Right ventricular free wall dyskinesis in the setting of left ventricular non compaction: a case report
Bibliographic record
Abstract
BACKGROUND: Left ventricular non compaction is a relatively rare congenital disorder characterized by prominent trabeculations and intertrabecular recesses with the potential for thromboembolism, arrhythmias, and sudden cardiac death as adverse effects. Echocardiography has traditionally been employed as the primary mode of imaging; however, with the advent of cardiac magnetic resonance as a more precise imaging technique, the disorder known as left ventricle non compaction is becoming more broadly defined with increasing recognition of right ventricle (RV) involvement. CASE PRESENTATION: This report describes a 52-year-old Caucasian female with new onset atrial fibrillation with an unusual finding of left ventricular non compaction and right ventricular dysfunction on transthoracic echocardiogram with preserved left ventricular ejection fraction. Cardiac magnetic resonance imaging demonstrated a disproportionately affected right ventricle, with apical free wall dyskinesis. CONCLUSIONS: This case illustrates the unique occurrence of left ventricular non compaction with preserved ejection fraction alongside RV free wall dyskinesis and RV systolic dysfunction. The significance of this is yet unknown given the paucity of existing literature. This report serves to highlight the vast heterogeneity within left ventricular non compaction as we are better able to delineate this disorder using increasingly sophisticated imaging techniques.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".