Use of MHT in women with cardiovascular disease: a systematic review and meta-analysis
Bibliographic record
Abstract
This systematic review assesses the effect of menopausal hormone therapy (MHT) on cardiovascular outcomes and risk factors in postmenopausal women with cardiovascular disease (CVD). The Medline, Embase and Cochrane databases were searched from inception to December 2022 for randomized controlled trials (RCTs) and observational studies using methodology from a previous Cochrane review. Quality assessment used the Cochrane risk of bias tool and Newcastle-Ottawa scale, respectively. From 5647 studies identified, 29 (23 RCTs and six observational studies) were included. Most studies were conducted in North America or Europe and investigated oral estrogens. Participants were older with varying frequency of cardiac risk factors and underlying CVD. No significant difference was observed between MHT users and controls regarding primary outcomes of non-fatal myocardial infarction, cardiovascular death or stroke. No difference in frequency of angina, heart failure and transient ischemic attacks was observed. Inconsistent effects of MHT on angiographic progression were seen and varied with glycemic status. Estradiol had a positive effect on flow-mediated dilatation. Limited studies identified differing effects of MHT on cardiac risk factors, varying with estrogen preparation. This study confirms no benefit of MHT for secondary CVD prevention, highlighting evidence limitations and the importance of shared decision-making when managing menopausal symptoms in women with CVD.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.020 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".