التفاصيل البيبلوغرافية
| العنوان: |
Comparison of a trauma comorbidity index with other measures of comorbidities to estimate risk of trauma mortality. |
| المؤلفون: |
Jenkins, Peter C., Dixon, Brian E., Savage, Stephanie A., Carroll, Aaron E., Newgard, Craig D., Tignanelli, Christopher J., Hemmila, Mark R., Timsina, Lava |
| المصدر: |
Academic Emergency Medicine; Oct2021, Vol. 28 Issue 10, p1150-1159, 10p |
| مصطلحات موضوعية: |
EXPERIMENTAL design, RESEARCH evaluation, RESEARCH methodology, RESEARCH methodology evaluation, RISK assessment, QUESTIONNAIRES, CHI-squared test, DESCRIPTIVE statistics, WOUNDS & injuries, PREDICTION models, STATISTICAL sampling, COMORBIDITY |
| مصطلحات جغرافية: |
INDIANA |
| مستخلص: |
Background: Comorbidities influence the outcomes of injured patients, yet a lack of consensus exists regarding how to quantify that association. This study details the development and internal validation of a trauma comorbidity index (TCI) designed for use with trauma registry data and compares its performance to other existing measures to estimate the association between comorbidities and mortality. Methods: Indiana state trauma registry data (2013–2015) were used to compare the TCI with the Charlson and Elixhauser comorbidity indices, a count of comorbidities, and comorbidities as separate variables. The TCI approach utilized a randomly selected training cohort and was internally validated in a distinct testing cohort. The C‐statistic of the adjusted models was tested using each comorbidity measure in the testing cohort to assess model discrimination. C‐statistics were compared using a Wald test, and stratified analyses were performed based on predicted risk of mortality. Multiple imputation was used to address missing data. Results: The study included 84,903 patients (50% each in training and testing cohorts). The Indiana TCI model demonstrated no significant difference between testing and training cohorts (p = 0.33). It produced a C‐statistic of 0.924 in the testing cohort, which was significantly greater than that of models using the other indices (p < 0.05). The C‐statistics of models using the Indiana TCI and the inclusion of comorbidities as separate variables—the method used by the American College of Surgeons Trauma Quality Improvement Program—were comparable (p = 0.11) but use of the TCI approach reduced the number of comorbidity‐related variables in the mortality model from 19 to one. Conclusions: When examining trauma mortality, the TCI approach using Indiana state trauma registry data demonstrated superior model discrimination and/or parsimony compared to other measures of comorbidities. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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