Mesenchymal Stem Cells Suppress Inflammatory Cytokines in Lipopolysaccharide Exposed Preterm and Term Human Pregnant Myometrial Cells

Objective  The objective of this study was to determine the cytokine response in human pregnant preterm and term myometrial cells exposed to lipopolysaccharide (LPS) and cocultured with mesenchymal stem cells (MSCs). Study Design  Myometrium was obtained at cesarean delivery in term and preterm patients. Human myometrial cells were exposed to 5 μg/mL LPS for 4 hours followed by 1 μg/mL LPS for 24 hours and were cocultured with MSCs for 24 hours. Culture supernatants were collected at 24 hours and expression of cytokines, including interleukin-1β (IL-1β), IL-6, IL-8, tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), and IL-10, was quantified by enzyme-linked immunosorbent assay. Results  There was significantly increased expression of the proinflammatory cytokines IL-1β, IL-6, IL-8, and TNF-α in preterm myometrial cells treated with LPS compared with untreated preterm myometrial cells. Coculture with MSCs significantly suppressed the proinflammatory cytokine levels in LPS-treated preterm versus treated term myometrial cells. Moreover, MSC cocultured preterm myometrial cells expressed increased levels of the anti-inflammatory cytokines TGF-β and IL-10 compared with treated term myometrial cells. Conclusion  MSCs ameliorate LPS-mediated inflammation in preterm human myometrial cells compared with term myometrial cells. Immunomodulatory effects of MSCs mediated through anti-inflammatory cytokine regulation suggest a potential cell-based therapy for preterm birth

Investigating the Association Between Metabolic Syndrome Conditions and Perinatal Mental Illness: A National Administrative Claims Study

BACKGROUND: Although the association between mental disorder and metabolic syndrome as a bidirectional relationship has been demonstrated, there is little knowledge of the cumulative and individual effect of these conditions on peripartum mental health. This study aims to investigate the association between metabolic syndrome conditions (MetS-C) and maternal mental illness in the perinatal period, while exploring time to incident mental disorder diagnosis in postpartum women. METHODS: This observational study identified perinatal women continuously enrolled 1 year prior to and 1 year post-delivery using Optum\u27s de-identified Clinformatics® Data Mart Database (CDM) from 2014 to 2019 with MetS-C i.e. obesity, diabetes, high blood pressure, high triglycerides, or low HDL (1-year prior to delivery); perinatal comorbidities (9-months prior to and 4-month postpartum); and mental disorder (1-year prior to and 1-year post-delivery). Additionally, demographics and the number of days until mental disorder diagnosis were evaluated in this cohort. The analysis included descriptive statistics and multivariable logistic regression. MetS-C, perinatal comorbidities, and mental disorder were assessed using the International Classification of Diseases, Ninth, and Tenth Revision diagnosis codes. RESULTS: 372,895 deliveries met inclusion/exclusion criteria. The prevalence of MetS-C was 13.43%. Multivariable logistic regression revealed prenatal prevalence (1.64, CI = 1.59-1.70) and postpartum incident (1.30, CI = 1.25-1.34) diagnosis of mental health disorder were significantly higher in those with at least one MetS-C. Further, the adjusted odds of having postpartum incident mental illness were 1.51 times higher (CI = 1.39-1.66) in those with 2 MetS-C and 2.12 times higher (CI = 1.21-4.01) in those with 3 or more MetS-C. Young women (under the age of 18 years) were more likely to have an incident mental health diagnosis as opposed to other age groups. Lastly, time from hospital discharge to incident mental disorder diagnosis revealed an average of 157 days (SD = 103 days). CONCLUSION: The risk of mental disorder (both prenatal and incident) has a significant association with MetS-C. An incremental relationship between incident mental illness diagnosis and the number of MetS-C, a significant association with younger mothers along with a relatively long period of diagnosis mental illness highlights the need for more screening and treatment during pregnancy and postpartum

Variations in Multiple Birth Rates and Impact on Perinatal Outcomes in Europe

Objective Infants from multiple pregnancies have higher rates of preterm birth, stillbirth and neonatal death and differences in multiple birth rates (MBR) exist between countries. We aimed to describe differences in MBR in Europe and to investigate the impact of these differences on adverse perinatal outcomes at a population level. Methods We used national aggregate birth data on multiple pregnancies, maternal age, gestational age (GA), stillbirth and neonatal death collected in the Euro-Peristat project (29 countries in 2010, N = 5 074 643 births). We also used European Society of Human Reproduction and Embryology (ESHRE) data on assisted conception and single embryo transfer (SET). The impact of MBR on outcomes was studied using meta-analysis techniques with random-effects models to derive pooled risk ratios (pRR) overall and for four groups of country defined by their MBR. We computed population attributable risks (PAR) for these groups. Results In 2010, the average MBR was 16.8 per 1000 women giving birth, ranging from 9.1 (Romania) to 26.5 (Cyprus). Compared to singletons, multiples had a nine-fold increased risk (pRR 9.4, 95% Cl 9.1–9.8) of preterm birth (<37 weeks GA), an almost 12-fold increased risk (pRR 11.7, 95% CI 11.0–12.4) of very preterm birth (<32 weeks GA). Pooled RR were 2.4 (95% Cl 1.5–3.6) for fetal mortality at or after 28 weeks GA and 7.0 (95% Cl 6.1–8.0) for neonatal mortality. PAR of neonatal death and very preterm birth were higher in countries with high MBR compared to low MBR (17.1% (95% CI 13.8–20.2) versus 9.8% (95% Cl 9.6–11.0) for neonatal death and 29.6% (96% CI 28.5–30.6) versus 17.5% (95% CI 15.7–18.3) for very preterm births, respectively). Conclusions Wide variations in MBR and their impact on population outcomes imply that efforts by countries to reduce MBR could improve perinatal outcomes, enabling better long-term child health

