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Record W2937859380 · doi:10.1016/j.cjco.2019.03.002

Practice Variation Among Canadian Pediatric Cardiologists in Medical Management of Dilated Ascending Aorta in Patients With Bicuspid Aortic Valve

2019· article· en· W2937859380 on OpenAlexaffabout
Arif Hussain, Andrew E. Warren, Robert P.-C. Chen, Santokh Dhillon

Bibliographic record

VenueCJC Open · 2019
Typearticle
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsBicuspid aortic valveMedicineAortic dissectionAortic valveAscending aortaCardiologyInternal medicinePopulationPediatricsAorta

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.276
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2019
Admission routes2
Has abstractyes

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