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Frontiers in Endocrinology 2024The prevalence of obesity among women of reproductive age is increasing worldwide, with implications for serious pregnancy complications. (Meta-Analysis)
Meta-Analysis
BACKGROUND
The prevalence of obesity among women of reproductive age is increasing worldwide, with implications for serious pregnancy complications.
METHODS
Following PRISMA guidelines, a systematic search was conducted in both Chinese and English databases up to December 30, 2020. Pregnancy complications and outcomes including gestational diabetes mellitus (GDM), gestational hypertension (GHTN), pre-eclampsia, cesarean section (CS), induction of labor (IOL), and postpartum hemorrhage (PPH) were analyzed. Random-effects or fixed-effects models were utilized to calculate the odds ratio (OR) with 95% confidence intervals (CIs).
RESULTS
Women with overweight and obesity issues exhibited significantly higher risks of GDM (OR, 2.92, 95%CI, 2.18-2.40 and 3.46, 95%CI, 3.05-3.94, respectively) and GHTN (OR, 2.08, 95%CI, 1.72-2.53 and 3.36, 95%CI, 2.81-4.00, respectively) compared to women of normal weight. Pre-eclampsia was also significantly higher in women with overweight or obesity, with ORs of 1.70 (95%CI, 1.44-2.01) and 2.82 (95%CI, 2.66-3.00), respectively. Additionally, mothers with overweight or obesity issues had significantly higher risks of CS (OR, 1.44, 95%CI, 1.41-1.47, and 2.23, 95%CI, 2.08-2.40), IOL (OR, 1.33, 95%CI, 1.30-1.35 and 1.96, 95%CI, 1.85-2.07), and PPH (OR, 1.67, 95%CI, 1.42-1.96 and 1.88, 95%CI, 1.55-2.29).
CONCLUSION
Women with overweight or obesity issues face increased risks of pregnancy complications and adverse outcomes, indicating dose-dependent effects.
Topics: Humans; Pregnancy; Female; Pregnancy Complications; Pregnancy Outcome; Body Mass Index; Obesity; Diabetes, Gestational; Pre-Eclampsia; Cesarean Section; Overweight; Postpartum Hemorrhage
PubMed: 38894748
DOI: 10.3389/fendo.2024.1280692 -
Nutrients Jun 2024: Emerging evidence suggests that essential trace elements, including iodine, play a vital role in depressive disorders. This study investigated whether prenatal dietary...
: Emerging evidence suggests that essential trace elements, including iodine, play a vital role in depressive disorders. This study investigated whether prenatal dietary iodine intake alone and in combination with supplemental iodine intake during pregnancy were associated with antepartum and postpartum depressive and anhedonia symptoms. : The study population included 837 mothers in the PRogramming of Intergenerational Stress Mechanisms (PRISM) study. The modified BLOCK food frequency questionnaire was used to estimate prenatal dietary and supplemental iodine intake, while the 10-item Edinburg Postpartum Depression Scale (EPDS) ascertained depressive symptoms. Analyses considered the global EPDS score and the anhedonia and depressive symptom subscale scores using dichotomized cutoffs. Logistic regression estimating odds ratios and 95% confidence intervals (CIs) assessed associations of iodine intake in the second trimester of pregnancy and 6-month postpartum depressive and anhedonia symptoms considering dietary intake alone and combined dietary and supplementary intake in separate models. : Most women were Black/Hispanic Black (43%) and non-Black Hispanics (35%), with 39% reporting a high school education or less. The median (interquartile range, IQR) dietary and supplemental iodine intake among Black/Hispanic Black (198 (115, 337) µg/day) and non-Black Hispanic women (195 (126, 323) µg/day) was higher than the overall median intake level of 187 (116, 315) µg/day. Relative to the Institute of Medicine recommended iodine intake level of 160-220 µg/day, women with intake levels < 100 µg/day, 100-<160 µg/day, >220-<400 µg/day and ≥400 µg/day had increased adjusted odds of 6-month postpartum anhedonia symptoms (aOR = 1.74 (95% CI: 1.08, 2.79), 1.25 (95% CI: 0.80, 1.99), 1.31 (95% CI: 0.82, 2.10), and 1.47 (95% CI: 0.86, 2.51), respectively). The corresponding estimates for postpartum global depressive symptoms were similar but of smaller magnitude. Prenatal iodine intake, whether below or above the recommended levels for pregnant women, was most strongly associated with greater anhedonia symptoms, particularly in the 6-month postpartum period. Further studies are warranted to corroborate these findings, as dietary and supplemental iodine intake are amenable to intervention.
