Objective To systematically review the dose-response relationship between cadmium exposure and the risk of stroke onset. Methods The PubMed, Web of Science, Cochrane Library, Embase, CNKI, VIP, WanFang Data, and CBM databases were electronically searched to collect studies related to objectives from inception to June 2024. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. Meta-analysis was then performed using Stata 15.1 software. Results There were 10 studies that involved 28 250 participants, and 7 of them were prospective cohort studies and 3 were case-control studies. Meta-analysis results showed that cadmium exposure significantly increased the risk of stroke (RR=1.39, 95%CI 1.20 to 1.59, P<0.01), blood cadmium exposure significantly increased the risk of stroke (RR=1.79, 95%CI 1.34 to 2.25, P<0.01), urinary cadmium exposure significantly increased the risk of stroke (RR=1.30, 95%CI 1.09 to 1.52, P<0.01). Blood cadmium exposure had a significantly nonlinear dose-response relationship associated with an increased risk of stroke (χ2=8.56, P<0.05). The risk of stroke increased by 15% with the blood cadmium exposure concentration of 0.8 μg/L (RR=1.15, 95%CI 0.98 to 1.36), and 51% with the blood cadmium exposure concentration of 1.2 μg/L (RR=1.51, 95%CI 1.14 to 2.01) than those without blood cadmium exposure. Urinary cadmium exposure had significantly linear dose-response relationship associated with an increased risk of stroke (χ2=2.47, P=0.12). The risk of stroke increased by 26% with the urinary cadmium exposure concentration of 0.8 μg/g (RR=1.26, 95%CI 1.20 to 1.31), and 31% with the urinary cadmium exposure concentration of 1.2 μg/g (RR=1.31, 95%CI 1.27 to 1.36) than those without urinary cadmium exposure. Conclusion Cadmium exposure increases the risk of stroke. There was a significant dose-response relationship between cadmium exposure and the risk of stroke.
ObjectiveTo systematically review the correlation between heavy metal exposure, especially Cadmium (Cd), Mercury (Hg), Lead (Pb) and the risk of kidney stone occurrence, and to explore the potential dose-response relationship between them. MethodsWe conducted a computerized search of Web of Science, PubMed, Cochrane Library, Embase, CNKI, WanFang Data, CBM, and VIP databases, with supplementary searches in Scopus, WHO IRIS, and Google Scholar, to collect studies on the correlation between heavy metal exposure and kidney stone, the search period ranging from the inception of each database to September 14, 2025. Two researchers independently screened the literature, extracted data, and assessed the quality of the included studies. Traditional meta-analysis and dose–response meta-analysis were performed using Stata 15.1 software. ResultsA total of 16 studies were included, comprising 13 cross-sectional studies and 3 case-control studies, involving 117 992 participants. The results of the meta-analysis showed a significant positive correlation between urinary Cd levels and the risk of kidney stone occurrence (OR=1.16, 95%CI 1.05 to 1.27, P<0.05). Further subgroup analysis and meta-regression indicated that region, gender, Cd exposure status and eGFR/proteinuria might be sources of heterogeneity. Blood Cd levels were significantly correlated with the risk of kidney stones (OR=1.31, 95%CI 1.03 to 1.65, P<0.05). There was an increasing linear dose-response relationship between blood Cd exposure and the risk of kidney stones (χ2=0.35, P>0.05), with each 1 μg/L increase in blood Cd corresponding to a 20% increase in the risk of kidney stones (OR=1.20, 95%CI 1.08 to 1.33). No significant associations were found between the levels of other metal exposures and the risk of kidney stones (PUHg=0.73, PUPb=0.82, PUCr=0.56, PUNi=0.06, PBHg=0.15, PBPb=0.52). Urinary Cd showed a significant nonlinear dose-response relationship with the risk of kidney stones (χ2=4.52, P<0.05). When urinary Cd exposure was 0.2 μg/L, the risk of kidney stones increased by 35% (OR=1.35, 95%CI 1.23 to 1.49), and for each 1μg/L increase in urinary Cd, the risk of kidney stones increased by 44% (OR=1.44, 95%CI 1.30 to 1.59). ConclusionCd exposure levels are significantly positively correlated with the risk of kidney stone occurrence, suggesting that Cd exposure may be a potential risk factor for kidney stones. No significant association was found between exposure to other metals and the risk of kidney stone occurrence. However, due to limitations in study design, further research is needed in the future to establish the causal relationship of this association.
In meta-analysis, heterogeneity in statistical measures across primary studies can significantly affect the efficiency of data synthesis and the accuracy of result interpretation. Such inconsistencies may introduce bias in effect size estimation and increase the complexity of pooled analyses. Therefore, establishing standardized approaches for data type transformation and harmonizing different statistical measures has become a critical step in ensuring the quality of meta-analyses. To achieve efficient and scientifically rigorous data integration, researchers need to master systematic data transformation techniques and develop standardized processing strategies. Based on this need, this study provides a comprehensive summary of effect size transformation methods in meta-analysis, focusing on standardizing binary and continuous variables. It offers practical guidance to support researchers in applying these methods consistently and accurately.
As the highest level of evidence in evidence-based medicine, systematic reviews have a profound impact on clinical practice and policy-making. However, challenges remain regarding the methodological rigor and reproducibility of their results. In recent years, replication research on systematic reviews has emerged as a critical approach to ensuring evidence quality, rational allocation of research resources and advancing evidence-based medicine. This article systematically reviews the theoretical foundations and research value of replication studies in systematic reviews, with a focus on their core design principles and implementation process. Key methodological steps are discussed, including assessing the necessity of replication, determining the type of replication, pre-registration, obtaining data and code, conducting independent re-analyses, and evaluating result consistency. Meanwhile, using the childhood deworming program as an illustrative case, we further outline the practical workflow of conducting replication research and demonstrate its importance in confirming the robustness of evidence and strengthening confidence in decision-making. In addition, this study synthesizes the methodological challenges encountered throughout the entire replication process, from literature searching to data analysis, and discusses future directions involving the integration of artificial intelligence, the development of reporting standards such as PRITERS, and the establishment of supportive research infrastructures. Overall, this work aims to provide methodological guidance for the standardized conduct of replication studies and to support the high-quality development of evidence-informed practice.