Bibliographic record
Abstract
OBJECTIVE: Thiazolidinediones (TZDs) are known to increase the risk of heart failure in patients with type 2 diabetes. We aimed to evaluate the magnitude of the risk of heart failure with TZDs and classify this adverse effect under the novel dose-time-susceptibility system. RESEARCH DESIGN AND METHODS: Evidence from randomized trials, controlled observational studies, anecdotal case reports, case series, and spontaneous reports in the Canadian Drug Reaction Monitoring Program (CADRMP) was analyzed in a teleo-analysis. RESULTS: A random-effects meta-analysis of three randomized controlled trials showed an odds ratio (OR) of 2.1 (95% CI 1.08-4.08; P = 0.03) for the risk of heart failure in patients randomized to TZDs compared with placebo. Four observational studies revealed an OR of 1.55 (1.33-1.80; P < 0.00001) for heart failure with TZDs. A dose-time-susceptibility analysis of 28 published reports and 214 spontaneous reports from the CADRMP database showed that heart failure was more likely to occur after several months (with median treatment duration of 24 weeks after initiation of therapy). Heart failure equally occurred at high and low doses. The adverse reaction was not limited to the elderly, with 42 of 162 (26%) of the reported cases occurring in patients aged <60 years. CONCLUSIONS: Our teleo-analysis confirms the increased magnitude of the risk of heart failure with TZDs. We estimate the number needed to harm with TZDs to be approximately 50 over 2.2 years. Existing guidelines and package inserts may have to be revised to incorporate these risk characteristics of TZDs.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".