The efficacy of coronary sinus reduction in refractory angina: A meta-analysis
Bibliographic record
Abstract
Abstract Objectives Refractory angina is a frequent complain of patients with coronary artery disease. Its management is challenging despite the available pharmacological approaches. Interventional approaches have also been attempted, with coronary sinus reduction (CSR) being the main treatment option. Purpose This meta-analysis aimed to assess the efficacy of CSR in improving symptoms and cardiovascular endpoints in patients with refractory angina. Methods We searched the Pubmed database till 26/2/2023 for studies assessing the impact of CSR in refractory angina. The primary outcome of interest was the improvement in Canadian Cardiovascular Society (CCS) category by at least one class. Secondary outcomes included the implantation success, the proportion of patients improving by at least two CCS classes, as well as the rates of new myocardial infarction/percutaneous coronary intervention and mortality at follow-up. Results The literature search resulted in 190 studies. After screening of title/abstract/full-text, a total of 10 studies (1400 patients) were included in the meta-analysis. The median follow-up was 12.8 months (range: 4-24 months). High rates of implantation success (97%, 95% confidence interval (CI) 95%-98) were reported. Improvement by at least one CCS class was reported by 77% (95% CI 73%-81%). Improvement by at least two CCS classes was seen in 41% (95% CI 36%-47%). The proportion of patients exhibiting a new myocardial infarction/percutaneous coronary intervention was 7% (95% CI 3%-16%), while the mortality rate was 7% (95% CI 3%-14%). Conclusion Coronary sinus reduction is a procedure accompanied by high success rates, and is effective in improving symptoms in a considerable proportion of patients with refractory angina.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.056 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".