Influence of cardiac arrest and SCAI shock stage on cardiac intensive care unit mortality
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Patients with concomitant cardiac arrest (CA) and shock are at increased risk of mortality, even when stratified according to shock severity. We sought to determine whether the presence of ventricular fibrillation (VF) modified the relationship between CA and mortality in cardiac intensive care unit (CICU) patients. METHODS: We retrospectively analyzed unique Mayo Clinic CICU patients admitted between 2007 and 2015. Society for Cardiovascular Angiography and Intervention (SCAI) shock stages A through E were classified at admission. Hospital mortality in each SCAI shock stage was stratified by the presence of CA, VF CA, or non-VF CA. RESULTS: We included 9,898 patients with a mean age of 68 years (38% females). CA was present in 12%, including 53% with VF CA and 47% with non-VF CA. Hospital mortality was higher in patients with CA compared to patients without CA (34% vs. 6%; adjusted odds ratio [OR] = 3.1, 95% CI [2.4, 4.0], p < .001), and patients with non-VF CA had higher hospital mortality than patients with VF CA (44% vs. 25%; adjusted OR = 2.1, 95% CI [1.4, 3.0], p < .001). After adjustment, patients with any CA or non-VF CA had higher hospital mortality at each SCAI stage, except stage E (all other p < .05), whereas patients with VF CA did not (all p > .1). CONCLUSIONS: CA rhythm modifies the relationship between CA and mortality in CICU patients, when accounting for coma, shock, and organ failure. Outcome studies examining CA in patients with cardiogenic shock need to account for important differences such as CA rhythm.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 it