Examining the relationship between pulmonary vascular structure and function in chronic obstructive pulmonary disease: a cross-sectional analysis.
Bibliographic record
Abstract
Background: People with chronic obstructive pulmonary disease (COPD) have reduced pulmonary diffusing capacity for carbon monoxide (DLCO) compared to healthy controls, likely due to lower pulmonary capillary blood volume (Vc) or membrane diffusing capacity (Dm). Previous work has shown reduced pulmonary vascular volumes measured by computed tomography (CT) in COPD compared to controls. The purpose of this study was to explore the potential associations between CT measured pulmonary vascular structure with DLCO, Vc and Dm. We hypothesized that those with greater pulmonary vascular volumes would show higher DLCO, Vc and Dm. Methods: Day 1: Enrollment and pulmonary function test. Day 2: Chest CT scan to quantify emphysema severity, total vessel volume (TVV), volume of vessels with a cross-sectional area <5mm2 (BV5), and between 5-10mm2 (BV5-10). Day 3: Multiple fraction of inspired O2 DLCO technique to determine Vc and Dm. Potential associations were evaluated by Pearson correlation. Results: To date, 35 people with COPD (18 females, mean FEV1 65±16% predicted; 69±7 years) have been recruited. DLCO adjusted for alveolar volume was correlated with TVV (r= 0.55, p<0.001), BV5 (r=0.47, p=0.006) and BV5-10 (r=0.48, p=0.004). Exploratory analyses revealed that among CT variables, Dm was associated with BV5-10 (r=0.46, p=0.006) and TVV (r=0.37, p=0.03), while Vc was not associated with any CT pulmonary vascular measurements. Conclusions: Our results suggest that DLCO and Dm are related to CT-measured pulmonary vascular volumes in COPD; supporting an association between pulmonary vascular function and structure.
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 | 0.002 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".