3958553
doi
10.5281/zenodo.3958553
oai:zenodo.org:3958553
Grabovschi, Ion
Nicolae Testemitsanu State University of Medicine and Pharmacy, Chisinau, the Republic of Moldova
Survival predictive model for severe trauma patients using proteases/antiproteases system components
Arnaut, Oleg
Nicolae Testemitsanu State University of Medicine and Pharmacy, Chisinau, the Republic of Moldova
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
trauma
survival predictive model
proteases
antiproteases
<p><strong>Background:</strong> Assessing the traumatic injuries severity, as well as estimating the severe trauma patient’s prognosis are the key moments in their management. Predictive models for severe trauma outcome need improvement. </p>
<p><strong>Material and methods: </strong>In the clinical study (65 severe trauma patients), proteases, antiproteases and treatment outcome (survival/non-survival) were considered. There were used two statistical instruments – dimension reduction analysis (principal component analysis) to prepare the data for modeling and modeling itself through multivariate logistic regression. </p>
<p><strong>Results: </strong>Principal component analysis evidenced 12 “latent” factors grouped in four models. The survival predictive model had the following characteristics: calibration χ²=1.547, df=7, р=.981; determination – 0.759; discrimination, sensitivity – 90.7%, specificity – 81.8 %, area under RОС curve – 0.95 (95%CI 0.912, 1.000). The model enrolled four “latent” factors (three destructive and one protective), male gender and ARDS development. </p>
<p><strong>Conclusions:</strong> In our research, the survival predictive model for severe trauma patients on base of proteases/antiproteases system components after dimension reduction procedure was elaborated. The model showed good characteristics and needs validation to be implemented in daily clinical practice</p>
Zenodo
2020-09-01
info:eu-repo/semantics/article
3958552
1598662764.87846
1415253
md5:89eed5a7aab1adece7f6a1082bc0b041
https://zenodo.org/records/3958553/files/MMJ-2020-63-3_38-42.pdf
public
10.5281/zenodo.3958552
isVersionOf
doi
Moldovan Medical Journal
63(3)
38-42
2020-09-01