Palliative care in cardiac intensive care units (CICUs): Insights from the Critical Care Cardiology Trials Network (CCCTN) registry
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: None. OnBehalf Critical Care Cardiology Trials Network (CCCTN) registry Introduction Palliative care is a practice focused on providing relief of symptoms of illness, while optimizing the quality of life for patients and families. We aimed to quantify palliative care (PC) practices and end-of-life decision-making in critically ill cardiac patients in contemporary CICUs. Methods The CCCTN Registry is a network of tertiary care CICUs in the United States and Canada. Between 2017 and 2020, up to 26 centers contributed an annual 2-month snapshot of all consecutive admissions to the CICU. We captured code status, rates of palliative care consultation, and decisions for comfort measures only (CMO) before all deaths in the CICU. Results Of 8231 admissions, 10% ended with death in the CICU and 2.6% were discharges to hospice. Of deceased patients, 68% were CMO before death. The median age of CMO patients was 70y (25th-75th: 59-78) vs. 67 (56-77) among deaths without CMO. In the CMO group, only 13% were DNR/DNI at admission, and the remainder were full code. Respiratory insufficiency and non-cardiogenic shock were the CICU indications most frequently associated with CMO. The median time from CICU admission to CMO decision was 3.4 days (25th-75th: 1.2-7.7) and was ≥7 days in 27% (Figure). Time from CMO decision to death was <24h in 88%, with a median of 3.8h (25th-75th 1.0-10.3). Before a CMO decision, 73% received mechanical ventilation and 25% mechanical circulatory support. Of total deaths, 34% of intubated patients were palliatively extubated. Formal PC services were engaged in only 28% of deaths. Conclusions In contemporary CICUs, CMO preceded death in 2/3 of cases. The high use of advanced ICU therapies, lengthy times to a CMO decision, and the very short time from CMO to death, highlight a potential opportunity for greater PC consultation, as well as training programs to build skills in PC for practitioners in the CICU. Abstract Figure
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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 | 0.022 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".