Physical Resilience Phenotype Trajectories in Incident Hemodialysis: Characterization and Mortality Risk Assessment

Melissa D Hladek; Jiafeng Zhu; Deidra C Crews; Mara A McAdams-DeMarco; Brian Buta; Ravi Varadhan; Tariq Shafi; Jeremy D Walston; Karen Bandeen-Roche

doi:10.1016/j.ekir.2022.06.009

Physical Resilience Phenotype Trajectories in Incident Hemodialysis: Characterization and Mortality Risk Assessment

Kidney Int Rep. 2022 Jun 23;7(9):2006-2015. doi: 10.1016/j.ekir.2022.06.009. eCollection 2022 Sep.

Authors

Melissa D Hladek¹, Jiafeng Zhu², Deidra C Crews³, Mara A McAdams-DeMarco⁴, Brian Buta⁵, Ravi Varadhan^{2

6}, Tariq Shafi^{7

8

9}, Jeremy D Walston⁵, Karen Bandeen-Roche^{1

2

5}

Affiliations

¹ Johns Hopkins School of Nursing, Baltimore, Maryland, USA.
² Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
³ Division of Nephrology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
⁴ Department of Surgery, New York University Grossman School of Medicine, New York, New York, USA.
⁵ Division of Geriatric Medicine and Gerontology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
⁶ Department of Oncology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
⁷ Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA.
⁸ Department of Population Health, John D. Bower School of Population Health, University of Mississippi Medical Center, Jackson, Mississippi, USA.
⁹ Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, USA.

Abstract

Introduction: Although life-saving, the physiologic stress of hemodialysis initiation contributes to physical impairment in some patients. Mortality risk assessment following hemodialysis initiation is underdeveloped and does not account for change over time. Measures of physical resilience, the ability of a physiologic state to overcome physiologic stressors, may help identify patients at higher mortality risk and inform clinical management.

Methods: We created 3 resilience categories (improving, stable, and declining) for trajectories of 4 phenotypes (physical function [PF], mental health [MH], vitality [VT], and general health [GH]) using SF-36 data collected the first year after hemodialysis initiation in the Choices for Healthy Outcomes in Caring for ESKD (CHOICE) study on 394 adults aged more than 55 years. Using mixed effects and Cox proportional hazard modeling, we assessed mortality following the first year on dialysis by resilience categories for each phenotype, adjusting for baseline phenotype and other confounders defined a priori over 4 years average follow-up.

Results: Based on global Wald tests, statistically significant associations of PF (P = 0.03) and VT (P = 0.0004) resilience categories with mortality were found independent of covariates. Declining PF trajectory was associated with higher mortality risk (hazard ratio [HR] = 1.32; 95% confidence interval [CI], 1.05-1.66), whereas improving VT trajectory was associated with lower mortality risk (HR= 0.73; 95% CI, 0.53 to 1.00), each as compared to stable trajectory.

Conclusion: Decreased resilience in PF and VT was independently associated with mortality. Phenotypic trajectories provide added value to baseline markers and patient characteristics when evaluating mortality. Hence, resilience measures hold promise for targeting population health interventions to the highest risk patients.

Keywords: dynamical systems; end-stage kidney disease; health-related quality of life; risk prediction.

Abstract

Grants and funding