Efficacy of lower doses of pioglitazone after stroke or transient ischaemic attack in patients with insulin resistance
Bibliographic record
Abstract
AIMS: Pioglitazone is a potent insulin-sensitizing drug with anti-atherosclerotic properties, but adverse effects have limited its use. We assessed the benefits and risks of lower versus higher doses of pioglitazone taken by participants in the Insulin Resistance Intervention in Stroke Trial. MATERIALS AND METHODS: Efficacy [myocardial infarction (MI) or recurrent stroke] new-onset diabetes) and adverse outcomes (oedema, weight gain, heart failure and bone fracture) were examined for subjects assigned to pioglitazone or placebo within strata defined by mode dose of study drug taken (i.e. the dose taken on most days in the study). RESULTS: Among the 1938 patients randomized to pioglitazone, the mode dose was <15 mg/day in 546 participants, 15 mg/day in 128, 30 mg/day in 89, and 45 mg/day in 1175. There was no significant effect on stroke/MI or new-onset diabetes with <15 mg/day. For 15 mg/30 mg/day pooled, the adjusted hazard ratios (95% CI) for stroke/MI were 0.48 (0.30, 0.76; p = .002) and 0.74 (0.69, 0.94) for 45 mg/day. For new-onset diabetes, the adjusted hazard ratios were 0.34 (0.15, 0.81; p = .001) and 0.31 (0.59, 0.94; p = .001) respectively. For oedema, weight gain and heart failure, the risk estimates for pioglitazone were lower for subjects taking <45 mg daily. For fractures, the increased risk with pioglitazone was similar across all dose strata. CONCLUSIONS: Lower doses of pioglitazone appear to confer much of the benefit with less adverse effects than the full dose. Further study is needed to confirm these findings so that clinicians may optimize dosing of this secondary prevention strategy in patients with stroke.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".