Food Insecurity in Pregnancy, Receipt of Food Assistance, and Perinatal Complications.

Importance: Food insecurity is a growing public health concern, but its association with perinatal complications remains unclear.

Objective: To examine whether food insecurity in pregnancy was associated with the risk of perinatal complications and determine whether these potential associations differed by receipt of food assistance.

Design, Setting, And Participants: This cohort study used data from a pregnancy survey conducted between June 22, 2020, and September 9, 2022, at Kaiser Permanente Northern California, an integrated health care system serving a diverse population of 4.

Testing the Ability and Limitations of ChatGPT to Generate Differential Diagnoses from Transcribed Radiologic Findings.

Background The burgeoning interest in ChatGPT as a potentially useful tool in medicine highlights the necessity for systematic evaluation of its capabilities and limitations. Purpose To evaluate the accuracy, reliability, and repeatability of differential diagnoses produced by ChatGPT from transcribed radiologic findings. Materials and Methods Cases selected from a radiology textbook series spanning a variety of imaging modalities, subspecialties, and anatomic pathologies were converted into standardized prompts that were entered into ChatGPT (GPT-3.

Prioritizing Variables for Observational Study Design using the Joint Variable Importance Plot.

Observational studies of treatment effects require adjustment for confounding variables. However, causal inference methods typically cannot deliver perfect adjustment on all measured baseline variables, and there is often ambiguity about which variables should be prioritized. Standard prioritization methods based on treatment imbalance alone neglect variables' relationships with the outcome.

In utero metabolomic signatures of refined grain intake and risk of gestational diabetes: A metabolome-wide association study.

Background: Epidemiologic evidence has linked refined grain intake to a higher risk of gestational diabetes (GDM), but the biological underpinnings remain unclear.

Objectives: We aimed to identify and validate refined grain-related metabolomic biomarkers for GDM risk.

Methods: In a metabolome-wide association study of 91 cases with GDM and 180 matched controls without GDM (discovery set) nested in the prospective Pregnancy Environment and Lifestyle Study (PETALS), refined grain intake during preconception and early pregnancy and serum untargeted metabolomics were assessed at gestational weeks 10-13.

Glycemic Control Trajectories and Risk of Perinatal Complications Among Individuals With Gestational Diabetes.

Importance: Glycemic control is the cornerstone of gestational diabetes management. Glycemic control trajectories account for differences in longitudinal patterns throughout pregnancy; however, studies on glycemic control trajectories are scarce.

Objective: To examine whether glycemic control trajectories from gestational diabetes diagnosis to delivery were associated with differential risk of perinatal complications.

Development and validation of prediction models for gestational diabetes treatment modality using supervised machine learning: a population-based cohort study.

Background: Gestational diabetes (GDM) is prevalent and benefits from timely and effective treatment, given the short window to impact glycemic control. Clinicians face major barriers to choosing effectively among treatment modalities [medical nutrition therapy (MNT) with or without pharmacologic treatment (antidiabetic oral agents and/or insulin)]. We investigated whether clinical data at varied stages of pregnancy can predict GDM treatment modality.

Predictive Metabolomic Markers in Early to Mid-pregnancy for Gestational Diabetes Mellitus: A Prospective Test and Validation Study.

Gestational diabetes mellitus (GDM) predisposes pregnant individuals to perinatal complications and long-term diabetes and cardiovascular diseases. We developed and validated metabolomic markers for GDM in a prospective test-validation study. In a case-control sample within the PETALS cohort (GDM n = 91 and non-GDM n = 180; discovery set), a random PETALS subsample (GDM n = 42 and non-GDM n = 372; validation set 1), and a case-control sample within the GLOW trial (GDM n = 35 and non-GDM n = 70; validation set 2), fasting serum untargeted metabolomics were measured by gas chromatography/time-of-flight mass spectrometry.

Perinatal Complications in Individuals in California With or Without SARS-CoV-2 Infection During Pregnancy.

Importance: Additional research from population-based studies is needed to inform the treatment of SARS-CoV-2 infection during pregnancy and to provide health risk information to pregnant individuals.

Objective: To assess the risk of perinatal complications associated with SARS-CoV-2 infection and to describe factors associated with hospitalizations.

Design, Setting, And Participants: This population-based cohort study included 43 886 pregnant individuals with longitudinal electronic health record data from preconception to delivery who delivered at Kaiser Permanente Northern California between March 1, 2020, and March 16, 2021.

Associations of household food insufficiency with childhood depression and anxiety: a nationwide cross-sectional study in the USA.

Objective: Household food insufficiency (HFIS) is a major public health threat to children. Children may be particularly vulnerable to HFIS as a psychological stressor due to their rapid growth and accelerated behavioural and cognitive states, whereas data focusing on HFIS and childhood mental disorders are as-yet sparse. We aimed to examine the associations of HFIS with depression and anxiety in US children.

Household mold, pesticide use, and childhood asthma: A nationwide study in the U.S.

Objectives: To investigate the associations of household mold and pesticide use with risk of childhood asthma and examine the potential effect modification by child's sex at a national level in the U.S.

Methods: Nationally representative data were drawn from the cross-sectional 2017 and 2018 National Surveys of Children's Health.