The quality of evidence for medical interventions does not improve or worsen: a metaepidemiological study of Cochrane reviews is a research paper published in Journal of Clinical Epidemiology (2020). On theSindex it has a DataRank of 1.2. It has been cited 36 times, with 20 citing works in its 1-hop citation network.
ObjectivesThe objective of the study was to determine the change in quality of evidence in updates of Cochrane reviews that were initially published between January 1, 2013 and June 30, 2014. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system to document evidence quality.Study design and settingWe searched the Cochrane Database of Systematic Reviews on March 20, 2020 to identify which of the reviews from the initial (2013/14) sample had been updated. Using the same methods to determine the quality of evidence in the previous analysis, we assessed the quality of evidence for the first-listed primary outcomes in the updated reviews.ResultsOf the 608 reviews in the original sample, 154 had been updated with and 151 contained available data for both original and updated systematic reviews (24.8%). The updated reviews included: 15 (9.9%) with high-quality evidence, 56 (37.1%) with moderate-quality evidence, 47 (31.1%) with low-quality evidence, and 33 (21.9%) with very low-quality evidence. No change in the GRADE quality of evidence was found for most (103, 68.2%) of the updated reviews. The quality of evidence rating was downgraded in 28 reviews (58.3%) and upgraded in 20 (41.7%), although only six reviews were promoted to high quality.ConclusionUpdated systematic reviews continued to suggest that only a minority of outcomes for health care interventions are supported by high-quality evidence. The quality of the evidence did not consistently improve or worsen in updated reviews.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.542
From this paper's citation signal
Citation Network Contribution
0.651
From 14 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 45% comes from its base citations and 55% from the citation network (14 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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