Demographics, Care Patterns, and Outcomes of Patients Admitted to Cardiac Intensive Care Units
Bibliographic record
Abstract
Importance: Single-center and claims-based studies have described substantial changes in the landscape of care in the cardiac intensive care unit (CICU). Professional societies have recommended research to guide evidence-based CICU redesigns. Objective: To characterize patients admitted to contemporary, advanced CICUs. Design, Setting, and Participants: This study established the Critical Care Cardiology Trials Network (CCCTN), an investigator-initiated multicenter network of 16 advanced, tertiary CICUs in the United States and Canada. For 2 months in each CICU, data for consecutive admissions were submitted to the central data coordinating center (TIMI Study Group). The data were collected and analyzed between September 2017 and 2018. Main Outcomes and Measures: Demographics, diagnoses, management, and outcomes. Results: Of 3049 participants, 1132 (37.1%) were women, 797 (31.4%) were individuals of color, and the median age was 65 years (25th and 75th percentiles, 55-75 years). Between September 2017 and September 2018, 3310 admissions were included, among which 2557 (77.3%) were for primary cardiac problems, 337 (10.2%) for postprocedural care, 253 (7.7%) for mixed general and cardiac problems, and 163 (4.9%) for overflow from general medical ICUs. When restricted to the initial 2 months of medical CICU admissions for each site, the primary analysis population included 3049 admissions with a high burden of noncardiovascular comorbidities. The top 2 CICU admission diagnoses were acute coronary syndrome (969 [31.8%]) and heart failure (567 [18.6%]); however, the proportion of acute coronary syndrome was highly variable across centers (15%-57%). The primary indications for CICU care included respiratory insufficiency (814 [26.7%]), shock (643 [21.1%]), unstable arrhythmia (521 [17.1%]), and cardiac arrest (265 [8.7%]). Advanced CICU therapies or monitoring were required for 1776 patients (58.2%), including intravenous vasoactive medications (1105 [36.2%]), invasive hemodynamic monitoring (938 [30.8%]), and mechanical ventilation (652 [21.4%]). The overall CICU mortality rate was 8.3% (95% CI, 7.3%-9.3%). The CICU indications that were associated with the highest mortality rates were cardiac arrest (101 [38.1%]), cardiogenic shock (140 [30.6%]), and the need for renal replacement therapy (51 [34.5%]). Notably, patients admitted solely for postprocedural observation or frequent monitoring had a mortality rate of 0.2% to 0.4%. Conclusions and Relevance: In a contemporary network of tertiary care CICUs, respiratory failure and shock predominated indications for admission and carried a poor prognosis. While patterns of practice varied considerably between centers, a substantial, low-risk population was identified. Multicenter collaborative networks, such as the CCCTN, could be used to help redesign cardiac critical care and to test new therapeutic strategies.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".