn    
33 3 6230 No diabetes 0 0 0 0 0 4368 947 130 3.0333 130 15.7833 No diabetes B 66.27 Male Caucasian B+ Yes No 16 173 56.7 18.9 HEAD TRAUMA gunshot wound TRUE 6 0 1 1 . 2 6230 . 5.22 5.3 No   None 5.22 No diabetes N N N Y N N N N Y Y Y duoneb zosyn fentanyl vecuronium levophed, neosynephrine
34 7 6235 No diabetes 0 0 0 0 0 3690 1020 120 2.5625 120 17.0000 No diabetes O 102.31 Male Caucasian O+ Yes No 30 172.7 76 25.4 HEAD TRAUMA gunshot wound TRUE 3 0 1 1 . 3 6235 . 8.1 . No   None 8.10 No diabetes Y Y N N N N N N Y N N Ancef, Levophed, Vecuronium  
35 5 6250 No diabetes 0 0 0 0 0 2732 1081 25 1.8972 25 18.0167 No diabetes O . Male Caucasian O+ Yes No 40 180.3 90.7 27.9 HEAD TRAUMA blunt injury TRUE 3 0 1 1 . 3 6250 . 7.31 . No   None 7.31 No diabetes Y Y N Y N N N N Y N Y cardizem cefazolin  
36 6 6251 No diabetes 0 0 0 0 0 5366 310 75 3.7264 75 5.1667 No diabetes A1 77.8 Female Caucasian A- Yes Yes 33 154.9 70 29.5 HEAD TRAUMA   TRUE 6 0 2 1 . 3 6251 . 1.92 5.3 No   None 1.92 No diabetes N N N N N N N N Y N N Ancef 1 Gm q8h    
37 9 6254 No diabetes 0 0 0 0 0 4677 1248 105 3.2479 105 20.8000 No diabetes A1B 69.9 Male Caucasian AB+ Yes Yes 38 167.6 86 30.5 ANOXIA asphyxiation TRUE 6 0 1 1 . 3 6254 . 6.43 5.3 No   None 6.43 No diabetes N N N N N N N N Y N Y Ancef    
38 10 6278 No diabetes 0 0 0 0 0 2653 895 87 1.8424 87 14.9167 No diabetes   33.6 Female African Am A No Unknown 10 157.5 52.4 21.3 ANOXIA cardiovascular TRUE 3 0 2 3 . 1 6278 . 4.54 6.3 No   None 4.54 No diabetes Y Y N N N N N N Y Y Y Levophed, Vancomycin, Ephedrine Vecuronium, Neosynephrine
39 14 6279 No diabetes 0 0 0 0 0 4860 2715 140 3.3750 140 45.2500 No diabetes   80.17 Male Caucasian O+ No Unknown 19 180.3 110.2 34 HEAD TRAUMA blunt injury TRUE 6 0 1 1 . 2 6279 . 8.01 . No   None 8.01 No diabetes N N N N N N N N Y N Y Ceftriaxone Lansoprazole  

Examined med list (other_meds1, 2, and 3) and it needs to be cleaned up so that each medication is placed into a separate field for further analysis. Given the number of records, the dataset was exported and pre-processed manually, then re-imported into the datafile.

In rare cases, dosages were given. This information was not used in the analysis and thus removed as part of the pre-processing. Generic or brand name of medication was used, but not both. Abbreviations were expanded to full medication names, where distinguishable. Blanks were recoded to 'none'. Misspellings were accounted for in the mappings.

In [65]:
PROC export data=study3 
     outfile="study3.csv" 
     dbms=csv
     replace;
run; 

PROC import datafile = 'study4.csv' 
            out      = study4
            dbms     = csv replace;
            getnames  = yes;
            guessingrows = 1000;
run;
quit;

PROC print data=study4;
run;
Out[65]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