Topics: Humans; Female; Pregnancy; Adult; Anhedonia; Depression, Postpartum; Iodine; United States; Cohort Studies; Dietary Supplements; Young Adult; Diet; Hispanic or Latino; Maternal Nutritional Physiological Phenomena; Black or African American; Prenatal Nutritional Physiological Phenomena
PubMed: 38892704
DOI: 10.3390/nu16111771 -
JMIR Public Health and Surveillance Jun 2024Delay in the diagnosis of neurodevelopmental disorders (NDDs) in toddlers and postnatal depression (PND) is a major public health issue. In both cases, early... (Observational Study)
Observational Study
BACKGROUND
Delay in the diagnosis of neurodevelopmental disorders (NDDs) in toddlers and postnatal depression (PND) is a major public health issue. In both cases, early intervention is crucial but too rarely implemented in practice.
OBJECTIVE
Our goal was to determine if a dedicated mobile app can improve screening of 5 NDDs (autism spectrum disorder [ASD], language delay, dyspraxia, dyslexia, and attention-deficit/hyperactivity disorder [ADHD]) and reduce PND incidence.
METHODS
We performed an observational, cross-sectional, data-based study in a population of young parents in France with at least 1 child aged <10 years at the time of inclusion and regularly using Malo, an "all-in-one" multidomain digital health record electronic patient-reported outcome (PRO) app for smartphones. We included the first 50,000 users matching the criteria and agreeing to participate between May 1, 2022, and February 8, 2024. Parents received periodic questionnaires assessing skills in neurodevelopment domains via the app. Mothers accessed a support program to prevent PND and were requested to answer regular PND questionnaires. When any PROs matched predefined criteria, an in-app recommendation was sent to book an appointment with a family physician or pediatrician. The main outcomes were the median age of the infant at the time of notification for possible NDD and the incidence of PND detection after childbirth. One secondary outcome was the relevance of the NDD notification by consultation as assessed by health professionals.
RESULTS
Among 55,618 children median age 4 months (IQR 9), 439 (0.8%) had at least 1 disorder for which consultation was critically necessary. The median ages of notification for probable ASD, language delay, dyspraxia, dyslexia, and ADHD were 32.5 (IQR 12.8), 16 (IQR 13), 36 (IQR 22.5), 80 (IQR 5), and 61 (IQR 15.5) months, respectively. The rate of probable ADHD, ASD, dyslexia, language delay, and dyspraxia in the population of children of the age included between the detection limits of each alert was 1.48%, 0.21%, 1.52%, 0.91%, and 0.37%, respectively. Sensitivity of alert notifications for suspected NDDs as assessed by the physicians was 78.6% and specificity was 98.2%. Among 8243 mothers who completed a PND questionnaire, highly probable PND was detected in 938 (11.4%), corresponding to a reduction of -31% versus our previous study without a support program. Suspected PND was detected a median 96 days (IQR 86) after childbirth. Among 130 users who filled in the satisfaction survey, 99.2% (129/130) found the app easy to use and 70% (91/130) reported that the app improved follow-up of their child. The app was rated 4.8/5 on Apple's App Store.
CONCLUSIONS
Algorithm-based early alerts suggesting NDDs were highly specific with good sensitivity as assessed by real-life practitioners. Early detection of 5 NDDs and PNDs was efficient and led to a possible 31% reduction in PND incidence.
