Intravenous immunoglobulin‐induced haemolysis: a case report and review of the literature
Bibliographic record
Abstract
OBJECTIVES: To review the incidence and clinical features of intravenous immunoglobulin (IVIg)-induced haemolysis. BACKGROUND: Haemolysis can be a severe complication of IVIg administration. It is due to the passive transfer of blood group antibodies and may result in significant anaemia and renal failure. METHODS: We report a case of severe IVIg-induced haemolysis; review the data reported to vigilance groups (The Medicines and Healthcare Products Regulatory Agency, European Union Drug Regulatory Authorities, Food and Drug Administration and the Canada Vigilance Centre) between January 1998 and May 2012; and systematically review IVIg-induced haemolysis case reports (between January 1948 and January 2013). RESULTS: Nine hundred-twenty five cases of IVIg-induced haemolysis were identified from a review of cases reported to vigilance groups; 62 case reports were included in the systematic review. The majority of these were due to administration of doses of at least 2 g kg(-1) of IVIg (97%). IVIg-induced haemolysis was reported most commonly for patients with blood group A (65%) or AB (26%). One case report noted that in two patients with IVIg-induced haemolysis both received IVIg from the same batch. CONCLUSION: We make the following recommendations for the management of suspected cases of IVIg-induced haemolysis: Stop IVIg infusion and perform tests for haemolysis. Check titres of anti-blood group antibodies in IVIg. Provide supportive management for patient with fluid and/or red blood cell transfusions if necessary. Consider quarantine of the IVIg batch if found to be high titre for anti-A/B. Report reaction to regulatory/vigilance body.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".