Frailty and Early Hospital Readmission After Kidney Transplantation

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 res...

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Veröffentlicht in:American journal of transplantation 2013-08, Vol.13 (8), p.2091-2095
Hauptverfasser: McAdams‐DeMarco, M. A., Law, A., Salter, M. L., Chow, E., Grams, M., Walston, J., Segev, D. L.
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Sprache:eng
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Zusammenfassung: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. In a prospective longitudinal cohort study of kidney transplant recipients, the authors find that frailty was a strong predictor of hospital readmission within 30 days of transplantation, improving risk prediction above and beyond registry‐based predictors.
ISSN:1600-6135
1600-6143
DOI:10.1111/ajt.12300