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. 2018 Apr;71(2):103-112.
doi: 10.4097/kjae.2018.71.2.103. Epub 2018 Apr 2.

Introduction to systematic review and meta-analysis

Affiliations

Introduction to systematic review and meta-analysis

EunJin Ahn et al. Korean J Anesthesiol. 2018 Apr.

Abstract

Systematic reviews and meta-analyses present results by combining and analyzing data from different studies conducted on similar research topics. In recent years, systematic reviews and meta-analyses have been actively performed in various fields including anesthesiology. These research methods are powerful tools that can overcome the difficulties in performing large-scale randomized controlled trials. However, the inclusion of studies with any biases or improperly assessed quality of evidence in systematic reviews and meta-analyses could yield misleading results. Therefore, various guidelines have been suggested for conducting systematic reviews and meta-analyses to help standardize them and improve their quality. Nonetheless, accepting the conclusions of many studies without understanding the meta-analysis can be dangerous. Therefore, this article provides an easy introduction to clinicians on performing and understanding meta-analyses.

Keywords: Anesthesiology; Meta-analysis; Randomized controlled trial; Systematic review.

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Figures

Fig. 1.
Fig. 1.
Levels of evidence.
Fig. 2.
Fig. 2.
Flowchart illustrating a systematic review.
Fig. 3.
Fig. 3.
Forest plot analyzed by two different models using the same data. (A) Fixed-effect model. (B) Random-effect model. The figure depicts individual trials as filled squares with the relative sample size and the solid line as the 95% confidence interval of the difference. The diamond shape indicates the pooled estimate and uncertainty for the combined effect. The vertical line indicates the treatment group shows no effect (OR = 1). Moreover, if the confidence interval includes 1, then the result shows no evidence of difference between the treatment and control groups.
Fig. 4.
Fig. 4.
Forest plot representing homogeneous data.
Fig. 5.
Fig. 5.
Funnel plot showing the effect size on the x-axis and sample size on the y-axis as a scatter plot. (A) Funnel plot without publication bias. The individual plots are broader at the bottom and narrower at the top. (B) Funnel plot with publication bias. The individual plots are located asymmetrically.
Fig. 6.
Fig. 6.
Funnel plot adjusted using the trim-and-fill method. White circles: comparisons included. Black circles: inputted comparisons using the trim-and-fill method. White diamond: pooled observed log risk ratio. Black diamond: pooled inputted log risk ratio.

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