Effect of weight loss, exercise and risk factor control in microvascular angina. A randomized controlled pilot trial
Bibliographic record
Abstract
Abstract Background Coronary microvascular dysfunction (CMD) is a common cause of angina in women and associated with adverse cardiovascular prognosis. Currently, no evidence-based treatment for CMD exists. Purpose To examine whether an intervention targeting cardiovascular risk factors is feasible and improves angina symptoms and microvascular function in women with CMD and no obstructive coronary artery disease. Methods We randomized 62 women aged 40–75, with body mass index >25 kg/m2, angina symptoms monthly or more and coronary flow velocity reserve (CFVR) <2.5 to a 24-week intervention comprising low energy diet, exercise training, and optimized medical treatment of hypertension, dyslipidemia and diabetes or to usual care. Patients were assessed before randomization and after 24 weeks. The primary outcomes were CFVR assessed by transthoracic Doppler stress-echocardiography and angina burden measured by the Seattle Angina Questionnaire (SAQ). Secondary endpoints were exercise capacity (VO2max), body composition and glycemic control, anxiety and depression symptoms measured by the Hospital Anxiety and Depression Scale (HADS). Results Fifty-six participants (90%) completed the study. Median age was 65 years. The intervention group obtained a mean weight loss of 10 kg, mainly (9 kg) from fat tissue (all p<0.0001), increased work load (p<0.01), decreased triglycerides, low density lipoprotein and low plasma cholesterol (all p<0.006). HbA1c in non-diabetes participants also decreased (p<0.05). There was a clinically relevant improvement in all angina symptoms (9–21-point increase on all SAQ scales (all p<0.01)) as well as in depression score (p=0.008). There was no effect on CFVR or other secondary outcomes. Conclusion A major weight loss and intensified risk factor control resulted in significant improvement in angina burden but no improvement of coronary microvascular function among women with microvascular angina. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Unlimited research funding sources from the Capital region of Denmark and Bispebjerg-Frederiksberg Hospital internal funding sources.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".