Hatim A Alsulaim1, Blair J Smart2, Anthony O Asemota1, R Sterling Haring3, Joseph K Canner1, David T Efron4, Elliott R Haut4, Eric B Schneider5. 1. Johns Hopkins Surgery Center for Outcomes Research, Johns Hopkins School of Medicine, Baltimore, MD, USA. 2. Johns Hopkins Surgery Center for Outcomes Research, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Surgery, Keck School of Medicine of USC, Los Angeles, CA, USA. 3. Johns Hopkins Surgery Center for Outcomes Research, Johns Hopkins School of Medicine, Baltimore, MD, USA; Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. 4. Johns Hopkins Surgery Center for Outcomes Research, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA. 5. Johns Hopkins Surgery Center for Outcomes Research, Johns Hopkins School of Medicine, Baltimore, MD, USA; Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: eschneider3@partners.org.
Abstract
BACKGROUND: Outcome studies in trauma using administrative data traditionally employ anatomy-based definitions of injury severity; however, physiologic factors, including consciousness, may correlate with outcomes. We examined whether accounting for conscious status in administrative data improved mortality prediction among patients with moderate to severe TBI. METHODS: Patients meeting Centers for Disease Control and Prevention (CDC) guidelines for TBI in the 2006 to 2011 Nationwide Emergency Department Sample were identified. Patients were dichotomized as having no/brief loss of consciousness (LOC) vs extended LOC greater than 1 hour using International Classification of Diseases, Ninth Revision (ICD-9) fifth digit modifiers. Receiver operating curves compared the ability of logistic regression to predict mortality in models that included LOC vs models that did not. RESULTS: Overall, 98,397 individuals met criteria, of whom 25.8% had extended LOC. In univariate analysis, AIS alone predicted mortality in 69.6% of patients (area under receiver operating characteristic curve .696, 95% CI .689 to .702), extended LOC alone predicted mortality in 76.8% (AUROC .768, 95% CI .764 to .773), and a combination of AIS and extended LOC predicted mortality in 82.6% of cases (AUROC .826, 95% CI .821 to .830). Similar differences were observed in best-fit models. CONCLUSIONS: Accounting for LOC along with anatomical measures of injury severity improves mortality prediction among patients with moderate/severe TBI in administrative datasets. Further work is warranted to determine whether other physiological measures may also improve prediction across a variety of injury types.
BACKGROUND: Outcome studies in trauma using administrative data traditionally employ anatomy-based definitions of injury severity; however, physiologic factors, including consciousness, may correlate with outcomes. We examined whether accounting for conscious status in administrative data improved mortality prediction among patients with moderate to severe TBI. METHODS:Patients meeting Centers for Disease Control and Prevention (CDC) guidelines for TBI in the 2006 to 2011 Nationwide Emergency Department Sample were identified. Patients were dichotomized as having no/brief loss of consciousness (LOC) vs extended LOC greater than 1 hour using International Classification of Diseases, Ninth Revision (ICD-9) fifth digit modifiers. Receiver operating curves compared the ability of logistic regression to predict mortality in models that included LOC vs models that did not. RESULTS: Overall, 98,397 individuals met criteria, of whom 25.8% had extended LOC. In univariate analysis, AIS alone predicted mortality in 69.6% of patients (area under receiver operating characteristic curve .696, 95% CI .689 to .702), extended LOC alone predicted mortality in 76.8% (AUROC .768, 95% CI .764 to .773), and a combination of AIS and extended LOC predicted mortality in 82.6% of cases (AUROC .826, 95% CI .821 to .830). Similar differences were observed in best-fit models. CONCLUSIONS: Accounting for LOC along with anatomical measures of injury severity improves mortality prediction among patients with moderate/severe TBI in administrative datasets. Further work is warranted to determine whether other physiological measures may also improve prediction across a variety of injury types.
Authors: Hannah J Schiffman; Zachariah P G Olufs; Michael R Lasarev; David A Wassarman; Misha Perouansky Journal: Br J Anaesth Date: 2020-05-25 Impact factor: 9.166