Abstract 13589: Prophylactic Anticoagulation to Prevent Left Ventricular Thrombus Following Myocardial Infarction: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Left ventricular thrombus (LVT) complicates an estimated 12% of anterior STEMI. The current standard of care for STEMI patients includes primary PCI and dual antiplatelet therapy (DAPT). Guidelines from the American Heart Association recommend consideration of prophylactic anticoagulation to prevent LVT in select high-risk patients following STEMI. These guidelines have a low certainty of evidence (level C), with most studies published prior to the current era of primary PCI and DAPT. Therefore, an updated review is needed in this area. Methods: Electronic databases, including EMBASE, MEDLINE and CENTRAL were systematically searched from January 2012 to June 2022. We included primary studies that used PCI as the lone revascularization strategy for STEMI. Studies were included if they compared the incidence of LVT in patients receiving prophylactic anticoagulation and DAPT with those receiving DAPT alone. Results: 7,378 studies were screened, with 4 studies eventually included in this review. One study was a randomized control trial and three were retrospective cohort studies. Pooled analysis using a fixed-effects model showed LVT was significantly less common in the triple therapy (TT) group compared to the DAPT group (OR = 0.38; 95% CI = 0.17-0.86; p = 0.02). However, using a random-effects model, there was no significant difference in LVT between the TT and DAPT group (OR = 0.42; 95% CI = 0.04-4.67; p = 0.33). Conclusions: Based on the current state of knowledge, there is no compelling evidence to either support or oppose prophylactic anticoagulation in STEMI. An appropriately powered clinical trial is warranted due to the need for more robust data in this area.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".