Low immunoglobulin levels affect the course of COPD in hospitalized patients
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) affects up to 10% of Canadians. Patients with COPD may present with secondary humoral immunodeficiency as a result of chronic disease, poor nutrition or frequent courses of oral corticosteroids; decreased humoral immunity may predispose these patients to mucosal infections. We hypothesized that decreased serum immunoglobulin (Ig) levels was associated with the severity of an acute COPD exacerbations (AECOPD). METHODS: A prospective study to examine cardiovascular risks in patients hospitalized for AECOPD, recruited patients on the day of hospital admission and collected data on length of hospital stay at index admission, subsequent emergency department visits and hospital readmissions. Immunoglobulin levels were measured in serum collected prospectively at recruitment. RESULTS: Among the 51 patients recruited during an admission for AECOPD, 14 (27.5%) had low IgG, 1 (2.0%) low IgA and 16 (31.4%) low IgM; in total, 24 (47.1%) had at least one immunoglobulin below the normal range. Patients with low IgM had longer hospital stay during the index admission compared to patients with normal IgM levels (6.0 vs. 3.0 days, p = 0.003), but no difference in other clinical outcomes. In the whole cohort, there was a negative correlation between serum IgM levels and length of hospital stay (R = - 0.317, p = 0.024). There was no difference in clinical outcomes between subjects with normal and low IgG levels. CONCLUSION: In patients presenting with AECOPD, low IgM is associated with longer hospital stay and may indicate a patient phenotype that would benefit from efforts to prevent respiratory infections. Trial registration statement: Retrospectively registered.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".