Increased maternal new‐onset psychiatric disorders after delivering a child with a major anomaly: a cohort study
Bibliographic record
Abstract
BACKGROUND: The birth of a child with a major congenital anomaly may create chronic caregiving stress for mothers, yet little is known about their psychiatric outcomes. AIMS: To evaluate the association of the birth of a child with a major congenital anomaly with subsequent maternal psychiatric risk. METHODS: This Danish nationwide cohort study included mothers who gave birth to an infant with a major congenital anomaly (n = 19 220) between 1997 and 2015. Comparators were randomly selected mothers, matched on maternal age, year of delivery and parity (n = 195 399). The primary outcome was any new-onset psychiatric diagnosis. Secondary outcomes included specific psychiatric diagnoses, psychiatric in-patient admissions and redeemed psychoactive medicines. Cox models were used to estimate hazard ratios (HRs), adjusted for socioeconomic and medical variables. RESULTS: Mothers of affected infants had an elevated risk for a new-onset psychiatric disorder vs. the comparison group (adjusted HR, 1.16, 95% CI 1.11-1.22). The adjusted HR was particularly elevated during the first postpartum year (1.65, 95% CI 1.42-1.90), but remained high for years, especially among mothers of children with multiorgan anomalies (1.37, 95% CI 1.18-1.57). The risk was also elevated for most specific psychiatric diagnoses, admissions and medicines. CONCLUSIONS: Mothers who give birth to a child with a major congenital anomaly are at increased risk of new-onset psychiatric disorders, especially shortly after birth and for mothers of children with more severe anomalies. Our study highlights the need to screen for mental illness in this high-risk population, as well as to integrate adult mental health services and paediatric care.
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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 | 0.001 |
| 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 | 0.001 |
| 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".