Construction of a comprehensive fetal monitoring database for the study of perinatal hypoxic ischemic encephalopathy.

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. (2) Assigning each birth to an objectively defined outcome class that included normal, acidosis, and hypoxic-ischemic encephalopathy. (3) Removing all personal health information from the EFM recordings and clinical records. (4) Preprocessing the deidentified EFM records to eliminate duplicates, reformat the signals, combine signals from different sensors, and bridge gaps to generate signals in a format that can be readily analyzed. (5) Post-processing the repaired EFM recordings to extract key features of the fetal heart rate, uterine activity, and their relations. (6) Populating a database that links the clinical information, EFM records, and EFM features to support easy querying and retrieval. •A multi-step process is required to build a comprehensive database linking electronic temporal fetal monitoring signals to a comprehensive set of clinical information about the infant, the mother, the pregnancy, labor, and outcome.•The current database documents more than 250,000 births including almost 4,000 acidosis and 400 HIE cases. This represents more than 80% of the births that occurred in 15 Northern California Kaiser Permanente Hospitals between 2011-2019. This is a valuable resource for studying the factors predictive of outcome.•The signal processing code and schemas for the database are freely available. The database will not be permitted to leave Kaiser firewalls, but a process is in place to allow interested investigators to access it.

Risk of postpartum readmission after hypertensive disorder of pregnancy and variation by discharge antihypertensive medication prescription.

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. Postpartum readmissions occurred within 6 weeks after discharge from delivery hospitalization. Cox regression models were used to evaluate the association between the type of antihypertensive medication prescription at discharge (none, labetalol only, nifedipine only, or 2 or more antihypertensive medications) and postpartum readmission, adjusted for type of hypertensive disorder of pregnancy, final inpatient systolic and diastolic blood pressures, age, body mass index, mode of delivery, insurance status, race and ethnicity, delivery facility, comorbidity score, smoking, preterm delivery, parity, and Neighborhood Deprivation Index. RESULTS: Among eligible patients with a hypertensive disorder of pregnancy, 1696 (3.0%) were readmitted within 6 weeks. Approximately 86% of patients were discharged without a prescription for antihypertensive medication; among those discharged with a prescription for antihypertensive medication, most were prescribed either labetalol only (54%) or nifedipine only (30%). The unadjusted readmission risk was the highest for patients discharged with a prescription for labetalol only (7.6%), lower for those discharged with a prescription for nifedipine only (3.6%) or 2 or more antihypertensive medications (3.2%), and the lowest for those discharged without a prescription for antihypertensive medication (2.5%). In the adjusted models, compared with discharge without a prescription for antihypertensive medication, discharge with a prescription for labetalol only was associated with a 63% (hazard ratio, 1.63; 95% confidence interval, 1.41-1.88) greater incidence of postpartum readmission, and discharge with a prescription for nifedipine only and discharge with a prescription for 2 or more antihypertensive medications were associated with 26% (hazard ratio, 0.74; 95% confidence interval, 0.59-0.93) and 47% (hazard ratio, 0.53; 95% confidence interval, 0.38-0.74) lower incidence of postpartum readmission, respectively. There was no strong evidence to suggest that the effect of the type of antihypertensive medication at discharge on the incidence of readmission varied by race and ethnicity (interaction P=.88). The results indicating an elevated risk associated with labetalol use were consistent in models that excluded patients with prepregnancy hypertension. CONCLUSION: Discharge with a prescription for nifedipine alone or multiple antihypertensive medications (vs no medication) was associated with a lower incidence of readmission, whereas discharge with a prescription for labetalol alone was associated with an elevated readmission incidence. A large-scale, prospective research to compare the effectiveness of commonly prescribed hypertension medications at discharge is warranted.

Maternal treatment with selective serotonin reuptake inhibitors during pregnancy and delayed neonatal adaptation: a population-based cohort study.

