Predictive Models for Kidney Recovery and Death in Patients Continuing Dialysis as Outpatients after Starting In Hospital.

Abstract

For patients who initiate dialysis during a hospital admission and continue to require dialysis after discharge, outpatient dialysis management could be improved by better understanding the future likelihood of recovery to dialysis-independence and the competing risk of death. We derived and validated linked models to predict the subsequent recovery to dialysis-independence and death within one year of hospital discharge using a population-based cohort of 7,657 patients in Ontario, Canada. Predictive variables included age, comorbidities, length of hospital admission, intensive care status, discharge disposition, and pre-hospital admission estimated glomerular filtration rate and random urine urine albumin to creatinine ratio. Models were externally validated in 1,503 contemporaneous patients from Alberta, Canada. Both models were created using proportional hazards survival analysis, with the 'Recovery Model' using Fine-Gray methods. Probabilities generated from both models were used to develop 16 distinct Recovery or Death Outcomes (ReDO) risk groups. ReDO risk groups in the derivation group had significantly distinct 1-year probabilities for recovery to dialysis-independence (1st Quartile: 10% [95%CI 9-11]; 4th Quartile: 73% [70-77]) and for death (1st Quartile: 12% [11-13]; 4th Quartile: 46% [43-50]). In the validation group, model discrimination was modest (c-statistics [95%CI] for recovery and for death quartiles were 0.70 [0.67-0.73] and 0.66 [0.62-0.69], respectively) but calibration was excellent (integrated calibration index [95%CI] was 7% [5-9] and 4% [2-6] for recovery and death, respectively). The ReDO models generated accurate expected probabilities of recovery to dialysis-independence and death in patients who continued outpatient dialysis after initiating dialysis in hospital. An online tool based on the models is available at: https://qxmd.com/calculate/calculator_874 Click to follow link.">https://qxmd.com/calculate/calculator_874.