Implantable cardioverter defibrillator therapy for patients with less severe left ventricular dysfunction
Bibliographic record
Abstract
PURPOSE OF REVIEW: The implantable cardioverter defibrillator (ICD) is an effective therapy for sudden cardiac death (SCD). Identifying patients who will benefit from an ICD is key. Most SCD events occur in patients with less severe left ventricular (LV) dysfunction, yet past trials and guidelines focus on those with severe LV dysfunction. Given the large pool of patients with less severe LV dysfunction and a modest risk of SCD, methods to identify those who might benefit from an ICD are required. RECENT FINDINGS: Observational studies indicate that abnormal cardiac repolarization and impaired autonomic function, particularly in combination, appear to identify patients with less severe LV dysfunction at risk of SCD. Extensive scarring also appears to identify patients at risk. Ongoing and planned studies will better define the role of using noninvasive tests to select patients for ICD therapy. SUMMARY: Noninvasive measures of cardiac structure, autonomic function and myocardial substrate appear to be promising in identifying patients with less severe LV dysfunction at risk of SCD. However, it is not clear that ICD therapy will improve survival in these patients. Until definitive data from prospective randomized trials are available it is premature to recommend use of these tools to guide ICD therapy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".