Obs set_num ptid Donor_Type Organ_Received_Datetime_Flag Organ_Frozen_Datetime_Flag Admit_Datetime_Flag Braindeath_Datetime_Flag Xclamp_Datetime_Flag Hospitalization_Stay_Minutes Transport_Duration_Minutes Processing_Time_Minutes Hospitalization_Stay_Days Processing_Time_Minutes1 transport_duration_hours DonorType abo_subtype oppc_PancreasWT oppc_Gender oppc_Ethnicity oppc_ABO multi_organ_donor non_hrt_beat_donor oppc_ageR oppc_heightR oppc_weightR oppc_bmiR cod_final death_mech_final replace hospbin donor sex ethnicity clamp_Datetime_Flag age_group nPODCaseID diabetes_Duration_yrs oppc_C_peptideR oppc_HbA1cR diabetes_history insulin_depd insulin_meds_taken cpeptide dataSetsDemographicsDonorType pt_steroids pt_diuretics pt_t3 pt_t4 anticonv antihype vasodil ddavp heparin arginine insulin dmed_other1 dmed_other2 dmed_other3 dmed_other4 dmed_other5 dmed_other6 dmed_other7 dmed_other8 dmed_other9
1 6 6003 No diabetes 0 0 0 0 0 3994 84 30 2.773611111 30 1.4 No diabetes O . Female Caucasian O+ Yes No 23 160 75 29.3 HEAD TRAUMA blunt injury TRUE 3 0 2 1   3 6003   . . No   None . No diabetes Y Y N Y Y N N N Y N N CEFEPIME none none DOPAMINE none none CLINDAMYCIN none none
2 1 6005 No diabetes 0 0 0 0 0 9184 1496 30 6.377777778 30 24.93333333 No diabetes A1 . Female Caucasian A- Yes No 5 104 17 15.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1   1 6005   . . No   None . No diabetes Y Y N N N N N N Y N Y MYCAMINE none none NARCAN none none REGATINE none none
3 3 6007 No diabetes 0 0 0 0 0 9985 264 20 6.934027778 20 4.4 No diabetes O . Male African Am O+ Yes No 9 143 41 20 ANOXIA   TRUE 9 0 1 3   1 6007   . . No   None . No diabetes Y Y N Y Y N Y N Y N Y ANCEF none none none none none none none none
4 7 6008 No diabetes 0 0 0 0 0 15058 112 30 10.45694444 30 1.866666667 No diabetes O . Female Caucasian O+ Yes Yes 50 160 62 24.2 HEAD TRAUMA blunt injury TRUE 9 0 2 1   3 6008   . . No   None . No diabetes N N N N Y N N N N N Y CEFEPINE none none ANCF none none KCL none none
5 5 6011 No diabetes 0 0 0 0 0 40531 59 42 28.14652778 42 0.983333333 No diabetes O . Female African Am O+ Yes No 46 163 70 26.3 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 3   3 6011   . . No   None . No diabetes Y Y N N N N N N Y N N PROPOFOL none none PENTOBARB none none VANC none none
6 9 6019 No diabetes 0 0 0 0 0 11642 215 40 8.084722222 40 3.583333333 No diabetes O . Male Caucasian O- Yes No 42 175 95 31 HEAD TRAUMA intracranial hemorrhage/stroke TRUE 9 0 1 1   3 6019   0.47 5.6 No   None 0.47 No diabetes Y Y N Y Y Y N N Y N Y NARCAN none none FACTOR 7 none none D5D none none
7 10 6047 No diabetes 0 0 0 0 0 4851 737 30 3.36875 30 12.28333333 No diabetes O 53.02 Male Caucasian O- Yes No 7.8 111.8 30 23.9 ANOXIA drowning TRUE 6 0 1 1   1 6047   0.65 5.5 No   No 0.65 No diabetes Y Y N Y Y N Y N Y Y Y CLEOCIN none none none none none none none none
8 11 6048 No diabetes 0 0 0 0 0 1927 368 55 1.338194444 55 6.133333333 No diabetes O 139 Male Caucasian O- Yes No 30 165.1 56 20.6 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 3 0 1 1   3 6048   17.91 . No   No 17.91 No diabetes Y Y N N N N Y Y Y Y N CEFEPIME none none VANCOMYCIN none none PROTONIX none none
9 10 6057 No diabetes 0 0 0 0 0 12416 709 255 8.622222222 255 11.81666667 No diabetes O 104.36 Male Caucasian O+ Yes No 22 188 92 26 HEAD TRAUMA blunt injury TRUE 9 0 1 1   3 6057   16.23 . No   No 16.23 No diabetes N Y N N N N Y N Y N N none none none none none none none none none
10 6 6060 No diabetes 0 0 0 0 0 13119 396 215 9.110416667 215 6.6 No diabetes A1 104 Male Caucasian A+ Yes No 24 175.3 100 32.7 HEAD TRAUMA blunt injury TRUE 9 0 1 1   3 6060   13.63 . No   No 13.63 No diabetes N Y N Y N N Y N Y N N COLACE PROTONIX PROPOFOL CLOACIN LEVAQUIN MORPHINE VANCOMYCIN AMINOPHLLINE none
11 14 6073 No diabetes 0 0 0 0 0 3560 754 50 2.472222222 50 12.56666667 No diabetes O 66.5 Male Caucasian O+ Yes No 19.2 165.1 98 36 ANOXIA cardiovascular TRUE 3 0 1 1   2 6073   0.69 . Unknown   No 0.69 No diabetes Y Y Y N N N N Y Y Y Y Invanz none none Magnesium none none potassium chloride none none
12 8 6099 No diabetes 0 1 0 0 0 2945 890 . 2.045138889 . 14.83333333 No diabetes A2B 85.56 Male Caucasian AB+ Yes No 14.2 175.3 92 30 HEAD TRAUMA blunt injury TRUE 3 0 1 1   2 6099   5.37 . No   No 5.37 No diabetes Y Y N Y N N N N Y Y Y neosynephrine none none merrem KCL none flolan none none
13 11 6104 No diabetes 0 1 0 0 0 4703 352 . 3.265972222 . 5.866666667 No diabetes O 55.2 Male Caucasian O+ Yes No 41 190.5 74 20.5 ANOXIA drug intoxication TRUE 6 0 1 1   3 6104   20.55 . No   No 20.55 No diabetes Y Y N N N N Y N Y N N NARCAN none none CEFEPIME none none none none none
14 1 6106 No diabetes 0 0 0 0 0 4164 1131 45 2.891666667 45 18.85 No diabetes A1 16.32 Male Caucasian A+ Yes No 2.9 94 16 18.1 ANOXIA drowning TRUE 3 0 1 1   1 6106   7.36 . No   None 7.36 No diabetes Y Y N Y N N N N Y Y Y Albuterol Atrovent Nystatin Unasyn Mag Vitamin K Na Bicarb KCl Pavulon
15 13 6115 No diabetes 0 0 0 0 0 16117 848 45 11.19236111 45 14.13333333 No diabetes A 3.9 Male Caucasian A1- Yes No 0.42 64 7 17.1 ANOXIA sids TRUE 9 0 1 1   1 6115   4.59 . No   No 4.59 No diabetes Y Y N N N N N N Y Y N CEFEPIME none none GENTAMYCIN none none vancomycin none none
16 1 6117 No diabetes 0 0 0 0 0 4785 940 65 3.322916667 65 15.66666667 No diabetes B 5.4 Male Caucasian B- Yes No 0.33 66 8.5 18.4 HEAD TRAUMA blunt injury TRUE 6 0 1 1   1 6117   3.27 . No   No 3.27 No diabetes N Y N Y N N N Y Y N Y Dopamine KCL Zosyn Dextrose none none none none none
17 4 6126 No diabetes 0 0 0 0 0 7024 673 340 4.877777778 340 11.21666667 No diabetes O 80.2 Male Caucasian O+ Yes No 25.2 175.3 77 25.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1   3 6126   0.88 . No   No 0.88 No diabetes Y Y N Y N N N N Y Y N ANCEF none none none none none none none none
18 7 6129 No diabetes 0 0 0 0 0 6058 1132 75 4.206944444 75 18.86666667 No diabetes O 58.84 Female Caucasian O- Yes No 42.9 152.4 54 23.4 ANOXIA intracranial hemorrhage/stroke TRUE 6 0 2 1   3 6129   0.51 5.2 No   No 0.51 No diabetes Y Y N N N Y N N Y N Y zosyn none none none none none vecuronium none none
19 4 6131 No diabetes 0 0 0 0 0 2743 1127 120 1.904861111 120 18.78333333 No diabetes B 108.92 Male Caucasian B+ Yes Yes 24.2 182.9 83 24.8 ANOXIA drug intoxication TRUE 3 0 1 1   3 6131   1.01 . No   No 1.01 No diabetes Y N N Y N N N N Y Y N dopamine neo none levophed none none ancef vonco zoayn
20 13 6134 No diabetes 0 0 0 0 0 2905 1010 75 2.017361111 75 16.83333333 No diabetes O 82.42 Male Caucasian O+ Yes No 26.7 180.3 65 20.1 ANOXIA drug intoxication TRUE 3 0 1 1   3 6134   3.59 . No   No 3.59 No diabetes Y Y N Y N Y N N Y Y N NEO BICARB none MILRINONE CARDEINE none ANCEF none none
21 11 6140 No diabetes 0 0 0 0 0 11767 835 195 8.171527778 195 13.91666667 No diabetes A1 65.1 Male Caucasian A+ Yes No 38 170.2 59 21.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 1 1   3 6140   11.1 6 No   No 11.1 No diabetes Y Y N Y N Y N N Y Y Y ROCEPHIN VANCOMYCIN none NIMBEX none none BENADRYL none none
22 15 6144 No diabetes 0 0 0 0 0 34014 426 90 23.62083333 90 7.1 No diabetes B 45 Female Hispanic/Latino B+ Yes Yes 7.5 124.5 25 16.3 Respiratory Distress/Failure natural causes TRUE 9 0 2 2   1 6144   1.27 . No   No 1.27 No diabetes N N N N N N N N Y N N none none none none none none none none none
23 9 6162 No diabetes 0 0 0 0 0 2193 1203 115 1.522916667 115 20.05 No diabetes B 81.5 Male African Am B+ Yes No 22.7 188 102 28.9 HEAD TRAUMA gunshot wound TRUE 3 0 1 3   3 6162   7.61 . No   No 7.61 No diabetes N Y N Y N N N N Y Y N unasyn none none none none none none none none
24 5 6165 No diabetes 0 0 0 0 0 6815 985 120 4.732638889 120 16.41666667 No diabetes O 97.41 Female Caucasian O+ Yes No 45.8 165.1 68 25 CEREBROVASCULAR/STROKE   TRUE 6 0 2 1   3 6165   4.45 5.6 No   No 4.45 No diabetes N Y N N N Y N N Y N N NIMBEX NARCAN FENTANYL ALBUTEROL ATROVENT none ZOSYN TOBRAMYCIN CISATRACURIUM
25 14 6172 No diabetes 0 0 0 0 0 10358 999 135 7.193055556 135 16.65 No diabetes A1 59.7 Female Caucasian A+ Yes No 19.2 172.7 97 32.4 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1   2 6172   8.02 5.4 No     8.02 No diabetes Y Y N Y N N N Y Y Y Y none none none none none none none none none
26 3 6174 No diabetes 0 0 0 0 0 1181 604 135 0.820138889 135 10.06666667 No diabetes O 79.3 Male Caucasian O+ Yes No 20.8 196 75 19.5 CEREBROVASCULAR/STROKE blunt injury TRUE 3 0 1 1   3 6174   3 . No     3 No diabetes Y N N Y N N N N Y Y Y dobutamine none none levophed neosynephrine none Ancef none none
27 8 6178 No diabetes 0 0 0 0 0 9414 741 145 6.5375 145 12.35 No diabetes A1 72.7 Female Caucasian A+ Yes No 24.5 182 92 27.5 ANOXIA cardiovascular TRUE 9 0 2 1   3 6178   4.55 5 No     4.55 No diabetes Y Y N Y N N N N Y Y Y Fentanyl KCL Calcium Gluconate none none none none none none
28 4 6179 No diabetes 0 0 0 0 0 20106 1464 120 13.9625 120 24.4 No diabetes O 72.4 Female Caucasian O- Yes Yes 21.8 157.5 51 20.7 HEAD TRAUMA blunt injury TRUE 9 0 2 1   3 6179   2.74 . No     2.74 No diabetes Y N N N N N N N Y Y N Lacrilube NaHCO3 none none none none none none none
29 13 6187 No diabetes 0 0 0 0 0 5485 625 60 3.809027778 60 10.41666667 No diabetes O 5.8 Male Caucasian O+ Yes Yes 0.33 63.5 6.7 17.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1   1 6187   0.72 . No   None 0.72 No diabetes N N N N N N Y N Y N N Rocephin none none Vancomycin none none none none none
30 15 6200 No diabetes 0 0 0 0 0 3449 1456 30 2.395138889 30 24.26666667 No diabetes   4.29 Female Hispanic/Latino O+ No Unknown 0.006575343 41 2.2 14.5 Pulmonary hypoplasia respiratory TRUE 3 0 2 2   1 6200   0.2 .     None 0.2 No diabetes                       none none none none none none none none none
31 15 6219 No diabetes 0 0 0 0 0 6322 1124 90 4.390277778 90 18.73333333 No diabetes AB 4.99 Male Hispanic/Latino AB+ Yes No 0.5 66 7.4 17 HEAD TRAUMA blunt injury TRUE 6 0 1 2   1 6219   1.53 . No   None 1.53 No diabetes N Y N N N Y Y N Y Y N Versed Rocuronium none Fentanyl none none Ancef none none
32 8 6229 No diabetes 0 0 0 0 0 4489 835 100 3.117361111 100 13.91666667 No diabetes O 45.6 Female Caucasian O+ Yes No 31 156 65.5 26.9 HEAD TRAUMA blunt injury TRUE 6 0 2 1   3 6229   6.23 5.5 No   None 6.23 No diabetes Y Y N Y N N N N Y N Y Zosyn none none none none none none none none
33 3 6230 No diabetes 0 0 0 0 0 4368 947 130 3.033333333 130 15.78333333 No diabetes B 66.27 Male Caucasian B+ Yes No 16 173 56.7 18.9 HEAD TRAUMA gunshot wound TRUE 6 0 1 1   2 6230   5.22 5.3 No   None 5.22 No diabetes N N N Y N N N N Y Y Y duoneb zosyn none none fentanyl vecuronium none none levophed neosynephrine none
34 7 6235 No diabetes 0 0 0 0 0 3690 1020 120 2.5625 120 17 No diabetes O 102.31 Male Caucasian O+ Yes No 30 172.7 76 25.4 HEAD TRAUMA gunshot wound TRUE 3 0 1 1   3 6235   8.1 . No   None 8.1 No diabetes Y Y N N N N N N Y N N Ancef Levophed none Vecuronium none none none none none
35 5 6250 No diabetes 0 0 0 0 0 2732 1081 25 1.897222222 25 18.01666667 No diabetes O . Male Caucasian O+ Yes No 40 180.3 90.7 27.9 HEAD TRAUMA blunt injury TRUE 3 0 1 1   3 6250   7.31 . No   None 7.31 No diabetes Y Y N Y N N N N Y N Y cardizem none none cefazolin none none none none none
36 6 6251 No diabetes 0 0 0 0 0 5366 310 75 3.726388889 75 5.166666667 No diabetes A1 77.8 Female Caucasian A- Yes Yes 33 154.9 70 29.5 HEAD TRAUMA   TRUE 6 0 2 1   3 6251   1.92 5.3 No   None 1.92 No diabetes N N N N N N N N Y N N Ancef none none none none none none none none
37 9 6254 No diabetes 0 0 0 0 0 4677 1248 105 3.247916667 105 20.8 No diabetes A1B 69.9 Male Caucasian AB+ Yes Yes 38 167.6 86 30.5 ANOXIA asphyxiation TRUE 6 0 1 1   3 6254   6.43 5.3 No   None 6.43 No diabetes N N N N N N N N Y N Y Ancef none none none none none none none none
38 10 6278 No diabetes 0 0 0 0 0 2653 895 87 1.842361111 87 14.91666667 No diabetes   33.6 Female African Am A No Unknown 10 157.5 52.4 21.3 ANOXIA cardiovascular TRUE 3 0 2 3   1 6278   4.54 6.3 No   None 4.54 No diabetes Y Y N N N N N N Y Y Y Levophed none none Vancomycin Ephedrine none Vecuronium Neosynephrine none
39 14 6279 No diabetes 0 0 0 0 0 4860 2715 140 3.375 140 45.25 No diabetes   80.17 Male Caucasian O+ No Unknown 19 180.3 110.2 34 HEAD TRAUMA blunt injury TRUE 6 0 1 1   2 6279   8.01 . No   None 8.01 No diabetes N N N N N N N N Y N Y Ceftriaxone none none Lansoprazole none none none none none

Processing of medications (entered in open text fields) to categories proceeded in a series of steps outlined below.

