Safety and efficacy of low-dose intracoronary thrombolysis during primary percutaneous coronary intervention in patients with ST elevation myocardial infarction: A meta-analysis of randomized trials
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In patients with ST elevation myocardial infarction (STEMI), intracoronary thrombolysis (ICT) may reduce thrombotic burden and microvascular obstruction in the infarct-related artery. We performed a meta-analysis to evaluate the role of adjunctive low-dose ICT during primary percutaneous coronary intervention (PPCI) in improving clinical outcomes and indices of microvascular function. We searched electronic databases (Cochrane, EMBASE, Medline; inception to October 2023) for randomized controlled trials (RCTs) evaluating the effects of adjunctive ICT in STEMI patients undergoing PPCI, compared with placebo or usual care. Study-level data on efficacy and safety outcomes were pooled using a fixed-effect model. The primary outcome was major adverse cardiovascular events (MACE). A total of 8 RCTs were included, comprising a total of 1,208 patients. Compared with placebo or usual care, ICT was associated with a trend towards lower MACE (11.3% vs. 15.1%; odds ratio [OR] 0.73, 95% confidence interval [CI] 0.51 to 1.04). Infarct size (mean difference [MD] -1.98, 95% CI -3.68 to -0.27; p=0.02), ST-segment resolution (MD: 6.06, 95% CI: 0.69 to 11.43; p=0.03) and corrected TIMI frame count (MD: -2.26, 95% CI: -4.03 to -0.48; p=0.01; I2=78%). The odds for major (0.7% vs. 0.7%; OR 0.94, 95% CI 0.24 to 3.7; p=0.93) and minor bleeding (7.7% vs. 4.3%; OR 1.81, 95% CI 0.87 to 3.76; p=0.11) were similar between the two groups. Adjunctive low-dose ICT during PPCI is safe, associated with a trend towards lower MACE, and may improve surrogate markers of microvascular function. These hypothesis-generating findings warrant validation in larger, adequately powered randomized trials.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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 it