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DOI: 10.1055/s-0041-1740023
Correlation between Noncompliance Behavior and Biochemical Parameters of Chronic Kidney Disease Patients Undergoing Hemodialysis
Funding This study received funding from Nitte (Deemed to be University) and the grant number was NUSR2/2018/10/70.
Abstract
Background and Objectives Compliance with dietary, fluid, and medication instructions is a critically significant factor for the health and well-being of patients undergoing hemodialysis for an extended period. The current study assessed the correlation between noncompliance behavior and biochemical parameters of chronic kidney disease (CKD) patients undergoing hemodialysis. The study's objectives were 1) to assess patients' noncompliance behavior using a questionnaire, 2) to determine the biochemical parameters of CKD patients having noncompliance behavior, and 3) to find the correlation between biological parameters and noncompliance behavior.
Methods A cross-sectional study was conducted from July 12, 2018, to February 10, 2019. A purposive sampling technique was used to recruit the participants, and 100 participants were included in the study. The End-Stage Renal Disease–Adherence Questionnaire was used to assess the non-compliance behavior.
Results Most dialysis patients (70%) were compliant with the therapeutic regime, while 30% failed to comply. The study revealed a significant positive correlation between noncompliance behavior and biochemical parameters of CKD patients undergoing hemodialysis (r = 0.578, p < 0.05).
Conclusion Noncompliance behavior is significantly correlated with the biochemical parameters among patients with CKD on dialysis. Optimal health is possible through fluid and dietary compliance in these patients. Hence, adherence behavior plays a significant role in the health and recovery of dialysis patients with CKD.
Keywords
biological parameter - chronic kidney disease - corelation - hemodialysis - noncompliance behaviorPublication History
Article published online:
31 December 2021
© 2021. Nitte (Deemed to be University). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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