Manfaat Trimetazidine Dalam Tatalaksana Pasien Chronic Coronary Syndrome Dengan Stable Angina
Bibliographic record
Abstract
Cardiovascular Disease (CVD) has resulted in the deaths of 17.9 million individuals in 2016, representing 31% of the global death. Coronary Artery Disease is a spectrum of CVD with a clinical manifestation called Chronic Coronary Syndrome (CCS). Stable angina is the main symptom of CCS that threatens patient safety. This paper aims to convey the in-depth benefits of Trimetazidine as an effective and safe pharmacological option for CCS patients with stable angina. This paper is a narrative review type literature study using the literature review method regarding the benefits of Trimetazidine (TMZ) for CCS patients with stable angina. As many as 16 references from research journal articles, case reports, and international guidelines are used. The analysis showed that administration of TMZ caused a significant frequency reduction of weekly angina attacks from 4.7 ± 3.5 to 2.2 ± 2.4 in the first month (p <0.001) and to 0.9 ± 1.3 in the third month (p <0.001). The decrease in weekly nitroglycerin consumption was -3.23, 95% CI: -4.23 to -2.24 (p <0.0001). The CCS classification of patients increased from 83% of patients classified in CCS class II or III to 32% after being given TMZ. There were no significant differences between the three doses of TMZ (3 × 20 mg, 2 × 35 mg, and 1 × 80 mg). TMZ has been reported to cause few mild side effects in patients. In general, the use of TMZ as monotherapy or in combination can improve the condition of CCS patients with stable 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".