In [73]:
/********step 1: Imported groupings of previously identified medications into categories 
          (see Kaddis et al, AJT, 2010; Campbell-Thompson et al, JAMA, 2012) for use in comparison.*/

PROC import datafile='med_list_categories.txt' out=categories dbms=dlm replace;
     delimiter='09'x;
     getnames=yes;
     guessingrows=1000;
run;
quit;

/********step 2: merge categories with med list*/

DATA opentextmerge;
     merge study4 categories;
run;

/********step 3: clean up medication list, i.e. change letters to all lowercase, remove white space between words*/

DATA opentextmerge1;
    set opentextmerge; 
    dmed_other1	=	lowcase	(	dmed_other1	)	;
    dmed_other2	=	lowcase	(	dmed_other2	)	;
    dmed_other3	=	lowcase	(	dmed_other3	)	;
    dmed_other4	=	lowcase	(	dmed_other4	)	;
    dmed_other5	=	lowcase	(	dmed_other5	)	;
    dmed_other6	=	lowcase	(	dmed_other6	)	;
    dmed_other7	=	lowcase	(	dmed_other7	)	;
    dmed_other8	=	lowcase	(	dmed_other8	)	;
    dmed_other9	=	lowcase	(	dmed_other9	)	;
   
    anestetics	=	lowcase	(	anestetics	)	;
    antibiotics	=	lowcase	(	antibiotics	)	;
    cardiovascular	=	lowcase	(	cardiovascular	)	;
    hormonal	=	lowcase	(	hormonal	)	;
    others	=	lowcase	(	others	)	;
    fluids_electrolytes	=	lowcase	(	fluids_electrolytes	)	;

    dmed_other1	=	kcompress	(	dmed_other1	)	;
    dmed_other2	=	kcompress	(	dmed_other2	)	;
    dmed_other3	=	kcompress	(	dmed_other3	)	;
    dmed_other4	=	kcompress	(	dmed_other4	)	;
    dmed_other5	=	kcompress	(	dmed_other5	)	;
    dmed_other6	=	kcompress	(	dmed_other6	)	;
    dmed_other7	=	kcompress	(	dmed_other7	)	;
    dmed_other8	=	kcompress	(	dmed_other8	)	;
    dmed_other9	=	kcompress	(	dmed_other9	)	;

    anestetics	=	kcompress	(	anestetics	)	;
    antibiotics	=	kcompress	(	antibiotics	)	;
    cardiovascular	=	kcompress	(	cardiovascular	)	;
    hormonal	=	kcompress	(	hormonal	)	;
    others	=	kcompress	(	others	)	;
    fluids_electrolytes	=	kcompress	(	fluids_electrolytes	)	;
run;

/********step 4: double-check categories dataset to make sure that a drug does not appear in more than 1 category*/

PROC iml;
    use opentextmerge1;
    /*creation of matrix from variables (n by 1 column matrix for each variable*/
    read all var {'anestetics'} into anestetics;
    read all var {'antibiotics'} into antibiotics;
    read all var {'cardiovascular'} into cardiovascular;
    read all var {'hormonal'} into hormonal;
    read all var {'others'} into others;
    read all var {'fluids_electrolytes'} into fluids_electrolytes;

    /*matrix initiation*/
    b=138; /*number of medications in longest list of (Anestetics, Antibiotics, Cardiovascular, Hormonal, Others, Fluids_Electrolytes)*/
    c=6; /*number of categories in list*/
    d=138;

    /*create macro and DO loop for matrix calculations*/
    %macro evaluation;   

    dmedrecode=j(b,c,0);

	do n=1 to b; /*number of records being examined for each variable*/
		do p=1 to d; /*max number of different entries in variable list that need to be checked*/
			/*coding notes: anestetics=1, antibiotics=2, cardiovascular=3, hormonal=4, others=5, fluids_electrolytes=6*/
			if (anestetics[n]=antibiotics[p]) then dmedrecode[n,1]=1; 
			if (anestetics[n]=cardiovascular[p]) then dmedrecode[n,1]=1; 
			if (anestetics[n]=hormonal[p]) then dmedrecode[n,1]=1; 
			if (anestetics[n]=others[p]) then dmedrecode[n,1]=1; 
			if (anestetics[n]=fluids_electrolytes[p]) then dmedrecode[n,1]=1; 

			if (antibiotics[n]=anestetics[p]) then dmedrecode[n,2]=1; 
			if (antibiotics[n]=cardiovascular[p]) then dmedrecode[n,2]=1; 
			if (antibiotics[n]=hormonal[p]) then dmedrecode[n,2]=1; 
			if (antibiotics[n]=others[p]) then dmedrecode[n,2]=1; 
			if (antibiotics[n]=fluids_electrolytes[p]) then dmedrecode[n,2]=1; 
			
			if (cardiovascular[n]=anestetics[p]) then dmedrecode[n,3]=1; 
			if (cardiovascular[n]=antibiotics[p]) then dmedrecode[n,3]=1; 
 			if (cardiovascular[n]=hormonal[p]) then dmedrecode[n,3]=1; 
			if (cardiovascular[n]=others[p]) then dmedrecode[n,3]=1; 
			if (cardiovascular[n]=fluids_electrolytes[p]) then dmedrecode[n,3]=1; 
			
			if (hormonal[n]=anestetics[p]) then dmedrecode[n,4]=1; 
			if (hormonal[n]=antibiotics[p]) then dmedrecode[n,4]=1; 
			if (hormonal[n]=cardiovascular[p]) then dmedrecode[n,4]=1; 
			if (hormonal[n]=others[p]) then dmedrecode[n,4]=1; 
			if (hormonal[n]=fluids_electrolytes[p]) then dmedrecode[n,4]=1; 

			if (others[n]=anestetics[p]) then dmedrecode[n,5]=1; 
			if (others[n]=antibiotics[p]) then dmedrecode[n,5]=1; 
			if (others[n]=hormonal[p]) then dmedrecode[n,5]=1; 
			if (others[n]=cardiovascular[p]) then dmedrecode[n,5]=1; 
			if (others[n]=fluids_electrolytes[p]) then dmedrecode[n,5]=1; 

			if (fluids_electrolytes[n]=anestetics[p]) then dmedrecode[n,6]=1; 
			if (fluids_electrolytes[n]=antibiotics[p]) then dmedrecode[n,6]=1; 
			if (fluids_electrolytes[n]=hormonal[p]) then dmedrecode[n,6]=1; 
			if (fluids_electrolytes[n]=cardiovascular[p]) then dmedrecode[n,6]=1; 
			if (fluids_electrolytes[n]=others[p]) then dmedrecode[n,6]=1;

end;
	end;

/*create matrix*/
create compare from dmedrecode;
append from dmedrecode;
close compare;

%mend evaluation;    
%evaluation;

quit;


data merged;
merge categories compare;
run;


proc freq data=compare;
tables col1 col2 col3 col4 col5 col6;
run;

/*NOTE: To interpret the results, compare the number of medications in each category to the frequency of 0's in the column.  
If they match, medications are not repeated across categories.  For example, there are 66 medications listed under anestetics and
the freq of 0's in col1 is 66; thus successful.  All columns pass*/


/********step 5: code open text medication fields into categories*/

proc iml;
    use opentextmerge1;
    /*creation of matrix from variables (n by 1 column matrix for each variable*/
    read all var {'dmed_other1'} into dmed1;
    read all var {'dmed_other2'} into dmed2;
    read all var {'dmed_other3'} into dmed3;
    read all var {'dmed_other4'} into dmed4;
    read all var {'dmed_other5'} into dmed5;
    read all var {'dmed_other6'} into dmed6;
    read all var {'dmed_other7'} into dmed7;
    read all var {'dmed_other8'} into dmed8;
    read all var {'dmed_other9'} into dmed9;

    read all var {'anestetics'} into anestetics;
    read all var {'antibiotics'} into antibiotics;
    read all var {'cardiovascular'} into cardiovascular;
    read all var {'hormonal'} into hormonal;
    read all var {'others'} into others;
    read all var {'fluids_electrolytes'} into fluids_electrolytes;

    /*matrix initiation*/
    a=39; /*number of donor records*/
    b=138; /*number of entries in longest list of (Anestetics, Antibiotics, Cardiovascular, Hormonal, Others)*/
    c=9; /*number of open text field variable names (i.e. dmed_other 1-9) that need to be re-coded*/

    /*create macro and DO loop for matrix calculations*/
    %macro evaluation;   

    dmedrecode=j(a,c,0);

    %do m=1 %to 9; /*number of open text field names that need to be re-coded*/
	do n=1 to a; /*number of donors being examined for each variable*/
		do p=1 to b; /*number of entries in variable list that need to be checked*/
			/*coding notes: anestetics=1, antibiotics=2, cardiovascular=3, hormonal=4, others=5, fluids_electrolytes=6*/
			if (dmed&m[n]=anestetics[p]) then dmedrecode[n,&m]=1; 
			if (dmed&m[n]=antibiotics[p]) then dmedrecode[n,&m]=2; 
			if (dmed&m[n]=cardiovascular[p]) then dmedrecode[n,&m]=3; 
			if (dmed&m[n]=hormonal[p]) then dmedrecode[n,&m]=4; 
			if (dmed&m[n]=others[p]) then dmedrecode[n,&m]=5; 
			if (dmed&m[n]=fluids_electrolytes[p]) then dmedrecode[n,&m]=6; 
		end;
	end;
%end;

    /*create matrix*/
    create textmedrecode from dmedrecode;
    append from dmedrecode;
    close textmedrecode;

    %mend evaluation;    
    %evaluation;

quit;

/*check to make sure all the text meds were re-coded into a category*/

proc freq data=textmedrecode;
tables col1 col2 col3 col4 col5 col6 col7 col8 col9;
run;


/*open up flags, see which meds are flagged,add to categories, then re-run*/

data flags;
merge opentextmerge1 textmedrecode;
run;

data flags1;
    set flags;
    if dmed_other1^="none" and col1=0 then flags1=1;
    if dmed_other2^="none" and col1=0 then flags2=1;
    if dmed_other3^="none" and col1=0 then flags3=1;
    if dmed_other4^="none" and col1=0 then flags4=1;
    if dmed_other5^="none" and col1=0 then flags5=1;
    if dmed_other6^="none" and col1=0 then flags6=1;
    if dmed_other7^="none" and col1=0 then flags7=1;
    if dmed_other8^="none" and col1=0 then flags8=1;
    if dmed_other9^="none" and col1=0 then flags9=1;
run;


/********step 6: join coded medication list into main study data table*/

DATA study5;
     merge study4 textmedrecode;
run;
Out[73]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

COL1 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 66 47.83 66 47.83
1 72 52.17 138 100.00
COL2 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 138 100.00 138 100.00
COL3 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 112 81.16 112 81.16
1 26 18.84 138 100.00
COL4 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 20 14.49 20 14.49
1 118 85.51 138 100.00
COL5 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 65 47.10 65 47.10
1 73 52.90 138 100.00
COL6 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 111 80.43 111 80.43
1 27 19.57 138 100.00

