A Multidisciplinary Aortopathy Clinic: The McGill Experience
Bibliographic record
Abstract
Background: Guidelines recommend that patients with thoracic aortic disease (TAD) be seen in a multidisciplinary aortopathy clinic, because of their complex and high-risk profile. However, reports on such clinics are limited. Methods: From September 2016 to May 2024, we evaluated 567 patients with TAD. They were seen by our multidisciplinary team, which is comprised of 1 cardiac surgeon, 2 vascular surgeons, 1 cardiologist, 1 cardiothoracic radiologist, a team of 4 engineering researchers, a dedicated member from the genetics department, and an administrative assistant. For patients who had computed tomography or magnetic resonance imaging performed outside our institution, image reanalysis was conducted by our cardiothoracic radiologist. Genetic testing was performed for patients with suspected hereditary TADs. Results: Reanalysis of external computed tomography and/or magnetic resonance imaging by our radiologist altered clinical decision-making in 5 of 51 cases (9.8%). Genetic testing that examined 25 genes associated with Marfan syndrome and related aortopathies was conducted on 250 patients, revealing a positive TAD gene in 32 (12.8%), a variant of unknown significance in 99 (39.6%), and a negative result in 119 (47.6%). Forty patients (7%) had surgery within a median of 2.7 months (quartile 1-quartile 3: 1.1-4.9) from their initial clinic visit. Conclusions: Our 8-year experience at the aortopathy clinic of McGill University demonstrates that a multidisciplinary approach to TAD can deliver complete, precise, and timely care to this complex 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".