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. 2024 Aug 28;25(1):279.
doi: 10.1186/s12882-024-03719-3.

Time to death and its predictors among patients with chronic kidney disease on hemodialysis at dialysis unit in Addis Ababa, Ethiopia: a retrospective cohort study

Affiliations

Time to death and its predictors among patients with chronic kidney disease on hemodialysis at dialysis unit in Addis Ababa, Ethiopia: a retrospective cohort study

Azeb Haile Tesfaye et al. BMC Nephrol. .

Abstract

Background: Chronic kidney disease is a progressive disease that affects more than 10% of the world's population and is also the leading cause of death in the twenty-first century. Furthermore, it imposes a significant financial burden on people undergoing hemodialysis. However, there is little research, particularly in the study area, on time to death and its predicators among hemodialysis patients in Ethiopia; therefore, knowing time to death and identifying predicators that affect survival time is crucial in order to improve survival time and enhance the prognosis of hemodialysis patients. The aim of this study was to assess time to death and its predictors among patients with chronic kidney disease on hemodialysis at a dialysis unit in Addis Ababa, Ethiopia, in 2023.

Methods: An institution-based retrospective cohort study was carried out among 370 chronic kidney disease patients on hemodialysis from January 1st, 2017 to December 30th, 2022. Data were extracted from April 1st-May 20th, 2023, and each variable was coded and entered into Epi Data version 3.1 and then exported into STATA version 15 software for analysis. Kaplan-Meier and the log-rank test were done. Bivariable Cox-proportional regression was done, and a variable whose p-value was < 0.25 and fulfilled the proportional hazard assumption by using graphical and Shenfield residuals was entered into multivariable Cox-proportional regression. Finally, a variable whose p-value < 0.05 and adjusted hazard ratio with its CI were declared statistically significant predictors.

Result: In this study, the overall median survival time was 47 months (95% CI: 36.7, 56), with an incidence rate of death of 16.8 per 1000 people per month of observation (95% CI: 13.8-20.3). Age 64 and above (Adjusted Hazard Ration: 2.8; 95% CI: 1.67-4.98), catheter vascular access (Adjusted Hazard Ration: 3.47; 95% CI: 2.03-5.93), cardiovascular disease (Adjusted Hazard Ration: 1.88; 95% CI: 1.15-3.07), and blood group B (Adjusted Hazard Ration: 2.07; 95% CI: 1.17-3.69) were significant predictors of time to death among hemodialysis patients. CONCLUSION AND RECOMMENDATION: The median survival time was 47 months, with an interquartile range of 40. Cardiovascular disease, older adults, central venous catheters, and blood type B were significant predictors of time to death for hemodialysis patients. Therefore, in order to improve the survival of hemodialysis patients, health professionals and concerned bodies should give concern to and work on those predictors.

Keywords: Addis Ababa; Chronic kidney disease; Cox-regression; Hemodialysis; Time to death.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Kaplan–Meier survival estimate of chronic kidney disease patients on hemodialysis at selected hospitals giving dialysis Service, Addis Ababa, Ethiopia, 2023
Fig. 2
Fig. 2
The outcome of chronic kidney disease patients on hemodialysis at selected hospitals giving dialysis Service, Addis Ababa, Ethiopia, 2023
Fig. 3
Fig. 3
There is survival difference b/n a vascular access with log rank test at p value of 0.0000 and chi.2 of 41.89. Kaplan–Meier survival curve for vascular access of chronic kidney disease patients on hemodialysis at a selected dialysis center in Addis Ababa, Ethiopia, 2023
Fig. 4
Fig. 4
It indicated that there is a difference of survival between those who had cardiovascular disease than of without cardiovascular disease at p-value of 0.0000. Kaplan–Meier survival curve for cardiovascular disease of chronic kidney diseases patients on hemodialysis at selected hospitals giving dialysis Service, Addis Ababa, Ethiopia, 2023
Fig. 5
Fig. 5
Cox-Snell residual plot to test Cox regression overall model fitness test for chronic kidney disease patients on hemodialysis at selected hospitals giving dialysis Service, Addis Ababa, Ethiopia, 2023

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