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Data from: Association between metabolic syndrome components and the risk of developing nephrolithiasis: Bayesian meta-analysis and meta-regression with dose-response analysis

Citation

Rahman, Ilham Akbar; Nusaly, Ilham Fauzan; Syahrir, Syakri; Nusaly, Harry (2021), Data from: Association between metabolic syndrome components and the risk of developing nephrolithiasis: Bayesian meta-analysis and meta-regression with dose-response analysis, Dryad, Dataset, https://doi.org/10.5061/dryad.76hdr7svg

Abstract

Nephrolithiasis has shifted to be a systemic disease. As opposed to an isolated urinary metabolic problem, it became determined that nephrolithiasis turned into considerably related to link with systemic diseases such as hypertension, obesity, dyslipidemia, and insulin resistance. The interplay between these four factors defines MetS (metabolic syndrome). In this review we aim to clarify the associations of metabolic syndrome and its components to kidney stone incident. Online databases of EMBASE, MEDLINE, and Google Scholar were searched up to October 2020 to identify observational studies examining the association between metabolic syndrome components and kidney stone incident. Bayesian Random-Effects Meta-Analysis and Meta-Regression were performed to observe the association. Linear dose-response analyses were conducted to shape the direction of the association. Data analysis was performed using STATA, and R statistics. This dataset contains supplementary material and figures as additional analysis of the study.

Methods

This dataset was created by several analyses consisting of sensitivity analysis, trim and fill analysis, and funnel plot asymmetry test. Our data was generated using STATA and R software. The purpose of this data is to present additional figures to explain the details for the study.