Frailty and early hospital readmission after kidney transplantation

Abstract

Early hospital readmission (EHR) after kidney transplantation (KT) is associated with increased morbidity and higher costs. Registry-based recipient, transplant and center-level predictors of EHR are limited, and novel predictors are needed. We hypothesized that frailty, a measure of physiologic reserve initially described and validated in geriatrics and recently associated with early KT outcomes, might serve as a novel, independent predictor of EHR in KT recipients of all ages. We measured frailty in 383 KT recipients at Johns Hopkins Hospital. EHR was ascertained from medical records as ≥1 hospitalization within 30 days of initial post-KT discharge. Frail KT recipients were much more likely to experience EHR (45.8% vs. 28.0%, p = 0.005), regardless of age. After adjusting for previously described registry-based risk factors, frailty independently predicted 61% higher risk of EHR (adjusted RR = 1.61, 95% CI: 1.18-2.19, p = 0.002). In addition, frailty improved EHR risk prediction by improving the area under the receiver operating characteristic curve (p = 0.01) as well as the net reclassification index (p = 0.04). Identifying frail KT recipients for targeted outpatient monitoring and intervention may reduce EHR rates.

Keywords: Frailty; readmission; transplantation.

Figure 1

Early Hospital Readmission, by Age and Frailty.

Figure 2

Receiver Operating Characteristic Curve for Early Hospital Readmission Prediction Models with and without Frailty. Note: AUC is the area under the receiver operating characteristic curve. The registry-based model with frailty had statistically significant improvement in EHR prediction (P=0.01). The P value was obtained from a chi-squared test of the difference in the AUC for the registry-based models with and without frailty.