Antenatal Kratom Exposure: Literature Review and Clinical Management Recommendations
Bibliographic record
Abstract
Abstract: In recent years, there has been a rapid interest in using kratom for the self-management of various chronic pain, anxiety and mood conditions, as well as, for the management of opioid withdrawal symptoms. The two main kratom alkaloids have stimulant and opioid-like effects that cause concerns during pregnancy. A literature review was conducted, and ten case reports relating to maternal kratom use were included consisting of 12 mother-infant dyads. Case reports indicated that regular use of kratom was associated with the presence of maternal kratom dependence and withdrawal. The route and amount of kratom use reported was highly variable. The majority of women were only identified in the postpartum period after infants displayed symptoms and signs of neonatal withdrawal. Management of maternal kratom use varied and included either opioid agonist treatment with buprenorphine or morphine or detoxification. Most of the exposed infants were described to develop neonatal abstinence syndrome and more than half required pharmacological treatment with morphine. All neonates were discharged home in the care of their mothers. Clinicians should be aware of the possible clinical effects of perinatal kratom exposure and be able to implement appropriate maternal and neonatal management strategies. Keywords: Mitragyna , pregnancy, opioids, neonatal abstinence syndrome, opioid agonist treatment
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".