Impact of Left Ventricular Diastolic Dysfunction on Lung Transplantation Outcome in Patients With Pulmonary Arterial Hypertension
Bibliographic record
Abstract
Diastolic dysfunction may influence perioperative outcome, early graft function, and long-term survival. We compared the outcomes of double lung transplantation (DLTx) for patients with pulmonary arterial hypertension (PAH) with preoperative left ventricular (LV) diastolic dysfunction with the outcomes of patients without diastolic dysfunction. Of 116 consecutive patients with PAH (who underwent transplantation between January 1995 and December 2013), 44 met our inclusion and exclusion criteria. Fourteen (31.8%) patients with diastolic dysfunction pretransplantation had a higher body mass index (29 [IQR 21.5–32.6] vs 22.4 [IQR 19.9–25.3] kg/m 2 ) and mean pulmonary arterial pressure (54.6 ± 10 mmHg vs 47 ± 11.3 mmHg) and right atrial pressure (16.5 ± 5.2 mmHg vs 10.6 ± 5.2 mmHg). The patients received extracorporeal life support more frequently (33% vs 7% [p = 0.02]), had worse APACHE II scores (21.7 ± 7.4 vs 15.3 ± 5.3 [p = 0.02]), and a trend toward worse ventilator-free days (2.5 [IQR 6.5–32.5] vs 17 [IQR 3–23] [p = 0.08]). There was no effect on development of primary graft dysfunction or intensive care unit/hospital survival. One-year survival was worse (hazard ratio [HR] 4.45, 95% confidence interval [CI] 1.3–22, p=0.02). Diastolic dysfunction was the only variable that correlated with overall survival (HR 5.4, 95% CI 1.3–22, p=0.02). Diastolic dysfunction leads to early postoperative morbidity and worse survival in patients with PAH after DLTx.
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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 | 0.003 |
| 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 | 0.001 | 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".