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Record W2745165979 · doi:10.1136/heartjnl-2017-311598

Developing a shared decision support framework for aortic root surgery in Marfan syndrome

2017· article· en· W2745165979 on OpenAlexaboutno aff
Tom Treasure, Annette King, Loreto Hidalgo Lemp, Tal Golesworthy, John Pepper, Johanna J.M. Takkenberg

Bibliographic record

VenueHeart · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineViewpointsMarfan syndromeAortic rootAortic surgeryFocus groupRoot (linguistics)Qualitative researchSurgeryFamily medicineAortaMarketing

Abstract

fetched live from OpenAlex

OBJECTIVE: The study is an early phase of development of a decision support framework for people with Marfan syndrome who are anticipating prophylactic aortic root surgery. Implications of the timing and the nature of the operation chosen were previously elicited in focus groups. In this step, we explored the range of relative values placed by individuals on the implications of decisions made about surgery. METHODS: Following the principles of the Ottawa Decision Support Framework, eight questions in the general form 'How important is it to you …' were framed by a panel. Marfan people, families and specialist doctors answered online. Quantitative and qualitative analyses were performed. RESULTS: Worldwide, 142 responses were received including 25 specialist doctors. Respondents were 55% female and 46% had previous aortic root surgery. Overall, active lifestyle was more important to males (p=0.03). Patients placed more importance than doctors on not deferring surgery (p=0.04) and on avoidance of anticoagulation in the interests of childbearing (p=0.009). Qualitative analysis showed differing but cogently reasoned values that were sometimes polarised, and mainly driven by the wish to maintain a good quality of life and active lifestyle. CONCLUSIONS: Given the cogency of these viewpoints, people anticipating root replacement surgery should have ample opportunity to express them and to have them acknowledged ahead of a consultation when they can then be fully explored in a mutually informed forum. If they differ from local medical practice, they can then be discussed in the process of reaching shared and individualised decisions.

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)0.003
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 score0.035
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 head0.063
GPT teacher head0.389
Teacher spread0.326 · 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

Citations24
Published2017
Admission routes1
Has abstractyes

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