Young adults in the cardiac intensive care unit: insights from the Critical Care Cardiology Trials Network registry
Bibliographic record
Abstract
AIMS: While the aging cardiac intensive care unit (CICU) population has been well studied, young adults represent a distinct and underexplored subgroup. We aimed to characterize the demographics, clinical presentations, resource utilization, and outcomes of young adults admitted to contemporary CICUs. METHODS AND RESULTS: We analysed consecutive adult CICU admissions from 2018 to 2023 within the Critical Care Cardiology Trials Network, a multicentre registry of advanced CICUs in North America. Patients aged 18-39 years were classified as 'young adults' and compared with those aged ≥40 years. Among 29 035 CICU admissions, 6.7% (n = 1959) were aged 18-39 years. Young adults were more likely to be female (40.0% vs. 36.4%, P = 0.001) and non-White (55.3% vs. 43.0%, P < 0.001), with fewer traditional cardiovascular risk factors. Heart failure was the leading admission diagnosis among young adults (26.4% vs. 19.5%, P < 0.001). Compared with older adults, young patients were more likely to present with cardiogenic shock (22.4% vs. 18.7%, P < 0.001) and cardiac arrest (12.7% vs. 10.6%, P = 0.003). Utilization of critical care therapies was higher, including mechanical circulatory support (13.1% vs. 11.4%, P = 0.02), with extracorporeal membrane oxygenation comprising a greater share (29.3% vs. 9.9%, P < 0.001). Young admissions had longer CICU stays [2.7 (1.2-5.8) vs. 2.2 (1.1-4.6) days, P < 0.001]. CICU mortality (6.5% vs. 10.5%, P < 0.001) and hospital mortality (9.5% vs. 14.4%, P < 0.001) were significantly lower in the young. CONCLUSION: Young adults admitted to the CICU represent a clinically distinct population, with higher rates of high-acuity presentations and intensive resource use yet lower short-term mortality.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".