Inhibition of delta-protein kinase C by delcasertib as an adjunct to primary percutaneous coronary intervention for acute anterior ST-segment elevation myocardial infarction: results of the PROTECTION AMI Randomized Controlled Trial
Bibliographic record
Abstract
AIMS: Delcasertib is a selective inhibitor of delta-protein kinase C (delta-PKC), which reduced infarct size during ischaemia/reperfusion in animal models and diminished myocardial necrosis and improved reperfusion in a pilot study during primary percutaneous coronary intervention (PCI) for ST elevation myocardial infarction (STEMI). METHODS AND RESULTS: A multicentre, double-blind trial was performed in patients presenting within 6 h and undergoing primary PCI for anterior (the primary analysis cohort, n = 1010 patients) or inferior (an exploratory cohort, capped at 166 patients) STEMI. Patients with anterior STEMI were randomized to placebo or one of three doses of delcasertib (50, 150, or 450 mg/h) by intravenous infusion initiated before PCI and continued for ∼2.5 h. There were no differences between treatment groups in the primary efficacy endpoint of infarct size measured by creatine kinase MB fraction area under the curve (AUC) (median 5156, 5043, 4419, and 5253 ng h/mL in the placebo, delcasertib 50, 150, and 450 mg/mL groups, respectively) in the anterior STEMI cohort. No treatment-related differences were seen in secondary endpoints of infarct size, electrocardiographic ST-segment recovery AUC or time to stable ST recovery, or left ventricular ejection fraction at 3 months. No differences in rates of adjudicated clinical endpoints (death, heart failure, or serious ventricular arrhythmias) were observed. CONCLUSIONS: Selective inhibition of delta-PKC with intravenous infusion of delcasertib during PCI for acute STEMI in a population of patients treated according to contemporary standard of care did not reduce biomarkers of myocardial injury.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".