Cardiac magnetic resonance parameters associated with surgery in a paediatric and young adult population with chronic aortic regurgitation
Bibliographic record
Abstract
BACKGROUND: The timing for intervention in patients with significant chronic aortic regurgitation is based on adult guidelines and criteria which may not apply to children. There is limited data on the use of cardiac MRI parameters to guide surgical decision-making in paediatrics. We examined associations between MRI quantification of aortic regurgitation and left ventricular volumetric function and the need for surgical intervention. METHODS: = 20). Ventricular volumetric functional parameters and aortic regurgitant volume and fraction were collected. Differences in MRI parameters between the groups were compared using unpaired t-tests. Receiver operating characteristic analysis identified MRI cut-off values with discriminatory ability towards primary end point of surgery (area under the curve > 0.7). RESULTS: Patients who underwent surgery had significantly larger ventricular volumes and aortic regurgitant fraction than those without surgery. Aortic regurgitant fraction and volume had the highest discriminatory power (0.93 and 0.92, respectively) between the two groups, followed by indexed left ventricular volumes (end-diastolic volume 0.85 and end-systolic volume 0.89). CONCLUSIONS: Current guidelines for surgical intervention in children with chronic aortic regurgitation are limited. Our findings suggest potential MRI-based threshold values that may aid in surgical decision-making and highlight the need future research for aortic valve surgery in children with chronic aortic regurgitation.
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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 | 0.004 |
| 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 | 0.000 | 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".