Maternal Chronic Physical Conditions and Alcohol and Substance Use Disorders in the Preconception and Perinatal Periods
Bibliographic record
Abstract
Background: Chronic physical conditions (CPC) and alcohol and substance use disorders (SUD) frequently co-occur, but this has not been examined perinatally. We explored the combined effects of CPC and prepregnancy SUD on perinatal SUD-related adverse events and outpatient care. Materials and methods: This population-based study comprised 77,474 people with and 664,751 without CPC with a birth in Ontario, Canada, 2013–2020. We measured the prevalence of prepregnancy SUD in both groups. We then calculated adjusted relative risks (aRR) of: (1) SUD-related adverse events (toxicity resulting in acute care use/death, or other SUD-related acute care use) and (2) outpatient care for SUD between conception and 365 days postpartum, comparing individuals with prepregnancy CPC and SUD (CPC + SUD), and those with CPC or SUD alone, to those with neither condition. Finally, adjusted relative excess risk due to interaction (aRERI) was calculated to quantify excess risk of the outcomes associated with CPC + SUD, wherein RERI > 0 indicated positive interaction. Results: aRRs of perinatal SUD-related adverse events were 26.79 (95% confidence interval [CI]: 23.12, 31.04) for people with CPC + SUD, 22.09 (95% CI: 19.59, 24.91) for SUD alone, and 2.01 (95% CI: 1.78, 2.27) for CPC alone—each relative to neither condition. There was evidence of positive interaction for CPC + SUD (aRERI: 3.69, 95% CI: 1.13, 6.46). Similar elevated aRRs were observed for perinatal outpatient care for SUD, but without a positive interaction for people with CPC + SUD. Conclusion: As people with both CPC and SUD have the highest risk of perinatal SUD-related adversity, they may need greater preconception and perinatal 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".