OBJECTIVE: Selective serotonin reuptake inhibitor (SSRI) use is common in pregnancy. It is associated with delayed neonatal adaptation. Most previous studies have not adjusted for the severity of maternal mental health disorders or examined the impact of SSRI type and dosage. We examined whether treatment with SSRIs in late pregnancy (after 20 weeks) is associated with delayed neonatal adaptation independent of maternal depression and anxiety. DESIGN, SETTING AND PATIENTS: Retrospective population-based birth cohort of 280 090 term infants born at 15 Kaiser Permanente Northern California hospitals, 2011-2019. Individual-level pharmacy, maternal, pregnancy and neonatal data were obtained from electronic medical records. EXPOSURE: Dispensed maternal SSRI prescription after 20 weeks of pregnancy. MAIN OUTCOME MEASURES: Delayed neonatal adaptation defined as a 5 min Apgar score ≤5, resuscitation at birth or admission to a neonatal intensive care unit for respiratory support. Secondary outcomes included each individual component of the primary outcome and more severe neonatal outcomes (pulmonary hypertension, hypoxic-ischaemic encephalopathy and seizures). RESULTS: 7573 (2.7%) infants were exposed to SSRIs in late pregnancy. Delayed neonatal adaptation occurred in 11.2% of exposed vs 4.4% of unexposed infants (relative risk 2.52 (95% CI 2.36 to 2.70)). After multivariable adjustment, there was an association between SSRI exposure and delayed neonatal adaptation (adjusted OR 2.14 (95% CI 1.96 to 2.32)). This association was dose dependent. Escitalopram and fluoxetine were associated with the highest risk of delayed neonatal adaptation. CONCLUSIONS: Infants exposed to SSRIs have increased risks of delayed adaptation in a type and dose-dependent relationship, pointing toward a causal relationship.

Timely Detection of Infants at Risk of Intrapartum Acidosis and Hypoxic-Ischemic Encephalopathy Using Cardiotocography.

This work aims to improve the intrapartum detection of fetuses with an increased risk of developing fetal acidosis or hypoxic-ischemic encephalopathy (HIE) using fetal heart rate (FHR) and uterine pressure (UP) signals. Our study population comprised 40,831 term births divided into 3 classes based on umbilical cord or early neonatal blood gas assessments: 374 with verified HIE, 3,047 with acidosis but no encephalopathy and 37,410 healthy babies with normal gases. We developed an intervention recommendation system based on a random forest classifier. The classifier was trained using classical and novel features extracted electronically from 20-minute epochs of FHR and UP. Then, using the predictions of the classifier on each epoch, we designed a decision rule to determine when to recommended intervention. Compared to the Caesarean rates in each study group, our system identified an additional 5.68% of babies who developed HIE (54.55% vs 60.23%, p < 0.01) with a specific alert threshold. Importantly, about 75% of these recommendations were made more than 200 minutes before birth. In the acidosis group, the system identified an additional 17.44% (37.15% vs 54.59%, p < 0.01) and about 2/3 of these recommendations were made more than 200 minutes before birth. Compared to the Caesarean rate in the healthy group, the associated false positive rate was increased by 1.07% (38.80% vs 39.87%, p<0.01).Clinical Relevance- This method recommended intervention in more babies affected by acidosis or HIE, than the intervention rate observed in practice and most often did so 200 minutes before delivery. This was early enough to expect that interventions would have clinical benefit and reduce the rate of HIE. Given the high burden associated with HIE, this would justify the marginal increase in the normal Cesarean rate.

Accounting for Nulliparity in the Prediction of Hypoxic-Ischemic Encephalopathy Using Cardiotocography.

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. In this study, we performed random forest classification using fetal heart rate and uterine pressure features from 40,831 births, including 374 that developed HIE. We analyzed a two-path classification approach that analyzed separately the fetuses from nulliparous and multiparous mothers, and a one-path classification approach that included the clinical variable for nulliparity as a classification feature. We compared these two approaches to a one-path classifier that had no information about the parity of the mothers. We also compared our results to the rate of Caesarean deliveries in each group, which is used clinically to interrupt the progression towards HIE. All the classifiers detected more fetuses that developed HIE than the observed Caesarean rate, but accounting for nulliparity did not improve performance.

Perinatal Hypoxic-Ischemic Encephalopathy: Incidence Over Time Within a Modern US Birth Cohort.

