Alprostadil vs. isosorbide dinitrate in ameliorating angina episodes in patients with coronary slow flow phenomenon: A randomized controlled trial
Bibliographic record
Abstract
Background The optimum therapy for coronary slow flow phenomenon (CSFP) stays debatable. This study compared the effectiveness of alprostadil with isosorbide dinitrate in alleviating angina episodes in CSFP patients. Methods In this prospective, randomized controlled study, 102 patients with CSFP without severe coronary artery stenosis that exhibited stable angina were allocated randomly in a ratio of 1:1 to either the alprostadil group (40 μg, three times per day, n = 51) or the isosorbide dinitrate group (5 mg, three times per day, n = 51). Frequency of angina events, intensity of suffering, and the Canadian Cardiovascular Society (CCS) grading of angina pectoris were evaluated at baseline and one month after. Additionally, the Seattle Angina Questionnaire (SAQ) was assessed. Results Baseline characteristics were comparable between the two groups. At 1-month follow-up, patients administered with alprostadil experienced fewer angina episodes [episodes per week, 1 (2) vs. 2 (2), P < 0.001] and less pain intensity [self-evaluated pain score, 2 (3) vs. 3 (4), P < 0.001] than those with isosorbide dinitrate. In the alprostadil group, 78.4% of patients were classified as CCS class I, significantly higher than the 47.1% seen in the isosorbide dinitrate group (P = 0.001). Furthermore, treatment of alprostadil led to a significant improvement in the SAQ score (7.09 U, 95% CI: 4.22–9.96, P < 0.001) compared to isosorbide dinitrate. Additionally, fewer patients suffered headaches when receiving alprostadil (7.8% vs. 19.6%, P = 0.084). Conclusion Alprostadil was more effective in ameliorating angina symptoms in CSFP patients than isosorbide dinitrate. Clinical trial registration [ www.chictr.org.cn ], identifier [ChiCTR2000033233].
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.000 |
| Research integrity | 0.002 | 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".