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

COL1 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 4 10.26 4 10.26
1 6 15.38 10 25.64
2 19 48.72 29 74.36
3 7 17.95 36 92.31
5 3 7.69 39 100.00
COL2 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 28 71.79 28 71.79
1 2 5.13 30 76.92
2 2 5.13 32 82.05
3 1 2.56 33 84.62
5 2 5.13 35 89.74
6 4 10.26 39 100.00
COL3 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 34 87.18 34 87.18
1 2 5.13 36 92.31
2 2 5.13 38 97.44
6 1 2.56 39 100.00
COL4 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 17 43.59 17 43.59
1 5 12.82 22 56.41
2 10 25.64 32 82.05
3 4 10.26 36 92.31
5 1 2.56 37 94.87
6 2 5.13 39 100.00
COL5 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 32 82.05 32 82.05
2 1 2.56 33 84.62
3 3 7.69 36 92.31
5 1 2.56 37 94.87
6 2 5.13 39 100.00
COL6 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 37 94.87 37 94.87
1 1 2.56 38 97.44
5 1 2.56 39 100.00
COL7 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 22 56.41 22 56.41
1 2 5.13 24 61.54
2 8 20.51 32 82.05
3 2 5.13 34 87.18
5 2 5.13 36 92.31
6 3 7.69 39 100.00
COL8 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 34 87.18 34 87.18
2 1 2.56 35 89.74
3 2 5.13 37 94.87
5 1 2.56 38 97.44
6 1 2.56 39 100.00
COL9 Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 36 92.31 36 92.31
1 2 5.13 38 97.44
2 1 2.56 39 100.00

wilcoxon rank sum for Processing_Time_Minutes1 on group1

Obs set_num ptid Donor_Type Organ_Received_Datetime_Flag Organ_Frozen_Datetime_Flag Admit_Datetime_Flag Braindeath_Datetime_Flag Xclamp_Datetime_Flag Hospitalization_Stay_Minutes Transport_Duration_Minutes Processing_Time_Minutes Hospitalization_Stay_Days Processing_Time_Minutes1 transport_duration_hours DonorType abo_subtype oppc_PancreasWT oppc_Gender oppc_Ethnicity oppc_ABO multi_organ_donor non_hrt_beat_donor oppc_ageR oppc_heightR oppc_weightR oppc_bmiR cod_final death_mech_final replace hospbin donor sex ethnicity clamp_Datetime_Flag age_group nPODCaseID diabetes_Duration_yrs oppc_C_peptideR oppc_HbA1cR diabetes_history insulin_depd insulin_meds_taken cpeptide dataSetsDemographicsDonorType pt_steroids pt_diuretics pt_t3 pt_t4 anticonv antihype vasodil ddavp heparin arginine insulin dmed_other1 dmed_other2 dmed_other3 dmed_other4 dmed_other5 dmed_other6 dmed_other7 dmed_other8 dmed_other9 COL1 COL2 COL3 COL4 COL5 COL6 COL7 COL8 COL9
1 6 6003 No diabetes 0 0 0 0 0 3994 84 30 2.773611111 30 1.4 No diabetes O . Female Caucasian O+ Yes No 23 160 75 29.3 HEAD TRAUMA blunt injury TRUE 3 0 2 1   3 6003   . . No   None . No diabetes Y Y N Y Y N N N Y N N CEFEPIME none none DOPAMINE none none CLINDAMYCIN none none 2 0 0 3 0 0 2 0 0
2 1 6005 No diabetes 0 0 0 0 0 9184 1496 30 6.377777778 30 24.93333333 No diabetes A1 . Female Caucasian A- Yes No 5 104 17 15.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1   1 6005   . . No   None . No diabetes Y Y N N N N N N Y N Y MYCAMINE none none NARCAN none none REGATINE none none 2 0 0 1 0 0 3 0 0
3 3 6007 No diabetes 0 0 0 0 0 9985 264 20 6.934027778 20 4.4 No diabetes O . Male African Am O+ Yes No 9 143 41 20 ANOXIA   TRUE 9 0 1 3   1 6007   . . No   None . No diabetes Y Y N Y Y N Y N Y N Y ANCEF none none none none none none none none 2 0 0 0 0 0 0 0 0
4 7 6008 No diabetes 0 0 0 0 0 15058 112 30 10.45694444 30 1.866666667 No diabetes O . Female Caucasian O+ Yes Yes 50 160 62 24.2 HEAD TRAUMA blunt injury TRUE 9 0 2 1   3 6008   . . No   None . No diabetes N N N N Y N N N N N Y CEFEPINE none none ANCF none none KCL none none 2 0 0 2 0 0 6 0 0
5 5 6011 No diabetes 0 0 0 0 0 40531 59 42 28.14652778 42 0.983333333 No diabetes O . Female African Am O+ Yes No 46 163 70 26.3 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 3   3 6011   . . No   None . No diabetes Y Y N N N N N N Y N N PROPOFOL none none PENTOBARB none none VANC none none 1 0 0 0 0 0 0 0 0
6 9 6019 No diabetes 0 0 0 0 0 11642 215 40 8.084722222 40 3.583333333 No diabetes O . Male Caucasian O- Yes No 42 175 95 31 HEAD TRAUMA intracranial hemorrhage/stroke TRUE 9 0 1 1   3 6019   0.47 5.6 No   None 0.47 No diabetes Y Y N Y Y Y N N Y N Y NARCAN none none FACTOR 7 none none D5D none none 1 0 0 0 0 0 0 0 0
7 10 6047 No diabetes 0 0 0 0 0 4851 737 30 3.36875 30 12.28333333 No diabetes O 53.02 Male Caucasian O- Yes No 7.8 111.8 30 23.9 ANOXIA drowning TRUE 6 0 1 1   1 6047   0.65 5.5 No   No 0.65 No diabetes Y Y N Y Y N Y N Y Y Y CLEOCIN none none none none none none none none 2 0 0 0 0 0 0 0 0
8 11 6048 No diabetes 0 0 0 0 0 1927 368 55 1.338194444 55 6.133333333 No diabetes O 139 Male Caucasian O- Yes No 30 165.1 56 20.6 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 3 0 1 1   3 6048   17.91 . No   No 17.91 No diabetes Y Y N N N N Y Y Y Y N CEFEPIME none none VANCOMYCIN none none PROTONIX none none 2 0 0 2 0 0 5 0 0
9 10 6057 No diabetes 0 0 0 0 0 12416 709 255 8.622222222 255 11.81666667 No diabetes O 104.36 Male Caucasian O+ Yes No 22 188 92 26 HEAD TRAUMA blunt injury TRUE 9 0 1 1   3 6057   16.23 . No   No 16.23 No diabetes N Y N N N N Y N Y N N none none none none none none none none none 0 0 0 0 0 0 0 0 0
10 6 6060 No diabetes 0 0 0 0 0 13119 396 215 9.110416667 215 6.6 No diabetes A1 104 Male Caucasian A+ Yes No 24 175.3 100 32.7 HEAD TRAUMA blunt injury TRUE 9 0 1 1   3 6060   13.63 . No   No 13.63 No diabetes N Y N Y N N Y N Y N N COLACE PROTONIX PROPOFOL CLOACIN LEVAQUIN MORPHINE VANCOMYCIN AMINOPHLLINE none 5 5 1 2 2 1 2 5 0
11 14 6073 No diabetes 0 0 0 0 0 3560 754 50 2.472222222 50 12.56666667 No diabetes O 66.5 Male Caucasian O+ Yes No 19.2 165.1 98 36 ANOXIA cardiovascular TRUE 3 0 1 1   2 6073   0.69 . Unknown   No 0.69 No diabetes Y Y Y N N N N Y Y Y Y Invanz none none Magnesium none none potassium chloride none none 2 0 0 6 0 0 6 0 0
12 8 6099 No diabetes 0 1 0 0 0 2945 890 . 2.045138889 . 14.83333333 No diabetes A2B 85.56 Male Caucasian AB+ Yes No 14.2 175.3 92 30 HEAD TRAUMA blunt injury TRUE 3 0 1 1   2 6099   5.37 . No   No 5.37 No diabetes Y Y N Y N N N N Y Y Y neosynephrine none none merrem KCL none flolan none none 3 0 0 2 6 0 0 0 0
13 11 6104 No diabetes 0 1 0 0 0 4703 352 . 3.265972222 . 5.866666667 No diabetes O 55.2 Male Caucasian O+ Yes No 41 190.5 74 20.5 ANOXIA drug intoxication TRUE 6 0 1 1   3 6104   20.55 . No   No 20.55 No diabetes Y Y N N N N Y N Y N N NARCAN none none CEFEPIME none none none none none 1 0 0 2 0 0 0 0 0
14 1 6106 No diabetes 0 0 0 0 0 4164 1131 45 2.891666667 45 18.85 No diabetes A1 16.32 Male Caucasian A+ Yes No 2.9 94 16 18.1 ANOXIA drowning TRUE 3 0 1 1   1 6106   7.36 . No   None 7.36 No diabetes Y Y N Y N N N N Y Y Y Albuterol Atrovent Nystatin Unasyn Mag Vitamin K Na Bicarb KCl Pavulon 5 5 2 2 6 5 6 6 1
15 13 6115 No diabetes 0 0 0 0 0 16117 848 45 11.19236111 45 14.13333333 No diabetes A 3.9 Male Caucasian A1- Yes No 0.42 64 7 17.1 ANOXIA sids TRUE 9 0 1 1   1 6115   4.59 . No   No 4.59 No diabetes Y Y N N N N N N Y Y N CEFEPIME none none GENTAMYCIN none none vancomycin none none 2 0 0 2 0 0 2 0 0
16 1 6117 No diabetes 0 0 0 0 0 4785 940 65 3.322916667 65 15.66666667 No diabetes B 5.4 Male Caucasian B- Yes No 0.33 66 8.5 18.4 HEAD TRAUMA blunt injury TRUE 6 0 1 1   1 6117   3.27 . No   No 3.27 No diabetes N Y N Y N N N Y Y N Y Dopamine KCL Zosyn Dextrose none none none none none 3 6 2 6 0 0 0 0 0
17 4 6126 No diabetes 0 0 0 0 0 7024 673 340 4.877777778 340 11.21666667 No diabetes O 80.2 Male Caucasian O+ Yes No 25.2 175.3 77 25.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1   3 6126   0.88 . No   No 0.88 No diabetes Y Y N Y N N N N Y Y N ANCEF none none none none none none none none 2 0 0 0 0 0 0 0 0
18 7 6129 No diabetes 0 0 0 0 0 6058 1132 75 4.206944444 75 18.86666667 No diabetes O 58.84 Female Caucasian O- Yes No 42.9 152.4 54 23.4 ANOXIA intracranial hemorrhage/stroke TRUE 6 0 2 1   3 6129   0.51 5.2 No   No 0.51 No diabetes Y Y N N N Y N N Y N Y zosyn none none none none none vecuronium none none 2 0 0 0 0 0 1 0 0
19 4 6131 No diabetes 0 0 0 0 0 2743 1127 120 1.904861111 120 18.78333333 No diabetes B 108.92 Male Caucasian B+ Yes Yes 24.2 182.9 83 24.8 ANOXIA drug intoxication TRUE 3 0 1 1   3 6131   1.01 . No   No 1.01 No diabetes Y N N Y N N N N Y Y N dopamine neo none levophed none none ancef vonco zoayn 3 2 0 3 0 0 2 0 2
20 13 6134 No diabetes 0 0 0 0 0 2905 1010 75 2.017361111 75 16.83333333 No diabetes O 82.42 Male Caucasian O+ Yes No 26.7 180.3 65 20.1 ANOXIA drug intoxication TRUE 3 0 1 1   3 6134   3.59 . No   No 3.59 No diabetes Y Y N Y N Y N N Y Y N NEO BICARB none MILRINONE CARDEINE none ANCEF none none 2 6 0 3 3 0 2 0 0
21 11 6140 No diabetes 0 0 0 0 0 11767 835 195 8.171527778 195 13.91666667 No diabetes A1 65.1 Male Caucasian A+ Yes No 38 170.2 59 21.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 1 1   3 6140   11.1 6 No   No 11.1 No diabetes Y Y N Y N Y N N Y Y Y ROCEPHIN VANCOMYCIN none NIMBEX none none BENADRYL none none 2 2 0 1 0 0 5 0 0
22 15 6144 No diabetes 0 0 0 0 0 34014 426 90 23.62083333 90 7.1 No diabetes B 45 Female Hispanic/Latino B+ Yes Yes 7.5 124.5 25 16.3 Respiratory Distress/Failure natural causes TRUE 9 0 2 2   1 6144   1.27 . No   No 1.27 No diabetes N N N N N N N N Y N N none none none none none none none none none 0 0 0 0 0 0 0 0 0
23 9 6162 No diabetes 0 0 0 0 0 2193 1203 115 1.522916667 115 20.05 No diabetes B 81.5 Male African Am B+ Yes No 22.7 188 102 28.9 HEAD TRAUMA gunshot wound TRUE 3 0 1 3   3 6162   7.61 . No   No 7.61 No diabetes N Y N Y N N N N Y Y N unasyn none none none none none none none none 2 0 0 0 0 0 0 0 0
24 5 6165 No diabetes 0 0 0 0 0 6815 985 120 4.732638889 120 16.41666667 No diabetes O 97.41 Female Caucasian O+ Yes No 45.8 165.1 68 25 CEREBROVASCULAR/STROKE   TRUE 6 0 2 1   3 6165   4.45 5.6 No   No 4.45 No diabetes N Y N N N Y N N Y N N NIMBEX NARCAN FENTANYL ALBUTEROL ATROVENT none ZOSYN TOBRAMYCIN CISATRACURIUM 1 1 1 5 5 0 2 2 1
25 14 6172 No diabetes 0 0 0 0 0 10358 999 135 7.193055556 135 16.65 No diabetes A1 59.7 Female Caucasian A+ Yes No 19.2 172.7 97 32.4 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1   2 6172   8.02 5.4 No     8.02 No diabetes Y Y N Y N N N Y Y Y Y none none none none none none none none none 0 0 0 0 0 0 0 0 0
26 3 6174 No diabetes 0 0 0 0 0 1181 604 135 0.820138889 135 10.06666667 No diabetes O 79.3 Male Caucasian O+ Yes No 20.8 196 75 19.5 CEREBROVASCULAR/STROKE blunt injury TRUE 3 0 1 1   3 6174   3 . No     3 No diabetes Y N N Y N N N N Y Y Y dobutamine none none levophed neosynephrine none Ancef none none 3 0 0 3 3 0 2 0 0
27 8 6178 No diabetes 0 0 0 0 0 9414 741 145 6.5375 145 12.35 No diabetes A1 72.7 Female Caucasian A+ Yes No 24.5 182 92 27.5 ANOXIA cardiovascular TRUE 9 0 2 1   3 6178   4.55 5 No     4.55 No diabetes Y Y N Y N N N N Y Y Y Fentanyl KCL Calcium Gluconate none none none none none none 1 6 6 0 0 0 0 0 0
28 4 6179 No diabetes 0 0 0 0 0 20106 1464 120 13.9625 120 24.4 No diabetes O 72.4 Female Caucasian O- Yes Yes 21.8 157.5 51 20.7 HEAD TRAUMA blunt injury TRUE 9 0 2 1   3 6179   2.74 . No     2.74 No diabetes Y N N N N N N N Y Y N Lacrilube NaHCO3 none none none none none none none 5 6 0 0 0 0 0 0 0
29 13 6187 No diabetes 0 0 0 0 0 5485 625 60 3.809027778 60 10.41666667 No diabetes O 5.8 Male Caucasian O+ Yes Yes 0.33 63.5 6.7 17.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1   1 6187   0.72 . No   None 0.72 No diabetes N N N N N N Y N Y N N Rocephin none none Vancomycin none none none none none 2 0 0 2 0 0 0 0 0
30 15 6200 No diabetes 0 0 0 0 0 3449 1456 30 2.395138889 30 24.26666667 No diabetes   4.29 Female Hispanic/Latino O+ No Unknown 0.006575343 41 2.2 14.5 Pulmonary hypoplasia respiratory TRUE 3 0 2 2   1 6200   0.2 .     None 0.2 No diabetes                       none none none none none none none none none 0 0 0 0 0 0 0 0 0
31 15 6219 No diabetes 0 0 0 0 0 6322 1124 90 4.390277778 90 18.73333333 No diabetes AB 4.99 Male Hispanic/Latino AB+ Yes No 0.5 66 7.4 17 HEAD TRAUMA blunt injury TRUE 6 0 1 2   1 6219   1.53 . No   None 1.53 No diabetes N Y N N N Y Y N Y Y N Versed Rocuronium none Fentanyl none none Ancef none none 1 1 0 1 0 0 2 0 0
32 8 6229 No diabetes 0 0 0 0 0 4489 835 100 3.117361111 100 13.91666667 No diabetes O 45.6 Female Caucasian O+ Yes No 31 156 65.5 26.9 HEAD TRAUMA blunt injury TRUE 6 0 2 1   3 6229   6.23 5.5 No   None 6.23 No diabetes Y Y N Y N N N N Y N Y Zosyn none none none none none none none none 2 0 0 0 0 0 0 0 0
33 3 6230 No diabetes 0 0 0 0 0 4368 947 130 3.033333333 130 15.78333333 No diabetes B 66.27 Male Caucasian B+ Yes No 16 173 56.7 18.9 HEAD TRAUMA gunshot wound TRUE 6 0 1 1   2 6230   5.22 5.3 No   None 5.22 No diabetes N N N Y N N N N Y Y Y duoneb zosyn none none fentanyl vecuronium none none levophed neosynephrine none 3 0 0 1 0 0 3 3 0
34 7 6235 No diabetes 0 0 0 0 0 3690 1020 120 2.5625 120 17 No diabetes O 102.31 Male Caucasian O+ Yes No 30 172.7 76 25.4 HEAD TRAUMA gunshot wound TRUE 3 0 1 1   3 6235   8.1 . No   None 8.1 No diabetes Y Y N N N N N N Y N N Ancef Levophed none Vecuronium none none none none none 2 3 0 1 0 0 0 0 0
35 5 6250 No diabetes 0 0 0 0 0 2732 1081 25 1.897222222 25 18.01666667 No diabetes O . Male Caucasian O+ Yes No 40 180.3 90.7 27.9 HEAD TRAUMA blunt injury TRUE 3 0 1 1   3 6250   7.31 . No   None 7.31 No diabetes Y Y N Y N N N N Y N Y cardizem none none cefazolin none none none none none 3 0 0 2 0 0 0 0 0
36 6 6251 No diabetes 0 0 0 0 0 5366 310 75 3.726388889 75 5.166666667 No diabetes A1 77.8 Female Caucasian A- Yes Yes 33 154.9 70 29.5 HEAD TRAUMA   TRUE 6 0 2 1   3 6251   1.92 5.3 No   None 1.92 No diabetes N N N N N N N N Y N N Ancef none none none none none none none none 2 0 0 0 0 0 0 0 0
37 9 6254 No diabetes 0 0 0 0 0 4677 1248 105 3.247916667 105 20.8 No diabetes A1B 69.9 Male Caucasian AB+ Yes Yes 38 167.6 86 30.5 ANOXIA asphyxiation TRUE 6 0 1 1   3 6254   6.43 5.3 No   None 6.43 No diabetes N N N N N N N N Y N Y Ancef none none none none none none none none 2 0 0 0 0 0 0 0 0
38 10 6278 No diabetes 0 0 0 0 0 2653 895 87 1.842361111 87 14.91666667 No diabetes   33.6 Female African Am A No Unknown 10 157.5 52.4 21.3 ANOXIA cardiovascular TRUE 3 0 2 3   1 6278   4.54 6.3 No   None 4.54 No diabetes Y Y N N N N N N Y Y Y Levophed none none Vancomycin Ephedrine none Vecuronium Neosynephrine none 3 0 0 2 3 0 1 3 0
39 14 6279 No diabetes 0 0 0 0 0 4860 2715 140 3.375 140 45.25 No diabetes   80.17 Male Caucasian O+ No Unknown 19 180.3 110.2 34 HEAD TRAUMA blunt injury TRUE 6 0 1 1   2 6279   8.01 . No   None 8.01 No diabetes N N N N N N N N Y N Y Ceftriaxone none none Lansoprazole none none none none none 2 0 0 0 0 0 0 0 0

