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Record W4310112817 · doi:10.1016/j.jacc.2022.09.038

Management of Heart Failure With Arrhythmia in Adults With Congenital Heart Disease

2022· review· en· W4310112817 on OpenAlexaff
Jeremy P. Moore, Ariane Marelli, Luke J. Burchill, Henry Chubb, S. Lucy Roche, Ari Cedars, Paul Khairy, Ali N. Zaidi, Jan Janoušek, David Crossland, Robert H. Pass, Jeffrey P. Jacobs, Jonathan N. Menachem, David S. Frankel, Sabine Ernst, Jim T. Vehmeijer, Mitchell I. Cohen

Bibliographic record

VenueJournal of the American College of Cardiology · 2022
Typereview
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsUniversité de MontréalMontreal Heart InstituteUniversity of TorontoUniversity Health NetworkMcGill University
Fundersnot available
KeywordsMedicineHeart failureHeart diseaseIntensive care medicineMultidisciplinary approachDiseaseCardiologyDisease managementManagement of heart failureInternal medicine

Abstract

fetched live from OpenAlex

Together, heart failure and arrhythmia represent the most important cardiovascular sources of morbidity and mortality among adults with congenital heart disease (ACHDs). Although traditionally conceptualized as operating within 2 distinct clinical silos, these scenarios frequently coexist within the same individual; consequently the mechanistic, therapeutic, and prognostic overlap between them demands increased recognition. In fact, given the near ubiquity of heart failure and arrhythmia among ACHDs, there is perhaps no other arena within cardiology where this critical intersection is more frequently observed. Optimal care for ACHDs therefore requires a heightened awareness of the relevant interactions as well as the pharmacologic and interventional resources that are increasingly available to the treating cardiologist. This review explores and highlights the overlap between these 2 fields to recommend a parallel, yet interactive, multidisciplinary approach to clinical management. Congenital heart disease categories are broken down into their archetypal subtypes to highlight subtleties of the pathophysiology, evaluation, and therapeutic approach.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.282
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations30
Published2022
Admission routes1
Has abstractno

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