The impact of funding on the quality and interpretation of systematic reviews of mechanical thrombectomy in stroke patients
Bibliographic record
Abstract
BackgroundFunding may impact the quality and findings of systematic reviews (SRs). We aimed to compare the methodological quality of funded and non-funded SRs that investigated the outcomes in ischemic stroke patients undergoing mechanical thrombectomy.MethodsWe conducted a comprehensive search strategy in different databases, including Ovid Cochrane Central Register of Controlled Trials, Ovid Embase, Ovid Medline (including epub ahead of print, in-process & other non-indexed citations), PubMed, Scopus and Web of Science Core Collection to retrieve all relevant SRs. Random sequence generation matched each funded SR with a non-funded one. A Measurement Tool to Assess Systematic Reviews (AMSTAR)-2 tool was used to assess the bias and quality of the included SRs. We also used uni- and multivariate analysis to perform our analysis, and results were expressed in odds ratio (OR) and 95% confidence interval (CI).ResultsWe retrieved 150 articles, which were randomized and matched into 100 SRs, including 50 funded and 50 non-funded studies. By multivariate analysis, we found that including randomized clinical trials (RCTs) (OR: 5.7; 95% CI: 1.8-17.8; p = 0.003) and reporting conflict of interests (OR: 5.2; 95 CI: 1.1-24; p = 0.036) were the only significant differences between funded and non-funded SRs. No significant differences were found regarding the overall confidence for low-quality (OR: 0.54; 95% CI: 0.09-3.2; p = 0.49) and moderate/high-quality SRs (OR: 0.17; 95% CI: 0.02-1.87; p = 0.14).ConclusionFunded studies tend to include RCTs more often and report conflict of interests with no significant impact on overall confidence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.115 | 0.114 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".