The role of late reperfusion in ST-segment elevation myocardial infarction: a real-world retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Early reperfusion of the coronary artery has become the first choice for patients with ST-segment elevation myocardial infarction (STEMI). How to deal with patients who miss the time window for early reperfusion is still controversial. Based on real-world data, this study was conducted to explore whether percutaneous coronary intervention (PCI) has an advantage over standard drug therapy in patients who miss the optimal treatment window. METHODS: Consecutive patients who were diagnosed with STEMI and met the inclusion criteria between 2009 and 2018 in our center were retrospectively included in this cohort study. The primary endpoint events were major adverse cardiac events (MACEs), including heart failure, sudden cardiac death, malignant arrhythmia, thrombi and bleeding events during the period of admission. Secondary endpoint events were components of MACEs. At the same time, we also evaluated angina pectoris at admission and discharge through Canadian Cardiovascular Society (CCS) grading. RESULTS: This study enrolled 417 STEMI patients and divided them into four groups (PCI < 3 days, 14.87%; 3 days<PCI < 7 days, 21.104%; PCI > 7 days, 34.29%; MED, 29.74%). During the period of admission, MACEs occurred in 52 cases. The incidence of MACEs was 11.29, 7.95, 4.20 and 25.81% in the four respective groups (p < 0.0001). The MED group had higher rates of MACEs (OR = 3.074; 95% CI 0.1.116-8.469, p = 0.03) and cardiac death (OR = 3.027; 95% CI 1.121-8.169, p = 0.029) compared to the PCI group. Although both treatments were effective in improving CCS grade at discharge, the PCI group improved more significantly (p < 0.0001). CONCLUSIONS: In the real world, delayed PCI can be more effective in patients with angina symptoms at discharge and reduce the incidence of MACEs and cardiac death during hospitalization. The timing of intervention was independent of the occurrence of MACEs during hospitalization and of improvement in symptoms.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".