An early revascularization strategy is associated with a survival benefit for diabetic patients in cardiogenic shock after acute myocardial infarction
Bibliographic record
Abstract
BACKGROUND: The role of diabetes mellitus (DM) in cardiogenic shock (CS) complicating an acute myocardial infarction (AMI) is not well understood. Previous studies have reported an in-hospital mortality rate for patients with DM and CS of about 60%. OBJECTIVES: This study compares the 1-year mortality rates of patients with DM and those without (NDM) and evaluates early revascularization (ERV) compared with initial medical stabilization (IMS) in patients with DM and CS. METHODS: Baseline characteristics, clinical and hemodynamic measures, and management were compared for 90 patients (31%) with DM and 198 with NDM (69%) who were randomized to ERV or IMS in the SHOCK Trial. RESULTS: When compared with NDM, patients with DM were of similar age but had higher rates of prior MI (44.4 vs. 27.8%, p = 0.007) and hypertension (56.2 vs. 42.5%, p = 0.04). The DM group had a lower rate of fibrinolytic therapy (44.4 vs. 60.1%, p = 0.02). In patients randomized to ERV, patients with DM had a higher rate of coronary artery bypass grafting (CABG) (50.0 vs. 30.9%, p = 0.03) despite similar rates of triple-vessel disease. The 1-year mortality rates in both groups were equivalent (58.9%). One-year mortality was not associated with diabetes (hazard ratio [HR] 1.02, 95% CI, 0.73-1.42, p = 0.91). The benefit of an ERV strategy was similar (HR [DM] 0.62; HR [NDM] 0.75, p = 0.58). Even after adjusting for the imbalance in CABG rates, 1-year mortality was not associated with DM. CONCLUSION: Diabetes mellitus is not a predictor of 1-year mortality in CS after AMI. The benefit from an ERV strategy is similar for DM and NDM. The management strategies and influence of DM on mortality in CS deserve further evaluation.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".