The Effects of Opioids on Female Reproductive Health Across the Life Course
Bibliographic record
Abstract
Opioids cover a broad class of natural, synthetic and semi-synthetic drugs which act on opioid receptors within the central and peripheral nervous system to produce powerful analgesic effects. This includes illicit opioid use (e.g., heroin) and use which is associated with opioid agonist maintenance treatment (e.g., methadone or buprenorphine/naloxone). The rate of long-term opioid use has increased substantially in recent years, particularly among women. In Canada, opioid misuse is now a leading cause of death and other adverse effects. Data on the association with female health across the life course has not been well-described. The purpose of this review is to provide an overview of the literature on trends in use of opioids among females aged 15 years and older in relation to fertility, pregnancy, breastfeeding, and health in older ages. We searched the medical literature between August 2018 and August 2019 to look for studies related to health implications for opioid use among women. Outcomes included associations with fertility, pregnancy-related complications, breastfeeding, and older age outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".