Comorbidity–Polypharmacy Score as Predictor of Outcomes in Older Trauma Patients: A Retrospective Validation Study

Introduction Traditional injury severity assessment is insufficient in estimating the morbidity and mortality risk for older (≥45 years) trauma patients. Commonly used tools involve complex calculations or tables, do not consider all comorbidities, and often rely on data that are not available early...

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Veröffentlicht in:World journal of surgery 2015-08, Vol.39 (8), p.2068-2075
Hauptverfasser: Mubang, Ronnie N., Stoltzfus, Jill C., Cohen, Marissa S., Hoey, Brian A., Stehly, Christy D., Evans, David C., Jones, Christian, Papadimos, Thomas J., Grell, Jennifer, Hoff, William S., Thomas, Peter, Cipolla, James, Stawicki, Stanislaw P.
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Sprache:eng
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Zusammenfassung:Introduction Traditional injury severity assessment is insufficient in estimating the morbidity and mortality risk for older (≥45 years) trauma patients. Commonly used tools involve complex calculations or tables, do not consider all comorbidities, and often rely on data that are not available early in the trauma patient’s hospitalization. The comorbidity–polypharmacy score (CPS), a sum of all pre-injury medications and comorbidities, was found in previous studies to independently predict morbidity and mortality in this older patient population. However, these studies are limited by relatively small sample sizes. Consequently, we sought to validate previous research findings in a large, administrative dataset. Methods A retrospective study of patients ages ≥45 years was performed using an administrative trauma database from St. Luke’s University Hospital’s Level I Trauma Center. The study period was from 1 January 2008 to 31 December 2013. Abstracted data included patient demographics, injury mechanism and severity [injury characteristics and severity score (ISS)], Glasgow coma scale (GCS), hospital and intensive care unit lengths of stay (HLOS and ILOS, respectively), morbidity, post-discharge destination, and in-hospital mortality. Univariate analyses were conducted with mortality, all-cause morbidity, and discharge destination as primary end-points. Variables reaching statistical significance ( p  ≤ 0.20) were included in a multivariate logistic regression model. Data are presented as adjusted odds ratios (AORs), with p  
ISSN:0364-2313
1432-2323
DOI:10.1007/s00268-015-3041-5