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Record W4402348754 · doi:10.1016/j.jacadv.2024.101254

High-Performing Fontan Patients

2024· article· en· W4402348754 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJACC Advances · 2024
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsHospital for Sick Children
FundersNational Center for Advancing Translational SciencesAdditional VenturesNational Institutes of HealthEnzon Pharmaceuticals
KeywordsCardiologyInternal medicineFontan procedureMedicineHeart disease

Abstract

fetched live from OpenAlex

Background: Fontan patients exhibit decreased exercise capacity. However, there is a subset of high-performing Fontan (HPF) patients with excellent exercise capacity. Objectives: tool using exercise data; 2) examine clinical factors associated with HPF patients; and 3) examine late outcomes in HPF patients. Methods: quartile. Multivariable logistic regression was employed to investigate factors associated with the HPF and Cox regression was used to examine the association between HPF patients and late outcomes (composite of death or listing for cardiac transplant). Results: = 0.01). Patients with at least moderate atrioventricular valve regurgitation, protein-losing enteropathy, or who were using psychiatric medications, were less likely to be an HPF patient. After a mean follow-up of 3.7 years, 46 (5.7%) patients developed a composite endpoint. HPF had a lower risk of death or listing for cardiac transplant (HR: 0.06 [95% CI: 0.01-0.25]). Conclusions: Patients with HPF have more favorable outcomes when compared to patients with lower exercise capacity. This large registry data highlights the role of exercise testing in providing personalized care and surveillance post-Fontan.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.286
Teacher spread0.278 · 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