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Record W3178464350 · doi:10.1161/circep.120.009726

Management of Congenital Long-QT Syndrome: Commentary From the Experts

2021· review· en· W3178464350 on OpenAlexaff
Elizabeth S. Kaufman, Lee L. Eckhardt, Michael J. Ackerman, Peter F. Aziz, Elijah R. Behr, Marina Cerrone, Mina K. Chung, Michael J. Cutler, Susan P. Etheridge, Andrew D. Krahn, Steven A. Lubitz, Marco Pérez, Silvia G. Priori, Jason D. Roberts, Dan M. Roden, Eric Schulze‐Bahr, Peter J. Schwartz, Wataru Shimizu, M. Benjamin Shoemaker, Raymond W. Sy, Jeffrey A. Towbin, Sami Viskin, Arthur A.M. Wilde, Wojciech Zaręba

Bibliographic record

VenueCirculation Arrhythmia and Electrophysiology · 2021
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsPopulation Health Research InstituteUniversity of British Columbia
FundersNational Heart, Lung, and Blood Institute
KeywordsExpert opinionVotingDiversity (politics)Divergence (linguistics)PsychologyMedicineKey (lock)Opinion leadershipIntensive care medicinePublic relationsPolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

While published guidelines are useful in the care of patients with long-QT syndrome, it can be difficult to decide how to apply the guidelines to individual patients, particularly those with intermediate risk. We explored the diversity of opinion among 24 clinicians with expertise in long-QT syndrome. Experts from various regions and institutions were presented with 4 challenging clinical scenarios and asked to provide commentary emphasizing why they would make their treatment recommendations. All 24 authors were asked to vote on case-specific questions so as to demonstrate the degree of consensus or divergence of opinion. Of 24 authors, 23 voted and 1 abstained. Details of voting results with commentary are presented. There was consensus on several key points, particularly on the importance of the diagnostic evaluation and of β-blocker use. There was diversity of opinion about the appropriate use of other therapeutic measures in intermediate-risk individuals. Significant gaps in knowledge were identified.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.291
Teacher spread0.272 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations19
Published2021
Admission routes1
Has abstractyes

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