End of life decisions in heart failure
Bibliographic record
Abstract
PURPOSE OF REVIEW: Heart failure is a significant public health concern around the world. Implantable cardioverter defibrillators with or without cardiac resynchronization therapy (CRT-D) have proven survival benefit. As patients progress to end-stage disease, management shifts to palliative care, and cardiologists are often confronted with how to best manage these devices. RECENT FINDINGS: Studies suggest that up to one-third of patients with an implantable cardioverter defibrillator receive painful shocks in the last 24 h of life. Disabling pacing or resynchronization devices may further weaken the heart function and expedite death, particularly if the patient has no underlying ventricular rhythm. Is it ethical or legal to discontinue functions of the implantable device? The discussion and the decision to be made are whether to continue both pacing and tachyarrhythmia therapies, disable tachyarrhythmia therapies while maintaining pacing, or discontinue both. SUMMARY: The decision to disable all or parts of the device function is ultimately up to the patient. To avoid painful shocks near the end of life, it is recommended that tachyarrhythmia therapies be turned off when the patient is being treated palliatively. After informed discussion, withdrawing the resynchronization or pacing device option is also acceptable if requested by the patient regardless of the potential outcomes.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".