Critical appraisal of systematic reviews and meta-analyses: a step-by-step guide for nephrologists

被引:0
|
作者
Cheungpasitporn, Wisit [1 ]
Wathanavasin, Wannasit [1 ,2 ]
Thongprayoon, Charat [1 ]
Kaewput, Wisit [3 ]
Tapolyai, Mihaly [4 ,5 ]
Fulop, Tibor [5 ,6 ]
机构
[1] Mayo Clin, Dept Med, Div Nephrol, Rochester, MN USA
[2] Charoenkrung Pracharak Hosp, Bangkok Metropolitan Adm, Dept Med, Nephrol Unit, Bangkok, Thailand
[3] Phramongkutklao Coll Med, Dept Mil & Community Med, Bangkok, Thailand
[4] Szent Margit Korhaz, Dept Nephrol, Budapest, Hungary
[5] Ralph H Johnson VA Med Ctr, Med Serv, Charleston, SC USA
[6] Med Univ South Carolina, Dept Med, Div Nephrol, Charleston, SC USA
关键词
Systematic reviews; meta-analyses; heterogeneity; risk of bias; nephrology; medical education; QUALITY; BIAS; HETEROGENEITY; TOOL;
D O I
10.1080/0886022X.2025.2476736
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Background Systematic reviews and meta-analyses play a pivotal role in evidence-based medicine, including nephrology, by consolidating findings from multiple studies. To maximize their utility, rigorous quality assessment during peer review is essential. Challenges such as heterogeneity, bias, and methodological flaws often undermine these studies, necessitating a structured appraisal process. Methods This guide outlines a framework for nephrologists on appraising systematic reviews and meta-analyses. Key areas include heterogeneity assessment using the I2 statistic, interpretation of forest plots for pooled effect estimates, and the use of funnel plots with Egger's test to identify potential publication bias. Risk of bias is evaluated using RoB 2 for randomized controlled trials and ROBINS-I for non-randomized studies. Subgroup and sensitivity analyses, along with meta-regression, address heterogeneity and examine the robustness of findings. Results The I2 statistic quantifies heterogeneity by estimating the proportion of variability in a meta-analysis. Funnel plots and Egger's test help detect publication bias. Major biases, such as selection, performance, detection, and publication bias, are identified using structured tools like AMSTAR 2, Cochrane RoB 2, and ROBINS-I. The GRADE framework further assesses the overall certainty of the evidence. Emphasis is placed on PRISMA compliance, protocol pre-registration, and transparent reporting of statistical analyses, subgroup, and sensitivity assessments. The inclusion of grey literature remains optional. Conclusion By focusing on key areas such as heterogeneity, risk of bias, and robust statistical methods, this guide enables nephrologists to critically appraise systematic reviews and meta-analyses, fostering better clinical decision-making and improved patient care in nephrology.
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页数:13
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