Influence of age and sex on left ventricular remodelling in chronic aortic regurgitation
Bibliographic record
Abstract
AIMS: Aortic regurgitant volumes (RVol) and left ventricular (LV) dimensions and volumes are essential parameters for assessing the severity and guiding surgical timing in aortic regurgitation (AR). However, normal LV volumes vary with age and sex, potentially affecting the interpretation of dilation. This study investigated the impact of sex and age on LV remodelling in chronic AR using cardiac magnetic resonance (CMR). METHODS AND RESULTS: This monocentric prospective cross-sectional study enrolled 290 consecutive adult patients (mean age 51 ± 16 years, 19% women) with chronic at least moderate AR by echocardiography between 2003 and 2022 to undergo a comprehensive CMR examination for evaluation of AR severity and LV remodelling. The correlation between regurgitant fraction (RF) and RVol was age and sex dependent, as both absolute but also body surface indexed RVol represented a higher RF in women and older patients. Also, women had less dilated ventricles and LV-EDVi and LV-ESVi increased less with increasing AR severity in females and with advancing age. Therefore, LV volumes and RVol underestimated AR severity by RF in such patients. However, women had larger LV diameters and more spherical ventricles. Therefore, LV diameters failed to accurately identify severe AR among females as opposed to males. Comparatively, age- and sex-specific LV volume thresholds could equally assess AR severity across sexes. CONCLUSION: Conventional parameters used to grade AR severity and LV remodelling are significantly influenced by age and sex. This encourages the use of age- and sex-specific volumetric thresholds for LV dilation monitoring and surgical referral in AR 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".