Impact of Aortic Prosthetic Heart Valve Dysfunction on Left Ventricular Afterload and on the Accuracy of Echo-Doppler Measurements
Bibliographic record
Abstract
Left heart side (left ventricle and left atrium) is responsible for delivering the oxygenated blood to all body organs, where a relatively strong left ventricle contraction is needed to deliver around 5 liters of blood per minute. As a consequence, the left heart side experiences a high pressure (∼150 mmHg). Therefore, the dysfunction (stenosis or incompetence) in the aortic and/or mitral heart valves in the left side of the heart is more common than the dysfunction in the pulmonary and tricuspid heart valves in the right side of the heart (Yoganathan et al., 2004). Heart valve surgical replacement is the most effective solution in severe functional heart valve disease (Pibarot and Dumesnil, 2009). Almost, half of the total implants of prosthetic heart valves (∼300,000) are mechanical (mainly bileaflet). In case of mechanical heart valve (MHV), a lifelong anti-coagulant should be taken to avoid thromboembolic events. Despite the significant improvement in valve design resulting in minimizing prosthetic valve complications (thromboembolic events or pannus formation), these complications are still possible with MHV Implantation.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".