The effects of pregnancy on the pharmacokinetics of infliximab and adalimumab in inflammatory bowel disease
Bibliographic record
Abstract
BACKGROUND: Transplacental transfer of infliximab and adalimumab results in detectable drug levels in the cord blood and infant. AIM: To determine if pregnancy influenced the pharmacokinetics of anti-TNF agents in women with inflammatory bowel disease. METHODS: Twenty-five women from the University of Calgary inflammatory bowel disease(IBD) pregnancy clinic on maintenance infliximab or adalimumab were recruited prospectively with serum bio-banking performed each trimester. Infliximab trough and adalimumab steady-state levels were the outcomes of interest and were analysed using the ANSER infliximab and adalimumab assays. Multivariate linear mixed-effects models were constructed to assess infliximab and adalimumab drug levels during pregnancy adjusting for the clinical covariates of albumin, BMI and CRP. RESULTS: Fifteen women (eight Crohn's disease, seven ulcerative colitis) received infliximab and 10 women with 11 pregnancies were treated with adalimumab. Median age was 29.6 years (IQR: 27.6-31.2 years). Median disease duration was 9.2 years (IQR: 3.16-15.0 years). Median trough infliximab concentrations were 8.50 μg/mL (IQR: 7.23-10.07 μg/mL), 10.31 μg/mL (IQR: 7.66-15.63 μg/mL) and 21.02 μg/mL (IQR: 16.01-26.70 μg/mL) at trimesters 1, 2 and 3 respectively. Significant changes in albumin and BMI (P < 0.05) but not CRP (P > 0.05) were documented throughout pregnancy. After adjusting for albumin, BMI and CRP, infliximab trough levels increased during pregnancy, by 4.2 μg/mL per trimester (P = 0.02), while adalimumab drug levels remained stable (P > 0.05). CONCLUSIONS: Infliximab levels rise during pregnancy, whereas adalimumab levels remain stable after accounting for changes in albumin, BMI and CRP. Therapeutic drug monitoring in the second trimester may be useful in guiding dosing in the third trimester.
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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 | 0.004 | 0.016 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".