Thrombosis of a mechanical aortic valve: stuck between a clot and a hard place
Bibliographic record
Abstract
A 57-year-old female with previous mechanical aortic (AVR) and mitral valve (MVR) replacements presented with decompensated heart failure in the setting of an elevated troponin. The patient’s history was notable for labile international normalized ratios (INR) on warfarin that was 1.0 on presentation. At the time of cardiac catheterization, the coronary arteries were patent. However, cinefluoroscopy demonstrated an immobile AVR leaflet concerning for valve thrombosis (Panel A, Supplementary data online, Video S1A). Following anticoagulation with IV heparin, a transthoracic echocardiogram (TTE) demonstrated severe aortic stenosis and severe aortic regurgitation across the AVR (Panel B). Cardiac computed tomography (CCT) confirmed the finding of AVR thrombosis (Panel C, Supplementary data online, Video S1C). On transoesophageal echocardiography (TEE), there was a large 17 × 14 mm echo-dense mass adherent to the AVR leaflet confirming the diagnosis (Panel D, Supplementary data online, Video S1D). As the patient’s operative risk was highly prohibitive for cardiac surgery, the patient was medically treated with a low-dose alteplase (TPA) infusion. Immediately following treatment with thrombolytic therapy, the patient developed a painful and pulseless left leg, confirmed to be an acute thromboembolic femoral artery occlusion on CT angiography. The patient underwent urgent thrombectomy via a combined open and endovascular approach (Panel E). Intraoperative cinefluoroscopy demonstrated restored AVR leaflet motion (Panel F, Supplementary data online, Video S1F). Repeat TTE imaging revealed markedly improved gradients across the AVR, with peak and mean gradients of 31 and 17 mmHg, respectively. This case highlights the complementary role of multimodality cardiovascular imaging with echocardiography, cinefluoroscopy, and CCT in the diagnosis and management of complications from mechanical valve thrombosis. Supplementary data are available at European Heart Journal online. All authors declare no disclosure of interest for this contribution. No data were generated or analysed for or in support of this paper.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".