Frailty as a predictor of morbidity and mortality in inpatient head and neck surgery.

IMPORTANCE The increasing number of elderly and comorbid patients undergoing surgical procedures raises interest in better identifying patients at increased risk of morbidity and mortality, independent of age. Frailty has been identified as a predictor of surgical complications. OBJECTIVE To establish the implications of frailty as a predictor of morbidity and mortality in inpatient otolaryngologic operations. DESIGN Retrospective review of medical records. SETTING National Surgical Quality Improvement Program (NSQIP) participating hospitals. PATIENTS NSQIP participant use files were used to identify 6727 inpatients who underwent operations performed by surgeons specializing in otolaryngology between 2005 and 2010. The study sample was 50.3% male and 10.2% African American, with a mean (range) age of 54.7 (16-90) years. MAIN OUTCOMES AND MEASURES A previously described modified frailty index (mFI) was calculated on the basis of NSQIP variables. The effect of increasing frailty on morbidity and mortality was evaluated using univariate analysis. Multivariate logistic regression was used to compare mFI with age, ASA, and wound classification. RESULTS The mean (range) mFI was 0.07 (0-0.73). As the mFI increased from 0 (no frailty-associated variables) to 0.45 (5 of 11) or higher, mortality risk increased from 0.2% to 11.9%. The risk of Clavien-Dindo grade IV complications increased from 1.2% to 26.2%. The risk of all complications increased from 9.5% to 40.5%. All results were significant at P < .001. In a multivariate logistic regression model to predict mortality or serious complication, mFI became the dominant significant predictor. CONCLUSIONS AND RELEVANCE The mFI is significantly associated with morbidity and mortality in this retrospective survey. Additional study with prospective analysis and external validation is needed. The mFI may provide an improved understanding of preoperative risk, which would facilitate perioperative optimization, risk stratification, and counseling related to outcomes.