Effect of frailty on short- and mid-term outcomes in vascular surgical patients. (12th March 2015)

• Record Type: Journal Article
• Authors: Ambler, G K; Brooks, D E; Al Zuhir, N; Ali, A; Gohel, M S; Hayes, P D; Varty, K; Boyle, J R; Coughlin, P A
• Is Part Of: British journal of surgery. Volume 102(2015)Supplement 6
• Page Start: 638
• Page End: 645
• Publication Date: 2015-03-12
• Subjects: Surgery -- Periodicals; 617.005
• DOI: 10.1002/bjs.9785
• Languages: English
• ISSNs: 0007-1323

Abstract

Abstract: Background: Frailty is a multidimensional vulnerability resulting from age-associated decline. The impact of frailty on outcomes was assessed in a cohort of vascular surgical patients. Methods: The study included patients aged over 65 years with length of hospital stay (LOS) greater than 2 days, who were admitted to a tertiary vascular unit over a single calendar year. Demographics, mode of admission, diagnosis, mortality, LOS and discharge destination were recorded, as well as a variety of frailty-specific characteristics. The impact of frailty on LOS, discharge destination, survival and readmission rate was assessed using multivariable regression techniques. The ability of the models to predict these outcomes was also assessed. Results: In total, 413 patients of median age 77 years were followed for a median of 18 (range 12–24) months. The in-hospital, 3- and 12-month mortality rates were 3·6, 8·5 and 13·8 per cent respectively. Receiver operating characteristic (ROC) curve analysis revealed that frailty-based regression models were excellent predictors of 12-month mortality (area under the ROC curve (AUC) = 0·81), prolonged LOS (AUC = 0·79) and discharge to a care institution (AUC = 0·84). A simple additive frailty score using six key features retained strong predictive power for 12-month mortality (AUC = 0·83), discharge to a care institution (AUC = 0·78) and prolonged LOS (AUC = 0·74). This frailty score was also strongly associated with readmission rates ( P < 0·001). Conclusion: Frailty in vascular surgery patients predicts a multiplicity of poorer outcomes. Optimal management should include identification of at-risk patients and treatment of modifiable risk factors. Abstract : Predicts adverse outcomes