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Solutions Using Machine Learning for Diabetes
Published in Punit Gupta, Dinesh Kumar Saini, Rohit Verma, Healthcare Solutions Using Machine Learning and Informatics, 2023
Jabar H. Yousif, Kashif Zia, Durgesh Srivastava
Diabetes affects individuals, families, businesses, and society as a whole. Six Arabic countries are among the ten highest globally for the prevalence of diabetes: Egypt, United Arab Emirates (UAE), Bahrain, Kuwait, Oman, and Saudi Arabia. Dietary modifications and physical activities can prevent all types of diabetes. Typically, health care providers treat diabetes with weight management plans, exercise, self-monitoring of blood glucose, and medication if required. Gestational diabetes is associated with several risks, including hypertensive disorder, Cesarean delivery, preterm birth, and infant shoulder dystocia [17].
Pathophysiology of Diabetes
Published in Jahangir Moini, Matthew Adams, Anthony LoGalbo, Complications of Diabetes Mellitus, 2022
Jahangir Moini, Matthew Adams, Anthony LoGalbo
Gestational diabetes mellitus (GDM) develops during pregnancy, characterized by a reduced ability to metabolize carbohydrates. This is usually due to a deficiency of insulin or insulin resistance. The condition disappears after the infant is delivered. However, in a large number of cases, it returns years afterward, as type 2 diabetes mellitus. Placental lactogen and extensive destruction of insulin by the placenta appear to play roles in precipitating GDM. Usually, pregnant women are screened for GDM between 24 and 28 weeks of gestation, via the 50 g, 1-hour glucose tolerance test. If the patient has risk factors for GDM, she will be screened in the first trimester. Risk factors include any previous pregnancy that involved GDM or a neonate heavier than 4,500 g at birth, unexplained fetal death, family history of diabetes in close relatives, previous persistent glycosuria, and a body mass index (BMI) over 30 kg/square meter (m2). With gestational diabetes, results are most accurately obtained via a glucose tolerance test. If the result is 140–199 mg/dL, a full glucose tolerance test is done. If the glucose is 200 mg/dL or higher, insulin is given. When 2 or more results are abnormal, the patient is placed on a controlled diet for the remainder of the pregnancy. If needed, insulin or oral hypoglycemics are administered. Rigid control of plasma glucose during pregnancy eliminates risks of adverse outcomes almost completely.
Exercise and pregnancy
Published in Hung N. Winn, Frank A. Chervenak, Roberto Romero, Clinical Maternal-Fetal Medicine Online, 2021
The current published literature includes the following consistent findings (3): Women who exercised before pregnancy and continued to do so during pregnancy tend to weigh less, gain less weight, and deliver by and large normal size and fewer macrosomic babies.All women, regardless of initial level of physical activity, decrease their activity as pregnancy progresses.Active pregnant diabetic women can prevent or ameliorate gestational diabetes.Physically active women appear to tolerate labor pain better.Lifestyle modification in pregnancy has a beneficial effect on mothers, their families, and future generations.
Effectiveness of mobile health interventions for pregnant women with gestational diabetes mellitus: a systematic review and meta-analysis
Published in Journal of Obstetrics and Gynaecology, 2023
Hui Xin Wei, Yi Ling Yang, Ting Yu Luo, Wei Qiang Chen
In recent years, more and more mHealth applications have been developed for GDM patients (Tian et al. 2021; Rasekaba 2021). Up to now, some mHealth programmes on the management of gestational diabetes have been implemented. Nevertheless, the resulting evidence is always limited and inadequate. An updated review of 32 studies revealed that mHealth interventions contributed to beneficial impacts on the glycemic level as well as certain maternal and neonatal/foetal complications in patients with GDM compared to the effects of standard care. However, this study did not explore the impact of mobile health on self-care management behaviours such as weight, diet, exercise, blood glucose monitoring in pregnant women with GDM (Xie and Dai et al. 2020). Furthermore, another meta-analysis manifested that mHealth interventions are mainly used to record and transmit blood glucose values to clinical nursing teams. No sufficient evidence suggests that mHealth interventions can produce significant effects on glycemic control of pregnant women with gestational diabetes mellitus (Ming et al. 2016). Laursen et al. assesses the effects of mHealth solutions for managing gestational and pregestational diabetes, the meta-analysis reveal no evidence that mHealth as an alternative to usual care when considering maternal and foetal outcomes (Laursen et al. 2022).
Effect of adenomyosis on adverse obstetrical outcomes in twin pregnancies achieved with assisted reproductive technology
Published in Journal of Obstetrics and Gynaecology, 2021
Mi Sun Kim, Ji Hyon Jang, Seulgee Park, Eun Hee Ahn, Sang Hee Jung
Patients who delivered after 24 weeks of gestation were included in the analysis of obstetrical and neonatal outcomes. The following obstetrical outcomes were assessed: overall foetal loss defined as the loss of one or both foetuses during gestation; early and late preterm deliveries, defined as delivery at ≥24 and <34 weeks and at ≥34 and <37 weeks, respectively; term delivery; maternal complications; estimated blood loss during delivery; and placental malposition, which was defined as placenta previa or a low-lying placenta that required caesarean delivery. The diagnosis of hypertensive disorders of pregnancy (HDP) was made according to the criteria of the American Congress of Obstetricians and Gynecologists (ACOG) (Anon 2013). Gestational diabetes mellitus was diagnosed using a 100 g oral glucose tolerance test. The mean birth weight, rate of neonate SGA and the need for neonatal intensive care unit (NICU) admission were also recorded for neonatal outcome. SGA was defined as a birth weight below the 10th percentile.
Caesarean delivery associated with adverse breastfeeding practices: a prospective cohort study
Published in Journal of Obstetrics and Gynaecology, 2020
Phung Thi Hoang Nguyen, Colin W. Binns, Anh Vo Van Ha, Cong Luat Nguyen, Tan Khac Chu, Dat Van Duong, Dung Van Do, Andy H. Lee
Other variables to be considered as plausible confounding factors were determined from the literature (Hobbs et al. 2016; Wallenborn and Masho 2016; Zhao et al. 2017; Doughty et al. 2018). These included maternal socio-demographic characteristics collected at the baseline interview, namely, age (years), education, occupation, parity, passive smoking, and gestational diabetes status. Passive smoking at home and workplace was obtained using the WHO STEPS questions (World Health Organization 2008b). The diagnosis of gestational diabetes followed the criteria from the International Association of Diabetes and Pregnancy Study Group (International Association of Diabetes Pregnancy Study Groups Consensus Panel et al. 2010). Further information on birth outcomes was retrieved from medical records, such as birthweight (g), admission to neonatal intensive care unit (yes/no), and preterm birth (defined as babies born alive before 37 weeks of gestation) (World Health Organization 2018b).