Cardiac Shock Wave Therapy for Coronary Heart Disease: an Updated Meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: The aim of this article is to study the efficacy and safety of cardiac shock wave therapy (CSWT) in the treatment of coronary heart disease (CAD). METHODS: A comprehensive search of electronic databases and a manual search of conference papers and abstracts were performed until September 30, 2018. The studies using RevMan 5.3 and STATA 14.0 softwares were reviewed, and meta-analyses were performed on 13 indicators, such as a six-min walking distance test (6MWT), New York Heart Association (NYHA) functional class, Seattle Angina Questionnaire (SAQ) score, angina class (Canadian Cardiology Society [CCS]), etc. RESULTS: A total of 26 articles were included. The total patient population was 855, of which 781 patients were treated with CSWT. Meta-analyses indicated that 6MWT (mean difference [MD] 75.64, 95% confidence interval [CI] 49.03, 102.25, P<0.00001) and NYHA (MD -0.70, 95% CI -0.92) in the CSWT group were comparable to those in the conventional revascularization group (MD -0.70, 95% CI -0.92, -0.49, P<0.00001). SAQ (MD 10.75, 95% CI 6.66, 14.83, P<0.00001), CCS (MD -0.99, 95% CI -1.13, -0.84, P<0.00001), nitrate dosage (MD -1.84, 95% CI -2.77, -1.12, P<0.00001), LVEF (MD 3.77, 95% CI 2.17, 5.37, P<0.00001), and SSS (MD -4.29, 95% CI -5.61, -2.96, P<0.00001), SRS (MD -2.90, 95% CI -4.85, -0.95, P=0.004), and the exercise test (standard mean difference 0.57, 95% CI 0.12, 1.02, P=0.01) all showed significant differences. CONCLUSION: CSWT may offer beneficial effects to patients with CAD, but more large-scale clinical studies are needed to further verify its therapeutic effect.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.103 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it