Epidemiology and Prognostic Significance of Acute Noncardiac Organ Dysfunction Across Cardiogenic Shock Subtypes
Bibliographic record
Abstract
BACKGROUND: The epidemiology and prognostic significance of acute noncardiac organ dysfunction across cardiogenic shock (CS) subtypes are not well-defined. METHODS: CS admissions from 2017 to 2022 in the Critical Care Cardiology Trials Network Registry were classified as acute myocardial infarction-related CS (AMI-CS), acute-on-chronic heart failure-related CS (AoC HF-CS), or de novo HF-CS, and categorized as having at least moderate respiratory, kidney, liver, and/or neurological dysfunction using established criteria. Burden of organ dysfunction was defined as no noncardiac organ dysfunction (NOD), single organ dysfunction, or multiorgan dysfunction (≥2) (MOD). Multivariable models were used to evaluate associations of burden and type of noncardiac organ dysfunction with in-hospital death. RESULTS: Among 3904 CS admissions, 29.4% had AMI-CS, 50.9% had AoC HF-CS, and 19.7% had de novo HF-CS. AMI-CS and de novo HF-CS had greater prevalence of MOD (35.0% and 33.9%, respectively) compared with AoC HF-CS (23.1%; P < .01). In-hospital mortality was higher with a greater burden of organ dysfunction in the overall CS cohort (single organ dysfunction vs NOD, adjusted odds ratio [aOR] for in-hospital death 2.5, 95% confidence interval [CI] 2.0-3.2; MOD vs NOD: aOR 6.5, 95% CI 5.1-8.2) and across each CS subtype. Kidney dysfunction was the most prognostically important form of organ dysfunction in the overall cohort (aOR 4.1, 95% CI 3.4-5.0) and for each CS subtype. CONCLUSIONS: Admissions for AoC HF-CS had a lower burden of acute noncardiac organ dysfunction compared with admissions for de novo HF-CS and AMI-CS. However, acute noncardiac organ dysfunction burden was similarly adversely prognostic across all CS subtypes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".