Independent determinants of the efficacy of nitrate therapy
Bibliographic record
Abstract
BACKGROUND: Asymmetric dosage regimens of isosorbide mononitrate provide better antianginal efficacy and quality of life in patients with stable angina pectoris than the daily administration of multiple small doses of the compound. It is not known whether certain patient characteristics contribute to this improved benefit. OBJECTIVE: To determine independent factors contributing to this improved benefit. Multiple linear regression analysis was performed with a self assessment study in 1350 patients with stable angina pectoris. Quality of life was assessed by the Marquis questionnaire for patients with angina and included the assessment of immobility, pain and psychological distress. Individual scores were calculated as the pooled sums of the assessment scores and were expressed on an ordinal scale of 10. RESULTS: Age did not influence the improvement in benefit. Gender, rhythmic disturbances, peripheral artery disease and the concomitant use of calcium channel blockers or beta-blockers were without effect. New York Heart Association angina classification was an independent variable: patients with a class I or II showed less benefit than did patients with class III or IV (p = 0.02). Obese patients as well as hypertensive patients (p = 0.04 and 0.02), and smokers also tended to benefit less (p = 0.08). In contrast, the presence of cholesterolemia and diabetes mellitus were associated with increase in the beneficial effect of nitrates on quality of life (p = 0.03 and 0.05). CONCLUSIONS: Patients with severe angina pectoris benefit better from nitrate therapy than do patients with New York Heart Association class I - II. Also, patients with coronary artery disease and concomitant diabetes mellitus or cholesterolemia may benefit better from nitric oxide donor therapy than patients without such condition. In contrast, patients with concomitant obesity, hypertension, or who are smokers may show less benefit.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".