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Transcatheter Interventions in Adults With Fontan Palliation

2024· review· en· W4404700988 on OpenAlexaff
Eduardo Flores‐Umanzor, Raquel Luna‐López, Pedro Cepas‐Guillén, Sílvia Montserrat, Bandar Alshehri, Rajesh Keshvara, Lusine Abrahamyan, Juan Manuel Carretero Bellón, Rafael Alonso-González, Mark Osten, Xavier Freixa, Josep Rodés‐Cabau, Lee Benson, Eric Horlick

Bibliographic record

VenueCirculation Cardiovascular Interventions · 2024
Typereview
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsInstitute for Work & HealthTed Rogers Centre for Heart ResearchUniversity Health NetworkHospital for Sick ChildrenFoothills Medical Centre
Fundersnot available
KeywordsMedicinePercutaneousFontan procedureHeart failurePsychological interventionCardiologyIntensive care medicineCardiac outputPopulationInternal medicineHemodynamicsHeart disease

Abstract

fetched live from OpenAlex

The Fontan circuit is associated with chronically elevated systemic venous pressures and decreased cardiac output, often leading to circuit failure. Managing Fontan circuit failure is complex and requires multiple therapeutic options. Transcatheter interventions have emerged as a reliable approach. They can alleviate obstructions and improve cyanosis by enhancing pulmonary blood flow and oxygen saturation. These procedures can also increase cardiac output and reduce systemic venous pressure, contributing to patient stabilization. In addition, they help mitigate volume overload and decrease the risk of bleeding during heart or combined heart and liver transplants. In recent years, percutaneous interventions have rapidly evolved and become a key therapeutic option for addressing various aspects of Fontan circuit failure. These interventions should be considered integral to the management strategy for this specific 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 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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.090
GPT teacher head0.370
Teacher spread0.279 · 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 designSystematic review
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
Published2024
Admission routes1
Has abstractyes

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