Now we need to re-code the pre-coded donor management medications (eg steroids, diuretics, etc) and integrate them into the categories

In [75]:
DATA study6;
    set study5;
    pt_steroids1=0 	;
    pt_diuretics1=0 	;
    pt_t31=0        	;
    pt_t41=0        	;
    anticonv1=0     	;
    antihype1=0      	;
    vasodi1l=0      	;
    ddavp1=0        	;
    heparin1=0      	;
    arginine1=0     	;
    insulin1=0      	;
    if pt_steroids='Y'  	then	pt_steroids1=4  	;
    if pt_diuretics='Y' 	then	pt_diuretics1=3 	;
    if pt_t3='Y'        	then	pt_t31=4        	;
    if pt_t4='Y'        	then	pt_t41=4        	;
    if anticonv='Y'     	then	anticonv1=5     	;
    if antihype='Y'      	then	antihype1=3      	;
    if vasodil='Y'      	then	vasodi1l=3      	;
    if ddavp='Y'        	then	ddavp1=3        	;
    if heparin='Y'      	then	heparin1=5      	;
    if arginine='Y'     	then	arginine1=3     	;
    if insulin='Y'      	then	insulin1=4      	;
run;

/*donormedsreceived=0 means the donor never received a single drug during the hospital stay, 
  =1 means that donor received 1 or more meds*/

