Bronchiectasis but not emphysema is more prevalent in non-PiZ alpha-1 antitrypsin deficiency (AATD) COPD than in usual COPD
Bibliographic record
Abstract
Bronchiectasis (BE) is associated with PiZ phenotypes of AATD. An association with non-PiZ phenotypes (SS, MS, MZ) is less certain. We wished to conduct a case-control study of BE prevalence among SS, MS and MZ genotypes vs. usual COPD. 16 subjects with non-PiZ phenotypes (NZ) (3 SS, 8 MS, 5 MZ) from community COPD screening for AATD had undergone chest CT scans. They were compared with 16 age, sex and FEV 1 matched COPD patients with AAT levels<1.15g/L but MM genotype (MM) and 16 similarly matched COPD patients with serum AAT levels≥1.15g/L and not genotyped (NG). Spirometry, lung volumes and diffusing capacity (D Lco ) were measured within 5.9±5.2SD months of imaging. CT scans were read for BE using a visual grading system. Lung emphysema on CT scan was determined using Airway Inspector (www.airwayinspector.org) to measure lung %area<-950HU (LAA%). Group differences between continuous variables were determined with ANOVA and proportions with z-statistic. Gender was M30:F18, age 70±18 years (mean±SD), smoking history 47±26 pack-years, FEV 1 68±23 %predicted and FEV 1 /FVC 55±13 % in the 48 subjects. Serum AAT levels were NZ 0.89±0.01SE g/L, MM 0.90±0.05 and NG 1.59±0.07. BE on CT scan occurred in 13/16 NZ (3/3 SS, 6/8 MS, 4/5 MZ), 4/16 MM (p=0.00071) and 5/16 NG (p=0.00219). Groups were similar for spirometry, lung volumes and D Lco . LAA% did not differ between groups (NZ 12.3±3.7SE, MM 12.0±2.7, NG 11.0±3.2, p=0.97). In this small group of COPD patients, BE was present more often in non-PiZ phenotype AATD subjects than MM genotype subjects, or COPD subjects with normal serum AAT levels. This may be a novel observation requiring confirmation in larger populations.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".