Bronchiectasis and immunosuppression: a single-center analysis.
Bibliographic record
Abstract
Bronchiectasis is a chronic respiratory disease characterized by abnormal and permanent dilation of portions of the bronchial tree, leading to mucus accumulation and the frequent development of bronchitis and pneumonia. Immunosuppression is one of the factors that can lead to the development of bronchiectasis. Therefore, we attempted to identify whether the group of immunosuppressed bronchiectasis patients exhibits distinctive characteristics in terms of severity, exacerbations, colonizations, hospitalizations, or functional decline. We have analyzed bronchiectasis patients classified as having immunodeficiency, rheumatologic or inflammatory bowel diseases, or those on chronic steroid therapy (e.g. prednisone 2.5 mg/die for at least 4 weeks per year), who are under routine follow-up at our center to identify potential specific characteristics compared to non-immunosuppressed patients. A total of 166 patients with bronchiectasis were considered, of whom 32 were classified as immunosuppressed. The chi-square p-value was calculated to determine whether the difference between the two distributions was statistically significant. No differences were observed between the two groups in terms of exacerbation frequency, hospitalizations, colonizations, isolations, or functional decline. However, regarding bronchiectasis severity, as assessed by the Bronchiectasis Severity Index (BSI), a higher proportion of patients with severe bronchiectasis (BSI > 9) was noted in the non-immunosuppressed group (41.04% vs. 37.50%, p-value 0.0001). Stratifying patients with bronchiectasis based on their characteristics and comorbidities could lead to a better classification of those at higher risk of developing greater disease severity.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".