Child neurodevelopment following treatment for nausea and vomiting of pregnancy with diclectin: A prospective controlled study
Bibliographic record
Abstract
Background Nausea and vomiting of pregnancy (NVP) occurs in 80% of women, may lead to Hyperemesis Gravidarum (HG). The only antiemetic approved by Health Canada for NVP is Diclectin (doxylamine and vitamin B6). Diclectin does not cause fetal dysmorphology, its effects on the developing central nervous system (CNS) remains to be established. Potential adverse effects of the drug on fetal CNS may constitute a serious public health issue. Objectives To assess whether children prospectively collected exposed in utero to NVP and Diclectin and tested with formal psychological tests are different from children exposed only to NVP, and from children not exposed to NVP, Diclectin, and other teratogens. Methods A prospective, controlled assessment 3 groups of mother-child pairs exposed to NVP and Diclectin (n=41), exposed to NVP (n=37) and unexposed to NVP or teratogens (n=30). We compared the neuro-cognitive outcomes, language, and measures of child behavior among the 3 groups. Results There were no significant differences between the groups in Global IQ percentile (79.4±20.5; 73.1±23.1; 73.4±27.3), total percentile of PLS-4 (80.4±28.5; 73.9±19.3; 76.5±24.1) and CPRS-R-L scores (48.4±7.7;50.3±9.1;49.2±8.5). Conclusions Exposure to Diclectin does not adversely affect neuro-cognitive development of early school children. When indicated, Diclectin therapy should be instituted to prevent HG, and improve pregnant women life style. Clinical Pharmacology & Therapeutics (2005) 77, P28–P28; doi: 10.1016/j.clpt.2004.11.109
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".