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Record W4319455356 · doi:10.1016/j.xagr.2023.100175

Prepregnancy body mass index and adverse perinatal outcomes in the presence of other maternal risk factors

2023· article· en· W4319455356 on OpenAlexafffund
Jeffrey N. Bone, K.S. Joseph, Laura A. Magee, Giulia M. Muraca, Neda Razaz, Chantal Mayer, Sarka Lisonkova

Bibliographic record

VenueAJOG Global Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsMcMaster UniversityImpactUniversity of British ColumbiaB.C. Women's Hospital & Health CentreBC Children's HospitalChildren's & Women's Health Centre of British Columbia
FundersHospital for Sick ChildrenMichael Smith Health Research BCUniversity of British ColumbiaSick Kids FoundationBC Children's Hospital
KeywordsBody mass indexObstetricsMedicineMass indexPregnancyInternal medicineBiology

Abstract

fetched live from OpenAlex

BACKGROUND: High prepregnancy body mass index is one of the most common risk factors for adverse perinatal events. OBJECTIVE: This study aimed to assess whether the association between maternal body mass index and adverse perinatal outcome is modified by other concomitant maternal risk factors. STUDY DESIGN: This was a retrospective cohort study of all singleton live births and stillbirths in the United States from 2016 to 2017, using data from the National Center for Health Statistics. Logistic regression was used to estimate the adjusted odds ratios and 95% confidence intervals between prepregnancy body mass index and a composite outcome of stillbirth, neonatal death, and severe neonatal morbidity. Modification of this association by maternal age, nulliparity, chronic hypertension, and prepregnancy diabetes mellitus was assessed on both multiplicative and additive scales. RESULTS: The study population included 7,576,417 women with singleton pregnancy; 254,225 (3.5%) were underweight, 3,220,432 (43.9%) had normal body mass index, 1,918,480 (26.1%) were overweight, and 1,062,177 (14.4%), 516,693 (7.0%), and 365,357 (5.0%) had class I, II, and III obesity, respectively. Rates of the composite outcome increased with increasing body mass index above normal values, compared with women with normal body mass index. Nulliparity (289,776; 38.6%), chronic hypertension (135,328; 1.8%), and prepregnancy diabetes mellitus (67,744; 0.89%) modified the association between body mass index and the composite perinatal outcome on both the additive and multiplicative scales. Nulliparous (vs parous) women had a higher rate of increase in adverse outcomes with increasing body mass index. For example, in nulliparous women, class III obesity was associated with 1.8-fold higher odds compared with normal body mass index (adjusted odds ratio, 1.77; 95% confidence interval, 1.73-1.83), whereas in parous women, the adjusted odds ratio was 1.35 (95% confidence interval, 1.32-1.39). Women with chronic hypertension or prepregnancy diabetes mellitus had higher outcome rates overall; however, the dose-response relationship with increasing body mass index was absent. Although the composite outcome rates increased with maternal age, the risk curves were relatively similar across obesity classes in all maternal age groups. Overall, underweight women had 7% higher odds of the composite outcome, and this increased to 21% in parous women. CONCLUSION: Women with elevated prepregnancy body mass index are at increased risk of adverse perinatal outcomes, and the magnitude of these risks differs by concomitant risk factors, including prepregnancy diabetes mellitus, chronic hypertension, and nulliparity. In particular, in woman with chronic hypertension or prepregnancy diabetes mellitus, there is no impact of increasing body mass index on adverse perinatal outcomes. However, overall rates remain high, and prepregnancy prevention of hypertension and diabetes mellitus should be emphasized among all women irrespective of body mass index.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.308
Teacher spread0.294 · 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 teacher head, 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

Citations5
Published2023
Admission routes2
Has abstractyes

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