Forest Plots + Meta-Analysis
Forest plots are the standard visual summary of a meta‑analysis: they show each included study’s effect estimate with its 95% confidence interval, the weight given to each study, and the pooled estimate. Mastery of forest‑plot interpretation is essential for critical appraisal in emergency medicine and for exam answers on measures of effect.
Purpose and when to use a forest plot
- To display individual study estimates with 95% confidence intervals and the pooled estimate (diamond).
- To show study weights and relative precision so the reader can see which studies drive the pooled result.
- To allow rapid assessment of direction and consistency of effect and to prompt investigation of heterogeneity.
- Forest plots may be used even when no pooled estimate is presented, provided outcomes and effect measures are sufficiently comparable (NICE).
Key elements (anatomy) of a forest plot
The columns from left to right:
- Study identifiers: author/trial name and year; cross‑reference to study characteristics in the review.
- Intervention Group (n/N) & Control Group (n/N): Events and totals for intervention and comparator arms when applicable. n refers to the number of participants who experienced the outcome in each group (for example in the Sirius study it was 19 in the intervention group and 14 in the control). N refers to the total number of participants in each group (for...