Mesenchymal Stem Cells Suppress Inflammatory Cytokines in Lipopolysaccharide Exposed Preterm and Term Human Pregnant Myometrial Cells

Objective  The objective of this study was to determine the cytokine response in human pregnant preterm and term myometrial cells exposed to lipopolysaccharide (LPS) and cocultured with mesenchymal stem cells (MSCs). Study Design  Myometrium was obtained at cesarean delivery in term and preterm patients. Human myometrial cells were exposed to 5 μg/mL LPS for 4 hours followed by 1 μg/mL LPS for 24 hours and were cocultured with MSCs for 24 hours. Culture supernatants were collected at 24 hours and expression of cytokines, including interleukin-1β (IL-1β), IL-6, IL-8, tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), and IL-10, was quantified by enzyme-linked immunosorbent assay. Results  There was significantly increased expression of the proinflammatory cytokines IL-1β, IL-6, IL-8, and TNF-α in preterm myometrial cells treated with LPS compared with untreated preterm myometrial cells. Coculture with MSCs significantly suppressed the proinflammatory cytokine levels in LPS-treated preterm versus treated term myometrial cells. Moreover, MSC cocultured preterm myometrial cells expressed increased levels of the anti-inflammatory cytokines TGF-β and IL-10 compared with treated term myometrial cells. Conclusion  MSCs ameliorate LPS-mediated inflammation in preterm human myometrial cells compared with term myometrial cells. Immunomodulatory effects of MSCs mediated through anti-inflammatory cytokine regulation suggest a potential cell-based therapy for preterm birth

A Structural, Cognitive, and Behavioral Model for Error Analysis of Group B Streptococcus Prophylaxis in Pregnancy

The objective of this study was to develop a structural-cognitive-behavioral model for error analysis of group B streptococcus (GBS) prophylaxis failure, classify delivery cases into this model, and examine compliance with treatment guidelines. A retrospective, cohort study was conducted of women with liveborn pregnancies greater than 24 weeks in April 2018 at a single hospital. We created a structural-cognitive-behavioral model of five assessments for adherence to GBS prophylaxis guidelines and then classified these into four distinct error stages. A descriptive analysis was performed to determine if the pregnancy had a perfect process, a GBS prophylaxis failure, or a fortuitous outcome. There were 313 women who met the study criteria. The rate of GBS positive was 12.8%, negative 37.4%, and unknown 49.8%. The most common errors were cognitive perception errors related to incorrectly documenting GBS status, 57.7% ( N = 79). Of these errors, 15.2% ( N = 12) led to GBS prophylaxis failure. Perfect outcomes occurred in 62.7% ( N = 196) women, GBS prophylaxis failure occurred in 13.7% ( N = 43), and fortuitous outcomes occurred in 23.6% ( N = 74). In our study, we were able to identify structural, cognitive, and behavioral errors that contribute to GBS prophylaxis failures. In other cases, these errors may contribute to fortuitous outcomes

The use of Complementary and Alternative Medicine in pregnancy: Data from the Avon Longitudinal Study of Parents and Children (ALSPAC)

Objectives - To report the frequency of Complementary and Alternative Medicine (CAM) use by a population of pregnant women in the UK. Design - Four postal self-completion questionnaires completed at 8, 12, 18 and 32 weeks’ gestation provided the source of CAMs used. Questions asked for written descriptions about the use of any treatments, pills, medicines, ointments, homeopathic medicines, herbal medicines, supplements, drinks and herbal teas. Setting - An observational, population-based, cohort study of parents and children of 14,541 pregnant women residing within the former county of Avon in south-west England. Data was available for 14,115 women. Results - Over a quarter (26.7%; n = 3774) of women had used a CAM at least once in pregnancy, the use rising from 6% in the 1st trimester to 12.4% in the 2nd to 26.3% in the 3rd. Herbal teas were the most commonly reported CAM at any time in pregnancy (17.7%; n = 2499) followed by homeopathic medicine (14.4%; n = 2038) and then herbal medicine (5.8%; n = 813). The most commonly used herbal product was chamomile used by 14.6% of women, the most commonly used homeopathic product was Arnica used by 3.1% of women. Other CAMs (osteopathy, aromatherapy, acupuncture/acupressure, Chinese herbal medicine, chiropractic, cranial sacral therapy, hypnosis, non-specific massage and reflexology) accounted for less than 1% of users. Conclusions - CAM use in pregnancy, where a wide range of CAMs has been assessed, has not been widely reported. Studies that have been conducted report varying results to this study (26.7%) by between 13.3% and 87% of pregnant women. Survey results will be affected by a number of factors namely the inclusion/exclusion of vitamins and minerals, the timing of data collection, the country of source, the number of women surveyed, and the different selection criteria of either recruiting women to the study or of categorising and identifying a CAM treatment or product

