Abstract 4145943: Recidivism in the Cardiac Intensive Care Unit: Insights from the Multinational Critical Care Cardiology Trials Network
Bibliographic record
Abstract
Background: Intensive Care Unit (ICU) readmission, or recidivism, can lead to increased resource use, longer hospital length-of-stay (LOS), higher costs,&worse survival. Given the potential clinical&financial impact of recidivism, it may be a useful quality metric for unit-&hospital-level comparisons. No prior studies, however, have comprehensively explored recidivism – its potential causes or consequences – across Cardiac Intensive Care Units (CICUs). Methods: The Critical Care Cardiology Trials Network (CCCTN) is a multicenter registry of advanced CICUs coordinated by the TIMI Study Group (Boston, MA). Consecutive admissions were captured (n=16,705)&those with > 1 readmission during the same hospitalization were identified. Multivariable logistic regression was used to determine baseline variables associated with recidivism, as well as the association of recidivism with in-hospital mortality. Results: A total of 1287 pts (7.7%) had CICU readmission. These pts were younger (p=0.015), had more diabetes (p=0.04), prior heart failure (HF)&chronic kidney disease (CKD) (p<0.001 for both), more frequently presented with decompensated HF or cardiogenic shock (p<0.001), were more often transferred from outside facilities (p<0.001), and had higher Sequential Organ Failure Assessment (SOFA) scores at presentation (p<0.001). Rates of CICU recidivism highly varied across institutions ( Fig-A ). Compared to those who were not readmitted, those readmitted to the CICU had greater critical care resource use during their 1 st CICU stay ( Fig-B ), along with longer initial CICU LOS (2.8 vs 2.2d)&hospital LOS (20.4 vs 7.6d) (both p<0.001). Hospital mortality was 20.3% in those readmitted to the CICU compared to 4.5% in those without readmission ( Fig-C ); adjusted odds ratio 6.22 (95% CI 5.25-7.38, p<0.001). This remained statistically significant after adjustment for code status. Conclusions: CICU recidivism varies significantly across centers and is associated with numerous comorbidities, higher illness severity, and greater resource use. One of every 5 pts readmitted to the CICU died in the hospital. Recidivism should be measured in future CICU-based studies, and could help to assess quality of CICU care.
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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 | 0.034 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| 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) | 0.003 | 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".