#10 Data Collection Process - Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.
#11 Data items - List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.
#13 Summary Measures - State the principal summary measures (e.g., risk ratio, difference in means).
#14 Synthesis of Results - Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I2) for each meta-analysis.
#16 Additional Analysis - Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.
#20 Results of Individual Studies - For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.
#21 Synthesis of Results - Present results of each meta-analysis done, including confidence intervals and measures of consistency.
#23 Additional Analysis - Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]).
This calculator can determine diagnostic test characteristics (sensitivity, specificity, likelihood ratios) and/or determine the post-test probability of disease given given the pre-test probability and test characteristics. Given sample sizes, confidence intervals are also computed.
Given information about the probability of an outcome under control and experimental treatments, this calculator produces measures of risk increase/decrease and number needed to treat or harm, including confidence intervals. If some patients were lost to follow-up, the calculator provides estimates for several different scenarios.