Arrhythmic risk stratification of post–myocardial infarction patients
Bibliographic record
Abstract
Post-myocardial infarction risk stratification, especially arrhythmic risk stratification, is an issue that has still not been wholly addressed in modern clinical cardiology. In the past 10 years, arrhythmic risk stratification has been approached mainly by evaluating frequency and complexity of premature ventricular contractions, detected on Holter monitoring, often in association with determination of percent ejection fraction. This methodology has been proven to be limited and fallacious according to the Cardiac Arrhythmia Suppression Trial I and II (CAST I,II) results, in which suppression of premature ventricular contractions or premature ventricular beats throughout by antiarrhythmic drugs resulted in an increase in both cardiac and arrhythmic mortality. Only amiodarone as an antiarrhythmic drug, as proven in the recent European Myocardial Infarct Amiodarone Trial (EMIAT) and Canadian Amiodarone Myocardial Infarction Trial (CAMIAT), was effective in reducing arrhythmic mortality without affecting cardiac mortality, in patients selected mainly because of a reduced ejection fraction, with and without premature ventricular contractions. Conversely, it is well known that beta-blockers are effective in preventing sudden death in post-acute myocardial infarction (AMI) patients, thus reducing cardiac and arrhythmic mortality. Conversely, in other institutions, risk stratification in post-AMI patients has been performed by electrophysiologic study obtained, without any previous noninvasive arrhythmic risk stratification, in all post-AMI patients. In recent years, many other noninvasive electrocardiology parameters, such as late potentials (signal-averaged electrocardiography), heart rate variability, baroreflex sensitivity, and, more recently, T-wave alternance, have been shown to be useful, but they are associated with a low specificity in the noninvasive identification of patients at high risk for arrhythmic mortality. Conversely, in the Multicenter Automatic Defibrillation Implantation Trial (MADIT), electrophysiology confirmed that inducibility of ventricular tachycardia shows high specificity and a high predictive value for arrhythmic events. Nevertheless, the MADIT study population is not comparable to a cohort of consecutive patients who have recently had a myocardial infarction. In this setting, the highest risk of arrhythmic events can be observed in patients with depressed percent ejection fraction (< 35%) and in the first 6 months after AMI. Today, the most convincing approach seems to be the one combining both noninvasive risk stratification parameters (e.g., premature ventricular beats > 10/h or reduced heart rate variability < 70 ms or a positive signal-averaged electrocardiogram) followed by a further arrhythmic risk stratification, obtained through electrophysiologic study. Several published and ongoing trials that utilize various arrhythmic risk stratification techniques as part of their protocol are reviewed.
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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".