BMC Pregnancy and Childbirth最新文献

{"title":"Women's experience of body weight management during and post-pregnancy: a mixed methods approach.","authors":"Rachel Nolan, Alison M Gallagher, Alyson J Hill","doi":"10.1186/s12884-024-07033-6","DOIUrl":"10.1186/s12884-024-07033-6","url":null,"abstract":"<p><strong>Background: </strong>Gaining excessive weight during pregnancy has been linked with adverse effects including increased risk of caesarean delivery and postpartum weight retention. Despite these recognised risks, currently no UK/Ireland gestational weight gain (GWG) guidelines exist, women are not routinely weighed throughout pregnancy and consequently, women's understanding of the importance of weight management during, and post-pregnancy remains poor. The present study explored factors influencing weight change during and post-pregnancy and identified potential opportunities that could help women manage weight during these periods.</p><p><strong>Methods: </strong>Women aged 18-45 years-old who had an uncomplicated pregnancy within the last 3 years were invited to complete an online questionnaire (n = 108) regarding their experience of changes in body weight during and post-pregnancy. Follow on focus groups (n = 13 women) were conducted online within the same population to delve deeper into the topic, the sessions were recorded, transcribed verbatim and data subjected to directive content analysis based on the socio-ecological model.</p><p><strong>Results: </strong>Respondents reported in the online questionnaire, they did not receive enough information around weight management during (81.5%) and post-pregnancy (86.1%). Focus group qualitative data identified barriers to managing weight at each level of the ecological model, at the intrapersonal (e.g., changes in diet), interpersonal (e.g., conflicting advice), environment and society (e.g., COVID-19 pandemic), and institutional and policy (e.g., system failing) levels. Potential strategies to help manage weight were also identified, at the intrapersonal (e.g., need for further information), interpersonal (e.g., support groups), environment and society (e.g., messaging), and institutional and policy (e.g., further follow-up care) levels.</p><p><strong>Conclusions: </strong>Mothers report receiving insufficient information around weight management, with barriers identified at each level of the ecological model. Highlighting that support and change is needed on multiple levels both during and post-pregnancy, with potential strategies identified, which could potentially inform future studies.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"823"},"PeriodicalIF":2.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11660891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing decision-making in tubal ectopic pregnancy using a machine learning approach to expectant management: a clinical article.","authors":"Liron Jurman, Karin Brisker, Raz Ruach Hasdai, Omer Weitzner, Yair Daykan, Zvi Klein, Ron Schonman, Yael Yagur","doi":"10.1186/s12884-024-07035-4","DOIUrl":"10.1186/s12884-024-07035-4","url":null,"abstract":"<p><strong>Objective: </strong>To refine decision-making regarding expectant management for ectopic pregnancy (EP) using machine learning.</p><p><strong>Methods: </strong>This retrospective study addressed expectant management in stable patients with ampullar EP, 2014-2022. Electronic medical record data included demographics, medical history, admission data, sonographic findings, and laboratory results. Follow-up data on βhCG levels and success rates were collected. Statistical analysis incorporated a Decision Tree Classifier, a decision tree-based machine learning model. The cohort was divided into training and testing groups for the machine learning model. This model was evaluated for accuracy, precision, recall, and F1 score to predict success of expectant management.</p><p><strong>Results: </strong>Among 878 cases of EP, the expectant management cohort, comprising 221 cases, exhibited a success rate of 79.6%, with 20.4% requiring subsequent intervention. Mean βhCG levels on admission were 1056.8 ± 1323.5 mIU. The Decision Tree Classifier demonstrated an accuracy of 89%, with precision, recall, and F1 scores of 92%, 95%, and 94%, respectively. Factors for predicting success included clinical symptoms such as pain, the percentage decrease in βhCG levels, gestational age and βhCG level at decision day. Moderate impactful features were white blood cell count, gravidity and maximum tubal dimensions. Smoking status, duration (hours) from time of EP diagnosis to second βhCG test and marital status were minimal significant predictors of success.