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Seeing the Forest by Looking at the Trees: How to Interpret a Meta-Analysis Forest Plot

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We suggest first looking at the type of outcome found in columns 5 and 6 as it influences the contents in other columns (Figures 1 and 2). If the outcome… Click to show full abstract

We suggest first looking at the type of outcome found in columns 5 and 6 as it influences the contents in other columns (Figures 1 and 2). If the outcome is binary, the number of events (numerator) and the total (denominator representing the population size) will be presented in columns 2 and 3, Figure 1. With binary data, the ratio between risks (risk ratio) or odds (odds ratio) are calculated and presented numerically in column 5 and graphically in column 6 along with its 95% confidence interval (95% CI). However, if the outcome is continuous, the difference in the means (mean difference) between the intervention and control groups is displayed in columns 5 and 6 with its 95% CI, Figure 2. And, the individual study means, standard deviations (sd) and sample sizes are given in columns 2 and 3.

Keywords: forest looking; trees interpret; interpret meta; looking trees; seeing forest; meta analysis

Journal Title: Global Spine Journal
Year Published: 2021

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