DATA study7;
    set study6;
    donormedsreceived=1;
    if (pt_diuretics1=0 and pt_t31=0  and pt_t41=0 and anticonv1=0 and antihype1=0 and vasodi1l=0 and ddavp1=0 and heparin1=0 and arginine1=0 and insulin1=0 and col1=0 and col2=0 and col3=0 and col4=0 and col5=0 and col6=0 and col7=0 and col8=0 and col9=0) then donormedsreceived=0;
    anestetics=0;
    antibiotics=0;
    cardiovascular=0;
    hormonal=0;
    others=0;
    fluids_electrolytes=0;
    if (pt_diuretics1=1 or pt_t31=1  or pt_t41=1 or anticonv1=1 or antihype1=1 or vasodi1l=1 or ddavp1=1 or heparin1=1 or arginine1=1 or insulin1=1 or col1=1 or col2=1 or col3=1 or col4=1 or col5=1 or col6=1 or col7=1 or col8=1 or col9=1 ) then anestetics=1;
    if (pt_diuretics1=2 or pt_t31=2  or pt_t41=2 or anticonv1=2 or antihype1=2 or vasodi1l=2 or ddavp1=2 or heparin1=2 or arginine1=2 or insulin1=2 or col1=2 or col2=2 or col3=2 or col4=2 or col5=2 or col6=2 or col7=2 or col8=2 or col9=2 ) then antibiotics=2;
    if (pt_diuretics1=3 or pt_t31=3  or pt_t41=3 or anticonv1=3 or antihype1=3 or vasodi1l=3 or ddavp1=3 or heparin1=3 or arginine1=3 or insulin1=3 or col1=3 or col2=3 or col3=3 or col4=3 or col5=3 or col6=3 or col7=3 or col8=3 or col9=3 ) then cardiovascular=3;
    if (pt_diuretics1=4 or pt_t31=4  or pt_t41=4 or anticonv1=4 or antihype1=4 or vasodi1l=4 or ddavp1=4 or heparin1=4 or arginine1=4 or insulin1=4 or col1=4 or col2=4 or col3=4 or col4=4 or col5=4 or col6=4 or col7=4 or col8=4 or col9=4 ) then hormonal=4;
    if (pt_diuretics1=5 or pt_t31=5  or pt_t41=5 or anticonv1=5 or antihype1=5 or vasodi1l=5 or ddavp1=5 or heparin1=5 or arginine1=5 or insulin1=5 or col1=5 or col2=5 or col3=5 or col4=5 or col5=5 or col6=5 or col7=5 or col8=5 or col9=5 ) then others=5;
    if (pt_diuretics1=6 or pt_t31=6  or pt_t41=6 or anticonv1=6 or antihype1=6 or vasodi1l=6 or ddavp1=6 or heparin1=6 or arginine1=6 or insulin1=6 or col1=6 or col2=6 or col3=6 or col4=6 or col5=6 or col6=6 or col7=6 or col8=6 or col9=6 ) then fluids_electrolytes=6;
run;

PROC freq data=study7;
    tables donormedsreceived anestetics antibiotics cardiovascular hormonal others fluids_electrolytes;
run;

PROC freq data=study7;
    tables hospbin*donormedsreceived hospbin*anestetics hospbin*antibiotics hospbin*cardiovascular hospbin*hormonal hospbin*others hospbin*fluids_electrolytes;
run;
Out[75]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

donormedsreceived Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 1 2.56 1 2.56
1 38 97.44 39 100.00
anestetics Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 25 64.10 25 64.10
1 14 35.90 39 100.00
antibiotics Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 9 23.08 9 23.08
2 30 76.92 39 100.00
cardiovascular Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 6 15.38 6 15.38
3 33 84.62 39 100.00
hormonal Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 13 33.33 13 33.33
4 26 66.67 39 100.00
others Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 1 2.56 1 2.56
5 38 97.44 39 100.00
fluids_electrolytes Frequency Percent Cumulative
Frequency
Cumulative
Percent
0 31 79.49 31 79.49
6 8 20.51 39 100.00

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

Frequency
Percent
Row Pct
Col Pct
Table of hospbin by donormedsreceived
hospbin donormedsreceived
0 1 Total
3
1
2.56
7.69
100.00
12
30.77
92.31
31.58
13
33.33
 
 
6
0
0.00
0.00
0.00
13
33.33
100.00
34.21
13
33.33
 
 
9
0
0.00
0.00
0.00
13
33.33
100.00
34.21
13
33.33
 
 
Total
1
2.56
38
97.44
39
100.00
Frequency
Percent
Row Pct
Col Pct
Table of hospbin by anestetics
hospbin anestetics
0 1 Total
3
10
25.64
76.92
40.00
3
7.69
23.08
21.43
13
33.33
 
 
6
8
20.51
61.54
32.00
5
12.82
38.46
35.71
13
33.33
 
 
9
7
17.95
53.85
28.00
6
15.38
46.15
42.86
13
33.33
 
 
Total
25
64.10
14
35.90
39
100.00
Frequency
Percent
Row Pct
Col Pct
Table of hospbin by antibiotics
hospbin antibiotics
0 2 Total
3
1
2.56
7.69
11.11
12
30.77
92.31
40.00
13
33.33
 
 
6
1
2.56
7.69
11.11
12
30.77
92.31
40.00
13
33.33
 
 
9
7
17.95
53.85
77.78
6
15.38
46.15
20.00
13
33.33
 
 
Total
9
23.08
30
76.92
39
100.00
Frequency
Percent
Row Pct
Col Pct
Table of hospbin by cardiovascular
hospbin cardiovascular
0 3 Total
3
1
2.56
7.69
16.67
12
30.77
92.31
36.36
13
33.33
 
 
6
3
7.69
23.08
50.00
10
25.64
76.92
30.30
13
33.33
 
 
9
2
5.13
15.38
33.33
11
28.21
84.62
33.33
13
33.33
 
 
Total
6
15.38
33
84.62
39
100.00
Frequency
Percent
Row Pct
Col Pct
Table of hospbin by hormonal
hospbin hormonal
0 4 Total
3
3
7.69
23.08
23.08
10
25.64
76.92
38.46
13
33.33
 
 
6
5
12.82
38.46
38.46
8
20.51
61.54
30.77
13
33.33
 
 
9
5
12.82
38.46
38.46
8
20.51
61.54
30.77
13
33.33
 
 
Total
13
33.33
26
66.67
39
100.00
Frequency
Percent
Row Pct
Col Pct
Table of hospbin by others
hospbin others
0 5 Total
3
1
2.56
7.69
100.00
12
30.77
92.31
31.58
13
33.33
 
 
6
0
0.00
0.00
0.00
13
33.33
100.00
34.21
13
33.33
 
 
9
0
0.00
0.00
0.00
13
33.33
100.00
34.21
13
33.33
 
 
Total
1
2.56
38
97.44
39
100.00
Frequency
Percent
Row Pct
Col Pct
Table of hospbin by fluids_electrolytes
hospbin fluids_electrolytes
0 6 Total
3
9
23.08
69.23
29.03
4
10.26
30.77
50.00
13
33.33
 
 
6
12
30.77
92.31
38.71
1
2.56
7.69
12.50
13
33.33
 
 
9
10
25.64
76.92
32.26
3
7.69
23.08
37.50
13
33.33
 
 
Total
31
79.49
8
20.51
39
100.00

Descriptive statistics

NOTE: See section 'Verification of Results' above for statistical testing and p-values for age, sex, BMI, and ethnicity.

In [44]:
PROC univariate data=study4;
     var oppc_ageR
         oppc_BMIR
         cpeptide
         transport_duration_hours;
run;

proc sort data=study4;
     by hospbin;
run;

proc means data=study4 n mean std;
      var oppc_ageR
          oppc_BMIR
          cpeptide
          transport_duration_hours; 
      by hospbin;
run;

proc freq data=study4;
     tables oppc_gender*hospbin
            oppc_ethnicity*hospbin
            cod_final*hospbin;
run;
Out[44]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The UNIVARIATE Procedure

Variable: oppc_ageR

Moments
N 39 Sum Weights 39
Mean 22.4099122 Sum Observations 873.986575
Std Deviation 14.6764597 Variance 215.398469
Skewness 0.06140327 Kurtosis -0.9562855
Uncorrected SS 27771.1042 Corrected SS 8185.14184
Coeff Variation 65.4909291 Std Error Mean 2.3501144
Basic Statistical Measures
Location Variability
Mean 22.40991 Std Deviation 14.67646
Median 22.70000 Variance 215.39847
Mode 0.33000 Range 49.99342
    Interquartile Range 24.00000

Note: The mode displayed is the smallest of 4 modes with a count of 2.

Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 9.535669 Pr > |t| <.0001
Sign M 19.5 Pr >= |M| <.0001
Signed Rank S 390 Pr >= |S| <.0001
Quantiles (Definition 5)
Level Quantile
100% Max 50.00000000
99% 50.00000000
95% 46.00000000
90% 42.90000000
75% Q3 33.00000000
50% Median 22.70000000
25% Q1 9.00000000
10% 0.42000000
5% 0.33000000
1% 0.00657534
0% Min 0.00657534
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.00657534 30 42.0 6
0.33000000 29 42.9 18
0.33000000 16 45.8 24
0.42000000 15 46.0 5
0.50000000 31 50.0 4

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The UNIVARIATE Procedure

Variable: oppc_bmiR

Moments
N 39 Sum Weights 39
Mean 24.0564103 Sum Observations 938.2
Std Deviation 5.62811527 Variance 31.6756815
Skewness 0.22255819 Kurtosis -0.8883397
Uncorrected SS 23773.4 Corrected SS 1203.6759
Coeff Variation 23.3954909 Std Error Mean 0.90121971
Basic Statistical Measures
Location Variability
Mean 24.05641 Std Deviation 5.62812
Median 24.20000 Variance 31.67568
Mode 17.10000 Range 21.50000
    Interquartile Range 9.40000
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 26.69317 Pr > |t| <.0001
Sign M 19.5 Pr >= |M| <.0001
Signed Rank S 390 Pr >= |S| <.0001
Quantiles (Definition 5)
Level Quantile
100% Max 36.0
99% 36.0
95% 34.0
90% 32.4
75% Q3 28.9
50% Median 24.2
25% Q1 19.5
10% 17.0
5% 15.7
1% 14.5
0% Min 14.5
Extreme Observations
Lowest Highest
Value Obs Value Obs
14.5 30 31.0 6
15.7 2 32.4 25
16.3 22 32.7 10
17.0 31 34.0 39
17.1 29 36.0 11

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The UNIVARIATE Procedure

Variable: cpeptide

Moments
N 34 Sum Weights 34
Mean 5.57823529 Sum Observations 189.66
Std Deviation 5.18447477 Variance 26.8787786
Skewness 1.37842197 Kurtosis 1.6019936
Uncorrected SS 1944.9678 Corrected SS 886.999694
Coeff Variation 92.9411273 Std Error Mean 0.88913009
Basic Statistical Measures
Location Variability
Mean 5.578235 Std Deviation 5.18447
Median 4.545000 Variance 26.87878
Mode . Range 20.35000
    Interquartile Range 6.34000
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 6.273812 Pr > |t| <.0001
Sign M 17 Pr >= |M| <.0001
Signed Rank S 297.5 Pr >= |S| <.0001
Quantiles (Definition 5)
Level Quantile
100% Max 20.550
99% 20.550
95% 17.910
90% 13.630
75% Q3 7.610
50% Median 4.545
25% Q1 1.270
10% 0.650
5% 0.470
1% 0.200
0% Min 0.200
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.20 30 11.10 21
0.47 6 13.63 10
0.51 18 16.23 9
0.65 7 17.91 8
0.69 11 20.55 13
Missing Values
Missing
Value
Count Percent Of
All Obs Missing Obs
. 5 12.82 100.00

