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

Author:

Clark Edward G.12ORCID,James Matthew T.34ORCID,Hiremath Swapnil12,Sood Manish M.125,Wald Ron67,Garg Amit X.689,Silver Samuel A.610ORCID,Tan Zhi3,van Walraven Carl5611

Affiliation:

1. Division of Nephrology, Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada

2. Kidney Research Centre, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada

3. Division of Nephrology, Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada

4. Department of Community Health Sciences, Cumming School of Medicine, O'Brien Institute of Public Health, University of Calgary, Calgary, Alberta, Canada

5. Department of Medicine and Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada

6. Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada

7. Division of Nephrology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada

8. Division of Nephrology, Department of Medicine, Western University, London, Ontario, Canada

9. Lawson Health Research Institute, London Health Sciences Centre, London, Ontario, Canada

10. Division of Nephrology, Department of Medicine, Queens University, Kingston, Ontario, Canada

11. Department of Medicine, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada

Abstract

Background 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. Methods We derived and validated linked models to predict the subsequent recovery to dialysis independence and death within 1 year of hospital discharge using a population-based cohort of 7657 patients in Ontario, Canada. Predictive variables included age, comorbidities, length of hospital admission, intensive care status, discharge disposition, and prehospital admission eGFR and random urine albumin-to-creatinine ratio. Models were externally validated in 1503 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 and Death in Outpatients” (ReDO) risk groups. Results ReDO risk groups in the derivation group had significantly distinct 1-year probabilities for recovery to dialysis independence (first quartile: 10% [95% confidence interval (CI), 9% to 11%]; fourth quartile: 73% [70% to 77%]) and for death (first quartile: 12% [11% to 13%]; fourth quartile: 46% [43% to 50%]). In the validation group, model discrimination was modest (c-statistics [95% CI] for recovery and for death quartiles were 0.70 [0.67 to 0.73] and 0.66 [0.62 to 0.69], respectively), but calibration was excellent (integrated calibration index [95% CI] was 7% [5% to 9%] and 4% [2% to 6%] for recovery and death, respectively). Conclusions 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 on the basis of the models is available at https://qxmd.com/calculate/calculator_874.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Transplantation,Nephrology,Critical Care and Intensive Care Medicine,Epidemiology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Acute Kidney Injury Management Strategies Peri-Cardiovascular Interventions;Interventional Cardiology Clinics;2023-10

2. Predicting Outcomes after Discharge from the Hospital on Dialysis;Clinical Journal of the American Society of Nephrology;2023-06-02

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