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Association of Preexisting Disability With Severe Maternal Morbidity or Mortality in Ontario, Canada

2021· article· en· W3129088236 on OpenAlexaffabout
Hilary K. Brown, Joel G. Ray, Simon Chen, Astrid Guttmann, Susan M. Havercamp, Susan L. Parish, Simone N. Vigod, Lesley A. Tarasoff, Yona Lunsky

Bibliographic record

VenueJAMA Network Open · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsCentre for Addiction and Mental HealthSt. Michael's HospitalInstitute for Clinical Evaluative SciencesHospital for Sick ChildrenThe Scarborough HospitalPublic Health OntarioUniversity of TorontoWomen's College Hospital
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsMedicineCohortRuralityIntellectual disabilityCohort studyPopulationPregnancyDemographyPediatricsPsychiatryEnvironmental healthRural area

Abstract

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Importance: Severe maternal morbidity and mortality are important indicators of maternal health. Pregnancy rates are increasing in women with disabilities, but their risk of severe maternal morbidity and mortality is unknown, despite their significant social and health disparities. Objective: To determine the risk of severe maternal morbidity or mortality among women with a physical, sensory, or intellectual/developmental disability compared with women without disabilities. Design, Setting, and Participants: This population-based cohort study used linked health administrative data in Ontario, Canada, from 2003 to 2018. The cohort included all singleton births to women with preexisting physical, sensory, and intellectual/developmental disabilities as well as with 2 disabilities or more compared with women without a disability. Data analysis was conducted from September 2019 to September 2020. Exposures: Disabilities were identified with published algorithms applied to diagnoses in 2 physician visits or more or at least 1 emergency department visit or hospitalization. Main Outcomes and Measures: Severe maternal morbidity (a validated composite of 40 diagnostic and procedural indicators) or all-cause maternal mortality, arising between conception and 42 days post partum. Relative risks were adjusted for maternal age, parity, income quintile, rurality, chronic medical conditions, mental illness, and substance use disorders. Results: The cohort comprised women with physical disabilities (144 972 women; mean [SD] age, 29.8 [5.6] years), sensory disabilities (45 259 women; mean [SD] age, 29.1 [6.0] years), intellectual/developmental disabilities (2227 women; mean [SD] age, 26.1 [6.4] years), and 2 or more disabilities (8883 women; mean [SD] age, 29.1 [6.1] years), and those without disabilities (1 601 363 women; mean [SD] age, 29.6 [5.4] years). The rate of severe maternal morbidity or death was 1.7% (27 242 women) in women without a disability. Compared with these women, the risk of severe maternal morbidity or death was higher in women with a physical disability (adjusted relative risk [aRR], 1.29; 95% CI, 1.25-1.34), a sensory disability (aRR, 1.14; 95% CI, 1.06-1.21), an intellectual/developmental disability (aRR, 1.57; 95% CI, 1.23-2.01), and 2 or more disabilities (aRR, 1.74; 95% CI, 1.55-1.95). Similar aRRs were observed for severe maternal morbidity or death arising in pregnancy, from birth to 42 days post partum, and from 43 to 365 days post partum. Women with disabilities were more likely than those without disabilities to experience multiple severe maternal morbidity indicators. The most prevalent indicators in all groups were intensive care unit admission, severe postpartum hemorrhage, puerperal sepsis, and severe preeclampsia. Conclusions and Relevance: In this study, women with a preexisting disability were more likely to experience severe maternal morbidity or mortality. Preconception and perinatal care provisions should be considered among women with a disability to mitigate the risk of these rare but serious outcomes.

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)0.003
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 score0.037
Threshold uncertainty score0.265

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.049
GPT teacher head0.324
Teacher spread0.275 · 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

Citations81
Published2021
Admission routes2
Has abstractyes

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