Decision-making for older adults with advanced heart disease: a framework for balancing benefit versus futility
Bibliographic record
Abstract
Medical futility in the cardiovascular care of older adults presents unique challenges that necessitate a nuanced understanding of both clinical and ethical dimensions. This state-of-the-art review explores the evolving concept of futility in the context of an ageing patient population and expanding armamentarium purported to treat even the most dire of cardiovascular diseases. The first objective is to delineate a framework for clinicians to elicit the different dimensions of futility, their relative importance to the patient, and their potential for improvement with the intervention being considered. Definitions are elaborated for quantitative futility-interventions with statistically negligible benefits-and qualitative futility-interventions misaligned with patient-specific goals and values. The second objective is to highlight the determinants of prohibitive risk, from the cardiovascular disease and procedural morbidity, to competing non-cardiovascular risks and frailty. A distinction is made between frailty and futility, and manifestations of severe frailty are reviewed based on the A-B-C-D-E mnemonic. The third and final objective is to discuss strategies and actionable approaches to care for patients once futility has been invoked. In addition to ongoing compassionate dialogue with the patient and family members, early initiation and aggressive pursuit of palliative care measures is beneficial for symptom control and quality of life. Ultimately, informed shared decision-making with a patient-centered philosophy is essential to uphold dignity and enhance the quality of life for older adults facing complex cardiovascular conditions.
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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 | 0.060 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".