</p><p><strong>Conclusion: </strong>The Decision Tree-Based classifier model, with 92% precision and 95% recall, may be a valuable tool for predicting treatment success in hemodynamically stable patients with EP, particularly within the initial 24 h of βhCG follow-up.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"825"},"PeriodicalIF":2.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11660628/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and analysis of a telemonitoring system for high-risk pregnant women in need of special care or attention.","authors":"Mojdeh Nazari, Shadi Moayed Rezaie, Fereshteh Yaseri, Hossein Sadr, Elham Nazari","doi":"10.1186/s12884-024-07019-4","DOIUrl":"10.1186/s12884-024-07019-4","url":null,"abstract":"<p><strong>Background: </strong>High-risk pregnancies, characterized by underlying health issues or unusual circumstances, pose increased risks to both maternal and neonatal health during pregnancy and childbirth. Global guidelines emphasize the importance of early identification, monitoring, and intervention to mitigate these risks.</p><p><strong>Method: </strong>We decided to design and implement a telemonitoring system for remotely monitoring and managing pregnancies in women with conditions such as hypertension, diabetes, or high-risk pregnancy. When a high-risk pregnant mom is discharged from the hospital, the Healthcare Center or Integrated Healthcare Services Center in her area is immediately notified via SMS to ensure her condition is monitored remotely. In addition to sending notifications, the patient's medical record, post-discharge care recommendations, drug prescription, re-visit time, and contact details are also sent to them via the application. The high-risk pregnant mom is followed up and all her information is recorded in the application for further use. To evaluate the usability of the proposed telemonitoring system, we conducted a laboratory study involving 92 participants, including pregnant mothers' care experts at hospitals, healthcare center experts, midwives at integrated healthcare services centers, and midwifery department experts with varying levels of digital skills. Participants performed activities related to the application's services, while their satisfaction was measured using the QUIS 7.0 questionnaires covering multiple aspects of usability, including user interface, system capabilities, and online help, with ratings on a Likert scale.</p><p><strong>Result: </strong>The usability evaluation revealed that the average satisfaction score across all usability dimensions was above 8, demonstrating a satisfactory level of system usage from all user perspectives. Additionally, the close alignment of mean and median scores, along with standard deviations below 1 for several dimensions, indicated consistent positive feedback among users.</p><p><strong>Conclusion: </strong>Our telemonitoring system demonstrates promise for enhancing the management of high-risk pregnancies, facilitating better health outcomes for mothers and infants through effective remote monitoring and support. The usability test results underscore the platform's effectiveness and user satisfaction, contributing valuable insights for future improvements in high-risk pregnancy care.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"817"},"PeriodicalIF":2.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11656914/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of pregnancy and neonatal outcomes in 100 pregnant women with Rh-negative blood type.","authors":"Bing-Cai Bi, Hong-Yan Yang, Jun-You Su, Li Deng","doi":"10.1186/s12884-024-06981-3","DOIUrl":"10.1186/s12884-024-06981-3","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to explore variations in prenatal care, delivery methods, influencing factors, and neonatal outcomes among Rh-negative pregnant women, so as to improve pregnancy healthcare for this demographic, raise the quality of maternal-fetal management, and safeguard the health of both mother and infant.</p><p><strong>Methods: </strong>This study included 200 women who received routine prenatal care, exhibited no other pregnancy complications, and were admitted for delivery. They were divided into an observation group (100 Rh-negative blood type) and a control group (100 Rh-positive blood type). The study examined differences in pregnancy management, clinical characteristics and pregnancy outcomes between the two groups.