Acquired low immunoglobulin levels and risk of clinically relevant infection in adult patients with systemic lupus erythematosus: a cohort study
Bibliographic record
Abstract
OBJECTIVE: Infection is a leading cause of death in the SLE population. Low immunoglobulin levels might be a potential risk for infection. We aimed to assess whether acquired low levels of any type of immunoglobulin increase the risk of clinically relevant infection in adult patients with SLE. METHODS: We compared adult SLE patients who had acquired any low immunoglobulin levels (IgA, IgM or IgG) for 2 years with patients with normal or high levels with respect to clinically relevant infection (defined as infections requiring intravenous or oral antibiotics) in a prospective cohort study. Group balance was achieved using propensity score adjustment, matching and inverse probability weighting. Primary analysis was time to event using Cox-regression modelling adjusting for potential confounders. Sensitivity analyses were conducted to examine several exposure and outcome definitions. RESULTS: Patients with hypogammaglobulinaemia had longer disease duration, more lupus nephritis history, higher proteinuria and more accumulated damage. Low IgA level was associated with increased risk of clinically relevant infection [hazard ratio (HR): 2.24, 95% CI: 1.61, 3.12] while low IgG (HR: 1.15, 95% CI: 0.84, 1.59) or low IgM (HR: 0.95, 95% CI: 0.73, 1.23) was not. Low immunoglobulin recovery in the first year was 2.5% (11), second year 8.2% (36), third year 10.1% (44) and fourth year 18.4% (80), and 60% (263) of acquired hypogammaglobulinaemia recovered over 4 years. CONCLUSION: The majority of acquired hypogammaglobulinaemia in adult patients with SLE is transient. Only low acquired IgA was associated with increased risk of infection among adult patients with SLE. Whether immunoglobulin replacement provides additional protective effect requires further investigation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".