Simplified frailty index to predict adverse outcomes and mortality in vascular surgery patients

Ann Vasc Surg. 2013 Oct;27(7):904-8. doi: 10.1016/j.avsg.2012.09.015. Epub 2013 May 24.

Abstract

Background: Frailty has been established as an important predictor of health-care outcomes. We hypothesized that the use of a modified frailty index would be a predictor of mortality and adverse occurrences in vascular surgery patients.

Methods: Under the data use agreement of the American College of Surgeons, and with institutional review board (IRB) approval, the National Surgical Quality Improvement Program (NSQIP) Participant Utilization File was accessed for the years 2005-2008 for inpatient vascular surgery patients. Using the Canadian Study of Health and Aging Frailty Index (FI), 11 variables were matched to the NSQIP database. An increase in FI implies increased frailty. The outcomes assessed were mortality, wound infection, and any occurrence. We then compared the effect of FI, age, functional status, relative value units (RVU), American Society of Anesthesiology (ASA) score, and wound status on mortality. Statistical analysis was done using chi-square analysis and stepwise logistic regression.

Results: A total of 67,308 patients were identified in the database, 3913 wound occurrences, 6691 infections, 12,847 occurrences of all kinds, and 2800 deaths. As the FI increased, postoperative wound infection, all occurrences, and mortality increased (P < 0.001). Stepwise logistic regression using the FI with the NSQIP variables of age, work RVU, ASA class, wound classification, emergency status, and functional status showed FI to have the highest odds ratio (OR) for mortality (OR = 2.058, P < 0.001).

Conclusions: A simplified FI can be obtained by easily identifiable patient characteristics, allowing for accurate prediction of postoperative morbidity and mortality in the vascular surgery population.

MeSH terms

  • Activities of Daily Living
  • Age Factors
  • Aged
  • Chi-Square Distribution
  • Decision Support Techniques*
  • Female
  • Frail Elderly*
  • Health Status
  • Health Status Indicators*
  • Humans
  • Logistic Models
  • Male
  • Multivariate Analysis
  • Odds Ratio
  • Postoperative Complications / mortality*
  • Retrospective Studies
  • Risk Assessment
  • Risk Factors
  • Surgical Wound Infection / etiology
  • Surgical Wound Infection / mortality
  • Treatment Outcome
  • Vascular Surgical Procedures / adverse effects*
  • Vascular Surgical Procedures / mortality*