MétaCan
Menu
Back to cohort
Record W4386807671 · doi:10.1016/j.cjcpc.2023.09.006

Navigating Arrhythmias in Tetralogy of Fallot Throughout the Lifespan: A Case-based Review

2023· review· en· W4386807671 on OpenAlexaff
Christophe Vô, Nabil Dib, Stefano Bartoletti, Blandine Mondésert, Marie-Hélène Gagnon, A Fournier, Paul Khairy

Bibliographic record

VenueCJC Pediatric and Congenital Heart Disease · 2023
Typereview
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineMontreal Heart Institute
Fundersnot available
KeywordsTetralogy of FallotMedicineCardiologyHeart diseaseVentricular tachycardiaInternal medicineComplicationTachycardiaQuality of life (healthcare)Intensive care medicine

Abstract

fetched live from OpenAlex

Arrhythmias are a common complication associated with tetralogy of Fallot (ToF), one of the most prevalent forms of congenital heart disease. As illustrated by this case-based review, various forms of arrhythmias can be encountered across the lifespan of patients with ToF, from infancy to older adulthood. These include atrioventricular block, junctional ectopic tachycardia, and atrial and ventricular arrhythmias. Arrhythmias have important implications on the health and quality of life of patients with ToF and require treatment by caregivers with dedicated expertise. The choice of pharmacologic and/or interventional therapies to alleviate symptoms, avoid complications, and mitigate risks depends in part on the type, severity, and frequency of the arrhythmia, as well as on the particularities of individual clinical scenarios. Preventing, monitoring for, and managing arrhythmias are an integral component of the care of patients with ToF throughout their lifespan that is critical to optimizing health outcomes.

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)0.004
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.378
Teacher spread0.324 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCJC Pediatric and Congenital Heart DiseaseSame topicCongenital Heart Disease StudiesFrench-language works237,207