Epidemiology and Health System Journal (Nov 2024)

Association Between Gallstone Disease and Kidney Stone Disease: A Systematic Review and Meta-analysis

  • Faramarz Beigi,
  • Alizamen Salehifard Jouneghani,
  • Saeid Heidari-Soureshjani,
  • Catherine MT Sherwin,
  • Ghorbanali Rahimian

DOI
https://doi.org/10.34172/ehsj.26270
Journal volume & issue
Vol. 11, no. 3
pp. 158 – 165

Abstract

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Background and aims: Gallstone disease (GSD) and kidney stone disease (KSD) have increased due to lifestyle in recent decades. This systematic review and meta-analysis aimed to investigate the association between these two diseases. Methods: A comprehensive electronic database search was conducted before August 25, 2024. This systematic review and meta-analysis included observational studies. The meta-analysis employed a random-effects model to compute the overall summary estimates of the association between GSD and KSD using risk ratios with 95% confidence intervals (CIs) as the primary measure of the effect size. Heterogeneity was evaluated using chi-square tests, the I² statistic, and forest plots. Publication bias was assessed through Begg’s and Egger’s tests. A P value of less than 0.05 was considered statistically significant, and all analyses were performed using Stata 17 software. Results: The meta-analysis included 9 studies encompassing 982847 participants. The pooled analysis revealed a statistically significant association between GSD and KSD, with a risk of 1.78 (95% CI: 1.572.03, P≤0.001). Begg’s and Egger’s tests demonstrated no significant bias (Begg’s test P=0.835, Egger’s test P=0.812). Variables such as study year, sample size, mean age of participants, mean follow-up, and study quality as determined by the Newcastle-Ottawa Scale (NOS) were examined, but none could significantly impact heterogeneity (P>0.10). Conclusion: This systematic review and meta-analysis provide evidence of a significant association between GSD and KSD. Therefore, further investigation into the underlying mechanisms and potential risk factors is necessary.

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