Densitometric and Functional Progression in Patients with Alpha-1 Antitrypsin Deficiency Genotype SZ
Bibliographic record
Abstract
Smoking is a key determinant of chronic obstructive pulmonary disease (COPD) development in patients with the SZ genotype. Few studies have evaluated the impact of other factors associated with emphysema progression. Objectives: To evaluate the progression of lung function and densitometric parameters in PiSZ alpha-1 antitrypsin deficiency (AATD) patients, and to assess the impact of smoking, exacerbation frequency, severity and time since diagnosis. The study also explores correlations between functional and densitometric measures, as well as regional emphysema patterns. Methods: This two-year observational study included 31 PiSZ AATD patients stratified by time since diagnosis (<5 vs. ≥5 years), smoking status (current, former, and never smokers), and exacerbation frequency (<2 vs. ≥2 exacerbations/year). Functional [forced expiratory volume in 1 s (FEV1), carbon monoxide diffusion (DLCO), and carbon monoxide transfer coefficient (KCO)] and densitometric [15th percentile lung density (PD-15) and lung volume with density less than -950 Hounsfield Units (HU-950)] parameters were assessed at baseline and follow-up. Mixed-effects models evaluated disease progression, while correlation and regional analyses highlighted structural–functional relationships and spatial emphysema patterns. Results: Patients diagnosed <5 years previously exhibited faster PD-15 decline (−6.0 ± 1.4 HU/year) than those diagnosed ≥5 years previously (−5.1 ± 1.3 HU/year; p < 0.05). Current smokers showed the most pronounced deterioration in PD-15 (−7.1 ± 1.6 HU/year) and HU-950 (+0.8 ± 0.3% volume/year) versus never smokers (−4.6 ± 1.3 HU/year and +0.4 ± 0.2% volume/year; p < 0.05). Frequent and severe exacerbations, along with pulmonary-related hospitalizations, worsened structural decline, particularly in basal regions. Strong correlations between both PD-15 and HU-950 with FEV1, DLCO, and KCO were observed in advanced stages (≥5 years since diagnosis). Conclusions: This study underscores the pivotal role of densitometry in PiSZ AATD, highlighting its ability to detect early structural changes often missed by functional measures. These findings support integrating densitometry into clinical practice to guide personalized interventions and improve outcomes.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".