Multidisciplinary Code Shock Team in Cardiogenic Shock: A Canadian Centre Experience
Why this work is in the frame
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Bibliographic record
Abstract
BackgroundCardiogenic shock (CS) is associated with high mortality. We report on a “Shock Team” approach of combined interdisciplinary expertise for decision making, expedited assessment, and treatment.MethodsWe reviewed 100 patients admitted in CS over 52 months. Patients managed under a Code Shock Team protocol (n = 64, treatment) from 2016 to 2019 were compared with standard care (n = 36, control) from 2015 to 2016. The cohort was predominantly male (78% treatment, 67% control) with a median age of 55 years (interquartile range [IQR], 43-64) for treatment vs 64 years (IQR, 48-69) for control (P = 0.01). New heart failure was more common in the treatment group: 61% vs 36%, P = 0.02. Acute myocardial infarction comprised 13% of patients in CS. There were no significant differences between treatment and control in markers of clinical acuity, including median left ventricular ejection fraction (18% vs 20%), prevalence of moderate-severe right ventricular dysfunction (64% vs 56%), median peak serum lactate (5.3 vs 4.7 mmol/L), acute kidney injury (70% vs 75%), or acute liver injury (50% vs 31%). Inotropes, dialysis, and invasive ventilation were required in 92%, 33%, and 66% of patients, respectively. Temporary mechanical circulatory support was used in 45% of treatment and 28% of control patients (P = 0.08). There were no significant differences in median hospital length of stay (17.5 days), 30-day survival (71%), or survival to hospital discharge (66%). Over 240 days (IQR, 14,847) of median follow-up, survival was 67% for treatment vs 42% for control (hazard ratio, 0.53; 95% confidence interval, 0.28-0.99; P = 0.03).ConclusionA multidisciplinary Code Shock Team approach for CS is feasible and may be associated with improved long-term survival.
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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) | 0.000 | 0.000 |
| 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