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Association of Adult Congenital Heart Disease With Pregnancy, Maternal, and Neonatal Outcomes

2019· article· en· W2943968094 on OpenAlexafffundabout
Kaylee Ramage, Kirsten Grabowska, Candice Silversides, Hude Quan, Amy Metcalfe

Bibliographic record

VenueJAMA Network Open · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsUniversity of TorontoUniversity of British ColumbiaUniversity of Calgary
FundersAlberta Children's Hospital Research Institute
KeywordsMedicinePregnancyHeart diseaseGestational agePopulationPediatricsOdds ratioLogistic regressionMedical recordObstetricsInternal medicine

Abstract

fetched live from OpenAlex

Importance: With the help of medical advances, more women with adult congenital heart disease (ACHD) are becoming pregnant. Adverse maternal, obstetric, and neonatal events occur more frequently in women with ACHD than in the general obstetric population. Adult congenital heart disease is heterogeneous, yet few studies have assessed whether maternal and neonatal outcomes differ across ACHD subtypes. Objective: To assess the association of ACHD and its subtypes with pregnancy, maternal, and neonatal outcomes. Design, Setting, and Participants: This cross-sectional study used data from the Discharge Abstract Database, which contains information on all hospitalizations in Canada (except Quebec) from fiscal years 2001-2002 through 2014-2015. Discharge Abstract Database information was linked with maternal and infant hospital records across Canada. All women who gave birth in hospitals during the study period were included in the study. Data were analyzed from December 18, 2017, to March 22, 2019. Exposures: Women with ACHD were identified using diagnostic and procedural codes. Subtypes of ACHD were classified using the Anatomic and Clinical Classification of Congenital Heart Defects scheme. Main Outcomes and Measures: Primary outcomes were defined a priori and included severe maternal morbidity (measured using the Maternal Morbidity Outcomes Indicator), neonatal morbidity and mortality (measured using the Neonatal Adverse Outcomes Indicator), ischemic placental disease, preterm birth, congenital anomalies, and small-for-gestational-age births. Absolute and relative rates of each outcome were calculated overall and by ACHD subtype. Logistic regression using generalized estimating equations assessed crude and adjusted odds ratios (aORs) for each outcome in women with ACHD compared with women without ACHD after adjustment for comorbidities, mode of delivery, and study year. Results: The 2114 women with ACHD included in the analysis (mean [SD] age, 29.4 [5.7] years) had significantly higher odds of maternal morbidity (aOR, 2.7; 95% CI, 2.2-3.4) and neonatal morbidity and mortality (aOR, 1.8; 95% CI, 1.6-2.1) compared with women without ACHD (n = 2 682 451). Substantial variation was observed between women with different subtypes of ACHD. For example, the aORs of preterm birth (<37 weeks) varied from 0.4 (95% CI, 0.4-0.5) for women with anomalies of atrioventricular junctions and valves to 4.7 (95% CI, 2.9-7.5) for women with complex anomalies of atrioventricular connections. Conclusions and Relevance: These results suggest that women with different subtypes of ACHD are not uniformly at risk for adverse maternal and neonatal outcomes. Although some women with ACHD can potentially expect healthy pregnancies, it appears that clinical care should be modified to address the heightened risks of certain ACHD subtypes.

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)0.006
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 score0.190
Threshold uncertainty score0.378

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.253
Teacher spread0.246 · 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".

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Citations102
Published2019
Admission routes3
Has abstractyes

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