</p><p><strong>Results: </strong>The results indicated that singleton pregnancies in Rh-negative mothers are associated with significantly higher rates of postpartum blood loss (305.1 ± 183.8 vs. 246.1 ± 84.9 mL, P = 0.004), neonatal hyperbilirubinemia (39% vs. 23%, P = 0.014), low birth weight (11% vs. 2%, P = 0.01), and NICU admission (30% vs. 18%, P = 0.046) compared to the control group. Among Rh-negative mothers, subgroup analysis by ethnicity revealed a higher incidence of fetal distress in the other ethnic groups compared to the Han and Zhuang groups (16.7%, 0, 6.5%, respectively, P = 0.025). Subgroup analysis based on ABO blood type within Rh-negative mothers did not show any statistical significance in various outcomes (all P > 0.05). Infants with neonatal hyperbilirubinemia born to Rh-negative mothers experienced a quicker resolution of hyperbilirubinemia compared to those whose mothers did not receive intramuscular anti-D immunoglobulin [1.0 (1.0, 1.5) vs. 5.0 (1.5, 10.0), P = 0.002].</p><p><strong>Conclusions: </strong>The Rh-negative blood type is linked to higher risks of neonatal hyperbilirubinemia, low birth weight, and increased postpartum hemorrhage, resulting in detrimental pregnancy outcomes. Administering anti-D immunoglobulin speeds up the resolution of neonatal hyperbilirubinemia. Thus, prudent and efficient use of anti-D immunoglobulin can mitigate adverse outcomes for both mothers and newborns.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"815"},"PeriodicalIF":2.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11653918/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142852482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating causal associations of chronotype with pregnancy and perinatal outcomes and its interactions with insomnia and sleep duration: a mendelian randomization study.","authors":"Qian Yang, Maria C Magnus, Fanny Kilpi, Gillian Santorelli, Ana Goncalves Soares, Jane West, Per Magnus, Siri E Håberg, Kate Tilling, Deborah A Lawlor, M Carolina Borges, Eleanor Sanderson","doi":"10.1186/s12884-024-07023-8","DOIUrl":"10.1186/s12884-024-07023-8","url":null,"abstract":"<p><strong>Background: </strong>Observational studies suggested chronotype was associated with pregnancy and perinatal outcomes. Whether these associations are causal is unclear. Our aims are to use Mendelian randomization (MR) to explore (1) associations of evening preference with stillbirth, miscarriage, gestational diabetes, hypertensive disorders of pregnancy, perinatal depression, preterm birth and offspring birthweight; and (2) differences in associations of insomnia and sleep duration with those outcomes between chronotype preferences.</p><p><strong>Methods: </strong>We conducted two-sample MR using 105 genetic variants reported in a genome-wide association study (N = 248,100) to instrument for lifelong predisposition to evening- versus morning-preference. We generated variant-outcome associations in European ancestry women from UK Biobank (UKB, N = 176,897), Avon Longitudinal Study of Parents and Children (ALSPAC, N = 6826), Born in Bradford (BiB, N = 2940) and the Norwegian Mother, Father and Child Cohort Study (MoBa, N = 57,430), and extracted equivalent associations from FinnGen (N = 190,879). We used inverse variance weighted (IVW) as main analysis, with weighted median and MR-Egger as sensitivity analyses. Relying on the individual participant data from UKB, ALSPAC, BiB and MoBa, we also conducted IVW analyses of insomnia and sleep duration on the pregnancy and perinatal outcomes, stratified by genetically predicted chronotypes.</p><p><strong>Results: </strong>In IVW and sensitivity analyses, we did not find robust evidence of associations of chronotype with the outcomes. Insomnia was associated with a higher risk of preterm birth among evening preference women (odds ratio 1.61, 95% confidence interval: 1.17, 2.21), but not among morning preference women (odds ratio 0.87, 95% confidence interval: 0.64, 1.18), with an interaction P-value = 0.01. There was no evidence of interactions between insomnia and chronotype on other outcomes, or between sleep duration and chronotype on any outcomes.</p><p><strong>Conclusions: </strong>This study raises the possibility of a higher risk of preterm birth among women with insomnia who also have an evening preference. Our findings warrant replications due to imprecise estimates.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"816"},"PeriodicalIF":2.