Abstract 18462: Hickam's Dictum Revisited: A Multifactorial Etiology of Stroke in a Patient With Rheumatic Mitral Stenosis and Atrial Septal Aneurysm
Bibliographic record
Abstract
A 64-year-old gentleman with rheumatic mitral stenosis (MS), coronary artery disease, and active tobacco abuse was admitted with a left posterior cerebral artery (PCA) territory ischemic cerebrovascular accident (CVA). He presented with confusion, headaches, and alexia with stable vital signs. He denied rest or exertional dyspnea. Physical exam revealed right homonymous hemianopia, mild right upper extremity dysmetria, decreased right facial sensation, and mild prosopagnosia. Initial neuroimaging confirmed an evolving left hemispheric infarct. Laboratory testing showed unremarkable inflammatory markers. Computed tomographic (CTA) and magnetic resonance angiography (MRA) of the head and neck confirmed left PCA territory acute or subacute infarction with occlusion of the left P2 segment. 12-lead electrocardiogram demonstrated normal sinus rhythm. Occult atrial fibrillation was not seen. Transthoracic echocardiogram (TTE) showed no evidence of right-to-left interatrial shunt. Moderate left atrial (LA) dilation, posterior mitral leaflet tip calcification, and a resting mean mitral gradient of 20 millimeters of mercury (mmHg) suggested severe mitral stenosis. Given the discrepancy between the patient’s symptoms and the TTE findings, transesophageal echocardiogram (TEE) was performed (Figure). The patient’s left PCA territory infarct was ascribed to multifactorial cardioembolic etiologies: 1) Atrial septal aneurysm (ASA) 2) Rheumatic MS and 3) Aortic arch atheroma. Anticoagulation was recommended and initiated 14 days after his CVA to minimize risk of hemorrhagic transformation. High-dose atorvastatin and aspirin were instituted. He progressed well through rehabilitation, demonstrating steady neurological improvement. The case underscores the importance of pursuing further investigation when discrepancies exist between clinical and objective data. ASA is an uncommon but under-recognized risk factor for cardioembolic stroke.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".