Interhospital Variation in Admissions Managed With Critical Care Therapies or Invasive Hemodynamic Monitoring in Tertiary Cardiac Intensive Care Units: An Analysis From the Critical Care Cardiology Trials Network Registry
Bibliographic record
Abstract
BACKGROUND: Wide interhospital variations exist in cardiovascular intensive care unit (CICU) admission practices and the use of critical care restricted therapies (CCRx), but little is known about the differences in patient acuity, CCRx utilization, and the associated outcomes within tertiary centers. METHODS: The Critical Care Cardiology Trials Network is a multicenter registry of tertiary and academic CICUs in the United States and Canada that captured consecutive admissions in 2-month periods between 2017 and 2022. This analysis included 17 843 admissions across 34 sites and compared interhospital tertiles of CCRx (eg, mechanical ventilation, mechanical circulatory support, continuous renal replacement therapy) utilization and its adjusted association with in-hospital survival using logistic regression. The Pratt index was used to quantify patient-related and institutional factors associated with CCRx variability. RESULTS: The median age of the study population was 66 (56-77) years and 37% were female. CCRx was provided to 62.2% (interhospital range of 21.3%-87.1%) of CICU patients. Admissions to CICUs with the highest tertile of CCRx utilization had a greater burden of comorbidities, had more diagnoses of ST-elevation myocardial infarction, cardiac arrest, or cardiogenic shock, and had higher Sequential Organ Failure Assessment scores. The unadjusted in-hospital mortality (median, 12.7%) was 9.6%, 11.1%, and 18.7% in low, intermediate, and high CCRx tertiles, respectively. No clinically meaningful differences in adjusted mortality were observed across tertiles when admissions were stratified by the provision of CCRx. Baseline patient-level variables and institutional differences accounted for 80% and 5.3% of the observed CCRx variability, respectively. CONCLUSIONS: In a large registry of tertiary and academic CICUs, there was a >4-fold interhospital variation in the provision of CCRx that was primarily driven by differences in patient acuity compared with institutional differences. No differences were observed in adjusted mortality between low, intermediate, and high CCRx utilization sites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".