Variations in Tacrolimus Whole Blood Concentrations During Pregnancy and Its Implications for Therapeutic Drug Monitoring: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Objectives Tacrolimus is a pregnancy-compatible immunosuppressive increasingly used in systemic lupus erythematosus (SLE) pregnancies. Physiological changes throughout pregnancy alters the whole blood concentrations of tacrolimus during gestation. However, data is very limited to guide clinicians caring for pregnant women receiving tacrolimus in interpreting tacrolimus trough levels and adjusting the dosage. We completed a systematic review focusing on the variations of maternal tacrolimus trough levels and dosage during SLE and non-SLE pregnancies. Methods Using a combination of relevant search terms and keywords, we systematically searched Embase, Ovid, PubMed, Web of Science and Cochrane Library up to January 2024. All observational studies which measured whole blood tacrolimus trough levels during pregnancy were included without language or date restriction. Random-effects models were used to estimate standardized mean differences (SMD) or mean differences (MD), with 95% confidence intervals (CI) of tacrolimus trough levels and doses before, during and after pregnancy. Results Of 404 publications identified, 282 were screened based on title and abstract, of which 53 full-text articles were assessed for eligibility. Eighteen articles were included in the systematic review and 13 in the meta-analysis. Only 2 studies assessed tacrolimus levels in SLE pregnancies, while the remainder were in pregnant organ transplant recipients. Tacrolimus levels significantly decreased during pregnancy compared to pre-pregnancy (SMD −1.05; 95% CI −1.72, −0.37) and significantly increased in the postpartum compared to levels during gestation (SMD 0.87; 95% CI 0.37, 1.37) (Figure 1). Mean differences in tacrolimus trough levels were −1.56 ng/ml (95% CI −2.82, −0.31) between first trimester and before pregnancy, −0.49 ng/ml (95% CI −1.04, −0.07) between second and first trimesters, 0.63 ng/ml (95% CI 0.30, 0.96) between third and second trimesters, and 1.28 ng/ml (95% CI 0.60, 1.96) between the postpartum and third trimesters. The variation in tacrolimus levels during pregnancy was usually addressed by increasing the dose during pregnancy vs pre-pregnancy (MD 1.35 mg/day, 95% CI 0.23, 2.48) and decreasing the dose in the postpartum vs pregnancy (MD −0.92 mg/day; 95% CI −1.8, −0.01) (Figure 1). Figure 1. (A) Forest plot of the standardized mean difference between tacrolimus whole blood concentrations during pregnancy (second or third trimester) and before pregnancy. (B) Forest plot of the standardized mean difference between tacrolimus whole blood concentrations in the post-partum and during pregnancy (second or third trimester). (C) Forest plot of the mean difference in mg/day between tacrolimus doses during pregnancy (second or third trimester) and before pregnancy. (D) Forest plot of the mean difference in mg/day between tacrolimus doses in the post-partum and during pregnancy (third trimester). Conclusion Tacrolimus blood levels decrease during the first and second trimesters, then return to pre-pregnancy levels in the postpartum. Pregnancy often requires increased tacrolimus doses to keep trough levels within therapeutic ranges. Higher dosages might increase the bio-effective tacrolimus fraction, raising safety concerns about dose augmentation during pregnancy. More research is necessary to help clinicians adjust tacrolimus in SLE and non-SLE pregnancies to ensure optimal therapeutic drug monitoring in high-risk groups.
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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 | 0.013 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".