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. METHODS: The study population included all 289,793 live-born infants ≥35 weeks gestational age born at 15 Kaiser Permanente Northern California hospitals between 2012 and 2019. Perinatal HIE was defined as the presence of both neonatal acidosis (i.e., cord blood pH < 7 or base deficit ≥10, or base deficit ≥10 on first infant gas) and neonatal encephalopathy confirmed by medical record review. Hospital discharge diagnoses of HIE were determined by extracting International Classification of Disease diagnostic codes for HIE assigned upon hospital discharge. RESULTS: The population incidence of perinatal HIE was 1.7 per 1000. Although the incidence of perinatal HIE did not change significantly, both hospital discharge diagnoses of HIE and treatment with therapeutic hypothermia increased significantly during the study period. The sensitivity and positive predictive value of a hospital discharge diagnosis of HIE for identifying perinatal HIE confirmed by chart review were 72% and 79%, respectively. CONCLUSIONS: During the study years, the incidence of perinatal HIE remained stable despite increases in hospital discharge diagnoses of HIE and in the use of therapeutic hypothermia. Our findings underscore the importance of applying stringent diagnostic criteria when diagnosing this complex condition.

Placental Histopathologic Findings of a Large Cohort of Patients With SARS-CoV-2 Infection During Pregnancy.

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. Retrospective cohort study of placentas from singleton pregnancies in Kaiser Permanente Northern California from March to December 2020. Pathologic findings were compared among those with confirmed cases of SARS-CoV-2 during pregnancy and those without. We examined the association between SARS-CoV-2 infection and categorical placental pathologies, controlling for maternal age, gestational age, prepregnancy body mass index, gestational hypertension, preeclampsia/eclampsia, preexisting diabetes, history of thrombosis, and stillbirth. A total of 2,989 singleton gestation placentas were analyzed, 416 (13%) from pregnancies with SARS-CoV-2 infection and 2,573 (86%) from those without infection. Among placentas from pregnancies with SARS-CoV-2, 54.8% had evidence of inflammation, 27.1% maternal malperfusion abnormality, 20.7% massive perivillous fibrin or chronic villitis, 17.3% villous capillary abnormality, and 15.1% fetal malperfusion. After controlling for risks factors and stratifying interval time between SARS-CoV-2 infection and delivery, no association was found between placental abnormalities and SARS-CoV-2 infection during pregnancy. SARS-CoV-2 infection was not associated with an increased risk of placentally mediated adverse outcomes during pregnancy, compared with placentas sent for other indications, in this large diverse cohort.

Multi-Chain Semi-Markov Analysis of Intrapartum Cardiotocography.

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. The goal was to evaluate differences in FHR and UP patterns between fetuses with normal outcomes and those who developed hypoxic-ischemic encephalopathy (HIE). For this purpose, we modeled the sequence of FHR patterns and uterine contractions using Multi-Chain Semi-Markov models (MCSMMs). These models estimate the probability of transitioning between FHR or UP patterns and the dwell time of each pattern. Our results showed that in comparison to the control group, the HIE group had: (1) more frequent uterine contractions during the last 12 hours before birth; (2) more frequent FHR decelerations during the last 12 hours before birth; (3) longer decelerations during the last eight hours before birth; and (4) shorter baseline durations during the last five hours before birth. These results demonstrate that the fetuses in the HIE group were subject to a more stressful environment than those in the normal group. Clinical Relevance- Our results revealed statistically significant differences in FHR/UP patterns between the normal and HIE groups in the hours before birth. This indicates that features derived using MCSMMs may be useful in a machine learning framework to detect infants at increased risk of developing HIE allowing preventive interventions.

The Nonlinear Dynamic Response of Intrapartum Fetal Heart Rate to Uterine Pressure.

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. In this study, we examined the assumption of linearity by comparing the performance of linear dynamic and nonlinear dynamic models of the UP-FHR system. The linear systems were defined by second-order state-space models. The nonlinear systems were defined by Hammerstein models: a cascade of a static nonlinearity and a linear second-order state-space model. Our results showed that nonlinear dynamic models were better than linear systems in 81.8% of UP-FHR segments.

Development and Validation of an Obstetric Comorbidity Risk Score for Clinical Use.