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11654309/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The association between gestational diabetes and fear of childbirth: a longitudinal register study.","authors":"Josephine Savard, Guro Pauck Bernhardsen, Anu Mykkänen, Leea Keski-Nisula, Soili Marianne Lehto","doi":"10.1186/s12884-024-07022-9","DOIUrl":"10.1186/s12884-024-07022-9","url":null,"abstract":"<p><strong>Background: </strong>Gestational diabetes mellitus is a common condition known to be associated with pregnancy complications, larger fetus size and depression, and may therefore lead to increased concerns linked to childbirth. We sought to determine whether gestational diabetes mellitus is linked to fear of childbirth, and whether the possible association is mediated by depressive symptoms.</p><p><strong>Methods: </strong>This study includes women who gave birth at the Kuopio University Hospital between 2019-2022 and had reported their level of fear of childbirth after gestational week 28 (n = 3293). Two outcome measures of fear of childbirth were used: self-rated intensity on a visual analogue scale, and obstetrician-confirmed diagnosis. Gestational diabetes mellitus was diagnosed based on plasma glucose concentrations in fasting state (≥ 5.3 mmol/l) and after a 75 g glucose load (one hour: ≥ 10.0 mmol/l, two hours: ≥ 8.6 mmol/l). The Edinburgh Postnatal Depression Scale (EPDS) was used to assess depressive symptoms in the third trimester. We performed logistic and linear regression analyses while adjusting for possible confounding factors and examined the controlled direct effect by including depressive symptoms in the model.</p><p><strong>Results: </strong>Gestational diabetes mellitus was associated with increased risk of fear of childbirth diagnosis (OR = 1.42, 95% CI 1.11─1.73) and higher levels of fear of childbirth (B = 0.31, 95% CI 0.09─0.53), but the associations were attenuated and no longer significant after further adjustments for body mass index and health behaviors (OR = 1.22, 95% CI 0.91─1.5; B = 0.11, 95% CI -0.13─0.35). Inclusion of depressive symptoms in the model attenuated the non-significant estimates further.</p><p><strong>Conclusions: </strong>The observed association between fear of childbirth and gestational diabetes mellitus in previous studies may result from the lack of adjustments for confounding factors.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"814"},"PeriodicalIF":2.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11654169/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142852423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gestational weight gain during pregnancy is the risk factor for Omicron infection: a retrospective case-control study.","authors":"Lin Yao, Peizhen Zhang, Jin Zhou, Tiantian He, Zhangmin Tan, Chuo Li, Yuzhu Yin","doi":"10.1186/s12884-024-07025-6","DOIUrl":"10.1186/s12884-024-07025-6","url":null,"abstract":"<p><strong>Background: </strong>It remains unclear whether gestational weight gain (GWG) during pregnancy is associated with Omicron infection in pregnant women.</p><p><strong>Objective: </strong>To investigate whether gestational weight gain during pregnancy is associated with an increased risk of Omicron infection.</p><p><strong>Methods: </strong>This is a retrospective case-control study of pregnant women from The Third Affiliated Hospital of Sun Yat-sen University from December 1 to 31, 2022. Pregnant women infected with Omicron were compared to those uninfected using chi-square statistics for categorical variables and t-tests or ANOVA for continuous variables. Multivariable logistic regression, along with subgroup analyses, was used to investigate the association between gestational weight gain during pregnancy and Omicron infection.</p><p><strong>Results: </strong>Our study included 369 pregnant women who met the eligibility criteria. The proportion of pregnant women in the term, infected and uninfected with Omicron was 113(30.6%) and 256(69.4%). Classified pregnant women according to GWG during pregnancy, GWG during pregnancy above IOM was significantly associated with an increased risk of Omicron infection (P = 0.006). After adjusting for demographic factors and pregnancy complications, this association was particularly notable (OR = 2.55, 95%CI = 1.35-4.85, P = 0.004). Classified pregnant women according to pregestational BMI, in normal-weight pregnant women, GWG during pregnancy above IOM was significantly associated with an increased risk of Omicron infection (P = 0.01). After adjusting for demographic factors and pregnancy complications, this association was particularly notable (OR = 2.56, 95%CI = 1.24-5.31, P = 0.01).