Assessment of humoral immune function in chronic obstructive pulmonary disease (COPD) patients
Bibliographic record
Abstract
Background: Patients with acute exacerbations of COPD (AECOPD) and humoral immunodeficiency are predisposed to similar recurrent, respiratory infections; indicating that antibody dysfunction may underlie AECOPD. Typhim Vi vaccine is a polysaccharide vaccine, and its response can be used to measure humoral immune function. Aims: We aim (i) to determine the presence and prevalence of humoral dysfunction in COPD with ≥1 AECOPD in the past year and (ii) its relationship with AECOPD frequency, using a Typhim vaccine test. Methods: Pre- and post-immunization anti-typhi IgG titers were quantified by the VaccZymeTM ELISA from 11 COPD patients (GOLD standard, ≥1 AECOPD, no malignancies or immunodeficiencies). Patients were grouped into responders and non-responders (≤2-fold post: pre-IgG). Results: To date, 11 AECOPD patients have been evaluated (mean age 69.18, 5 females). 5 of 11 (45%) patients were non-responders. Mean number of exacerbations per year was 3.20±1.79 for non-responders and 1.33±1.50 for responders. Higher St. George9s Respiratory Questionnaire scores (Spearman, ρ=-0.52, p<0.05) and older age (ρ=-0.59, p<0.05) were moderately correlated with lower post: pre-immunization IgG fold change. There were no statistical differences regarding COPD Assessment Test scores (ρ=0.13), smoking history (ρ=0.18), and Ig subtypes (IgG ρ=0.19, IgA ρ=-0.02, IgE ρ=0.50, IgM ρ=-0.05). Conclusion: Inadequate antibody response has been observed in some COPD patients (5/11 sample size), specifically those with more exacerbations, lower quality of life, and advanced age. Anti-typhi IgG response may be a biomarker for COPD phenotyping. Further investigation in a larger patient cohort is underway.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".