QT Prolongation and Safety in the Indian Population
Why this work is in the frame
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Bibliographic record
Abstract
The QT interval in electrocardiogram (ECG) reflects the total duration of ventricular myocardial depolarization and repolarization. It has been well recognized that many condition may cause QT interval prolongation. Unfortunately, numbers of cardiac and non-cardiac drug prolong the QT interval and cause a distinctive polymorphic ventricular tachycardia termed torsade de pointes (TdP). TdP can degenerate into ventricular fibrillation, which leads to sudden cardiac death. Recently various regulatory and clinical bodies of Europe, USA, Canada and Australia have made their focus on the drugs that induce prolongation of QT interval. Committee for Proprietary Medicinal Products (CPMP) of the European Agency issued a document entitled 'Points to Consider: The assessment of the potential for QT interval prolongation by non-cardiovascular medicinal products' [1, 2]. In addition, USFDA adopted the guideline 'Clinical evaluation of QT/QTc interval prolongation and proarrhythmic potential for non-anti arrhythmic drugs' [3]. These documents and guidelines are primarily concern with development of novel agents and the new use or new dose of already approved drugs. The scope of this guideline is to study the effect of drugs on QT prolongation and give idea of evaluation of drug's effects on QT prolongation. Today more than 50 available drugs (both old and new) have been identify, which prolong the QT interval [1]. Several drugs have been withdrawn from many countries on this basis but many of these drugs are still available in Indian market and potentially creating life-threatening arrhythmias. This article will focus on recommendation of study on the normal limits of QT interval in Indian population and preparation of the database, which can be helpful in withdrawal of drugs from the market that produces QT prolongation.
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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 | 0.001 | 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 it