The Delayed-Release Combination of Doxylamine and Pyridoxine (Diclegis®/Diclectin®) for the Treatment of Nausea and Vomiting of Pregnancy
Bibliographic record
Abstract
Nausea and vomiting of pregnancy (NVP) affects up to 85 % of all pregnancies. Effective treatment can greatly improve a woman's quality of life, reduce the risk for maternal and fetal complications, and reduce healthcare costs. Unfortunately, many women receive either no pharmacological treatment or are recommended therapies for which fetal safety and efficacy have not been established. First-line treatment of NVP, as recommended by several leading healthcare and professional organizations, is the combination of doxylamine and pyridoxine. This combination, formulated as a 10 mg/10 mg delayed-release tablet, was approved by the US Food and Drug Administration (FDA) for the treatment of NVP in April 2013 under the brand name Diclegis(®), and has been on the Canadian market since 1979, currently under the brand name Diclectin(®). The efficacy of Diclegis(®)/Diclectin(®) has been demonstrated in several clinical trials, and, more importantly, studies on more than 200,000 women exposed to doxylamine and pyridoxine in the first trimester of pregnancy have demonstrated no increased fetal risk for congenital malformations and other adverse pregnancy outcomes. The present review aims to present the scientific evidence on the effectiveness and fetal safety of Diclegis(®)/Diclectin(®) for the treatment of NVP to justify its use as first-line treatment for NVP.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".