Conflicts of interest in clinical practice: lessons learned from cardiovascular medicine.
Bibliographic record
Abstract
Cardiovascular diseases represent a major burden worldwide, and clinical trials are critical to define treatment improvements. Since various conflicts of interest (COIs) may influence trials at multiple levels, cardiovascular research represents a paradigmatic example to analyze their effects and manage them effectively to re-establish the centrality of evidence-based medicine.Despite the manifest role of industry, COIs may differently affect both sponsored and non-sponsored studies in many ways. COIs influence may start from the research question, data collection and adjudication, up to result reporting, including the spin phenomenon. Outcomes and endpoints (especially composite) choice and definitions also represent potential sources for COIs interference. Since large randomized controlled trials significantly influence international guidelines, thus impacting also clinical practice, their critical assessment for COIs is mandatory. Despite specific protocols aimed to mitigate COI influence, even scientific societies and guideline panels may not be totally free from COIs, negatively affecting their accountability and trustworthiness.Shared rules, awareness of COI mechanisms and transparency with external data access may help promoting evidence-based research and mitigate COIs impact. Managing COIs effectively should preserve public trust in the cardiovascular profession without compromising the positive relationships between investigators and industry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | Insufficient payload (model declined to judge) Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| grok | MetaresearchResearch integrity Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | medium |
| opus | Research integrityMetaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".