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Record W3213373125 · doi:10.1182/blood-2021-147941

Intravenous Immunoglobulin in the Management of Severe Early Onset Red Blood Cell Alloimmunization

2021· article· en· W3213373125 on OpenAlexaffabout
Evangelia Vlachodimtropoulou Koumoutsea, Tsz Kin Lo, Clarissa Bambao, Gregory A. Denomme, Gareth Seaward, Rory Windrim, Francine Tessier, Edmond Kelly, Nimrah Abbasi, Greg Ryan

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsMedicineGestationPregnancyFetusAnemiaObstetricsGestational ageBlood transfusionPediatricsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract OBJECTIVE: We report the outcome of pregnancies treated with intravenous immunoglobulin (IVIG) for severe red blood cell alloimmunization, evaluating whether IVIG defers the development of severe fetal anaemia and its consequences. BACKGROUND: Although fetal anemia can be treated very successfully with intrauterine transfusion (IUT), procedures before 20 weeks' gestation can be very challenging technically and may be hemodynamically stressful to an extremely premature and already compromised fetus. The procedure-related fetal loss rate is approximately 5.6% for IUTs performed < 20 weeks' gestation, compared to 1.6% overall. IVIG may prevent hemolysis and could therefore be a noninvasive alternative for early transfusions. STUDY DESIGN: We included consecutive pregnancies over a nineteen year period in the Fetal Medicine Unit, Mount Sinai Hospital, University of Toronto, Canada, of alloimmunized women with a history of severe early onset haemolytic disease who received IVIG until intrauterine transfusion could safely be performed. Previous untreated pregnancies were used as controls. IVIG therapy was commenced between 11 and 14 weeks' gestation. Our usual protocol was IVIG 2 g/kg per week every 3 weeks, until the first IUT could be performed. Each 2g/kg dose was administered over 2 days, 1g/kg per day, to reduce the chance of severe headaches. In three pregnancies, IVIG 1g/kg was given weekly. We compared the clinical outcomes (gestation at first IUT, fetal Hb at first FBS, gestation at delivery, perinatal survival) between previous pregnancies without IVIG and the subsequent pregnancy treated with IVIG. In comparing fetal Hb's between two pregnancies, a linear relationship between fetal Hb and gestation was used to correct for variable gestations. The fetal Hb was converted to a standardized fetal Hb value (multiples of the standard deviation [SD]). Statistical analysis was performed on 'Statistical Package for Social Science Version 16.0' (SPSS Inc, Chicago, Illinois). RESULTS: Seventeen women referred to our unit for a previous pregnancy loss secondary to severe RBC alloimmunization received IVIG treatment in 20 subsequent pregnancies; all eventually requiring intrauterine transfusion. For previous early losses despite transfusion, immunoglobulin was associated with a relative increase in fetal hemoglobin between treated and untreated pregnancies of 32.6 g/L (95%CI 15.2-50.0, P=0.003) and improved perinatal survival (8/8 vs 0/6, P=0.001). For previous losses <20 weeks, it enabled first transfusion deferral in subsequent pregnancies to at least 19.9 (mean 23.2) weeks. Of the 17 live-born babies from IVIG-treated pregnancies, three (18%) required an exchange transfusion, eight (47%) a simple "top-up" transfusion, and six (35%) phototherapy. CONCLUSION: Our results show that, among severely sensitized cases with previous early fetal loss despite IUT, use of IVIG in subsequent pregnancies is associated with a significantly higher fetal Hb before first IUT, deferral of first IUT, delivery at a later gestation and increased perinatal survival. The timing of the first FBS/IUT was delayed by 3 weeks in pregnancies treated with IVIG compared to a previous untreated pregnancy. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.207
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

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