Hemosiderin in sputum macrophages may predict infective exacerbations of chronic obstructive pulmonary disease: a retrospective observational study
Bibliographic record
Abstract
BACKGROUND: Infective exacerbations of COPD are common and are accompanied by neutrophilic bronchitis in sputum. Increased respiratory iron content has been associated with respiratory tract infection, though it is unclear if this represents a predisposing factor for infection or the sequelae of inflammation. Iron overload, as assessed in the airways, may be an important biomarker for recurrent infective exacerbations of COPD. The purpose of our study was to determine if hemosiderin in sputum macrophages is related to infective exacerbations of COPD. METHODS: We undertook a retrospective observational study of 54 consecutive patients who presented with an exacerbation of COPD and had sputum examined including assessment for hemosiderin in alveolar macrophages. The relation between infective exacerbations in the previous two years and the percent of hemosiderin-positive macrophages was analyzed with linear regression. To account for the non-parametric distribution of infective exacerbations, negative binomial regression modelling was used to account for other covariates. RESULTS: The percent of hemosiderin positive alveolar macrophages (hemosiderin index), analyzed parametrically and non-parametrically, demonstrated a significant correlation with increasing numbers of infective exacerbations in the previous two years. In a multivariate regression analysis, hemosiderin index was an independent predictor of infective exacerbations. COPD patients with raised hemosiderin index (≥20%) had higher levels of sputum IL-6 compared to patients with lower levels (<20%). CONCLUSIONS: High hemosiderin index in sputum alveolar macrophages measured at the time of AECOPD may be related to the frequency of infective exacerbations of COPD.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".