Experts' Consensus on Use of Long-Acting Nitroglycerine in the Management of Angina and Chronic Coronary Syndrome in India.
Bibliographic record
Abstract
AIM: To address the existing gaps in knowledge about long-acting nitroglycerine (LA-NTG) and provide recommendations to address these issues. METHODOLOGY: Approved LA-NTG questionnaire that included 17 questions related to the role of LA-NTG in the management of angina and chronic coronary syndrome (CCS) was shared with 150 expert cardiologists from different regions from India. Results of these survey questionnaires were further discussed in 12 regional level meetings. The opinions and suggestions from all the meetings were compiled and analyzed. Further, recommendations were made with the help of attending national cardiology experts and a consensus statement was derived. RESULTS: This is the first consensus on LA-NTG, summarizing the clinical evidence from India and suggesting recommendations based on these data. The experts recommended early use of LA-NTG as a first-line antianginal therapy in combination with beta-blocker since it improves exercise tolerance in patients with CCS. A strong consensus was observed for using LA-NTG in patients with co-morbid hypertension, diabetes, chronic kidney disease and post-percutaneous coronary intervention angina. As a part of cardiac rehabilitation, LA-NTG allows patients with angina to exercise to a greater functional capacity. CONCLUSIONS: A national consensus was observed for several aspects of LA-NTG in the management of angina and CCS. The clinical experience of the experts confirmed an extremely satisfied patient perception about the efficacy of LA-NTG.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.044 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".