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Record W4390260618 · doi:10.1093/ije/dyad184

Association of pre-existing maternal cardiovascular diseases with neurodevelopmental disorders in offspring: a cohort study in Sweden and British Columbia, Canada

2023· article· en· W4390260618 on OpenAlexaffabout
Muhammad Zakir Hossin, Lorena Fernández de la Cruz, Kyla A. McKay, Tim F. Oberlander, Anna Sandström, Neda Razaz

Bibliographic record

VenueInternational Journal of Epidemiology · 2023
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of British Columbia
FundersForskningsrådet om Hälsa, Arbetsliv och VälfärdVetenskapsrådetStockholms Läns LandstingKarolinska Institutet
KeywordsOffspringMedicineHazard ratioCohortCohort studyHeart diseasePopulationConfidence intervalPediatricsAttention deficit hyperactivity disorderPregnancyInternal medicineAutism spectrum disorderAutismPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: We aimed to investigate the associations of pre-existing maternal cardiovascular disease (CVD) with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and intellectual disability (ID) in offspring. METHODS: This population-based cohort study included singletons live-born without major malformations in Sweden (n = 2 699 675) and British Columbia (BC), Canada (n = 887 582) during 1990-2019, with follow-up from age 1 year until the outcome, death, emigration or December 2020, whichever came first. The primary exposure was defined as a composite CVD diagnosed prior to conception: cerebrovascular disease, arrhythmia, heart failure, valvular and congenital heart diseases. The incidences of ADHD, ASD and ID, comparing offspring of mothers with versus without CVD, were calculated as adjusted hazard ratios (aHRs). These results were compared with models using paternal CVD as negative control exposure. RESULTS: Compared with offspring of mothers without CVD, offspring of mothers with CVD had 1.15-fold higher aHRs of ADHD [95% confidence interval (CI): 1.10-1.20] and ASD (95% CI 1.07-1.22). No association was found between maternal CVD and ID. Stratification by maternal CVD subtypes showed increased hazards of ADHD for maternal heart failure (HR 1.31, 95% CI 1.02-1.61), cerebrovascular disease (HR 1.20, 95% CI 1.08-1.32), congenital heart disease (HR 1.18, 95% CI 1.08-1.27), arrhythmia (HR 1.13, 95% CI 1.08-1.19) and valvular heart disease (HR 1.12, 95% CI 1.00-1.24). Increased hazards of ASD were observed for maternal cerebrovascular disease (HR 1.25, 95% CI 1.04-1.46), congenital heart disease (HR 1.17, 95% CI 1.01-1.33) and arrythmia (HR 1.12, 95% CI 1.01-1.21). Paternal CVD did not show associations with ADHD, ASD or ID, except for cerebrovascular disease which showed associations with ADHD and ASD. CONCLUSIONS: In this large cohort study, pre-existing maternal CVD was associated with increased risk of ADHD and ASD in offspring.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.021
GPT teacher head0.310
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2023
Admission routes2
Has abstractyes

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