Publications by authors named "Heather Forquer"

Neonatal hypoxic-ischemic encephalopathy (HIE) is caused by sustained hypoxemia near birth. Clinical assessment using cardiotocography (CTG), which measures the fetal heart rate (FHR) and maternal uterine pressure (UP), aims to identify infants at increased risk of HIE. Although CTG is nonstationary, current automated methods for its analysis use time invariant discrimination rules.

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Article Synopsis
  • * Researchers analyzed data from around 41,000 term births, comparing 374 cases of HIE, 3,056 with fetal acidosis, and 37,546 healthy infants, using a random forest classifier for prediction.
  • * The system showed improved detection rates for HIE (61.8%) and fetal acidosis (48.3%) without increasing false positives in healthy infants, allowing for potential early clinical interventions.
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Background And Objectives: The Kaiser Permanente Neonatal Early-Onset Sepsis (EOS) Calculator has been an effective tool for risk stratification to safely reduce newborn antibiotic exposure. The calculator was derived from data on infants born between 1993 and 2007. Since that time, US obstetric practice has adopted universal antepartum screening for group B Streptococcus and intrapartum antibiotic prophylaxis guidance has changed.

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This article describes the methods used to build a large-scale database of more than 250,000 electronic fetal monitoring (EFM) records linked to a comprehensive set of clinical information about the infant, the mother, the pregnancy, labor, and outcome. The database can be used to investigate how birth outcome is related to clinical and EFM features. The main steps involved in building the database were: (1) Acquiring the raw EFM recording and clinical records for each birth.

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Background: Patients with hypertensive disorders of pregnancy have a high rate of postpartum readmission.

Objective: This study aimed to evaluate whether the type of antihypertensive medication prescribed at discharge was associated with postpartum readmission after a hypertensive disorder of pregnancy.

Study Design: This was a retrospective cohort study of 57,254 pregnancies complicated by hypertensive disorders of pregnancy between 2012 and 2018 in the electronic obstetrical database of Kaiser Permanente Northern California.

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Article Synopsis
  • This study focuses on improving the detection of fetuses at risk for fetal acidosis or hypoxic-ischemic encephalopathy (HIE) during labor by analyzing fetal heart rate (FHR) and uterine pressure (UP) signals.
  • A random forest classifier was developed to give intervention recommendations based on feature data from FHR and UP collected in 20-minute intervals, showing a significant increase in identifying at-risk babies well before delivery.
  • The system identified more cases of HIE and acidosis, suggesting early intervention opportunities that could lower HIE rates, despite a slight rise in cesarean section rates among healthy births.
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  • The study investigates the effects of selective serotonin reuptake inhibitors (SSRIs) taken by pregnant women after 20 weeks on neonatal adaptation, which can be delayed in infants exposed to these medications.
  • Conducted on a large population of 280,090 infants born in Northern California from 2011 to 2019, it found that 11.2% of infants exposed to SSRIs experienced delayed adaptation compared to 4.4% in non-exposed infants.
  • The research suggests a significant, dose-dependent relationship between SSRI use in late pregnancy and delayed neonatal adaptation, especially with certain SSRIs like escitalopram and fluoxetine having the highest associated risks.
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Nulliparous pregnancies, those where the mother has not previously given birth, are associated with longer labors and hence expose the fetus to more contractions and other adverse intrapartum conditions such as chorioamnionitis. The objective of the present study was to test if accounting for nulliparity could improve the detection of fetuses at increased risk of developing hypoxic-ischemic encephalopathy (HIE). During labor, clinicians assess the fetal heart rate and uterine pressure signals to identify fetuses at risk of developing HIE.

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Background: Recent studies suggest that the incidence of perinatal hypoxic-ischemic encephalopathy (HIE) may be increasing in developed countries. However, this observed increase may be due to increased ascertainment and increased treatment with therapeutic hypothermia rather than an increase in disease burden. In a US population-based cross-sectional study, we determined the incidence of perinatal HIE over time.

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Pregnant individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are at a higher risk for adverse pregnancy outcomes. Previous small cohort studies have shown increased frequency of placental lesions associated with maternal vascular malperfusion, fetal vascular malperfusion, and inflammation among patients with SARS-CoV-2, without controlling for cardiometabolic risk factors among many such patients. We aimed to evaluate whether SARS-CoV-2 infection during pregnancy is independently associated with placental abnormalities when controlling for risk factors that could affect placental histopathology.

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Visual assessment of the evolution of fetal heart rate (FHR) and uterine pressure (UP) patterns is the standard of care in the intrapartum period. Unfortunately, this assessment has high levels of intra- and inter-observer variability. This study processed and analyzed FHR and UP patterns using computerized pattern recognition tools.

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The research objective of our group is to improve the intrapartum detection of cardiotocography tracings associated with an increased risk of developing fetal acidosis and subsequent hypoxic-ischemic encephalopathy (HIE). The detection methods that we aim to develop must be sensitive to abnormal tracings without causing excessive unnecessary interventions. Past studies showed that the dynamic response of fetal heart rate (FHR) to uterine pressure (UP) during the intrapartum could be modelled using linear systems.

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A comorbidity summary score may support early and systematic identification of women at high risk for adverse obstetric outcomes. The objective of this study was to conduct the initial development and validation of an obstetrics comorbidity risk score for automated implementation in the electronic health record (EHR) for clinical use. The score was developed and validated using EHR data for a retrospective cohort of pregnancies with delivery between 2010 and 2018 at Kaiser Permanente Northern California, an integrated health care system.

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Article Synopsis
  • The study aims to enhance the identification of fetal heart rate tracings that indicate severe acidosis at birth, potentially preventing hypoxic-ischemic encephalopathy (HIE) while minimizing unnecessary interventions during normal births.
  • The researchers analyzed fetal heart rate signals from 21,853 births with normal outcomes and 163 cases of HIE, examining changes over the last 6 hours before delivery using 20-minute intervals.
  • Results indicated that specific metrics such as approximate entropy, standard deviation, and deceleration capacity could effectively signal the risk of HIE as early as 120 minutes before birth, allowing for timely medical interventions.
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Objective: This experiment tested the effects of an individualized risk-based online mammography decision intervention. The intervention employs exemplification theory and the Elaboration Likelihood Model of persuasion to improve the match between breast cancer risk and mammography intentions.

Methods: 2918 women ages 35-49 were stratified into two levels of 10-year breast cancer risk (<1.

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This study investigated how content and context features of headlines drive selective exposure when choosing between headlines of a monthly e-mail health newsletter in a naturalistic setting over a period of nine months. Study participants received a monthly e-mail newsletter and could freely open it and click any headline to read the accompanying article. In each e-mail newsletter, nine headlines competed with each other for selection.

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This article shares an in-depth summary of a formative evaluation that used quantitative data to inform the development and selection of promotional ads for the antismoking communication component of a social marketing campaign. A foundational survey provided cross-sectional data to identify beliefs about quitting smoking that campaign messages should target, as well as beliefs to avoid. Pretesting draft ads against quantitative indicators of message effectiveness further facilitated the selection and rejection of final campaign ads.

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While eHealth technologies are promisingly efficient and widespread, theoretical frameworks capable of predicting long-term use, termed continuance, are lacking. Attempts to extend prominent information technology (IT) theories to the area of eHealth have been limited by small sample sizes, cross-sectional designs, self-reported as opposed to actual use measures, and a focus on technology adoption rather than continuance. To address these gaps in the literature, this analysis includes empirical evidence of actual use of an eHealth technology over the course of one year.

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