A Role for Alveolar Exhaled Nitric Oxide Measurement in the Diagnosis of Hepatopulmonary Syndrome
Bibliographic record
Abstract
GOALS: The authors sought to characterize predominantly alveolar exhaled nitric oxide (eNO) in hepatopulmonary syndrome (HPS) compared with non-HPS, changes after liver transplantation, and diagnostic properties. BACKGROUND: HPS is defined by liver disease, intrapulmonary vascular dilatations (IPVDs), and hypoxemia. Rat models and small human studies suggest that NO overproduction may cause IPVDs. STUDY: A retrospective review of the Canadian HPS Database (2007 to 2017) and prospective eNO measurement (main outcome) in healthy controls (measurement expiratory flow, 200 mL/s). HPS was defined as: (1) liver disease; (2) contrast echocardiography consistent with IPVDs; and (3) partial pressure of arterial oxygen <70 mm Hg with alveolar-arterial gradient >20 mm Hg; subclinical HPS as criteria (1) and (2) only; and no HPS as criterion (1) only. Current smokers and subjects with asthma or pulmonary hypertension were excluded. A linear mixed effects model was used to compare eNO between groups and before and after transplantation. RESULTS: eNO was 10.4±0.7 ppb in HPS (n=26); 8.3±0.6 ppb in subclinical HPS (n=38); 7.1±1.0 ppb in no HPS (n=15); and 5.6±0.7 ppb in controls (n=30) (P<0.001). eNO decreased from 10.9±0.8 ppb preliver to 6.3±0.8 ppb postliver transplant (n=6 HPS, 6 subclinical HPS) (P<0.001). eNO <6 ppb was 84.4% (73.1% to 92.2%) sensitive and ≥12 ppb was 78.1% (69.4% to 85.3%) specific for HPS (vs. subclinical HPS). CONCLUSIONS: HPS subjects have higher alveolar eNO than non-HPS subjects, levels normalize with liver transplantation. Applying eNO cutoff values may aid in HPS diagnosis.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".