Intravenous Immunoglobulins as Adjunct Treatment to Phototherapy in Isoimmune Hemolytic Disease of the Newborn: A Retrospective Case-Control Study
Bibliographic record
Abstract
BACKGROUND: Isoimmune hemolytic disease is a major cause of neonatal severe indirect hyperbilirubinemia that requires phototherapy or exchange transfusion which is an invasive procedure to avoid brain injury. Administration of intravenous immunoglobulin (IVIG) is used as an adjunct treatment to phototherapy in order to decrease the rate of exchange transfusion. METHODS: This retrospective case-control study aimed to describe the safety and efficacy of IVIG therapy in newborns with isoimmune hemolytic disease and to compare their clinical outcomes to those of a control group who were treated only with phototherapy. Criteria for IVIG treatment were variable; when phototherapy threshold was reached or when exchange transfusion level was approached, using either indication is based on the attending discretion. RESULTS: Ninety-four infants were included in the IVIG group, compared to 108 infants in the control group. Most of the included infants were term infants and most common cause was ABO incompatibility. There were no side effects documented in all the included infants. The IVIG group had more severe hemolysis with average highest bilirubin of 14.6 ± 3.7 mg/dL in the IVIG group versus 12.6 ± 3 in the control group (P = 0.0001). Complication of hemolysis was seen more in the IVIG group with higher rate of rebound hyperbilirubinemia, blood transfusion and exchange transfusion. CONCLUSIONS: IVIG use as an adjunct treatment to phototherapy in isoimmune hemolytic disease of the newborns is safe. The favorable results of the phototherapy only group were supportive of using selective criteria for administration of IVIG in neonates with isoimmune hemolytic disease.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".