Practice Variation Among Canadian Pediatric Cardiologists in Medical Management of Dilated Ascending Aorta in Patients With Bicuspid Aortic Valve
Bibliographic record
Abstract
BACKGROUND: Medical therapy is often prescribed to reduce the rate of aortic dilatation and prevent aortic dissection in patients with bicuspid aortic valve (BAV) despite a lack of evidence. We conducted an anonymous survey to gain insight into Canadian clinical practice regarding medical therapy used to slow the progression of aortic dilatation in patients with BAV. METHODS: A questionnaire was sent to 115 paediatric cardiologists and 18 adult congenital heart disease specialists in Canada. RESULTS: score between ≥ 2 and < 5. The remaining 25% of responders (20/81) reported prescribing medications on the basis of absolute aortic diameter, and 80% (16/20) of them considered initiating medical therapy at an aortic diameter > 40 mm to < 50 mm. For practical purposes, however, 40% of respondents (45/113) would not or rarely consider medical therapy for this indication because of variation in the threshold for initiating treatment. Ten of 14 adult congenital heart disease specialists' responses (71%), reported prescribing medications who were excluded because of missing data. CONCLUSION: The majority of Canadian paediatric cardiologists reported prescribing medications to slow the rate of aortic dilatation in patients with BAV. However, there is heterogeneity in the criteria to prescribe medical therapy. A multicenter randomized controlled trial is needed to establish the role of medical therapy in this patient population.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".