Rates of Fetal Polydrug Exposures in Methadone-Maintained Pregnancies from a High-Risk Population
Bibliographic record
Abstract
UNLABELLED: Methadone maintenance treatment (MMT) is the standard of care during pregnancy for opioid-dependency, showing efficacy in improving prenatal care and reducing risk of relapse. By design, however, MMT is only intended to prevent withdrawal thus facilitating cognitive behavioural interventions. In order to maximize the benefits of MMT, it is essential that methadone is both properly prescribed and that additional addiction treatment is concurrently administered. This study aims to determine the effectiveness of MMT engagement in high-risk pregnant women in reducing polydrug use by objective laboratory examination of neonatal meconium. PATIENTS AND METHODS: Over a 29-month period, the Motherisk Laboratory at the Hospital for Sick Children in Toronto analyzed meconium samples as per request by social services and hospitals for drugs of abuse. RESULTS: Of the 904 meconium samples received, 273 were tested for methadone with 164 positive and 109 negative for methadone. Almost half of the methadone positive samples (46.34%) were also positive for at least one other opioid compound, which did not differ statistically from the methadone-negative control samples (46.79%; Chi square test, p=0.94). No differences were found between the methadone positive and negative groups in rates of concurrent amphetamines, cocaine, cannabis, and alcohol use indicating a similar risk of polydrug use between pregnant women taking or not taking methadone in this population. DISCUSSION: The high rates of additional opioid and other drug use in the MMT group, suggest that MMT is failing this population of patients. It is possible that methadone doses during pregnancy are not appropriately adjusted for changes in pharmacokinetic parameters (e.g. blood volume, renal function) during the second and third trimesters. This may result in sub-therapeutic dosing creating withdrawal symptoms leading to additional substance use. Alternatively, these results may be demonstrating a substantial lack in delivery of addiction support services in this vulnerable population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".