Effect of Proprietary Chinese Medicine on Coronary Microvascular Dysfunction in Patients with Microvascular Angina: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Background . Microvascular angina (MVA) has received increasing attention and interest in recent years, but there are still some shortcomings in the diagnosis and treatments at current stage. In recent years, several studies have confirmed the efficacy of proprietary Chinese medicines (PCMs) in improving MVA symptoms; however, there is no systematic review and meta‐analysis to comprehensively assess the efficacy of PCMs in this area. Objective . Investigating the clinical efficacy of proprietary Chinese medicines for treating MVA and coronary microvascular function. Methods . We looked up articles from January 1, 2012, to the present from eight databases. Then, we screened the literature and followed the 2019 version 2 of Cochrane risk of bias tool for systematic review. The Stata/SE 15.0 software was used for the meta‐analysis. Results . There are 21 studies, including 1,641 patients who were included in this review. According to the results, the combination of PCMs and conventional MVA treatment was able to further enhance clinical efficacy [RR = 1.28, 95% CI (1.20, 1.36), p < 0.001], prolong the time of duration on the treadmill exercise testing (TET) [SMD = 1.49, 95% CI (0.63, 2.36), p = 0.001] and improve levels of NO [SMD = −1.77 95% CI (−2.11, −1.43), p < 0.001]. At the same time, PCMs could also decrease the microvascular resistance index (IMR) [SMD = −1.79, 95% CI (−2.58, −1.00), p < 0.001)], serum level of hs‐CRP [SMD = −1.21, 95% CI (−1.84, −0.58), p < 0.001] and ET‐1 [SMD = −1.77 95% CI (−2.11, −1.43), p < 0.001]. Regards to medication safety, a total of 27 adverse events occurred, including 10 cases in the intervention group and 17 cases in the control group. Conclusion . The study suggests that the combination of PCMs and conventional MVA treatment enhances clinical efficacy and could better improve coronary microvascular function. In the future, we expect more high‐quality, randomized, double‐blind clinical studies to validate the safety, and efficacy of PCMs to provide valuable evidence‐based medicine (EBM) for the treatment of MVA with PCMs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".