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The UNIVARIATE Procedure

Variable: transport_duration_hours

Moments
N 39 Sum Weights 39
Mean 14.0213675 Sum Observations 546.833333
Std Deviation 8.2263865 Variance 67.6734349
Skewness 1.21574691 Kurtosis 4.2226733
Uncorrected SS 10238.9417 Corrected SS 2571.59053
Coeff Variation 58.6703579 Std Error Mean 1.31727608
Basic Statistical Measures
Location Variability
Mean 14.02137 Std Deviation 8.22639
Median 14.13333 Variance 67.67343
Mode 13.91667 Range 44.26667
    Interquartile Range 11.63333
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 10.64421 Pr > |t| <.0001
Sign M 19.5 Pr >= |M| <.0001
Signed Rank S 390 Pr >= |S| <.0001
Quantiles (Definition 5)
Level Quantile
100% Max 45.250000
99% 45.250000
95% 24.933333
90% 24.266667
75% Q3 18.733333
50% Median 14.133333
25% Q1 7.100000
10% 3.583333
5% 1.400000
1% 0.983333
0% Min 0.983333
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.983333 5 20.8000 37
1.400000 1 24.2667 30
1.866667 4 24.4000 28
3.583333 6 24.9333 2
4.400000 3 45.2500 39

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The MEANS Procedure

Variable N Mean Std Dev
oppc_ageR
oppc_bmiR
cpeptide
transport_duration_hours
13
13
12
13
20.2851212
24.3384615
5.5575000
14.9012821
11.1983265
5.9706977
4.8066150
6.1285929
Variable N Mean Std Dev
oppc_ageR
oppc_bmiR
cpeptide
transport_duration_hours
13
13
13
13
23.1430769
23.8615385
4.6438462
16.1833333
16.9891428
5.3965326
5.4161634
9.9433372
Variable N Mean Std Dev
oppc_ageR
oppc_bmiR
cpeptide
transport_duration_hours
13
13
9
13
23.8015385
23.9692308
6.9555556
10.9794872
16.1397139
5.9497037
5.6170991
7.8703945

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

Frequency
Percent
Row Pct
Col Pct
Table of oppc_Gender by hospbin
oppc_Gender hospbin
3 6 9 Total
Female
3
7.69
21.43
23.08
4
10.26
28.57
30.77
7
17.95
50.00
53.85
14
35.90
 
 
Male
10
25.64
40.00
76.92
9
23.08
36.00
69.23
6
15.38
24.00
46.15
25
64.10
 
 
Total
13
33.33
13
33.33
13
33.33
39
100.00
Frequency
Percent
Row Pct
Col Pct
Table of oppc_Ethnicity by hospbin
oppc_Ethnicity hospbin
3 6 9 Total
African Am
2
5.13
50.00
15.38
0
0.00
0.00
0.00
2
5.13
50.00
15.38
4
10.26
 
 
Caucasian
10
25.64
31.25
76.92
12
30.77
37.50
92.31
10
25.64
31.25
76.92
32
82.05
 
 
Hispanic/Latino
1
2.56
33.33
7.69
1
2.56
33.33
7.69
1
2.56
33.33
7.69
3
7.69
 
 
Total
13
33.33
13
33.33
13
33.33
39
100.00
Frequency
Percent
Row Pct
Col Pct
Table of cod_final by hospbin
cod_final hospbin
3 6 9 Total
ANOXIA
5
12.82
41.67
38.46
4
10.26
33.33
30.77
3
7.69
25.00
23.08
12
30.77
 
 
CEREBROVASCULAR/STROKE
2
5.13
28.57
15.38
1
2.56
14.29
7.69
4
10.26
57.14
30.77
7
17.95
 
 
HEAD TRAUMA
5
12.82
27.78
38.46
8
20.51
44.44
61.54
5
12.82
27.78
38.46
18
46.15
 
 
Pulmonary hypoplasia
1
2.56
100.00
7.69
0
0.00
0.00
0.00
0
0.00
0.00
0.00
1
2.56
 
 
Respiratory Distress/Failure
0
0.00
0.00
0.00
0
0.00
0.00
0.00
1
2.56
100.00
7.69
1
2.56
 
 
Total
13
33.33
13
33.33
13
33.33
39
100.00

Need to obtain the range of hospitalization stay

In [45]:
PROC means data=study4 n mean std median min max;
     var Hospitalization_Stay_Days;
run;
Out[45]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The MEANS Procedure

Analysis Variable : Hospitalization_Stay_Days
N Mean Std Dev Median Minimum Maximum
39 5.7273860 5.6585730 3.3750000 0.8201389 28.1465278
In [46]:
proc sort data=study4;
by oppc_ageR;
run;

proc print data=study4;
run;

