Background: Hypertensive disturbances during pregnancy are the leading cause of maternal and fetal death; unfortunately, no effective treatment exists. Therefore, interventions that reduce the likelihood of developing preeclampsia during pregnancy are required. This study aimed to see how Progressive Muscle Relaxation (PMR) compared to breathing exercise techniques affected Blood Pressure (BP) levels among mildly preeclamptic pregnant women.
Materials And Methods: A convenience sample was used in a quasi-experimental study of 75 mild preeclamptic pregnant women in the Obstetrical Outpatient Clinics at the Suez Canal University Hospital in Ismailia, Egypt. They were divided into three groups: study group [I]: the deep breathing exercise group; study group [II]: the PMR group; and study group [III]: the control group. Data were collected using two methods: an interviewing information collection tool and a physiological measurement tool.
Results: There was a statistical significant difference in systolic and diastolic blood pressure after six weeks of training among intervention groups (PMR and breathing excercise technique with value 0.001 for both groups) compered to contol group. However, there was no statistical difference in BP (systolic or diastolic) after two weeks of intervention among the three groups.
Conclusions: PMR and breathing techniques could effectively control BP in pregnancy complicated by mild preeclampsia. Both techniques could be introduced in routine antenatal care for women diagnosed with mild preeclampsia. Health and fitness professionals should focus more on preparing and delivering various sports programs incorporating various muscle relaxations and breathing techniques.
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http://dx.doi.org/10.4103/ijnmr.ijnmr_33_22 | DOI Listing |
EClinicalMedicine
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Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Unity Health Toronto, Toronto, ON M5B 1W8, Canada.
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Machine learning (ML) is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis, thus creating machines that can complete tasks otherwise requiring human intelligence. Among its various applications, it has proven groundbreaking in healthcare as well, both in clinical practice and research. In this editorial, we succinctly introduce ML applications and present a study, featured in the latest issue of the .
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Division of Hypertension, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
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Front Pharmacol
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