Characteristics and Outcomes of Adults With Congenital Heart Disease in the Cardiac Intensive Care Unit
Bibliographic record
Abstract
Little is known regarding the characteristics, treatment patterns, and outcomes in patients with adult congenital heart disease (ACHD) admitted to cardiac intensive care units (CICUs). The authors sought to better define the contemporary epidemiology, treatment patterns, and outcomes of ACHD admissions in the CICU. The Critical Care Cardiology Trials Network is a multicenter network of CICUs in North America. Participating centers contributed prospective data from consecutive admissions during 2-month annual snapshots from 2017 to 2022. We analyzed characteristics and outcomes of admissions with ACHD compared with those without ACHD. Multivariable logistic regression was used to assess mortality in ACHD vs non-ACHD admissions. Of 23,299 CICU admissions across 42 sites, there were 441 (1.9%) ACHD admissions. Shunt lesions were most common (46.1%), followed by right-sided lesions (29.5%) and complex lesions (28.7%). ACHD admissions were younger (median age 46 vs 67 years) than non-ACHD admissions. ACHD admissions were more commonly for heart failure (21.3% vs 15.7%, P < 0.001), general medical problems (15.6% vs 6.0%, P < 0.001), and atrial arrhythmias (8.6% vs 4.9%, P < 0.001). ACHD admissions had a higher median presenting Sequential Organ Failure Assessment score (5.0 vs 3.0, P < 0.001). Total hospital stay was longer for ACHD admissions (8.2 vs 5.9 days, P < 0.01), though in-hospital mortality was not different (12.7% vs 13.6%; age- and sex-adjusted OR: 1.19 [95% CI: 0.89-1.59], P = 0.239). This study illustrates the unique aspects of the ACHD CICU admission. Further investigation into the best approach to manage specific ACHD-related CICU admissions, such as cardiogenic shock and acute respiratory failure, is warranted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".