Possible mechanisms for intravenous immunoglobulin–associated hemolysis: clues obtained from review of clinical case reports
Bibliographic record
Abstract
BACKGROUND: Intravenous immunoglobulin (IVIG) is an efficacious treatment modality for a number of conditions and is usually well tolerated with few reports of serious adverse events; however, the administration of IVIG may occasionally result in clinically significant hemolysis. STUDY DESIGN AND METHODS: The literature was reviewed for case reports and case series of IVIG-associated hemolysis. The cases were scrutinized for clues as to the possible mechanism(s) of the hemolysis. RESULTS: Review of the 129 individual cases reported in the literature identifies clinical features shared by the majority of patients. These features included non-O blood group patients and treatment with high-dose IVIG as an immune-modulating agent for an underlying inflammatory or immune-mediated disorder. Other patient factors such as secretor phenotype, soluble ABH substance, and Fcgamma receptor polymorphisms may also play a role. CONCLUSIONS: It is known that high-dose IVIG given to non-O blood group patients with underlying inflammatory and/or immune-mediated disorders is associated with increased risk of hemolysis. This review reveals additional patient characteristics in cases of IVIG-associated hemolysis, including underrepresentation of D- and group B cases, higher incidence in pediatric Kawasaki disease and unique at-risk patient groups including allogeneic stem cell transplant recipients with group A donor in a group O recipient, and patients in whom soluble AB substance is removed by plasma exchange at the same time as receiving IVIG.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".