Efficacy and safety of intracoronary epinephrine versus conventional treatments alone in STEMI patients with refractory coronary no‐reflow during primary PCI: The RESTORE observational study
Bibliographic record
Abstract
OBJECTIVES: We aimed to compare intracoronary (IC) epinephrine versus conventional treatments alone in patients with ST-elevation myocardial infarction and refractory coronary no-reflow during primary percutaneous coronary intervention (PPCI). METHODS: Thirty consecutive patients with severe refractory coronary no-reflow (TIMI 0-1, MBG 0-1) during PPCI were prospectively included after initial failure of conventional treatments. Conventional treatments used in both groups included IC nitrates, thrombectomy. Glycoprotein IIb/IIIa inhibitors and adenosine. Patients received IC epinephrine or no epinephrine. RESULTS: Intracoronary administration of epinephrine yielded significantly better coronary flow patterns (28.6% TIMI 3, 64.3% TIMI 2, 7.1% TIMI 1, and 0% TIMI 0), compared to those after treatment with conventional agents alone (18.8% TIMI 3, 12.5% TIMI 2, 37.5% TIMI 1, and 31.3% TIMI 0) (p value between groups = .004). In the IC epinephrine vs. no epinephrine group there was a significant reduction of 30-day composite of death or heart failure (35.7% vs. 81.25%), improvement of ejection fraction (p = .01) and ST-segment resolution (p = .01). CONCLUSIONS: The findings of this proof-of-concept study suggest that as compared to use of conventional agents alone, IC epinephrine provides substantial improvement of coronary flow in STEMI patients with refractory no-reflow during PPCI that may result into improved prognosis.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".