Background: 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. Methods: 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. The outcome used for model development consisted of adverse obstetric events from delivery hospitalization (e.g., eclampsia, hemorrhage, death). Candidate predictors included maternal age, parity, multiple gestation, and any maternal diagnoses assigned in health care encounters in the 12 months before admission for delivery. We used penalized regression for variable selection, logistic regression to fit the model, and internal validation for model evaluation. We also evaluated prenatal model performance at 18 weeks of pregnancy. Results: The development cohort (n = 227,405 pregnancies) had an outcome rate of 3.8% and the validation cohort (n = 41,683) had an outcome rate of 2.9%. Of 276 candidate predictors, 37 were included in the final model. The final model had a validation c-statistic of 0.72 (95% confidence interval [CI] 0.70-0.73). When evaluated at 18 weeks of pregnancy, discrimination was modestly diminished (c-statistic 0.68 [95% CI 0.67-0.70]). Conclusions: The obstetric comorbidity score demonstrated good discrimination for adverse obstetric outcomes. After additional appropriate validation, the score can be automated in the EHR to support early identification of high-risk women and assist efforts to ensure risk-appropriate maternal care.

Temporal Evolution of Intrapartum Fetal Heart Rate Features.

Our research goal is to improve the intrapartum identification of tracings associated with severe acidosis at birth and subsequent hypoxic-ischemic encephalopathy so that timely interventions could avoid such complications without causing excessive unnecessary interventions in births with normal outcomes. The present study examines the evolution of fetal heart rate (FHR) features over the course of labor. We analyzed FHR signals collected in the last 6 hours before delivery in 21,853 births with normal neonatal outcomes and in 163 that developed hypoxic-ischemic encephalopathy (HIE) from 15 hospitals of Kaiser Permanente Northern California. We divided these six hours into 18 nonoverlapping 20-minute epochs. The power spectral density of each epoch was divided into three bands: low frequency (LF, 30-150 mHz), movement frequency (MF, 150-500 mHz), and high frequency (HF, 500-1000 mHz). We also estimated the LF/(MF+HF) ratio, the mean and standard deviation of the FHR signal, the approximate entropy (ApEn), and the deceleration capacity (DC). In our results, ApEn, the standard deviation, and DC showed a promising ability to detect risk of HIE as early as 120 minutes before birth, which gives enough leading time for timely interventions.

Effects of a risk-based online mammography intervention on accuracy of perceived risk and mammography intentions.

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 (<1.5%; ≥1.5%) then randomly assigned to one of eight conditions: two comparison conditions and six risk-based intervention conditions that varied according to a 2 (amount of content: brief vs. extended) x 3 (format: expository vs. untailored exemplar [example case] vs. tailored exemplar) design. Outcomes included mammography intentions and accuracy of perceived breast cancer risk. RESULTS: Risk-based intervention conditions improved the match between objective risk estimates and perceived risk, especially for high-numeracy women with a 10-year breast cancer risk ≤1.5%. For women with a risk≤1.5%, exemplars improved accuracy of perceived risk and all risk-based interventions increased intentions to wait until age 50 to screen. CONCLUSION: A risk-based mammography intervention improved accuracy of perceived risk and the match between objective risk estimates and mammography intentions. PRACTICE IMPLICATIONS: Interventions could be applied in online or clinical settings to help women understand risk and make mammography decisions.

Selective Exposure to Health Information: The Role of Headline Features in the Choice of Health Newsletter Articles.

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. Textual and visual information of the headlines was content-analyzed, and clickstream data on the headlines were collected automatically. The results showed that headlines invited more frequent audience selections when they provided efficacy-signaling information in an imperative voice, when they used a moderate number of negative emotion words, when they presented negative thumbnail images while mentioning cancer or other diseases, and when they were placed higher in position.

Predicting continuance-findings from a longitudinal study of older adults using an eHealth newsletter.

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. This large (n = 4,570) longitudinal study focuses on older adults, a population with many health needs and among whom eHealth use may be particularly important. With three measurement points over the course of a year, this study examined the effects of utilitarian and hedonic beliefs on the continued use of an eHealth newsletter using constructs from IT adoption and continuance theories. Additional analyses compared the relative strength of intentions compared to earlier use in predicting later use. Usage intention was strongly predicted by both hedonic beliefs and utilitarian beliefs. In addition, utilitarian beliefs had both direct effects on intention and indirect effects, mediated by hedonic beliefs. While intention predicted subsequent use, earlier use was a significantly stronger predictor of use than intention. These findings make a theoretical contribution to an emerging literature by shedding light on the complex interplay of reasoned action and automaticity in the context of eHealth continuance.

Applying Quantitative Approaches to the Formative Evaluation of Antismoking Campaign Messages.

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. Finally, we consider lessons learned from the process of balancing quantitative methods and judgment to make formative decisions about more and less promising persuasive messages for campaigns.