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Record W4225674159

Perinatal Mental Illness and Risk of Incident Autoimmune Disease: A Population-Based Propensity-Score Matched Cohort Study

2021· article· en· W4225674159 on OpenAlexaboutno aff
Brown HK, A Wilton, Nan Liu, Ray JG, Dennis CL, Vigod SN

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsPropensity score matchingMedicineCohortCohort studyMental illnessPopulationAutoimmune diseaseDiseasePediatricsInternal medicineMental healthPsychiatryEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Hilary K Brown,1– 5 Andrew Wilton,5 Ning Liu,5 Joel G Ray,5,6 Cindy-Lee Dennis,6,7 Simone N Vigod3– 5 1Department of Health & Society, University of Toronto Scarborough, Toronto, ON, Canada; 2Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; 3Department of Psychiatry, University of Toronto, Toronto, ON, Canada; 4Women’s College Research Institute, Women’s College Hospital, Toronto, ON, Canada; 5ICES, Toronto, ON, Canada; 6Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON, Canada; 7Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, CanadaCorrespondence: Hilary K BrownDepartment of Health & Society, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, CanadaTel +1 416 208 2239Email hk.brown@utoronto.caBackground: Studies have demonstrated elevated risk for autoimmune disease associated with perinatal mental illness, but the extent to which this risk is specific to mental illness arising perinatally, and not mental illness generally, is unknown. Our objective was to compare the risk of autoimmune disease in women with mental illness arising within the perinatal period to (1) women with mental illness arising outside the perinatal period and (2) women who did not develop mental illness.Methods: We conducted a population-based matched cohort study of women aged 15– 49 years with no history of mental illness or autoimmune disease in Ontario, Canada, 1998– 2018. The exposed, 60,701 women with mental illness arising between conception and 365 days postpartum were propensity score-matched to (1) 264,864 women with mental illness arising non-perinatally and (2) 469,164 women who did not develop mental illness. Hazard ratios (HR) for autoimmune disease were generated using Cox proportional hazards models.Results: The incidence of autoimmune disease was similar among women with mental illness arising perinatally compared to those with mental illness arising non-perinatally (138.4 vs 140.7 per 100,000 person-years; HR 0.98, 95% CI 0.92– 1.05), and elevated among women with mental illness arising perinatally compared to those who did not develop mental illness (138.4 vs 88.9 per 100,000 person-years; HR 1.54, 95% CI 1.44– 1.64). The HR for the latter comparison was more pronounced for autoimmune disease with brain-reactive antibodies than other autoimmune disease.Conclusion: Perinatal mental illness is associated with increased risk of autoimmune disease that is no different than that of mental illness arising non-perinatally. Women with mental illness, regardless of the timing of onset, could benefit from early detection of autoimmune disease.Keywords: autoimmune diseases, cohort studies, mental disorders, women’s health

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)0.004
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.252
GPT teacher head0.569
Teacher spread0.317 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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