Multimodality cardiac imaging of a left ventricular thrombus: a case report
Bibliographic record
Abstract
BACKGROUND: Left ventricular thrombus (LVT) formation occasionally complicates patient recovery post myocardial infarction, conveying a significant risk of systemic embolism. Accordingly, thrombus detection and subsequent anticoagulation is imperative in order to minimize patient morbidity and mortality. Transthoracic echocardiography (TTE) is the imaging modality most widely used to screen for thrombus formation despite its suboptimal sensitivity and specificity. CASE PRESENTATION: This report describes the discordant imaging findings of a LVT in a 56 year old Caucasian male with an anterior ST elevation myocardial infarction. Left ventriculography revealed a filling defect, suggestive of a potential left ventricular (LV) thrombus, which could not be confirmed by TTE. Cardiac magnetic resonance imaging (MRI) demonstrated evidence of a full thickness scar involving the mid to distal anterior wall and apical regions, with confirmation of a small LV apical thrombus. CONCLUSIONS: This case illustrates the limitations of TTE when used as a tool to screen for thrombus formation. It highlights the importance of multimodality cardiac imaging for the detection of post myocardial infarction (MI) complications, in the context of a high clinical suspicion.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".