False positive computed tomographic angiography for Stanford type A aortic dissection
Bibliographic record
Abstract
BACKGROUND: Computed tomographic angiography (CTA) has emerged as the defacto imaging test to rule out acute aortic dissection; however, it is not without flaws. We report a case of a false-positive CTA with respect to Stanford Type A aortic dissection. CASE: A 52 year-old male presented with sudden onset shortness of breath. He denied chest pain. Due to severe hypertension and an Emergency Department bedside ultrasound suggesting an intimal flap in the aorta, CTA was requested to better assess the ascending aorta and was interpreted as consistent with Stanford Type A aortic dissection with thrombosis of the false lumen in the ascending aorta. However, intra-operative imaging (TEE and epi-aortic scanning) did not identify an intimal flap or dissection, and neither did definitive surgical inspection of the aorta. The suspected aortic dissection and thrombosed false lumen were not visualized on repeat CTA two days later. DISCUSSION: False positive diagnosis of Stanford Type A aortic dissection on CTA can be the result of technical factors, streak artifacts, motion artifacts, and periaortic structures. In this case, non-uniform arterial contrast enhancement secondary to unrecognized biventricular dysfunction resulted in the false positive CTA appearance of an intimal flap and mural thrombus. Intra-operative TEE and epi-aortic scanning were proven correct in excluding aortic dissection by the standard of definitive surgical inspection of the aorta.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".