Publications by authors named "Celia Gray"
Context: The obesity epidemic in the United States is continuing to worsen. Obesity is a known risk factor for pregnancy morbidity. However, many studies use the patient's body mass index (BMI) at the time of delivery, do not stratify by class of obesity, or utilize billing codes as the basis of their study, which are noted to be inaccurate.
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- - The study focuses on understanding what factors influence individuals to complete follow-up genetic visits after receiving potentially actionable genetic disease risk results from a genomic screening program.
- - Conducted as a cohort study using biobank data in Pennsylvania, it revealed that less than half of the 1,160 participants completed a genetics visit, indicating a need for better engagement strategies.
- - Key factors that encouraged visit completion included being younger, female, married or divorced, and having lower health comorbidity levels, suggesting targeted interventions could improve follow-up rates.
Background: To adequately predict significant postpartum hemorrhage (PPH) at hospital admission, we evaluated and compared the accuracy of three risk assessment tools: 1. California Maternal Quality Care Collaborative (CMQCC), 2. American College of Obstetrics and Gynecology Safe Motherhood Initiative (ACOG SMI) and 3.
View Article and Find Full Text PDFObjective: To improve upon the accuracy of ICD codes for identifying maternal and neonatal outcomes by developing algorithms that incorporate readily available EHR data.
Study Design: Algorithms were developed for gestational hypertension (GHTN), pre-eclampsia (PreE), gestational diabetes mellitus (GDM) and were compared to ICD codes and chart review. Accuracy and sensitivity analyses were calculated with their respective 95% confidence limits for each of the comparisons between algorithms, ICD codes alone, and chart review.