A prospective observational study of the incidence, natural history, and risk factors for intravenous immunoglobulin‐mediated hemolysis
Bibliographic record
Abstract
BACKGROUND: Intravenous Immune Globulin (IVIG) is used to treat numerous immune-mediated and inflammatory conditions. There is growing awareness of hemolysis, occasionally severe, as a side-effect of this therapy. While most cases are associated with anti-A and/or anti-B isoagglutinins, the frequency and mechanism of hemolysis remain poorly characterized. STUDY DESIGN AND METHODS: A prospective observational study was conducted to determine incidence, natural history and risk factors for IVIG-mediated hemolysis. A total of 99 infusions of high-dose IVIG (2 g/kg or higher) administered to 78 non-group O patients were monitored and graded according to Canadian IVIG Hemolysis Pharmacovigilance Group. Serum ferritin and C3/C4 levels were monitored as indicators of macrophage activation and complement consumption, respectively. Supplementary investigations included assessment for ABO zygosity, Secretor status, FcR polymorphisms, eluate IgG subclass, monocyte monolayer assay, and a panel of cytokines. RESULTS: Hemolysis was observed in 32 of 99 (32%) of infusions, with 19 of 99 (19%) grade 2 or higher. Hemolysis was only apparent 5-10 days after a completed IVIG infusion in 84% of cases and was associated with increases in serum ferritin without complement-consumption. In univariate analysis, increased risk was observed in group AB patients, first-time IVIG recipients, those not taking immuosuppressive medications, or patients treated with a specific IVIG brand; however, in multivariate analysis, product association was no longer observed. No other patient- or practice-related risk factors were identified. CONCLUSION: IVIG-mediated hemolysis is common and frequently severe. Monitoring for 5-10 days following an infusion should be considered in non-O patients receiving high-dose IVIG with known risk factors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".