| Literature DB >> 25097332 |
A Chandrashekar1, S Ramakrishnan2, D Rangarajan2.
Abstract
Despite the continuous improvement of dialysis technology and pharmacological treatment, mortality rates for dialysis patients are still high. A 2-year prospective study was conducted at a tertiary care hospital to determine the factors influencing survival among patients on maintenance hemodialysis. 96 patients with end-stage renal disease surviving more than 3 months on hemodialysis (8-12 h/week) were studied. Follow-up was censored at the time of death or at the end of 2-year study period, whichever occurred first. Of the 96 patients studied (mean age 49.74 ± 14.55 years, 75% male and 44.7% diabetics), 19 died with an estimated mortality rate of 19.8%. On an age-adjusted multivariate analysis, female gender and hypokalemia independently predicted mortality. In Cox analyses, patient survival was associated with delivered dialysis dose (single pool Kt/V, hazard ratio [HR] =0.01, P = 0.016), frequency of hemodialysis (HR = 3.81, P = 0.05) and serum albumin (HR = 0.24, P = 0.005). There was no significant difference between diabetes and non-diabetes in relation to death (Relative Risk = 1.109; 95% CI = 0.49-2.48, P = 0.803). This study revealed that mortality among hemodialysis patients remained high, mostly due to sepsis and ischemic heart disease. Patient survival was better with higher dialysis dose, increased frequency of dialysis and adequate serum albumin level. Efforts at minimizing infectious complications, preventing cardiovascular events and improving nutrition should increase survival among hemodialysis patients.Entities:
Keywords: Hemodialysis; mortality; survival
Year: 2014 PMID: 25097332 PMCID: PMC4119332 DOI: 10.4103/0971-4065.132985
Source DB: PubMed Journal: Indian J Nephrol ISSN: 0971-4065
Demographic and clinical characteristics
Figure 1Native kidney disease
Hemodialysis characteristics
Figure 2Causes of death in the cohort (n= 19)
Relationship between frequency of dialysis and weekly Kt/V
Investigation profile in relation to the patient outcome
Multivariate logistic regression analysis to predict factors influencing mortality
Assessment of covariates using Cox regression proportional hazard function
Figure 3Cumulative patient survival and dialysis dose (Kt/V)
Figure 6Cumulative patient survival and diabetes status