Role of Critical Care Medicine Training in the Cardiovascular Intensive Care Unit: Survey Responses From Dual Certified Critical Care Cardiologists
Bibliographic record
Abstract
Background Cardiovascular intensive care units ( CICUs ) have evolved from coronary care wards into distinct units for critically ill patients with primary cardiac diseases, often suffering from illnesses that cross multiple disciplines. Mounting evidence has demonstrated improved survival with the incorporation of dedicated CICU providers with expertise in critical care medicine ( CCM ). This is the first study to systematically survey dual certified physicians in order to assess the relevance of CCM training to contemporary CICU care. Methods and Results Utilizing American Board of Internal Medicine data through 2014, 397 eligible physicians had obtained initial certification in both cardiovascular disease and CCM . A survey to delineate the role of critical care training in the CICU was provided to these physicians. Among those surveyed, 120 physicians (30%) responded. Dual certified physicians reported frequent use of their CCM skills in the CICU , highlighting ventilator management, multiorgan dysfunction management, end-of-life care, and airway management. The majority (85%) cited these skills as the reason CCM training should be prioritized by future CICU providers. Few (17%) agreed that general cardiology fellowship alone is currently sufficient to care for patients in the modern CICU . Furthermore, there was a consensus that there is an unmet need for cardiologists trained in CCM (70%) and that CICU s should adopt a level system similar to trauma centers (61%). Conclusions Citing specific skills acquired during CCM training, dual certified critical care cardiologists reported that their additional critical care experience was necessary in their practice to effectively deliver care in the modern CICU .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".