Predictors of mortality among hemodialysis patients in Hamadan province using random survival forests - TAPAK, LEILI (J Prev Med Hyg, 2020)
BACKGROUND: Hemodialysis patients are at a high risk for morbidity and mortality. This study aimed to find the predictors of mortality and survival in hemodialysis patients in Hamadan province of Iran. METHODS: A number of 785 patients during the entire 10 years were enrolled into this historical cohort study. Data were gathered by a checklist of hospital records. The survival time was the time between the start of hemodialysis treatment to patient’s death as the end point. Random survival forests (RSF) method was used to identify the main predictors of survival among the patients. RESULTS: The median survival time was 613 days. The number of 376 deaths was occurred. The three most important predictors of survival were hemoglobin, CRP and albumin. RSF method predicted survival better than the conventional Cox-proportional hazards model (out-of-bag C-index of 0.808 for RSF vs. 0.727 for Cox model). CONCLUSIONS: We found that positivity of CRP, low serum albumin and low serum hemoglobin were the top three most important predictors of low survival for HD patients