Renal Dysfunction Is Associated With Poststroke Discharge Disposition and In-Hospital Mortality: Findings From Get With The Guidelines-Stroke

Background and Purpose Kidney disease is a frequent comorbidity in patients presenting with acute ischemic stroke. We evaluated whether the estimated glomerular filtration rate (eGFR) on admission is associated with poststroke in-hospital mortality or discharge disposition. Methods In this cohort study, data from ischemic stroke patients in Get With The Guidelines-Stroke linked to fee-for-service Medicare data were analyzed. The Modification of Diet in Renal Disease study equation was used to calculate the eGFR (mL/min/1.73 m(2)). Dialysis was identified by International Classification of Diseases, Ninth Revision codes. Adjusted multivariable Cox proportional hazards models were used to determine the independent associations of eGFR with discharge disposition and in-hospital mortality. Adjusted individual models also examined whether the association of clinical and demographic factors with outcomes varied by eGFR level. Results Of 232236 patients, 47.3% had an eGFR 60, 26.6% an eGFR 45 to 59, 16.8% an eGFR 30 to 44, 5.6% an eGFR 15 to 29, 0.7% an eGFR<15 without dialysis, and 2.8% were receiving dialysis. Of the total cohort, 11.8% died during the hospitalization or were discharged to hospice, and 38.6% were discharged home. After adjusting for other relevant variables, renal dysfunction was independently associated with an increased risk of in-hospital mortality that was highest among those with eGFR <15 without dialysis (odds ratio, 2.52; 95% confidence interval, 2.07-3.07). An eGFR 15 to 29 (odds ratio, 0.82; 95% confidence interval, 0.78-0.87), eGFR <15 (odds ratio, 0.72; 95% confidence interval, 0.61-0.86), and dialysis (odds ratio, 0.86; 95% confidence interval, 0.79-0.94) remained associated with lower odds of being discharged home. In addition, the associations of several clinical and demographic factors with outcomes varied by eGFR level. Conclusions eGFR on admission is an important predictor of poststroke short-term outcomes.