Quantitative Assessment of Three-Dimensional Aorto-Mitral Angle in Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
Background This study explored the correlation between the 3-dimensional aorto-mitral angle and pressure gradients in patients with obstructive hypertrophic cardiomyopathy (HCM) undergoing septal myectomy, with or without aortic shortening. Methods A single-site, retrospective observational study was conducted at a tertiary-level hospital; 67 patients underwent septal myectomy for obstructive HCM. Preoperative and postoperative transesophageal images were analyzed offline to measure the end-systolic 3-dimensional aorto-mitral angle with Mitral Valve Quantification software and Doppler-derived pressure gradients. The angle's impact on pressure gradients after myectomy, with or without aortic shortening, was evaluated by linear regression. Results Regression analysis found no significant relationship between aorto-mitral angle changes and postmyectomy pressure gradients ( r = 0.03; 95% CI, −0.22 to 0.28; P = .81), regardless of aortic shortening. No major angle differences were observed between myectomy-only patients and those with additional aortic shortening (97.0° ± 8.4° vs 100.4° ± 8.7°; P = .78). Conclusions The reduced angle seen in patients with obstructive HCM did not return to normal values after septal myectomy, even with normalized pressure gradients. Aortic shortening did not significantly influence the aorto-mitral angle after myectomy either.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".