A two-center study on the pharmacokinetics of intravenous immunoglobulin before and during pregnancy in healthy women with poor obstetrical histories
Bibliographic record
Abstract
BACKGROUND: Despite the increasing use of intravenous immunoglobulin (IVIG) in obstetrics, information on its pharmacokinetics and optimal dosing during each trimester pregnancy is lacking. The aim of this study was to characterize IVIG pharmacokinetics in pregnant women with a history of idiopathic secondary recurrent miscarriage or obstetrical antiphospholipid syndrome and to make dosing recommendations by comparing serum immunoglobulin G (IgG) concentrations in women receiving IVIG to placebo controls, before and during pregnancy. METHODS: Women enrolled in an IVIG trial for idiopathic secondary recurrent miscarriage (n = 25) or an IVIG study for obstetrical antiphospholipid syndrome (n = 10); 22 received IVIG 0.5-1.0 g/kg and 13 received the equivalent volume of saline, every 4 weeks from pre-pregnancy until 18-20 weeks of gestation, with dosing adjusted for her weight prior to each infusion. Serum IgG concentrations were measured by rate nephelometry before and 0.5 h, and 1, 2, 3 and 4 weeks following an infusion. Sampling was performed pre-pregnancy and in the first and second trimesters. RESULTS: Area under the curve (AUC) did not differ significantly within the IVIG group between the three sampling periods. Estimated contributions of IVIG [calculated as mean AUC (IVIG group) minus mean AUC (control group)] were 4890.8 g h/l pre-pregnancy, 5591.4 g h/l first trimester and 4755.1 g h/l second trimester (P> 0.05, non-significant). For the IVIG 0.5 and 1.0 g/kg subgroups, the overall estimated contribution of exogenous IVIG was ~4000 and ~6400 g h/l, respectively. CONCLUSIONS: With a weight-adjusted dosage of IVIG, drug exposure, based on AUC calculations, was maintained at the pre-pregnancy level. Therefore, we recommend a weight-adjusted dosage of IVIG during the first and second trimesters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".