Preterm Birth and Risk of Psychiatric Disorders: A Register-Linkage Cohort Study: Liens entre la naissance prématurée et le risque de troubles psychiatriques : une étude de cohorte avec couplage de registres
Bibliographic record
Abstract
Objectives The objectives of this study were to quantify the associations between preterm birth and adolescent-to-adult psychiatric disorders in the Quebec (Canada) population and to determine whether sex and socioeconomic status (SES) modified this relationship. Methods This was an observational cohort study using administrative data from the province of Quebec, Canada. All eligible children born preterm between 1976 and 1995 were identified ( N = 100,040) and matched 1:2 with term-born children. Individuals were followed from age 11 years until either incident diagnosis of a psychiatric disorder (attention-deficit/hyperactivity disorder [ADHD], psychosis, bipolar disorder, anxiety, or depression), death, or December 2019. Preterm birth was considered as a binary (<37 weeks gestational age) and categorical exposure (extreme, <28; very, 28–31; moderate-to-late, 32–36 weeks gestational age), in addition to continuous gestational age in weeks. Cox proportional hazard models were applied. Effect-modifying roles of sex and SES were investigated in interaction analyses. Results Compared to term-born children, those born preterm had a higher risk of all outcomes, with magnitudes ranging from HR 1.16 for ADHD (95% confidence interval 1.13, 1.19) to 1.05 for anxiety (1.04, 1.07). A dose-response relationship was observed, with increasing risks of ADHD, psychosis, and anxiety as the degree of preterm birth increased. Despite some statistically significant associations, there was no clinically significant evidence of effect modification by sex or SES. Conclusions Children born preterm had an increased risk of psychiatric disorders in adolescence-to-adulthood, with similar risks across sexes and socioeconomic strata of the population. Policies for early and continued mental health surveillance in this susceptible group are important to initiate appropriate interventions.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".