Combined aortic stenosis and regurgitation: double the trouble
Bibliographic record
Abstract
### Learning objectives Mixed aortic valve disease (MAVD) refers to the coexistence of aortic stenosis (AS) and aortic regurgitation (AR). Despite the relatively high prevalence of MAVD, there are very few data on the outcome and management of this entity.1–6 Nonetheless, a few recent studies have reported that the prognosis of patients with combined moderate AS and moderate AR is similar or worse than those with isolated severe AS or AR.2 3 The therapeutic management of MAVD is complex and is currently based on the guideline recommendations for the predominant lesion, AS or AR.1 7 The objective of this Education in Heart article is to provide an overview of the prevalence, pathophysiology, outcomes, diagnosis, severity grading and strategies for the therapeutic management of MAVD. ### Prevalence of MAVD In a nationwide epidemiology study conducted in Sweden,8 the overall incidence rate of multiple valve disease was 6.4 per 100 000 person-years. This rate increased markedly with age and was higher in men (8.5 per 100 000 person-years) than in women (5.8 per 100 000 person-years).8 MAVD was the most frequent multiple valve disease and 17.9% of patients with AR were diagnosed with concomitant AS. ### Pathophysiology of MAVD The pathophysiology and clinical impact of MAVD are complex and relate to the severity and chronicity of each aortic valve lesion and to the repercussions of these lesions on the remodelling and function of the left ventricle (LV) and other upstream cardiac chambers.5 In patients …
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".