Attention-deficit/hyperactivity disorder in pregnancy and the postpartum period
Bibliographic record
Abstract
Attention-deficit/hyperactivity disorder is a childhood-onset neurodevelopmental disorder that frequently persists into adulthood with 3% of adult women having a diagnosis of attention-deficit/hyperactivity disorder. Many women are diagnosed and treated during their reproductive years, which leads to management implications during pregnancy and the postpartum period. We know from clinical practice that attention-deficit/hyperactivity disorder symptoms frequently become challenging to manage during the perinatal period and require additional support and attention. There is often uncertainty among healthcare providers about the management of attention-deficit/hyperactivity disorder in the perinatal period, particularly the safety of pharmacotherapy for the developing fetus. This guideline is focused on best practices in managing attention-deficit/hyperactivity disorder in the perinatal period. We recommend (1) mitigating the risks associated with attention-deficit/hyperactivity disorder that worsen during the perinatal period via individualized treatment planning; (2) providing psychoeducation, self-management strategies or coaching, and psychotherapies; and, for those with moderate or severe attention-deficit/hyperactivity disorder, (3) considering pharmacotherapy for attention-deficit/hyperactivity disorder, which largely has reassuring safety data. Specifically, providers should work collaboratively with patients and their support networks to balance the risks of perinatal attention-deficit/hyperactivity disorder medication with the risks of inadequately treated attention-deficit/hyperactivity disorder during pregnancy. The risks and impacts of attention-deficit/hyperactivity disorder in pregnancy can be successfully managed through preconception counselling and appropriate perinatal planning, management, and support.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".