Transplantation, Waitlist Status, and County Indices of Economic Health in West Virginia

Author:

Shawwa Khaled1ORCID,Thompson Jesse2ORCID,Chaudhary Vishy1,Parravani Anthony1,Poling Mark1,Pellegrino Bethany1ORCID,Schmidt Rebecca1

Affiliation:

1. Division of Nephrology, Department of Medicine, West Virginia University School of Medicine, Morgantown, West Virginia

2. Department of Medicine, West Virginia University School of Medicine, Morgantown, West Virginia

Abstract

Key Points Patients with ESKD coming from impoverished counties are less likely to be waitlisted or transplanted.Insurance status modified the relationship between county poverty rates and waitlisting/transplant. Background Kidney transplantation is the optimal treatment for patients with ESKD. Given lower rates of kidney transplant in West Virginia (WV), we searched for potential predictors, focusing on the indices of economic health. Methods Data on the initiation of RRT, being waitlisted for, and receiving a kidney transplant between 1965 and 2020 were collected from United States Renal Data System. Data on county poverty rate (PR) and economic distress were collected from the Appalachian Regional Commission. Results Of the 23,055 WV patients identified, 2999 (13%) were transplanted compared with 514,050 (15.3%) for the rest of the United States (P < 0.001). Patients who never received a kidney transplant were from counties with higher PRs (17.95%) compared with transplanted patients (17.44%; P < 0.001). Waitlisted patients (2,375) came from counties with lower PRs than those who were never waitlisted (17.48 versus 17.94%; P < 0.001). Waitlisted patients were less likely to be from distressed or at-risk counties (32 versus 34.3%; P = 0.05) than patients who were never waitlisted. In multivariable logistic regression, county PR remained an independent predictor of being transplanted (odds ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P = 0.008) or waitlisted (odds ratio, 0.9; 95% confidence interval, 0.84 to 0.96; P = 0.001) per 5% increase in PR after adjusting for age, sex, body mass index, alcohol use, functional status, and comorbid medical conditions. Group/employer health insurance seemed to modify the relationship between PR and waitlist, where PR remained an independent predictor of waitlisting among patients with insurance. Conclusions Waitlisted patients and transplant recipients from WV were more likely to hail from counties with lower PRs and those in better economic health.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Psychiatry and Mental health,Neuropsychology and Physiological Psychology

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