</p><p><strong>Conclusion: </strong>Among women with normal weight, gestational weight gain during pregnancy above IOM was an independent risk factor for Omicron infection.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"818"},"PeriodicalIF":2.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11657632/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142852178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is expectant management feasible for select patients diagnosed with a heterotopic tubal pregnancy following in vitro fertilization/intracytoplasmic sperm injection?","authors":"Yuyao Mao, Yangqin Peng, Mingxiang Zheng, Pei Cai, Fei Gong, Hui Chen, Ge Lin, Yan Ouyang, Xihong Li","doi":"10.1186/s12884-024-07029-2","DOIUrl":"10.1186/s12884-024-07029-2","url":null,"abstract":"<p><strong>Background: </strong>Heterotopic pregnancy (HP) is a rare type of pathological pregnancy, and the most common site of concomitant ectopic pregnancy (EP) is the fallopian tube. Some studies have shown that expectant treatment could be considered because some EPs tend to regress spontaneously. However, data on the expectant treatment of HP are lacking. This study aimed to examine the outcomes of eutopic pregnancies following expectant management of concomitant tubal EP after in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI).</p><p><strong>Methods: </strong>This was a retrospective, observational matched cohort study. All patients who conceived with tubal HP (HTP) via IVF/ICSI and were treated expectantly between January 2010 and December 2021 were enrolled. Each HTP patient managed expectantly (A) was randomly matched with one control patient who conceived with a solely eutopic pregnancy (B) and one HTP patient who underwent surgical therapy (C) from our clinical database according to predefined criteria. The expectant group and the control groups were matched for maternal age (MA; ±1 year), gravidity (0; ≥1) and gestational age (GA) at presentation (± 2 days). The pregnancy outcomes of the study group and the control groups were compared.</p><p><strong>Results: </strong>More than three-quarters of the EPs in patients treated expectantly were inhomogeneous solid masses (n = 95, 76.6%), and an empty gestational sac was the second most common (n = 18, 14.5%). The rates of live birth (76.6%, 79.0%, 73.4%; P = 0.647 (A versus B); P = 0.557 (A versus C)) and early miscarriage (21.8%, 19.4%, 25.8%; P = 0.637 (A versus B); P = 0.456 (A versus C)) in the expectant group were similar to those in the eutopic group and those in the surgical group. There were no significant differences in of the preterm birth rate (7.3%, 7.3%, 7.3%; P = 1.000 (A versus B); P = 1.000 (A versus C)), perinatal mortality (1.0%, 1.0%, 1.1%; P = 1.000 (A versus B); P = 1.000 (A versus C)), GA at delivery (38.7 ± 2.1, 38.4 ± 2.4, 38.5 ± 2.3 weeks; P = 0.286 (A versus B); P = 0.425 (A versus C)) or birth weight (3294.8 ± 507.2, 3238.2 ± 646.1, 3194.5 ± 452.9 g; P = 0.498 (A versus B); P = 0.157 (A versus C)).</p><p><strong>Conclusion: </strong>Expectant management was an option for select women with HTP. The prognoses of the concomitant eutopic pregnancies were comparable to those of the solely eutopic singleton pregnancies and the HTPs managed surgically. The application of this protocol in clinical practice significantly reduces the need for surgical or medical treatment of EP. Notably, close follow-up is required, and patients need to be vigilant and have immediate access to medical resources in case of an emergency.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"813"},"PeriodicalIF":2.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11653753/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142852483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting maternal risk level using machine learning models.","authors":"Sulaiman Salim Al Mashrafi, Laleh Tafakori, Mali Abdollahian","doi":"10.1186/s12884-024-07030-9","DOIUrl":"10.1186/s12884-024-07030-9","url":null,"abstract":"<p><strong>Background: </strong>Maternal morbidity and mortality remain critical health concerns globally. As a result, reducing the maternal mortality ratio (MMR) is part of goal 3 in the global sustainable development goals (SDGs), and previously, it was an important indicator in the Millennium Development Goals (MDGs). Therefore, identifying high-risk groups during pregnancy is crucial for decision-makers and medical practitioners to mitigate mortality and morbidity. However, the availability of accurate predictive models for maternal mortality and maternal health risks is challenging. Compared with traditional predictive models, machine learning algorithms have emerged as promising predictive modelling methods providing accurate predictive models.