NYMC Faculty Publications

Title

Thirty-day Readmissions After Transcatheter Aortic Valve Replacement in the United States: Insights from the Nationwide Readmissions Database

Document Type

Article

Publication Date

1-1-2017

Department

Medicine

Abstract

BACKGROUND: Readmissions after cardiac procedures are common and contribute to increased healthcare utilization and costs. Data on 30-day readmissions after transcatheter aortic valve replacement (TAVR) are limited. METHODS AND RESULTS: Patients undergoing TAVR (International Classification of Diseases-Ninth Revision-CM codes 35.05 and 35.06) between January and November 2013 who survived the index hospitalization were identified in the Nationwide Readmissions Database. Incidence, predictors, causes, and costs of 30-day readmissions were analyzed. Of 12 221 TAVR patients, 2188 (17.9%) were readmitted within 30 days. Length of stay >5 days during index hospitalization (hazard ratio [HR], 1.47; 95% confidence interval [CI], 1.24-1.73), acute kidney injury (HR, 1.23; 95% CI, 1.05-1.44), >4 Elixhauser comorbidities (HR, 1.22; 95% CI, 1.03-1.46), transapical TAVR (HR, 1.21; 95% CI, 1.05-1.39), chronic kidney disease (HR, 1.20; 95% CI, 1.04-1.39), chronic lung disease (HR, 1.16; 95% CI, 1.01-1.34), and discharge to skilled nursing facility (HR, 1.16; 95% CI, 1.01-1.34) were independent predictors of 30-day readmission. Readmissions were because of noncardiac causes in 61.8% of cases and because of cardiac causes in 38.2% of cases. Respiratory (14.7%), infections (12.8%), bleeding (7.6%), and peripheral vascular disease (4.3%) were the most common noncardiac causes, whereas heart failure (22.5%) and arrhythmias (6.6%) were the most common cardiac causes of readmission. Median length of stay and cost of readmissions were 4 days (interquartile range, 2-7 days) and $8302 (interquartile range, $5229-16 021), respectively. CONCLUSIONS: Thirty-day readmissions after TAVR are frequent and are related to baseline comorbidities, TAVR access site, and post-procedure complications. Awareness of these predictors can help identify and target high-risk patients for interventions to reduce readmissions and costs.

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