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

• Published in: World journal of surgery Vol. 39; no. 8; pp. 2068 - 2075
• Main Authors: 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.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.08.2015; Springer Nature B.V
• Subjects: Abdominal Surgery; Aged; Aged, 80 and over; Cardiac Surgery; Comorbidity; Female; Follow Institutional Review Board Approval; General Surgery; Glasgow Coma Scale; Hospital Mortality; Humans; Intensive Care Units - utilization; Length of Stay - statistics & numerical data; Logistic Models; Male; Medicine; Medicine & Public Health; Middle Aged; Multivariate Analysis; Original Scientific Report; Patient Discharge - statistics & numerical data; Polypharmacy; Prospective Studies; Retrospective Studies; Subsequent Intensive Care Unit; Surgery; Thoracic Surgery; Trauma Centers; Trauma Outcome; Trauma Patient; Vascular Surgery; Wounds and Injuries - mortality; Wounds and Injuries - therapy; Trauma Outcome; Trauma Patient; Glasgow Coma Scale; Follow Institutional Review Board Approval; Subsequent Intensive Care Unit
• ISSN: 0364-2313; 1432-2323
• DOI: 10.1007/s00268-015-3041-5

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  < 0.05 denoting statistical significance. Results A total of 5863 patient records were analyzed. Average patient age was 68.5 ± 15.3 years (52 % male, 89 % blunt mechanism, mean GCS 14.3). Mean HLOS and ILOS increased significantly with increasing CPS ( p  < 0.01). Independent predictors of mortality included age (AOR 1.05, p  < 0.01), CPS (per-unit AOR 1.08, p  < 0.02), GCS (AOR 1.43 per-unit decrease, p  < 0.01), and ISS (per-unit 1.08, p  < 0.01). Independent predictors of all-cause morbidity included age (AOR 1.02, p  < 0.01), GCS (AOR per-unit decrease 1.08, p  < 0.01), ISS (per-unit AOR 1.09, p  < 0.01), and CPS (per-unit AOR 1.04, p  < 0.01). CPS did not independently predict need for discharge to a facility. Conclusions This study confirms that CPS is an independent predictor of all-cause morbidity and mortality in older trauma patients. However, CPS was not independently associated with need for discharge to a facility. Prospective multicenter studies are needed to evaluate the use of CPS as a predictive and interventional tool, with special focus on correlations between specific pre-existing conditions, pharmacologic interactions, and morbidity/mortality patterns.