TRIAL REGISTRATION
ClinicalTrials.gov NCT06301087; https://www.clinicaltrials.gov/study/NCT06301087.
Topics: Humans; Cross-Sectional Studies; Female; Mobile Applications; Neurodevelopmental Disorders; Early Diagnosis; Male; Child, Preschool; Child; Depression, Postpartum; Infant; France; Adult; Surveys and Questionnaires
PubMed: 38888952
DOI: 10.2196/58565 -
BMC Women's Health Jun 2024Pregnant women in rural Uganda largely rely on medicinal plants for inducing labor, treating postpartum hemorrhage (PPH), and inducing abortion. 90% of the women in both...
Understanding maternal Ethnomedical Folklore in Central Uganda: a cross-sectional study of herbal remedies for managing Postpartum hemorrhage, inducing uterine contractions and abortion in Najjembe sub-county, Buikwe district.
UNLABELLED
Pregnant women in rural Uganda largely rely on medicinal plants for inducing labor, treating postpartum hemorrhage (PPH), and inducing abortion. 90% of the women in both rural and urban Uganda use plants to manage pregnancy symptoms like constipation, heartburn, morning sickness, body aches, nausea, and vomiting. After delivery women continue using plants to manage postpartum complications and for infant care especially herbal baths. This study documented how ethnomedical folklore has been used to aid childbirth, manage postpartum hemorrhage, and induce abortion.
METHODS
A cross-sectional ethnobotanical survey was conducted from May - December 2023 in Najjemebe sub-county, Buikwe district. 206 respondents from 12 villages were selected using snowball sampling. Key informants included Traditional Birth Attendants (TBAs) and herbalists. Data was collected using semi-structured questionnaires and focus group discussions. Voucher specimens of the plants were identified and authenticated at Makerere University Herbarium. Data were analyzed using descriptive statistics, Informant Consensus factor (ICF), Use Reports (URs), paired comparisons, and GraphPad Prism® version 9.0.0 software.
RESULTS
All respondents (N = 206, 100%), used plants to induce labour, treat PPH, and induce abortion. One hundred four plant species were documented: most cited or preferred were: Hoslundia opposita (N = 109, 53%), Phytolacca dodecandra (N = 72, 35%), and Commelina erecta (N = 47, 23%). The plants belonged to 49 families, Lamiaceae (16.3%) and Fabaceae (14.3%) having the majority of the species. Herbs were 42 (40%) and trees 23 (22%). Oral administration 95(72%) was the commonest, then topical 19 (14.4%) and vaginal 14(10.6%).
CONCLUSION
Health surveys revealed that about 27% of deliveries in Uganda take place outside a health facility. Due to the oxytocic effects of plant species reported in this study, they play a triple role of being uterotonics, abortifacients, and treating postpartum haemmorhage. The dilemma lies in the unknown dosages and toxicity levels that could endanger both the mother's and the unborn child's lives. Due to Uganda's high rates of population growth, overall fertility, maternal mortality, and morbidity, policies, and programmes on gendered health provision need to be reevaluated. Integrating herbal medicine into health care systems appears to be a feasible solution.
Topics: Humans; Female; Uganda; Cross-Sectional Studies; Adult; Pregnancy; Postpartum Hemorrhage; Medicine, African Traditional; Abortion, Induced; Phytotherapy; Plants, Medicinal; Middle Aged; Young Adult; Ethnobotany; Surveys and Questionnaires; Plant Preparations; Midwifery; Male
PubMed: 38886787
DOI: 10.1186/s12905-024-03205-w -
Scientific Reports Jun 2024Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, enabling timely transfer and implementation of prophylactic therapies....
Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, enabling timely transfer and implementation of prophylactic therapies. We attempted to utilize machine learning (ML) using basic pre-labor clinical data and laboratory measurements to predict postpartum Hemoglobin (Hb) in non-complicated singleton pregnancies. The local databases of two academic care centers on patient delivery were incorporated into the current study. Patients with preexisting coagulopathy, traumatic cases, and allogenic blood transfusion were excluded from all analyses. The association of pre-delivery variables with 24-h post-delivery hemoglobin level was evaluated using feature selection with Elastic Net regression and Random Forest algorithms. A suite of ML algorithms was employed to predict post-delivery Hb levels. Out of 2051 pregnant women, 1974 were included in the final analysis. After data pre-processing and redundant variable removal, the top predictors selected via feature selection for predicting post-delivery Hb were parity (B: 0.09 [0.05-0.12]), gestational age, pre-delivery hemoglobin (B:0.83 [0.80-0.85]) and fibrinogen levels (B:0.01 [0.01-0.01]), and pre-labor platelet count (B*1000: 0.77 [0.30-1.23]). Among the trained algorithms, artificial neural network provided the most accurate model (Root mean squared error: 0.62), which was subsequently deployed as a web-based calculator: https://predictivecalculators.shinyapps.io/ANN-HB . The current study shows that ML models could be utilized as accurate predictors of indirect measures of PPH and can be readily incorporated into healthcare systems. Further studies with heterogenous population-based samples may further improve the generalizability of these models.
Topics: Humans; Machine Learning; Female; Hemoglobins; Pregnancy; Adult; Algorithms; Postpartum Hemorrhage; Postpartum Period; Delivery, Obstetric
PubMed: 38886458
DOI: 10.1038/s41598-024-64278-z -
BMC Pregnancy and Childbirth Jun 2024Postpartum depression is a complex mental health condition that often occurs after childbirth and is characterized by persistent sadness, anxiety, and fatigue. Recent...
BACKGROUND
Postpartum depression is a complex mental health condition that often occurs after childbirth and is characterized by persistent sadness, anxiety, and fatigue. Recent research suggests a metabolic component to the disorder. This study aims to investigate the causal relationship between blood metabolites and postpartum depression using mendelian randomization (MR).
METHODS
This study used a bi-directional MR framework to investigate the causal relationship between 1,400 metabolic biomarkers and postpartum depression. We used two specific genome-wide association studies datasets: one with single nucleotide polymorphisms data from mothers diagnosed with postpartum depression and another with blood metabolite data, both of which focused on people of European ancestry. Genetic variants were chosen as instrumental variables from both datasets using strict criteria to improve the robustness of the MR analysis. The combination of these datasets enabled a thorough examination of genetic influences on metabolic profiles associated with postpartum depression. Statistical analyses were conducted using techniques such as inverse variance weighting, weighted median, and model-based estimation, which enabled rigorous causal inference from the observed associations. postpartum depression was defined using endpoint definitions approved by the FinnGen study's clinical expert groups, which included leading experts in their respective medical fields.
RESULTS
The MR analysis identified seven metabolites that could be linked to postpartum depression. Out of these, one metabolite was found to be protective, while six were associated with an increased risk of developing the condition. The results were consistent across multiple MR methods, indicating a significant correlation.
CONCLUSIONS
This study emphasizes the potential of metabolomics for understanding postpartum depression. The discovery of specific metabolites associated with the condition sheds new insights on its pathophysiology and opens up possibilities for future research into targeted treatment strategies.
Topics: Humans; Depression, Postpartum; Female; Mendelian Randomization Analysis; Genome-Wide Association Study; Polymorphism, Single Nucleotide; Metabolomics; Biomarkers; Adult; White People; Pregnancy
PubMed: 38877415
DOI: 10.1186/s12884-024-06628-3 -
Journal of Clinical Psychopharmacology
Topics: Humans; Pakistan; Female; Depression, Postpartum; Anti-Bacterial Agents; Adult; Prescription Drug Overuse; Young Adult; Pregnancy
PubMed: 38875440
DOI: 10.1097/JCP.0000000000001877 -
Journal of the American Heart... Jun 2024Adverse cardiovascular events during pregnancy (eg, preeclampsia) occur at higher rates among individuals with overweight or obesity (body mass index ≥25 kg/m) and...
