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Adding to the mounting evidence for geographic inequity in liver transplantation: Hospital length of stay
Author(s) -
Kueht Michael,
Goss John A.,
Rana Abbas
Publication year - 2018
Publication title -
clinical transplantation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.918
H-Index - 76
eISSN - 1399-0012
pISSN - 0902-0063
DOI - 10.1111/ctr.13336
Subject(s) - medicine , liver transplantation , proportional hazards model , multivariate analysis , transplantation , cohort , multivariate statistics , survival analysis , covariate , cohort study , demography , emergency medicine , statistics , mathematics , sociology
Background Severe geographic inequities in liver transplantation have persisted for years. Previous investigators have demonstrated 90‐day transplant rates varying from 14% to 82% and death rates varying from 18% to 86%.[1][Gentry SE, 2013] The aim of this analysis was to utilize a robust multivariate analysis to investigate whether geographic inequities affected the length of stay after liver transplantation. Methods We conducted a unique Kaplan‐Meier analysis with the event being discharge from the hospital and length of stay as the time to the event, using a cohort of 66 674 recipients listed in the UNOS database from 2002 to 2016. Multivariate Cox regression using 43 covariates was used for time‐to‐event analysis. Results Region 9 (0.82; CI 0.79‐0.85), Region 2 (0.85; CI 0.83‐0.88), and Region 10 (0.96; CI 0.93‐0.99) were statistically significant factors for prolonged hospital stay. The following covariates were the most significant factors for prolonged hospital stay: serum sodium >150 mE q/L (0.70; CI 0.62‐0.78), ICU admission (0.77; CI 0.74‐0.80), hospital admission (0.81; 0.79‐0.83), region 9 (0.82; CI 0.79‐0.85), and ventilator dependence (0.82; CI 0.76‐0.88). Conclusion In this analysis, we demonstrate regional disparities in hospital length of stay that are significant in robust multivariable Cox regression analysis. We hope the transplant community will take immediate measures to correct geographic inequities.