Predictive factors of 30-day unplanned readmission after lower extremity bypass

Abstract

Background: Thirty-day unplanned readmission after lower extremity bypass represents a large cost burden and is a logical target for cost-containment strategies. We undertook this study to evaluate factors associated with unplanned readmission after lower extremity bypass.

Methods: This is a retrospective analysis from a prospective institutional registry. All lower extremity bypasses for occlusive disease from January 1995 to July 2011 were included. The primary end point was 30-day unplanned readmission. Secondary end points included graft patency and limb salvage.

Results: Of 1543 lower extremity bypasses performed, 84.5% were for critical limb ischemia and 15.5% were patients with intermittent claudication. Twenty-seven patients (1.7%) died in-house and were excluded from further analysis. Of 1516 lower extremity bypasses analyzed, 42 (2.8%) were in patients with a planned readmission within 30 days, and 349 (23.0%), in patients with an unplanned readmission. Most unplanned readmissions were wound related (62.9%). By multivariable analysis, preoperative predictive factors for unplanned readmission were dialysis dependence (odds ratio [OR], 1.73; P = .004), tissue loss indication (OR, 1.62; P = .0004), and history of congestive heart failure (OR, 1.43; P = .03). Postoperative predictors included distal inflow source (OR, 1.38; P = .016), in-hospital wound infection (OR, 8.30; P < .0001), in-hospital graft failure (OR, 3.20; P < .0001), and myocardial infarction (OR, 1.96; P < .04). Neither index length of stay nor discharge disposition independently predicted unplanned readmission. Unplanned readmission was associated with loss of assisted primary patency (hazard ratio, 1.39; 95% confidence interval, 1.08-1.80; P = .01) and long-term limb loss (hazard ratio, 1.68; 95% confidence interval, 1.23-2.29; P = .001).

Conclusions: Thirty-day unplanned readmission is a frequent occurrence after lower extremity bypass (23.0%). Stratifying patients by risk factors associated with unplanned readmission is essential for quality improvement and equitable resource allocation when disease-specific bundling strategies are being derived.