Insulin Glargine Safety in Pregnancy
Bibliographic record
Abstract
OBJECTIVE: Insulin glargine (Lantus) is an extended-action insulin analog with greater stability and duration of action than regular human insulin. The long duration of action and decreased incidence of hypoglycemia provide potential advantages for its use in pregnancy. However, the placental pharmacokinetics of insulin glargine have not been studied. Therefore, the objective of this study was to determine whether insulin glargine crosses the human placenta using the human perfused placental lobule technique. RESEARCH DESIGN AND METHODS: Placentae were obtained with informed consent after elective cesarean section delivery of noncomplicated term pregnancies. Insulin glargine, at a therapeutic concentration of 150 pmol/l (20 microU/ml) was added to the maternal circulation. Additional experiments were carried out at insulin glargine concentrations 1,000-fold higher than therapeutic levels (150, 225, and 300 nmol/l). A subsequent perfusion for which the maternal circuit remained open and insulin glargine was continuously infused at 150 pmol/l was completed for further confirmation of findings. The appearance of insulin glargine in the fetal circulation was analyzed by a chemiluminescence immunoassay. RESULTS: Results from perfusions carried out at therapeutic concentrations (150 pmol/l) of insulin glargine showed no detectable insulin glargine in the fetal circuit. After perfusion with very high insulin glargine concentrations of 150, 225, and 300 nmol/l, the rate of transfer remained low at 0.079 +/- 0.01, 0.14, and 0.064 pmol . min(-1) . g tissue(-1), respectively. CONCLUSIONS: Insulin glargine, when used at therapeutic concentrations, is not likely to cross the placenta.
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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 | 0.002 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".