Validation of a Brief Measure for Complicated Grief Specific to Reproductive Loss

Objective Complicated grief reactions follow some pregnancy outcomes, like miscarriage, stillbirth, neonatal death, infant death, selective reduction, or termination of pregnancy. Stigma can delay treatment and worsen outcomes. Screening tools such as the Edinburgh Postnatal Depression Scale detect complicated grief poorly, and specific tools for prolonged or complicated grief after a reproductive loss are cumbersome. In this study, a five-item questionnaire to detect complicated grief after reproductive loss of any type was designed and preliminary validated. Methods A questionnaire patterned after the extensively validated Brief Grief Questionnaire (BGQ) was created by a group of physicians and lay advocates to employ non-traumatic but specific language related to grief after miscarriage, stillbirth, neonatal death, infant death, selective reduction, or termination of pregnancy. One hundred and forty women at a large academic center were recruited in person and via social media to validate the questionnaire with well-studied instruments for anxiety (7-item Panic Disorder Severity Scale, PDSS), trauma (22-item Impact of Events Scale), and reproductive grief and depressive symptoms (33-item Perinatal Grief Scale [PGS]). Results The response rate was 74.9%. Of the 140 participants, 18 (12.8%) experienced their loss during high-risk pregnancies, and 65 (46.4%) were recruited via social media. Seventy-one (51%) respondents had a score \u3e 4, a positive screen for the BGQ. On average, women experienced their loss 2 years prior to participation (IQR 1-5 years). Cronbach\u27s alpha was 0.77 (95% CI: 0.69-0.83). The goodness of fit indices of the model met Fornell and Larker criteria (RMSEA = 0.167, CFI = 0.89, SRMR = 0.06). The AVE was 0.42 and the CR 0.78. Conclusions This investigator-created screening tool is internally consistent and meets preliminary criteria for discriminant validity. This tool can be refined prior to testing for sensitivity and specificity in screening for complicated grief after a reproductive loss

Digital Health Technologies for High-Risk Pregnancy Management: Three Case Studies Using Digilego Framework

OBJECTIVE: High-risk pregnancy (HRP) conditions such as gestational diabetes mellitus (GDM), hypertension (HTN), and peripartum depression (PPD) affect maternal and neonatal health. Patient engagement is critical for effective HRP management (HRPM). While digital technologies and analytics hold promise, emerging research indicates limited and suboptimal support offered by the highly prevalent pregnancy digital solutions within the commercial marketplace. In this article, we describe our efforts to develop a portfolio of digital products leveraging advances in social computing, data science, and digital health. METHODS: We describe three studies that leverage core methods from RESULTS: Scalable social computing models using deep learning classifiers with reasonable accuracy have allowed us to capture and examine psychosociobehavioral drivers associated with HRPM. Our work resulted in two digital health solutions, MyPregnancyChart and MomMind are developed. Initial evaluation of both tools indicates positive acceptance from potential end users. Further evaluation with MomMind revealed statistically significant improvements ( DISCUSSION: Digilego framework provides an integrative methodological lens to gain micro-macro perspective on women\u27s needs, theory integration, engagement optimization, as well as subsequent feature and content engineering, which can be organized into core and specialized digital pathways for women engagement in disease management. CONCLUSION: Future works should focus on implementation and testing of digital solutions that facilitate women to capture, aggregate, preserve, and utilize, otherwise siloed, prenatal information artifacts for enhanced self-management of their high-risk conditions, ultimately leading to improved health outcomes

Digital Technology Needs in Maternal Mental Health: A Qualitative Inquiry.

Digital technologies offer many opportunities to improve mental healthcare management for women seeking pre- and-postnatal care. They provide a discrete, practical medium that is well-suited for the sensitive nature of mental health. Women who are more prone to experiencing peripartum depression (PPD), such as those of low-socioeconomic background or in high-risk pregnancies, can benefit the most from such technologies. However, current digital interventions directed towards this population provide suboptimal support, and their responsiveness to end user needs is quite limited. Our objective is to understand the digital terrain of information needs for low-socioeconomic status women with high-risk pregnancies, specifically within the management of their mental health. This qualitative study consists of semi-structured focus groups and interviews with a sample of nineteen patients. A total of eleven core themes emerged from participant comments. Resulting themes highlighted the need for digital technologies that promote personalized care, a sense of community, and improved provider communication