Integrating palliative care into the modern cardiac intensive care unit: a review
Bibliographic record
Abstract
Abstract The modern cardiac intensive care unit (CICU) specializes in the care of a broad range of critically ill patients with both cardiac and non-cardiac serious illnesses. Despite advances, most conditions that necessitate CICU admission such as cardiogenic shock, continue to have a high burden of morbidity and mortality. The CICU often serves as the final destination for patients with end-stage disease, with one study reporting that one in five patients in the USA die in an intensive care unit (ICU) or shortly after an ICU admission. Palliative care is a broad subspecialty of medicine with an interdisciplinary approach that focuses on optimizing patient and family quality of life (QoL), decision-making, and experience. Palliative care has been shown to improve the QoL and symptom burden in patients at various stages of illness, however, the integration of palliative care in the CICU has not been well-studied. In this review, we outline the fundamental principles of high-quality palliative care in the ICU, focused on timeliness, goal-concordant decision-making, and family-centred care. We differentiate between primary palliative care, which is delivered by the primary CICU team, and secondary palliative care, which is provided by the consulting palliative care team, and delineate their responsibilities and domains. We propose clinical triggers that might spur serious illness communication and reappraisal of patient preferences. More research is needed to test different models that integrate palliative care in the modern CICU.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".