Survival and Mortality Predictors Among Hemodialysis Patients in a Pakistani Tertiary Care Center: A Retrospective Cohort Study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: End-stage renal disease (ESRD) is a growing public health burden in low- and middle-income countries, including Pakistan, where access to maintenance hemodialysis (MHD) is expanding, but long-term survival outcomes remain underreported. This study evaluated the survival duration and clinical predictors of mortality among patients undergoing MHD at a tertiary care hospital in Pakistan. Methods: A retrospective analysis of prospectively collected data was conducted on patients receiving MHD between 2012 and 2014 at Mayo Hospital, King Edward Medical University, Lahore. Patients on dialysis for ≥3 months were included. Demographic and clinical data were extracted from records. Survival was assessed using Kaplan-Meier analysis, and predictors of mortality were evaluated using Cox proportional hazards regression. Results: Of the 158 patients enrolled, 152 met inclusion criteria. Over a 122-week follow-up, 48 (31.5%) patients died and 104 survived. The overall mean survival was 108 ± 2 weeks. Multivariable Cox regression identified increasing age (HR = 1.04, p<0.001), body weight (HR = 1.03, p=0.015), and underweight status (HR = 1.93, p=0.034) as independent risk factors for mortality. Conversely, higher body mass index (BMI) (HR = 0.80, p<0.001) and serum albumin (HR = 0.52, p=0.036) were protective. Conclusion: Survival in hemodialysis patients is significantly influenced by age, nutritional status, and albumin levels. These findings support the implementation of routine nutritional assessments and targeted interventions to reduce mortality. Future studies should explore broader determinants in multicenter prospective cohorts to improve long-term outcomes for ESRD patients in resource-limited settings.
Authors: Irfan Elahi, Mehwish Mushtaq, Muhammad Anees, Shahbaz Pervaiz, Sana Kifayat, Bilal Javaid, SameeUllah Khan
Language: English
Subfield: Nephrology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4411041014