Late-breaking abstract: HRCT comparisons of tobacco smoking (TS-COPD) and biomass smoke induced COPD (BS-COPD) phenotypes from an Indian rural setting
Bibliographic record
Abstract
Although biomass smoke associated COPD (BS- COPD) is highly prevalent in India and other developing countries, there is paucity of knowledge whether this COPD is morphologically similar or different from tobacco-smoke associated COPD (TS-COPD). Aim: To compare lung-HRCT patterns of BS-COPD with that of TS-COPD and healthy subjects. Method: Inspiratory and expiratory axial HRCT images were obtained from 42 BS-COPD, 38 TS-COPD, 20 healthy biomass exposed ( BS-Healthy) and 14 Healthy-smokers (TS-Healthy) subjects from a rural setting in India. Lung abnormalities were evaluated at the parenchymal and airway levels using visual semi-quantitative scoring of HRCT morphology by two independent experienced radiologist. The parenchymal patterns were scored at a lobar level to the nearest 5%, and the airways abnormalities were graded on a four point scale. Results: Compared to TS-COPD, subjects with BS-COPD had significantly lower mean sum emphysema scores (265.±343 vs 40±70, p<0.001), and significantly higher mean "low attenuation area" (LAA) scores (479±233 vs 279±238, p=0.004). "Bronchial wall thickening scores " and "tree in bud scores" were similar in TS-COPD and BS-COPD (p>0.05). The Mean sum emphysema scores and LAA scores amongst TS-Healthy and BS-healthy were significantly lower than TS-COPD and BS-COPD ( both p<0.05), with no significant differences between the healthy groups(p<0.05) Conclusion: Indian subjects with BS-COPD had lower emphysema but higher air-trapping compared to TS-COPD, suggesting primarily a small airway pathology.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".