A comment-driven evidence appraisal approach to promoting research findings into practice when only uncertain evidence is available

Abstract

Background Comments in PubMed are usually short papers for supporting or refuting claims, or discussing methods and findings in original articles. This study aims to explore whether they can be used as a quick and reliable evidence appraisal instrument for promoting research findings into practice, especially in emergency situations such as COVID-19 in which only missing, incomplete or uncertain evidence is available. Methods Evidence–comment networks (ECNs) were constructed by linking COVID-19-related articles to the commentaries (letters, editorials or brief correspondence) they received. PubTator Central was used to extract entities with a high volume of comments from the titles and abstracts of the articles. Among them, six drugs were selected, and their evidence assertions were analysed by exploring the structural information in the ECNs as well as the sentiment of the comments (positive, negative, neutral). Recommendations in WHO guidelines were used as the gold standard control to validate the consistency, coverage and efficiency of comments in reshaping clinical knowledge claims. Results The overall positive/negative sentiments of comments were aligned with recommendations for/against the corresponding treatments in the WHO guidelines. Comment topics covered all significant points of evidence appraisal and beyond. Furthermore, comments may indicate the uncertainty regarding drug use for clinical practice. Half of the critical comments emerged 4.25 months earlier on average than the guideline release. Conclusions Comments have the potential as a support tool for rapid evidence appraisal as they have a selection effect by appraising the benefits, limitations and other clinical practice issues of concern in existing evidence. We suggest as a future direction an appraisal framework based on the comment topics and sentiment orientations to leverage the potential of scientific commentaries supporting evidence appraisal and decision-making.