A Simplified Frailty Index to Predict Perioperative Risk in the Orthopedic Population

1Henry Ford Hospital, Detroit, MI

Meeting: Hospital Medicine 2011, May 10-13, Dallas, Texas.

Abstract number: 139


There are limited tools to aid in stratifying peri‐operative risk in orthopedic surgical patients. Frailty has been associated with poor clinical outcomes yet is difficult to measure. We sought to better understand the implications of frailty measures for perioperative risk stratification. We hypothesized that a simplified modification of the Canadian Study of Health and Aging frailty index (FI) could be constructed from standard demographic variables. Furthermore, we hypothesized that this index would serve as a robust predictor of postoperative morbidity and mortality.


Under the Data Use Agreement of the American College of Surgeons, and with institutional review board approval, the National Surgical Quality Improvement Program (NSQIP) Participant Utilization File was accessed for the years 2005–2008 for inpatient orthopedic patients. Preoperative clinical NSQIP variables were matched to 1 of the 71 FI variables. There were 11 matches (changes in daily activities, malignant disease, gastrointestinal problems, respiratory problems, clouding or delirium, hypertension, lung problems, cardiac problems, congestive heart failure, and other medical problems). A modified perioperative FI was determined by the number of NSQIP variables above in which an abnormality was present divided by the number of items considered (11), with an increase in the FI implying increased frailty. The outcomes assessed were 30‐day wound occurrence, infection, any occurrence, and mortality. Statistical analysis was done using chi‐square analysis and stepwise logistic regression.


There were 67,308 patients with 3913 wound occurrences, 6691 infections, 12,847 occurrences of all kinds, and 2800 deaths in the database. Table 1 summarizes the proportion of patients experiencing each occurrence based on the FI. As the FI increased, postoperative mortality increased (P < 0.001). Stepwise logistic regression using the FI, with NSQIP variables of age, work RVU, ASA class, wound classification, emergency status, and functional status, was significant (P < 0.001), with the FI having the highest odds ratio (OR) for each occurrence: wound occurrence (OR, 9.8), infection (OR, 5.4), any minor/major occurrence (OR, 5.1), and death (OR 3.1); P < 0.001 for all occurrences reported.


A frailty index based on simple, preoperatively identifiable patient clinical information can accurately assess the risk of postoperative morbidity and mortality. The use of such an index may be an easy method to improve perioperative risk stratification in high‐risk elderly populations.


P. Watson ‐ none; V. Velanovich ‐ none; I. Rubinfeld ‐ none; H. Antoine ‐ none

To cite this abstract:

Watson P, Antoine H, Swartz A, Velanovich V, Rubinfeld I. A Simplified Frailty Index to Predict Perioperative Risk in the Orthopedic Population. Abstract published at Hospital Medicine 2011, May 10-13, Dallas, Texas. Abstract 139. Journal of Hospital Medicine. 2011; 6 (suppl 2). https://www.shmabstracts.com/abstract/a-simplified-frailty-index-to-predict-perioperative-risk-in-the-orthopedic-population/. Accessed March 28, 2020.

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