Hematological and Urine Analysis Changes in Pre and Post Hemodialysis Patients with Chronic Kidney Disease in a Tertiary Care Hospital in Puducherry- South India
DOI:
https://doi.org/10.63001/tbs.2025.v20.i02.S2.pp664-670Keywords:
Chronic Kidney Disease (CKD), Hemodialysis, Hematological Changes, Platelet Count, Coagulation Parameters, Urine AnalysisAbstract
Background: Chronic kidney disease (CKD) often necessitates hemodialysis, which can impact hematological and urine parameters. This study aims to evaluate the changes in these parameters in CKD patients undergoing hemodialysis at a tertiary care hospital in Puducherry.
Methods: An observational study was conducted at a tertiary care hospital involving 55 CKD patients (44 males and 11 females) aged 29 to 80 years (mean age 58.11 ± 1.46 years). Hematological and urine samples were collected pre- and post-dialysis. Complete blood count, coagulation profiles, and urine analysis were carried out using automated machinery. The paired t-test assessed significant differences between pre- and post-dialysis values.
Results: Post-dialysis, there was a significant increase in mean hemoglobin (Hb) levels (7.70 g/dL to 8.35 g/dL, P = 0.0009) and a slight, non-significant decrease in hematocrit (HCT) levels (25.62% to 24.24%, P = 0.2772). Platelet counts significantly decreased (186.1818 x103/μl to 162.3455 x103/μl, P = 0.0008), with a slight reduction in platelet distribution width (PDW). Clotting time significantly increased (4.117273 minutes to 4.291818 minutes, P = 0.0241). Red blood cell (RBC) indices remained stable, with minor changes in MCV, MCH, and MCHC. Urine analysis showed no significant differences in pre- and post-dialysis.
Conclusion: Hemodialysis in CKD patients induces significant hematological changes, particularly in Hb concentration, platelet count, and coagulation parameters, without significant alterations in urine composition. Limitations include the small sample size and single-center design. Future research should involve larger, multi-center cohorts and longitudinal follow-up to understand long-term trends and outcomes better.