Retrospective Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Diabetes. Sep 15, 2023; 14(9): 1385-1392
Published online Sep 15, 2023. doi: 10.4239/wjd.v14.i9.1385
Effects of paricalcitol combined with hemodiafiltration on bone-metabolism-related indexes in patients with diabetic nephropathy and chronic renal failure
Xiao-Ying Ma, Yu-Ping Sheng, Xing-Meng Yang, Hao-Ran Zhang, Fu-Yun Sun
Xiao-Ying Ma, Yu-Ping Sheng, Xing-Meng Yang, Hao-Ran Zhang, Fu-Yun Sun, Department of Nephrology, Cangzhou Central Hospital, Cangzhou 061000, Hebei Province, China
Author contributions: Ma XY designed and performed the research and wrote the paper; Sun FY designed the research and supervised the report; Sheng YP and Yang XM designed the research and contributed to the analysis; Zhang HR provided clinical advice.
Institutional review board statement: The study was reviewed and approved by the Cangzhou Central Hospital.
Informed consent statement: All participants have signed an informed consent form.
Conflict-of-interest statement: The authors declare no conflicts of interest for this article.
Data sharing statement: Clinical data for this study can be obtained from the corresponding author.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Fu-Yun Sun, MM, Professor, Department of Nephrology, Cangzhou Central Hospital, No. 16 Xinhua West Road, Yunhe District, Cangzhou 061000, Hebei Province, China. 17734498766@163.com
Received: May 4, 2023
Peer-review started: May 4, 2023
First decision: May 15, 2023
Revised: May 25, 2023
Accepted: August 7, 2023
Article in press: August 7, 2023
Published online: September 15, 2023
Processing time: 132 Days and 3.8 Hours
ARTICLE HIGHLIGHTS
Research background

Diabetic nephropathy (DN) is one of the common complications of diabetes, mainly manifested as glomerular damage. As it progresses, DN may lead to chronic renal failure (CRF), which seriously affects quality of life and life expectancy.

Research motivation

Hemodialysis filtration is an effective method for treating CRF, but patients receiving hemodialysis often experience abnormalities in blood calcium and phosphorus. Paroxycarbinol can promote intestinal calcium absorption and inhibit the secretion and differentiation of Paricalcitol cells by binding to vitamin D receptors. However, it is still unclear whether periostenol has an effect on calcium phosphate metabolism disorder in patients with CRF due to DN.

Research objectives

Supplement the blank of paracalcitol combined with hemodiafiltration in the treatment of CRF, and increases the clinical treatment plan for disorder of calcium and phosphate metabolism during hemodialysis and filtration.

Research methods

We retrospectively analyzed and observed the effect of paricalcitol combined with hemodiafiltration on calcium phosphate metabolism disorder in patients with CRF due to DN. For the first time, a risk model for predicting efficacy was established using a least absolute shrinkage and selection operator (LASSO) regression model.

Research results

We found that the combination of paricalcitol and hemodialysis filtration significantly improved the metabolic disorder of calcium phosphate metabolism disorder in patients, and improved efficacy. Using the LASSO model, we established a risk score to predict efficacy, which provides a new reference for clinical treatment and efficacy prediction.

Research conclusions

Paricalcitol can improve calcium phosphate metabolism disorder in hemodialysis patients, and the risk model established by LASSO regression model effectively predicts clinical efficacy.

Research perspectives

As a retrospective study, we cannot collect more samples and observe the prognosis of patients. We hope to conduct randomized controlled trials in future studies to observe the long-term prognosis.