We used random effects bivariate

Call To Action: You’re giving a speech, not for your health, but for a reason. There’s something you want out of the audience. You here to give them information, but also a call to action. We included publications reporting results from the same study or studies based on overlapping samples only if they complemented each other in terms of reported results (for instance, if they reported results for different cut off values); we took care to avoid double counting.Two reviewers (ZZ, EY) independently assessed the methodological quality of the included studies by using a modified version of the QUADAS 2 tool (web appendix 2).13 Any disagreements were resolved through discussion and, if necessary, arbitration by another reviewer (CH).We constructed two by two tables, calculated sensitivity and specificity with 95% confidence intervals, and created coupled forest plots for each subset of data. We used random effects bivariate models to do separate meta analyses for different pre specified cut off values.14 We explored heterogeneity in the first instance through visual examination of the forest plot and the receiver operating characteristics plot for each set of raw data. We considered the following sources of heterogeneity and, if appropriate, added them to a bivariate regression model: target condition, reference test, patients’ characteristics, and QUADAS 2 items.

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