Isoagglutinin‐reduced immunoglobulin retains efficacy in mouse models of immune thrombocytopenia and rheumatoid arthritis and is less likely to cause intravenous immunoglobulin–associated hemolysis
Bibliographic record
Abstract
BACKGROUND: Immunoglobulin therapy including intravenous immunoglobulin (IVIg) has been used as an effective treatment for autoimmune/inflammatory conditions with few side effects. However, high-dose IVIg (1-2 g/kg) has been recognized as a cause of hemolytic anemia in non-blood group O patients. Hemolysis when observed has been due to anti-A/anti-B isoagglutinins contained in the IVIg. Recently, an isoagglutinin-reduced IVIg, whereby the anti-A and anti-B titers have been reduced by immunoaffinity chromatography, has been introduced; however, whether this new product is as efficacious as nonreduced immunoglobulin (Ig) or will result in less IVIg-associated hemolysis has not been resolved. STUDY DESIGN AND METHODS: B red blood cells, to estimate clinical significance of the IgG isoagglutinins. We also used immune thrombocytopenia (ITP) and rheumatoid arthritis (RA) mouse models to examine the in vivo efficacy of isoagglutinin-reduced versus -nonreduced Ig on the amelioration of the diseases. RESULTS: In contrast to nonreduced Ig, phagocytosis was largely absent when isoagglutinin-reduced Ig was used at a concentration equivalent to a patient receiving 2 g/kg. The in vivo efficacy of isoagglutinin-reduced versus nonreduced Ig on the amelioration of experimental ITP and RA was similar, indicating no loss of efficacy due to the chromatographic removal of isoagglutinins. CONCLUSION: Isoagglutinin-reduced Ig should have efficacy similar to nonreduced Ig and result in less IVIg-associated hemolysis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".