Left Ventricular Thrombus in Myocardial Infarction After Successful Primary Percutaneous Coronary Intervention: Prevalence and Predictors—A Middle Eastern Single-Centre Experience
Bibliographic record
Abstract
Background Left ventricular thrombus (LVT) is a well-recognized complication of myocardial infarction that affects patient outcomes and warrants screening. Methods This retrospective study included 308 consecutive patients who presented with acute ST-elevation myocardial infarction and were treated with primary percutaneous coronary intervention. Results Early screening for LVT by echocardiography and cardiac magnetic resonance revealed the following: LVT (+) group (36 patients [11.7%]) and LVT (−) group (272 patients [88.3%]). The 2 powerful independent variables associated with LVT formation were left anterior descending–related infarct (odds ratio, 10.17; P < 0.0001) and severe left ventricular systolic dysfunction (odds ratio, 8.3; P = 0.0001). The lower the left ventricular ejection fraction, the higher the risk of LVT was. Multivessel coronary artery disease and the type of early invasive strategy (culprit lesion only vs complete revascularization) were not predictive of LVT. The impact of environment (i.e., hot climate, exercise) and dehydration on the risk of LVT formation is uncertain. Conclusion Early LVT formation is a frequent complication in acute ST-elevation myocardial infarction despite timely intervention. Its independent predictors are left anterior descending–related infarct and severe left ventricular systolic dysfunction. In patients with multivessel coronary artery disease, there was no significant difference between lesion-only culprits and complete revascularization in reducing the risk of LVT development. Further studies in larger numbers of patients are needed because of the uncertainties regarding the links between the biological effects of the environment and the risk of LVT formation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".