Patterns of Antiemetic Use Among American Women With Nausea and Vomiting of Pregnancy
Bibliographic record
Abstract
INTRODUCTION: Nausea and vomiting of pregnancy is the most common condition during gestation. Over the last 30 years, there has not been a U.S. Food and Drug Administration (FDA)-approved antiemetic for nausea and vomiting of pregnancy. The objective of this study was to provide information on the pattern of antiemetic use among American women calling Motherisk NVP Helpline in Toronto, the only such service worldwide. METHODS: We reviewed the intake forms of American women calling the Helpline in the past 10 years. Clinical and demographic data with details on nausea and vomiting of pregnancy treatment, nausea and vomiting of pregnancy symptoms, and concomitant medical conditions were extracted. RESULTS: A total of 522 women were included in the study. A total of 10.3% of the women had mild, 77.7% had moderate, and 12% had severe nausea and vomiting of pregnancy. A total of 15.5% had hyperemesis gravidarum. Of all women, 28% did not receive any antiemetic although 71.4% of them had moderate and 12.9% had severe nausea and vomiting of pregnancy. A total of 42.3% was treated with one antiemetic drug, 17.2% with two, 9% with three, and 3.4% took four or more. Doxylamine was used by 57.7% of the treated women, 55.9% used ondansetron, 35.7% used other antihistamines, and 13.8% used metoclopramide. The most frequent monotherapy was doxylamine (48%) followed by ondansetron (39%). Women receiving two antiemetic drugs were mostly on a combination of ondansetron and doxylamine (35.6%), ondansetron and another antiemetic (31.1%), and doxylamine with another antiemetic (20%). CONCLUSIONS: The lack of a FDA-approved drug for nausea and vomiting of pregnancy has led American women to be treated suboptimally. Since the FDA approval of the doxylamine–pyridoxine combination (Diclegis), both physicians and women will gain more confidence in a safe and effective option.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".