Association of Global Longitudinal Strain and Long‐Term Transplant‐Free Survival in Fontan Patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Patients with single-ventricle physiology undergoing Fontan operations face high morbidity and mortality risks. While classic-pattern dyssynchrony (CPD) and protein-losing enteropathy (PLE) are known predictors of adverse outcomes, the role of global longitudinal strain (GLS) as an independent predictor of heart failure remains unclear. METHODS: A retrospective cohort study of 135 Fontan-operated patients from 2014 to 2015 evaluated the predictive value of GLS alongside PLE and CPD on mortality and transplantation after 9 years. Echocardiographic data, including GLS, were analyzed using speckle tracking strain analysis in 132 patients. The primary endpoint was transplant-free survival. RESULTS: Among 132 Fontan patients, 15 had classic-pattern dyssynchrony, 29 had protein-losing enteropathy, 37 had moderately reduced global longitudinal strain (GLS ←8% ≥-16%), and 18 had severely reduced GLS (≥-8%). Cox regression analysis showed moderately reduced GLS increased mortality risk (HR 5.8, 95% CI 1.27-26.5, p = 0.023), with severely reduced GLS showing an HR of 10.3 (95% CI 2.18-48.6, p = 0.003). These results were comparable to CPD (HR 11.5, p = 0.002) and PLE (HR 14.9, p < 0.001). CONCLUSION: Global longitudinal strain emerged as the best independent factor for predicting long-term transplant-free survival in Fontan patients, highlighting the importance of GLS assessment in routine follow-up to identify high-risk individuals for early intervention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".