proc freq data=study4;
tables age_group;
run;
Out[46]:
SAS Output

wilcoxon rank sum for Processing_Time_Minutes1 on group1

Obs set_num ptid Donor_Type Organ_Received_Datetime_Flag Organ_Frozen_Datetime_Flag Admit_Datetime_Flag Braindeath_Datetime_Flag Xclamp_Datetime_Flag Hospitalization_Stay_Minutes Transport_Duration_Minutes Processing_Time_Minutes Hospitalization_Stay_Days Processing_Time_Minutes1 transport_duration_hours DonorType abo_subtype oppc_PancreasWT oppc_Gender oppc_Ethnicity oppc_ABO multi_organ_donor non_hrt_beat_donor oppc_ageR oppc_heightR oppc_weightR oppc_bmiR cod_final death_mech_final replace hospbin donor sex ethnicity clamp_Datetime_Flag age_group nPODCaseID diabetes_Duration_yrs oppc_C_peptideR oppc_HbA1cR diabetes_history insulin_depd insulin_meds_taken cpeptide dataSetsDemographicsDonorType pt_steroids pt_diuretics pt_t3 pt_t4 anticonv antihype vasodil ddavp heparin arginine insulin dmed_other1 dmed_other2 dmed_other3 dmed_other4 dmed_other5 dmed_other6 dmed_other7 dmed_other8 dmed_other9
1 15 6200 No diabetes 0 0 0 0 0 3449 1456 30 2.395138889 30 24.26666667 No diabetes   4.29 Female Hispanic/Latino O+ No Unknown 0.006575343 41 2.2 14.5 Pulmonary hypoplasia respiratory TRUE 3 0 2 2   1 6200   0.2 .     None 0.2 No diabetes                                        
2 1 6117 No diabetes 0 0 0 0 0 4785 940 65 3.322916667 65 15.66666667 No diabetes B 5.4 Male Caucasian B- Yes No 0.33 66 8.5 18.4 HEAD TRAUMA blunt injury TRUE 6 0 1 1   1 6117   3.27 . No   No 3.27 No diabetes N Y N Y N N N Y Y N Y Dopamine KCL Zosyn Dextrose          
3 13 6187 No diabetes 0 0 0 0 0 5485 625 60 3.809027778 60 10.41666667 No diabetes O 5.8 Male Caucasian O+ Yes Yes 0.33 63.5 6.7 17.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1   1 6187   0.72 . No   None 0.72 No diabetes N N N N N N Y N Y N N Rocephin     Vancomycin          
4 13 6115 No diabetes 0 0 0 0 0 16117 848 45 11.19236111 45 14.13333333 No diabetes A 3.9 Male Caucasian A1- Yes No 0.42 64 7 17.1 ANOXIA sids TRUE 9 0 1 1   1 6115   4.59 . No   No 4.59 No diabetes Y Y N N N N N N Y Y N CEFEPIME     GENTAMYCIN     vancomycin    
5 15 6219 No diabetes 0 0 0 0 0 6322 1124 90 4.390277778 90 18.73333333 No diabetes AB 4.99 Male Hispanic/Latino AB+ Yes No 0.5 66 7.4 17 HEAD TRAUMA blunt injury TRUE 6 0 1 2   1 6219   1.53 . No   None 1.53 No diabetes N Y N N N Y Y N Y Y N Versed Rocuronium   Fentanyl     Ancef    
6 1 6106 No diabetes 0 0 0 0 0 4164 1131 45 2.891666667 45 18.85 No diabetes A1 16.32 Male Caucasian A+ Yes No 2.9 94 16 18.1 ANOXIA drowning TRUE 3 0 1 1   1 6106   7.36 . No   None 7.36 No diabetes Y Y N Y N N N N Y Y Y Albuterol Atrovent Nystatin Unasyn Mag Vitamin K Na Bicarb KCl Pavulon
7 1 6005 No diabetes 0 0 0 0 0 9184 1496 30 6.377777778 30 24.93333333 No diabetes A1 . Female Caucasian A- Yes No 5 104 17 15.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1   1 6005   . . No   None . No diabetes Y Y N N N N N N Y N Y MYCAMINE     NARCAN     REGATINE    
8 15 6144 No diabetes 0 0 0 0 0 34014 426 90 23.62083333 90 7.1 No diabetes B 45 Female Hispanic/Latino B+ Yes Yes 7.5 124.5 25 16.3 Respiratory Distress/Failure natural causes TRUE 9 0 2 2   1 6144   1.27 . No   No 1.27 No diabetes N N N N N N N N Y N N                  
9 10 6047 No diabetes 0 0 0 0 0 4851 737 30 3.36875 30 12.28333333 No diabetes O 53.02 Male Caucasian O- Yes No 7.8 111.8 30 23.9 ANOXIA drowning TRUE 6 0 1 1   1 6047   0.65 5.5 No   No 0.65 No diabetes Y Y N Y Y N Y N Y Y Y CLEOCIN                
10 3 6007 No diabetes 0 0 0 0 0 9985 264 20 6.934027778 20 4.4 No diabetes O . Male African Am O+ Yes No 9 143 41 20 ANOXIA   TRUE 9 0 1 3   1 6007   . . No   None . No diabetes Y Y N Y Y N Y N Y N Y ANCEF                
11 10 6278 No diabetes 0 0 0 0 0 2653 895 87 1.842361111 87 14.91666667 No diabetes   33.6 Female African Am A No Unknown 10 157.5 52.4 21.3 ANOXIA cardiovascular TRUE 3 0 2 3   1 6278   4.54 6.3 No   None 4.54 No diabetes Y Y N N N N N N Y Y Y Levophed     Vancomycin Ephedrine   Vecuronium Neosynephrine  
12 8 6099 No diabetes 0 1 0 0 0 2945 890 . 2.045138889 . 14.83333333 No diabetes A2B 85.56 Male Caucasian AB+ Yes No 14.2 175.3 92 30 HEAD TRAUMA blunt injury TRUE 3 0 1 1   2 6099   5.37 . No   No 5.37 No diabetes Y Y N Y N N N N Y Y Y neosynephrine     merrem KCL   flolan    
13 3 6230 No diabetes 0 0 0 0 0 4368 947 130 3.033333333 130 15.78333333 No diabetes B 66.27 Male Caucasian B+ Yes No 16 173 56.7 18.9 HEAD TRAUMA gunshot wound TRUE 6 0 1 1   2 6230   5.22 5.3 No   None 5.22 No diabetes N N N Y N N N N Y Y Y duoneb zosyn     fentanyl vecuronium     levophed neosynephrine  
14 14 6279 No diabetes 0 0 0 0 0 4860 2715 140 3.375 140 45.25 No diabetes   80.17 Male Caucasian O+ No Unknown 19 180.3 110.2 34 HEAD TRAUMA blunt injury TRUE 6 0 1 1   2 6279   8.01 . No   None 8.01 No diabetes N N N N N N N N Y N Y Ceftriaxone     Lansoprazole          
15 14 6073 No diabetes 0 0 0 0 0 3560 754 50 2.472222222 50 12.56666667 No diabetes O 66.5 Male Caucasian O+ Yes No 19.2 165.1 98 36 ANOXIA cardiovascular TRUE 3 0 1 1   2 6073   0.69 . Unknown   No 0.69 No diabetes Y Y Y N N N N Y Y Y Y Invanz     Magnesium     potassium chloride    
16 14 6172 No diabetes 0 0 0 0 0 10358 999 135 7.193055556 135 16.65 No diabetes A1 59.7 Female Caucasian A+ Yes No 19.2 172.7 97 32.4 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 1   2 6172   8.02 5.4 No     8.02 No diabetes Y Y N Y N N N Y Y Y Y                  
17 3 6174 No diabetes 0 0 0 0 0 1181 604 135 0.820138889 135 10.06666667 No diabetes O 79.3 Male Caucasian O+ Yes No 20.8 196 75 19.5 CEREBROVASCULAR/STROKE blunt injury TRUE 3 0 1 1   3 6174   3 . No     3 No diabetes Y N N Y N N N N Y Y Y dobutamine     levophed neosynephrine   Ancef    
18 4 6179 No diabetes 0 0 0 0 0 20106 1464 120 13.9625 120 24.4 No diabetes O 72.4 Female Caucasian O- Yes Yes 21.8 157.5 51 20.7 HEAD TRAUMA blunt injury TRUE 9 0 2 1   3 6179   2.74 . No     2.74 No diabetes Y N N N N N N N Y Y N Lacrilube NaHCO3              
19 10 6057 No diabetes 0 0 0 0 0 12416 709 255 8.622222222 255 11.81666667 No diabetes O 104.36 Male Caucasian O+ Yes No 22 188 92 26 HEAD TRAUMA blunt injury TRUE 9 0 1 1   3 6057   16.23 . No   No 16.23 No diabetes N Y N N N N Y N Y N N                  
20 9 6162 No diabetes 0 0 0 0 0 2193 1203 115 1.522916667 115 20.05 No diabetes B 81.5 Male African Am B+ Yes No 22.7 188 102 28.9 HEAD TRAUMA gunshot wound TRUE 3 0 1 3   3 6162   7.61 . No   No 7.61 No diabetes N Y N Y N N N N Y Y N unasyn                
21 6 6003 No diabetes 0 0 0 0 0 3994 84 30 2.773611111 30 1.4 No diabetes O . Female Caucasian O+ Yes No 23 160 75 29.3 HEAD TRAUMA blunt injury TRUE 3 0 2 1   3 6003   . . No   None . No diabetes Y Y N Y Y N N N Y N N CEFEPIME     DOPAMINE     CLINDAMYCIN    
22 6 6060 No diabetes 0 0 0 0 0 13119 396 215 9.110416667 215 6.6 No diabetes A1 104 Male Caucasian A+ Yes No 24 175.3 100 32.7 HEAD TRAUMA blunt injury TRUE 9 0 1 1   3 6060   13.63 . No   No 13.63 No diabetes N Y N Y N N Y N Y N N COLACE PROTONIX PROPOFOL CLOACIN LEVAQUIN MORPHINE VANCOMYCIN AMINOPHLLINE  
23 4 6131 No diabetes 0 0 0 0 0 2743 1127 120 1.904861111 120 18.78333333 No diabetes B 108.92 Male Caucasian B+ Yes Yes 24.2 182.9 83 24.8 ANOXIA drug intoxication TRUE 3 0 1 1   3 6131   1.01 . No   No 1.01 No diabetes Y N N Y N N N N Y Y N dopamine neo   levophed     ancef vonco zoayn
24 8 6178 No diabetes 0 0 0 0 0 9414 741 145 6.5375 145 12.35 No diabetes A1 72.7 Female Caucasian A+ Yes No 24.5 182 92 27.5 ANOXIA cardiovascular TRUE 9 0 2 1   3 6178   4.55 5 No     4.55 No diabetes Y Y N Y N N N N Y Y Y Fentanyl KCL Calcium Gluconate            
25 4 6126 No diabetes 0 0 0 0 0 7024 673 340 4.877777778 340 11.21666667 No diabetes O 80.2 Male Caucasian O+ Yes No 25.2 175.3 77 25.1 HEAD TRAUMA blunt injury TRUE 6 0 1 1   3 6126   0.88 . No   No 0.88 No diabetes Y Y N Y N N N N Y Y N ANCEF                
26 13 6134 No diabetes 0 0 0 0 0 2905 1010 75 2.017361111 75 16.83333333 No diabetes O 82.42 Male Caucasian O+ Yes No 26.7 180.3 65 20.1 ANOXIA drug intoxication TRUE 3 0 1 1   3 6134   3.59 . No   No 3.59 No diabetes Y Y N Y N Y N N Y Y N NEO BICARB   MILRINONE CARDEINE   ANCEF    
27 11 6048 No diabetes 0 0 0 0 0 1927 368 55 1.338194444 55 6.133333333 No diabetes O 139 Male Caucasian O- Yes No 30 165.1 56 20.6 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 3 0 1 1   3 6048   17.91 . No   No 17.91 No diabetes Y Y N N N N Y Y Y Y N CEFEPIME     VANCOMYCIN     PROTONIX    
28 7 6235 No diabetes 0 0 0 0 0 3690 1020 120 2.5625 120 17 No diabetes O 102.31 Male Caucasian O+ Yes No 30 172.7 76 25.4 HEAD TRAUMA gunshot wound TRUE 3 0 1 1   3 6235   8.1 . No   None 8.1 No diabetes Y Y N N N N N N Y N N Ancef Levophed   Vecuronium          
29 8 6229 No diabetes 0 0 0 0 0 4489 835 100 3.117361111 100 13.91666667 No diabetes O 45.6 Female Caucasian O+ Yes No 31 156 65.5 26.9 HEAD TRAUMA blunt injury TRUE 6 0 2 1   3 6229   6.23 5.5 No   None 6.23 No diabetes Y Y N Y N N N N Y N Y Zosyn                
30 6 6251 No diabetes 0 0 0 0 0 5366 310 75 3.726388889 75 5.166666667 No diabetes A1 77.8 Female Caucasian A- Yes Yes 33 154.9 70 29.5 HEAD TRAUMA   TRUE 6 0 2 1   3 6251   1.92 5.3 No   None 1.92 No diabetes N N N N N N N N Y N N Ancef                
31 9 6254 No diabetes 0 0 0 0 0 4677 1248 105 3.247916667 105 20.8 No diabetes A1B 69.9 Male Caucasian AB+ Yes Yes 38 167.6 86 30.5 ANOXIA asphyxiation TRUE 6 0 1 1   3 6254   6.43 5.3 No   None 6.43 No diabetes N N N N N N N N Y N Y Ancef                
32 11 6140 No diabetes 0 0 0 0 0 11767 835 195 8.171527778 195 13.91666667 No diabetes A1 65.1 Male Caucasian A+ Yes No 38 170.2 59 21.7 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 1 1   3 6140   11.1 6 No   No 11.1 No diabetes Y Y N Y N Y N N Y Y Y ROCEPHIN VANCOMYCIN   NIMBEX     BENADRYL    
33 5 6250 No diabetes 0 0 0 0 0 2732 1081 25 1.897222222 25 18.01666667 No diabetes O . Male Caucasian O+ Yes No 40 180.3 90.7 27.9 HEAD TRAUMA blunt injury TRUE 3 0 1 1   3 6250   7.31 . No   None 7.31 No diabetes Y Y N Y N N N N Y N Y cardizem     cefazolin          
34 11 6104 No diabetes 0 1 0 0 0 4703 352 . 3.265972222 . 5.866666667 No diabetes O 55.2 Male Caucasian O+ Yes No 41 190.5 74 20.5 ANOXIA drug intoxication TRUE 6 0 1 1   3 6104   20.55 . No   No 20.55 No diabetes Y Y N N N N Y N Y N N NARCAN     CEFEPIME          
35 9 6019 No diabetes 0 0 0 0 0 11642 215 40 8.084722222 40 3.583333333 No diabetes O . Male Caucasian O- Yes No 42 175 95 31 HEAD TRAUMA intracranial hemorrhage/stroke TRUE 9 0 1 1   3 6019   0.47 5.6 No   None 0.47 No diabetes Y Y N Y Y Y N N Y N Y NARCAN     FACTOR 7     D5D    
36 7 6129 No diabetes 0 0 0 0 0 6058 1132 75 4.206944444 75 18.86666667 No diabetes O 58.84 Female Caucasian O- Yes No 42.9 152.4 54 23.4 ANOXIA intracranial hemorrhage/stroke TRUE 6 0 2 1   3 6129   0.51 5.2 No   No 0.51 No diabetes Y Y N N N Y N N Y N Y zosyn           vecuronium    
37 5 6165 No diabetes 0 0 0 0 0 6815 985 120 4.732638889 120 16.41666667 No diabetes O 97.41 Female Caucasian O+ Yes No 45.8 165.1 68 25 CEREBROVASCULAR/STROKE   TRUE 6 0 2 1   3 6165   4.45 5.6 No   No 4.45 No diabetes N Y N N N Y N N Y N N NIMBEX NARCAN FENTANYL ALBUTEROL ATROVENT   ZOSYN TOBRAMYCIN CISATRACURIUM
38 5 6011 No diabetes 0 0 0 0 0 40531 59 42 28.14652778 42 0.983333333 No diabetes O . Female African Am O+ Yes No 46 163 70 26.3 CEREBROVASCULAR/STROKE intracranial hemorrhage/stroke TRUE 9 0 2 3   3 6011   . . No   None . No diabetes Y Y N N N N N N Y N N PROPOFOL     PENTOBARB     VANC    
39 7 6008 No diabetes 0 0 0 0 0 15058 112 30 10.45694444 30 1.866666667 No diabetes O . Female Caucasian O+ Yes Yes 50 160 62 24.2 HEAD TRAUMA blunt injury TRUE 9 0 2 1   3 6008   . . No   None . No diabetes N N N N Y N N N N N Y CEFEPINE     ANCF     KCL    

wilcoxon rank sum for Processing_Time_Minutes1 on group1

The FREQ Procedure

age_group Frequency Percent Cumulative
Frequency
Cumulative
Percent
1 11 28.21 11 28.21
2 5 12.82 16 41.03
3 23 58.97 39 100.00