Impact of presentation and transfer delays on complete ST-segment resolution before primary percutaneous coronary intervention: insights from the ATLANTIC trial
Bibliographic record
Abstract
AIMS: The aim of this study was to identify predictors of complete ST-segment resolution (STR) pre-primary percutaneous coronary intervention (PCI) in patients enrolled in the ATLANTIC trial. METHODS AND RESULTS: ECGs recorded at the time of inclusion (pre-hospital [pre-H]-ECG) and in the catheterisation laboratory before angiography (pre-PCI-ECG) were analysed by an independent core laboratory. Complete STR was defined as ≥70%. Complete STR occurred pre-PCI in 12.8% (204/1,598) of patients and predicted lower 30-day composite MACCE (OR=0.10, 95% CI: 0.002-0.57, p=0.001) and total mortality (OR=0.16, 95% CI: 0.004-0.95, p=0.035). Independent predictors of complete STR included the time from index event to pre-H-ECG (OR=0.94, 95% CI: 0.89-1.00, p=0.035), use of heparins before pre-PCI-ECG (OR=1.75, 95% CI: 1.25-2.45, p=0.001) and time from pre-H-ECG to pre-PCI-ECG (OR=1.09, 95% CI: 1.03-1.16, p=0.005). In the pre-H ticagrelor group, patients with complete STR had a significantly longer delay between pre-H-ECG and pre-PCI-ECG compared to patients without complete STR (median 53 [44-73] vs. 49 [38.5-61] mins, p=0.001); however, this was not observed in the control group (in-hospital ticagrelor) (50 [40-67] vs. 49 [39-61] mins, p=0.258). CONCLUSIONS: Short patient delay, early administration of anticoagulant and ticagrelor if a long transfer delay is expected may help to achieve reperfusion prior to PCI. Pre-H treatment may be beneficial in patients with longer transfer delays, allowing the drug to become biologically active.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".