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We use a standardized protocol and reporting form to extract trial characteristics, patient data, outcomes and study quality.
Several researchers attempted to extract trial characteristics, namely population description, study interventions, and outcomes, from journal article abstracts.
As we had unrestricted access to submitted protocols and correspondence between RECs and researchers, we were able to extract trial characteristics and REC comments without having to obtain permission from researchers or rely on a survey of researchers to obtain these data, excluding the introduction of response bias [ 23].
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Then, we extracted trial data from the time-course data.
All studies that extracted trial author-industry financial ties or employment data reported it in the review.
To empirically assess the risk of bias in the treatment effects in reviews, we will perform stratified analyses across trials according to all the different extracted trial characteristics and derive p values for interaction between trial characteristics and treatment effect.
We then extracted trials from each run, 500 ms before to 1 sec after image onset.
Descriptive data for the extracted trials are shown in Table 1.
Two reviewers independently identified trials, extracted trial-level data and performed risk of bias assessments using the Cochrane Risk of Bias tool.
Two reviewers independently identified and extracted trial-level data from randomized trials investigating unfractionated or low molecular heparin administered to patients with sepsis, severe sepsis, septic shock or DIC associated with infection.
To extract single trial information from the local field potential (LFP), we used principal components analysis (PCA) of event-related data.
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CEO of Professional Science Editing for Scientists @ prosciediting.com