</p><p><strong>Methods: </strong>This work aims to explore the potential of machine learning (ML) algorithms in maternal risk level prediction using a nationwide maternal mortality dataset from Oman for the first time. A total of 402 maternal deaths from 1991 to 2023 in Oman were included in this study. We utilised principal component analysis (PCA) in the ML algorithms and compared them to the results of model performance without PCA. We employed and compared ten ML algorithms, including decision tree (DT), random forest (RF), K-Nearest Neighbors (KNN), Naïve Bayes (NB), Extreme Gradient Boosting (xgboost), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Logistic Regression (LR), Support Vector Machine (SVM) and Artificial Neural Network (ANN). Different metrics, including, accuracy, sensitivity, precision, and the F1- score, were utilised to assess Model performance.</p><p><strong>Results: </strong>The results indicated that the RF model outperformed the other methods in predicting the risk level (low or high) with an accuracy of 75.2%, precision of 85.7% and F1- score of 73% after PCA was applied.</p><p><strong>Conclusions: </strong>We applied several machine learning models to predict maternal risk levels for the first time using real data from Oman. RF outperformed the other algorithms in this classification problem. A reliable estimate of maternal risk level would facilitate intervention plans for medical practitioners to reduce maternal death.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"820"},"PeriodicalIF":2.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11657143/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142852484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy and safety of domperidone and metoclopramide on human milk production in postpartum mothers: a bayesian network meta-analysis of randomized controlled trials.","authors":"Si Si, Ge Zhao, Guang Song, Jing Liu","doi":"10.1186/s12884-024-07027-4","DOIUrl":"10.1186/s12884-024-07027-4","url":null,"abstract":"<p><strong>Background: </strong>Breastfeeding is the most advantageous nutrition for infants because of its many health benefits. However, lactation insufficiency is a prevalent issue among women, particularly those who give birth prematurely. Galactagogues, such as domperidone and metoclopramide, have been reported and may be beneficial for lactation insufficiency. However, the optimal pharmacological galactagogue remains unclear.</p><p><strong>Methods: </strong>The PubMed, MEDLINE, Embase, ClinicalTrials.gov, and Cochrane Library databases were searched from their inception to April 23, 2023. The primary aim of this research was to assess the efficacy and safety of domperidone and metoclopramide using Bayesian network meta-analysis. The efficacy outcome was the increased breast milk volume (in mL/day). The safety outcome was the frequency of maternal drug-related adverse events during the study period.</p><p><strong>Results: </strong>Seventeen randomized controlled trials were included in the final analyses. Preterm mothers who took domperidone had a greater increase in breast milk volume than those who took metoclopramide or placebo (domperidone vs. metoclopramide: MD = 82.84, 95% CI: 37.04-118.95; domperidone vs. placebo: MD = 88.30, 95% CI: 59.48-118.62). However, in the term mothers, domperidone did not show the above benefit compared with metoclopramide or placebo (domperidone vs. metoclopramide: MD = 93.67, 95% CI: -186.11-375.59; domperidone vs. placebo: MD = 126.25, 95% CI: -49.91-304.55). Both in preterm and term mothers, metoclopramide was no better than the placebo. There was no difference in the frequency of maternal drug-related adverse outcomes among domperidone, metoclopramide, and placebo.</p><p><strong>Conclusion: </strong>Domperidone increased the daily breast milk volume in mothers of preterm infants, without serious adverse events. However, this conclusion is limited due to the small sample sizes in the studies analyzed.</p>","PeriodicalId":9033,"journal":{"name":"BMC Pregnancy and Childbirth","volume":"24 1","pages":"819"},"PeriodicalIF":2.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11656551/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}