Rationale of α-Ketoanalogue Supplemented with Low Protein Diet for the Treatment of Chronic Kidney Disease

Abstract

Background: Chronic kidney disease (CKD) has challenged the healthcare system for years. Use of α- ketoanalogue (KA) supplemented with a low protein diet (LPD) may improve renal function. In this study, we aim to find out the effectiveness of KA supplemented with LPD for the therapy of CKD.

Methods: A quantitative cross-sectional study was conducted at Shree Birendra Hospital with 25 control and 25 treatment groups. The control group was treated with LPD (0.8 g/kg/day), while the treatment group was treated with KA (3 tablets/day for 4 weeks followed by 6 tablets/day for the next 16 weeks) along with LPD. The baseline parameters were measured on day 0, then subsequently at week 4, week 12, and lastly at the end of week 16. Results were then compared with the control group for analysis.

Results: The serum level of creatinine showed a progressive decline in the treatment group (2.03±0.39 to 1.68±0.51) in comparison to the control group (2.03±0.36 to 2.54±0.69). However, there was a progressive decline in the level of blood urea (99.07±11.87 to 72.11±26.90) up to 12th week of treatment, and a slight increment was observed in the 16th week of treatment (72.11±26.90 to 86.06±27.90) but the level was below the baseline value (99.07). Similarly, the blood level of sodium and potassium was slightly affected by the increase in sodium and decrease in potassium level from the baseline in the treatment group. The level of serum albumin was increased in the treatment group as compared to the control group. The systolic blood pressure was increased in both the treatment and control group whereas the diastolic blood pressure was decreased in the treatment group rather than the control group.

Conclusion: KA supplemented with LPD shows a significant improvement in renal function of CKD III patients that delays the time for dialysis or transplant. However, further substantial multi-institutional randomized studies are necessary to generalize the findings.