Echocardiographic assessment of right heart function in heart transplant recipients and the relation to exercise hemodynamics
Bibliographic record
Abstract
This study aimed to characterize right heart function in heart transplantation (HTx) patients using advanced echocardiographic assessment and simultaneous right heart catheterization (RHC). Comprehensive two-dimensional (2D) and three-dimensional (3D) echocardiographic assessment of right heart function was performed in 105 subjects (64 stable HTx patients and 41 healthy controls). RHC was performed at rest and during semi-supine maximal exercise test. Compared with controls, in conclusion, HTx patients had impaired right ventricle (RV) systolic function in terms of decreased RV-free wall (FW) global longitudinal strain (GLS) (-20 ± 5% vs. -28 ± 5%, P < 0.0001) and 3D-ejection fraction (EF) (50 ± 8% vs. 60 ± 6%, P < 0.0001). In HTx patients, echocardiographic RV systolic function was significantly correlated with NYHA-class (3D-RVEF: r = -0.62, P < 0.0001; RV-FW-GLS: r = -0.41, P = 0.0009) and cardiac allograft vasculopathy (3D-RVEF: r = -0.42, P = 0.0005; RV-FW-GLS: r = -0.25, P = 0.0444). RHC demonstrated a good correlation between invasively assessed resting RV-stroke volume index and exercise capacity (r = 0.58, P < 0.0001) and NYHA-class (r = -0.41, P = 0.0009). RV systolic function is reduced in HTx patients compared with controls. 3D RVEF and 2D longitudinal deformation analyses are associated with clinical performance in stable HTx patients and seem suitable in noninvasive routine right heart function evaluation after HTx. Invasively assessed RV systolic reserve was strongly associated with exercise capacity.
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 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 | 0.000 | 0.001 |
| 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) | 0.000 | 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".