Corticosteroids compared with intravenous immunoglobulin for the treatment of immune thrombocytopenia in pregnancy
Bibliographic record
Abstract
Treatment options for immune thrombocytopenia (ITP) in pregnancy are limited, and evidence to guide management decisions is lacking. This retrospective study of singleton pregnancies from 2 tertiary centers compared the effectiveness of intravenous immunoglobulin (IVIg) and corticosteroids in treatment of ITP. Data from 195 women who had 235 pregnancies were reviewed. Treatment was not required in 137 pregnancies (58%). Of the remaining 98 pregnancies in 91 women, 47 (48%) were treated with IVIg and 51 were treated with corticosteroids as the initial intervention. Mean maternal platelet count at birth did not differ between groups (IVIg 69 × 10(9)/L vs corticosteroids 77 × 10(9)/L; P = .71) nor did the proportion of mothers who achieved a platelet count response (IVIg 38% vs corticosteroids 39%; P = .85). There were no fatal or severe maternal, fetal, or neonatal hemorrhages. Of 203 neonates in whom platelet counts were available, 56 (28%) had a birth platelet count <150 × 10(9)/L and 18 (9%) had platelet counts <50 × 10(9)/L. Nadir platelet counts for most affected neonates occurred at birth, although for some neonates, nadir platelet counts occurred up to 6 days postnatally. Intracranial hemorrhage was noted in 2 neonates (nadir platelet counts were 135 and 18 × 10(9)/L). There were no neonatal deaths. The majority of pregnant women with a history of ITP did not require treatment, and neonatal outcomes were comparable for mothers who received IVIg or corticosteroids for treatment of maternal ITP.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".