Abstract 14539: Interhospital Differences in the Use of Critical Care Therapies in Coronary Intensive Care Units and Its Association With In-Hospital Mortality: Insights From the Critical Care Cardiology Trials Network
Bibliographic record
Abstract
Background: Previous studies have shown wide interhospital variation in cardiovascular intensive care unit (CICU) admission practices and use of critical care restricted therapies and monitoring (CCRx), but little is known about practice differences among tertiary and academic CICUs. Methods: The Critical Care Cardiology Trials Network (CCCTN) is a multicenter registry of tertiary and academic CICUs in the USA and Canada that contributed consecutive patient data in annual 2-month periods from 2017 to 2021. The analysis included 13,318 admissions across 28 sites and compared interhospital variability in CCRx and its association with in-hospital survival. Results: CCRx was provided to 61.4% (interhospital range 28.3 - 86.7%) of CICU patients. Admissions to CICUs in the highest tertile of CCRx utilization, compared with the lower tertile, had a greater burden of comorbidities; less frequently admitted patients with ACS (18.7% vs 35.8%); more frequently admitted cardiac arrest (4.9% vs 2.6%) or cardiogenic shock (5.8% vs 1.9%); and had higher median admission Sequential Organ Failure Assessment (SOFA) scores (5.0 vs 2.0), lactate (1.9 vs 1.8 mmol/L), and creatinine (1.3 vs 1.1 mg/dL) levels. Unadjusted in-hospital mortality varied widely between CICUs (median 12.6%; range 4.0-23.5%; p<0.001). After adjustment for patient differences, the correlation between CICU provision of CCRx and in-hospital mortality was weak (r=0.287, p<0.001). Conclusions: In a large registry of tertiary and academic CICUs, there was large interhospital variability in the provision of CCRx. The weak adjusted correlation with in-hospital mortality suggests that standardized CICU admission criteria could reduce disparities in admission practices and improve health-resource allocation. Figure 1: Unadjusted correlation between individual CICU utilization of critical care restricted therapies and in-hospital all-cause 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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".