Improvements in Maternal Cardiovascular Health Over the Perinatal Period Longitudinally Predict Lower Postpartum Psychological Distress Among Individuals Who Began Their Pregnancies With Overweight or Obesity.
BACKGROUND
Adverse cardiovascular events during pregnancy (eg, preeclampsia) occur at higher rates among individuals with overweight or obesity (body mass index ≥25 kg/m) and have been associated with postpartum depression. The present study examined whether changes in cardiovascular health (CVH) during the perinatal period, as defined by the American Heart Association's Life's Essential 8 framework, predicted postpartum psychological functioning among individuals with prepregnancy body mass index ≥25 kg/m.
METHODS AND RESULTS
Pregnant individuals (N = 226; mean ± SD age = 28.43 ± 5.4 years; mean body mass index = 34.17 ± 7.15 kg/m) were recruited at 12 to 20 weeks of gestation (mean, 15.64 ± 2.45 weeks) for a longitudinal study of health and well-being. Participants completed ratings of depression and perceived stress and reported on CVH behaviors (dietary intake, physical activity, nicotine exposure, and sleep) at baseline and at 6 months postpartum. Body mass index and CVH behaviors were used to calculate a composite CVH score at both time points. Linear regression analyses were performed to examine whether change in CVH related to postpartum symptom scores. Because sleep was measured in only a subset of participants (n = 114), analyses were conducted with and without sleep. Improved CVH was associated with lower postpartum depression (β = -0.18, <0.01) and perceived stress (β = -0.13, =0.02) scores. However, when including sleep, these relationships were no longer significant (all >0.4).
CONCLUSIONS
Improvements in CVH from early pregnancy to 6 months postpartum were associated with lower postpartum depressive symptoms and perceived stress but not when including sleep in the CVH metric, potentially due to the large reduction in sample size. These data suggest that intervening during pregnancy to promote CVH may improve postpartum psychological functioning among high-risk individuals.
Topics: Humans; Female; Pregnancy; Adult; Longitudinal Studies; Depression, Postpartum; Body Mass Index; Postpartum Period; Obesity; Psychological Distress; Overweight; Young Adult; Maternal Health; Sleep; Risk Factors; Time Factors; Exercise; Pregnancy Complications
PubMed: 38874183
DOI: 10.1161/JAHA.123.034153 -
BMC Medical Informatics and Decision... Jun 2024Cesarean section-induced postpartum hemorrhage (PPH) potentially causes anemia and hypovolemic shock in pregnant women. Hence, it is helpful for obstetricians and...
BACKGROUND
Cesarean section-induced postpartum hemorrhage (PPH) potentially causes anemia and hypovolemic shock in pregnant women. Hence, it is helpful for obstetricians and anesthesiologists to prepare pre-emptive prevention when predicting PPH occurrence in advance. However, current works on PPH prediction focus on whether PPH occurs rather than assessing PPH amount. To this end, this work studies quantitative PPH prediction with machine learning (ML).
METHODS
The study cohort in this paper was selected from individuals with PPH who were hospitalized at Shijiazhuang Obstetrics and Gynecology Hospital from 2020 to 2022. In this study cohort, we built a dataset with 6,144 subjects covering clinical parameters, anesthesia operation records, laboratory examination results, and other information in the electronic medical record system. Based on our built dataset, we exploit six different ML models, including logistic regression, linear regression, gradient boosting, XGBoost, multilayer perceptron, and random forest, to automatically predict the amount of bleeding during cesarean section. Eighty percent of the dataset was used as model training, and 20 was used for verification. Those ML models are constantly verified and improved by root mean squared error(RMSE) and mean absolute error(MAE). Moreover, we also leverage the importance of permutation and partial dependence plot (PDP) to discuss their feasibility.
