Impact of serial measurements of tricuspid annular plane systolic excursion on mortality and morbidity after heart transplantation
Bibliographic record
Abstract
The impact of right ventricular (RV) dysfunction on long-term post-HTx outcomes remains uncertain. We assessed the impact of serial measurements of Tricuspid Annular Plane Systolic Excursion (TAPSE) on post-HTx mortality and morbidity. This two-center retrospective cohort study included consecutive adult HTx recipients (2000-2017). We used multivariable extended hazard regression models to evaluate the association between TAPSE and left ventricular ejection fraction (LVEF), entered as time-dependent variables, and all-cause mortality, cardiac allograft vasculopathy (CAV), acute cellular rejection (ACR), and chronic kidney disease (CKD). TAPSE was modelled using cubic splines. We included 485 HTx recipients (9461 TAPSE measurements), median (25th- 75th percentile) 19 (10-27) mm; median age was 52 (41-59) years, and 71.3% were male. During a follow-up of 6.7 (3.0-10.8) years, 92 patients died, 225 had ACR >2R, 234 CAV, and 91 CKD. By multivariable analysis, for each 1-mm decrease in patients with a TAPSE value <15mm, mortality increased by 22% (P<.001). For the average HTx recipient with a TAPSE of 15mm, 10mm, and 6mm, 1-year mortality was 3%, 7%, and 17%, and 5-year mortality was 8%, 20%, and 43%, respectively. Reduced TAPSE was significantly associated with increased CAV but notACR and CKD. A decrease in TAPSE below 15mm represents clinically significant graft dysfunction, warranting close monitoring.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".