Management and Outcomes of Type I and Type II Myocardial Infarction in Cardiogenic Shock
Bibliographic record
Abstract
Introduction Type I myocardial infarction (T1MI) or Type II MI (T2MI) have different underlying mechanisms, however in the setting of cardiogenic shock (CS), it is not understood if patients experience resultantly different outcomes. The objective of this study was to determine clinical features, biomarker patterns, and outcomes in these subgroups. Methods Patients from the CAPITAL-DOREMI trial presenting with acute myocardial infarction (AMI) associated CS (n=103) where classified as T1MI (n=61) or T2MI (n=42). The primary endpoint was a composite of all‐cause in‐hospital mortality, cardiac arrest, the need for mechanical circulatory support, or initiation of renal replacement therapy (RRT) at 30‐days. Secondary endpoints were evaluated as individual components of the primary endpoint. Results Patients with T1MI CS did not have a higher incidence of the primary composite endpoint when compared to T2MI CS (adjusted HR, 1.63; 95% CI, 0.96-2.77; P=0.07). Cardiac biomarkers including troponin I (p<0.001) and creatine kinase levels (p=0.001) were elevated in patients with T1MI CS when compared to T2MI. Furthermore, patients with T1MI CS presented with decreased urine output (p=0.01) when compared to T2MI. Predictors of T2MI CS included non-ischemic ventricular dysfunction (p=0.002), atrial fibrillation (p=0.02), and chronic obstructive pulmonary disease (p=0.002). Conclusion There were no differences in adverse clinical outcomes between patients with T1MI and T2MI CS, although the events were numerically increased and the sample size was small. Overall, this study provides a hypothesis generating analysis regarding the clinical and biochemical outcomes in T1MI vs. T2MI CS.
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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 | 0.002 |
| 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 | 0.001 | 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".