RESULT
The experiment results show that random forest obtains the highest accuracy for PPH amount prediction compared to other ML methods. Random forest reaches the mean absolute error of 21.7, less than 5.4 prediction error. It also gains the root mean squared error of 33.75, less than 9.3 prediction error. On the other hand, the experimental results also disclose indicators that contributed most to PPH prediction, including Ca, hemoglobin, white blood cells, platelets, Na, and K.
CONCLUSION
It effectively predicts the amount of PPH during a cesarean section by ML methods, especially random forest. With the above insight, ML predicting PPH amounts provides early warning for clinicians, thus reducing complications and improving cesarean sections' safety. Furthermore, the importance of ML and permutation, complemented by incorporating PDP, promises to provide clinicians with a transparent indication of individual risk prediction.
Topics: Humans; Female; Cesarean Section; Postpartum Hemorrhage; Machine Learning; Pregnancy; Adult
PubMed: 38872184
DOI: 10.1186/s12911-024-02571-7 -
JAMA Network Open Jun 2024Innovative approaches are needed to address the increasing rate of postpartum morbidity and mortality associated with hypertensive disorders.
IMPORTANCE
Innovative approaches are needed to address the increasing rate of postpartum morbidity and mortality associated with hypertensive disorders.
OBJECTIVE
To determine whether assessing maternal blood pressure (BP) and associated symptoms at time of well-child visits is associated with increased detection of postpartum preeclampsia and need for hospitalization for medical management.
DESIGN, SETTING, AND PARTICIPANTS
This is a pre-post quality improvement (QI) study. Individuals who attended the well-child visits between preimplementation (December 2017 to December 2018) were compared with individuals who enrolled after the implementation of the QI program (March 2019 to December 2019). Individuals were enrolled at an academic pediatric clinic. Eligible participants included birth mothers who delivered at the hospital and brought their newborn for well-child check at 2 days, 2 weeks, and 2 months. A total of 620 individuals were screened in the preintervention cohort and 680 individuals were screened in the QI program. Data was analyzed from March to July 2022.
EXPOSURES
BP evaluation and preeclampsia symptoms screening were performed at the time of the well-child visit. A management algorithm-with criteria for routine or early postpartum visits, or prompt referral to the obstetric emergency department-was followed.
MAIN OUTCOME AND MEASURES
Readmission due to postpartum preeclampsia. Comparisons across groups were performed using a Fisher exact test for categorical variables, and t tests or Mann-Whitney tests for continuous variables.
RESULTS
A total of 595 individuals (mean [SD] age, 27.2 [6.1] years) were eligible for analysis in the preintervention cohort and 565 individuals (mean [SD] age, 27.0 [5.8] years) were eligible in the postintervention cohort. Baseline demographic information including age, race and ethnicity, body mass index, nulliparity, and factors associated with increased risk for preeclampsia were not significantly different in the preintervention cohort and postintervention QI program. The rate of readmission for postpartum preeclampsia differed significantly in the preintervention cohort (13 individuals [2.1%]) and the postintervention cohort (29 individuals [5.6%]) (P = .007). In the postintervention QI cohort, there was a significantly earlier time frame of readmission (median [IQR] 10.0 [10.0-11.0] days post partum for preintervention vs 7.0 [6.0-10.5] days post partum for postintervention; P = .001). In both time periods, a total of 42 patients were readmitted due to postpartum preeclampsia, of which 21 (50%) had de novo postpartum preeclampsia.
CONCLUSIONS AND RELEVANCE
This QI program allowed for increased and earlier readmission due to postpartum preeclampsia. Further studies confirming generalizability and mitigating associated adverse outcomes are needed.
Topics: Humans; Female; Adult; Pregnancy; Pre-Eclampsia; Early Diagnosis; Quality Improvement; Patient Readmission; Postpartum Period; Hypertension; Infant, Newborn; Puerperal Disorders
PubMed: 38869897
DOI: 10.1001/jamanetworkopen.2024.16844