External Validation of Predictors of Mortality in Polytrauma Patients.
J Surg Res
; 301: 618-622, 2024 Sep.
Article
in En
| MEDLINE
| ID: mdl-39094520
ABSTRACT
INTRODUCTION:
The Parkland Trauma Index of Mortality (PTIM) is an integrated, machine learning 72-h mortality prediction model that automatically extracts and analyzes demographic, laboratory, and physiological data in polytrauma patients. We hypothesized that this validated model would perform equally as well at another level 1 trauma center.METHODS:
A retrospective cohort study was performed including â¼5000 adult level 1 trauma activation patients from January 2022 to September 2023. Demographics, physiologic and laboratory values were collected. First, a test set of models using PTIM clinical variables (CVs) was used as external validation, named PTIM+. Then, multiple novel mortality prediction models were developed considering all CVs designated as the Cincinnati Trauma Index of Mortality (CTIM). The statistical performance of the models was then compared.RESULTS:
PTIM CVs were found to have similar predictive performance within the PTIM + external validation model. The highest correlating CVs used in CTIM overlapped considerably with those of the PTIM, and performance was comparable between models. Specifically, for prediction of mortality within 48 h (CTIM versus PTIM) positive prediction value was 35.6% versus 32.5%, negative prediction value was 99.6% versus 99.3%, sensitivity was 81.0% versus 82.5%, specificity was 97.3% versus 93.6%, and area under the curve was 0.98 versus 0.94.CONCLUSIONS:
This external cohort study suggests that the variables initially identified via PTIM retain their predictive ability and are accessible in a different level 1 trauma center. This work shows that a trauma center may be able to operationalize an effective predictive model without undertaking a repeated time and resource intensive process of full variable selection.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Multiple Trauma
Limits:
Adult
/
Aged
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Female
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Humans
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Male
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Middle aged
Language:
En
Journal:
J Surg Res
/
J. surg. res
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Journal of surgical research
Year:
2024
Document type:
Article
Country of publication: