Abstract 11098: End-Organ Dysfunction Differs in Patients With Heart Failure-Related vs. Acute Myocardial Infarction-Related Cardiogenic Shock
Bibliographic record
Abstract
Introduction: Severity of end-organ dysfunction correlates with outcomes in acute myocardial infarction-related cardiogenic shock (AMI-CS). The epidemiology of end-organ dysfunction in heart failure-related cardiogenic shock (HF-CS) has not been well described. Methods: Cardiac intensive care unit (CICU) admissions with CS in the Critical Care Cardiology Trials Network Registry (2017-2021) were identified and categorized as AMI-CS and HF-CS ( de novo or acute-on-chronic HF). Admissions for each CS sub-type were characterized as having respiratory, kidney, liver, and/or neurologic dysfunction using definitions adapted from the Sequential Organ Failure Assessment score ( Fig A ). Outcomes were assessed by burden of non-cardiac organ dysfunction: no end-organ dysfunction (NEOD), single system end-organ dysfunction (SEOD), or multi-system end-organ dysfunction (MEOD). Results: A total of 2,911 CS admissions from 35 CICUs were identified, most of which were for HF-CS (71%, N = 2,068). The proportions of patients with NEOD, SEOD, and MEOD were 25%, 36%, 39% for HF-CS vs. 16%, 35%, 49% for AMI-CS (p<0.01). NEOD, SEOD, and MEOD rates were 19%, 31%, and 49% for de novo HF-CS vs. 27%, 37%, and 36% for acute-on-chronic HF-CS (p<0.01). Predominant type of organ dysfunction differed among CS sub-types, with higher rates of respiratory dysfunction in AMI-CS and de novo HF-CS (p<0.01) and higher rates of hepatic dysfunction in both de novo and acute-on-chronic HF-CS (p<0.01; Fig A ). In-hospital mortality was lower in acute-on-chronic HF-CS compared with de novo HF-CS or AMI-CS (25% vs. 32% vs. 38%; p<0.01), with a similar gradient of risk according to burden of non-cardiac organ dysfunction (p int = 0.64; Fig B ). Conclusions: End-organ dysfunction pattern and burden differ among de novo HF-CS, acute-on-chronic HF-CS, and AMI-CS. Overall mortality is lowest in acute-on-chronic HF-CS, but mortality is similarly associated with burden of end-organ dysfunction among CS types.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".