Treatment of Attention Deficit Hyperactivity Disorder (ADHD) in Pregnant Women: A Systematic Review of Cohort Studies
Bibliographic record
Abstract
Aims The aim of this systematic review is to identify and appraise pharmacological options available for management of ADHD in pregnant women and adverse effects of ADHD medications on pregnancy and foetus (malformations or long-term effects). Methods Systematic review of prospective or retrospective cohort studies, available on this topic till September 2021 after PubMed and MEDLINE search, carried out by 2 reviewers independently. The preliminary search was conducted in March 2021, though the reviewers carried out timely cross-referencing as required. All cohort studied except those with ambiguous methodology were included. The data were further extracted using Microsoft excel after Quality Assessment was completed using NewCastle Ottawa Scale. A narrative synthesis was undertaken as meta-analysis was not feasible owing to heterogeneity between studies included. Results Eighteen Cohort studies were included (N = 28227 pregnant women with ADHD) of which 16 were deemed as good quality. Multiple confounders were identified. The review noted that use of stimulants/non-stimulants reduced symptoms and improved functionality in these expectant mothers. Findings from our review overall indicate low risk of developing malformations with ADHD medications, with only Methylphenidate (notably cardiac) and Modafinil showing slightly increased though statistically significant risk. We also noted slightly increased risk for reduced Apgar scores, abortions on maternal request, pre-eclampsia and preterm births. There was no conclusive association noted between neuro-developmental delay or future ADHD in baby/child. Conclusion A case-by-case approach needs to be adopted for every patient, looking at how ADHD affects daily functioning and balancing that against adverse pregnancy outcomes. Also, innovative practices like drug holidays, as required medications, drug free trial while planning pregnancy etc. will help practitioners streamline the treatment of this group of patients better. Issues like research being restricted to certain countries, small sample size, record-based analysis, issues in ascertaining adherence, confounding factors, ethical conundrums etc. were noted.
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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 | 0.011 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".