Objectives: to analyze the factors associated with maternal well-being during childbirth among postpartum women in Minas Gerais.
Methods: a cross-sectional study nested within a cohort was conducted with postpartum women in a municipality of Minas Gerais. The Maternal Well-being in Childbirth Scale 2 was used. The prevalence of maternal well-being during childbirth was estimated. The magnitude of the association between maternal distress and care practices was estimated using the Prevalence Ratio (PR), applying Poisson regression.
Results: a total of 183 postpartum women aged between 15 and 46 years participated, with 26.2%, 27.9%, and 45.9% reporting excellent, adequate, and poor well-being during childbirth care, respectively. Maternal distress was more prevalent among women who underwent cesarean sections (PR = 1.60) and those who did not receive breastfeeding information (PR = 1.59).
Conclusions: a high prevalence of maternal distress during childbirth was observed, associated with cesarean delivery and the lack of breastfeeding information.
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http://dx.doi.org/10.1590/0034-7167-2023-0304 | DOI Listing |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11654529 | PMC |
Nihon Koshu Eisei Zasshi
December 2024
Department of Public Health, Kurume University School of Medicine.
Objectives We evaluated the number of hospitalizations among public assistance recipients for each major classification according to the International Classification of Diseases 10th Revision (ICD-10), adjusting for sex and age differences in the general Japanese population. This study aimed to provide a comprehensive assessment of hospitalization patterns among public assistance recipients by disease category.Methods We used indirect methods to adjust for sex and age, with public assistance recipients and the entire Japanese population as the observation and reference groups, respectively.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
December 2024
Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, 5612 AZ, North Brabant, The Netherlands.
This study aimed to predict preterm birth in nulliparous women using machine learning and easily accessible variables from prenatal visits. Elastic net regularized logistic regression models were developed and evaluated using 5-fold cross-validation on data from 8,830 women in the Nulliparous Pregnancy Outcomes Study: New Mothers-to-Be (nuMoM2b) dataset at three prenatal visits: - , - , and - weeks of gestational age (GA). The models' performance, assessed using Area Under the Curve (AUC), sensitivity, specificity, and accuracy, consistently improved with the incorporation of data from later prenatal visits.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
December 2024
Department of Paediatrics & Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Background: Adverse birth outcomes (preterm birth, low birth weight, small for gestational age, and stillbirth) seem to persist in infants born to people with HIV, even in the context of maternal antiretroviral therapy. However, findings have been disparate, inconclusive, and difficult to compare directly across settings, partly owing to variable outcome definitions. We aimed to collate, compare, and map existing adverse birth outcome definitions to inform a harmonized approach to universally measure these outcomes in studies including pregnant people with HIV.
View Article and Find Full Text PDFBackground: With the COVID-19 emergency, the provision of healthcare had to be reorganized. Community Health Services for Families of Trieste adopted new methods to ensure continuity of care and the maintenance of the Standards and Good Practices of the Baby Friendly Initiative of UNICEF for the Birth Care Pathway. The aim of the study was to identify the perceived needs of women, couples, caregivers, and health professionals during the COVID-19 pandemic and evaluate new healthcare strategies, identifying weaknesses and strengths, and future developments.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
December 2024
Department of Gynecology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, China.
Purpose: This study aimed to identify novel biomarkers for preeclampsia (PE) diagnosis by integrating Weighted Gene Co-expression Network Analysis (WGCNA) with machine learning techniques.
Patients And Methods: We obtained the PE dataset GSE25906 from the gene expression omnibus (GEO) database. Analysis of differentially expressed genes (DEGs) and module genes with Limma and Weighted Gene Co-expression Network analysis (WGCNA).
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