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Lipid accumulation product and visceral adiposity index: two indices to predict metabolic syndrome and insulin resistance in chronic kidney disease patients Cover

Lipid accumulation product and visceral adiposity index: two indices to predict metabolic syndrome and insulin resistance in chronic kidney disease patients

Open Access
|May 2023

Abstract

Objective. Chronic kidney disease (CKD), metabolic syndrome (MetS) and insulin resistance (IR) are the major health problems associated with the increasing risk of cardiovascular and cerebrovascular complications.

Methods. This cross-sectional study included 209 CKD patients of stage (3–5) on conservative treatment to assess the usage of lipid accumulation product (LAP) and visceral adiposity index (VAI) to predict both MetS and IR in CKD patients.

Results. In males, from the anthropometric measurements, LAP was the best predictor of MetS with 94.4% sensitivity and 77.8% specificity. VAI was the next one with 83.3% sensitivity and 69.4% specificity. The same results were obtained in females. The receiver operating characteristic (ROC) curve showed LAP as the best predictor of MetS with the highest 92.6% sensitivity and 60.6% specificity followed by VAI with 83.6% sensitivity and 83.6% specificity. In addition, LAP was a good predictor of IR with more than 70% sensitivity in both males and females. VAI as a predictor of IR showed 62.2% sensitivity in males and 69.9% in females.

Conclusion. The present data indicate that both LAP and VAI can serve as predictors of MetS and IR in CKD patients, whereas LAP is the best anthropometric measure to predict MetS and LAP is more sensitive and specific than VAI in IR predicting in both males and females.

DOI: https://doi.org/10.2478/enr-2023-0012 | Journal eISSN: 1336-0329 | Journal ISSN: 1210-0668
Language: English
Page range: 99 - 105
Published on: May 15, 2023
Published by: Slovak Academy of Sciences, Mathematical Institute
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2023 Ahmed Mohamed Fahmy, Nelly El Shall, Ibrahim Kabbash, Loai El Ahwal, Amal Selim, published by Slovak Academy of Sciences, Mathematical Institute
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.