Review of the quality of observational studies of the association between rosiglitazone and acute myocardial infarction.
Bibliographic record
Abstract
BACKGROUND: Following the publication of a meta-analysis reporting a risk of acute myocardial infarction (AMI) with rosiglitazone that led to severe restrictions being placed on its use, several observational studies of the association were reported. The lifting of restrictions in the United States in 2013 makes a review of these studies pertinent. OBJECTIVE: To evaluate the quality of population-based observational studies of the rosiglitazone-AMI association. METHODS: PubMed and Embase literature databases were searched for observational studies evaluating the association that were published between 2006 and 2010. Publications satisfying the inclusion criteria were reviewed using the Checklist for Retrospective Database Studies. RESULTS: Nineteen studies satisfied the inclusion criteria. Reasons for the research design and data source were absent or unclear in 18 (95%) and 16 (84%), respectively. Administrative data were used exclusively in 14 (74%). Baseline periods for prior diagnoses and medications varied widely. Reimbursement constraints on rosiglitazone use were reported in only seven studies (37%), although all were likely to have been impacted by them. What was being tested in half of the rosiglitazone treatment comparisons lacked specificity and clarity. All relied on risk ratios and, for 90% of the comparisons, the ratios were between 0.5 and two - a level at which residual confounding can lead to spurious significance. CONCLUSION: Important deficiencies existed in the rosiglitazone studies suggesting that standards for methods and reporting of observational safety analyses need improvement. In particular, detailed clinical data should be included when the risk of confounding by indication is likely to be high.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.071 | 0.291 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".