Background And Objectives: Recently, early mobilization and discharge after cardiac surgery have been recommended. However, many patients are anxious about returning to daily life soon after undergoing heart operations. To resolve this problem, an individualized rehabilitation plan for each patient is important. Rehabilitation programs must estimate the level of cardiac function in daily life. This study evaluated self-measurements of heart rate and blood pressure during home-based exercise training.
Methods: Thirty-six patients, 28 men and 8 women (mean age 58 +/- 19 years) who underwent cardiac operations were enrolled in this study. None of the patients experienced postoperative complications. Changes in heart rate and blood pressure during daily activities at home were measured by the patients. This data was then used to plan individual rehabilitation programs.
Results: The blood pressure rose from 114 +/- 17 to 139 +/- 21 mmHg (mean increase of 25 +/- 15 mmHg) when the patients were asked to walk up and down a set of stairs. Thirteen patients (36%) exhibited an increase in blood pressure of 30 mmHg or more while ascending the stairs. The patients' blood pressure returned to its pre-exercise level after 5 min. The heart rate rose from 84 +/- 15 to 113 +/- 14 beats/min (mean increase of 29 +/- 8 beats/min) during the exercise. During the home-based training period, the maximum blood pressure was 133 +/- 22 mmHg, and the maximum heart rate was 97 +/- 13 beats/min.
Conclusions: The patients were very careful during their trial outpatient period, as this was their first post-cardiac surgery experience. Consequently, the degree of exercise at home was even more mild than in hospital. Self-measurement of heart rate and blood pressure was feasible. By referring to these measurements, the patients were able to monitor and increase their level of exercise. This post-cardiac surgery rehabilitation program is helpful for early returning to daily life activities.
Download full-text PDF |
Source |
---|
Best Pract Res Clin Anaesthesiol
September 2024
Division of Maternal-Fetal Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, L1, Boston, MA, 02115, USA. Electronic address:
Preeclampsia is a life-threatening complication that develops in 2-8% of pregnancies. It is characterized by elevated blood pressure after 20 weeks of gestation and may progress to multiorgan dysfunction, leading to severe maternal and fetal morbidity and mortality. The only definitive treatment is delivery, and efforts are focused on early risk prediction, surveillance, and severity mitigation.
View Article and Find Full Text PDFInt J Numer Method Biomed Eng
January 2025
College of Chemistry and Life Science, Beijing University of Technology, Beijing, China.
The accurate non-invasive detection and estimation of central aortic pressure waveforms (CAPW) are crucial for reliable treatments of cardiovascular system diseases. But the accuracy and practicality of current estimation methods need to be improved. Our study combines a meta-learning neural network and a physics-driven method to accurately estimate CAPW based on personalized physiological indicators.
View Article and Find Full Text PDFEClinicalMedicine
October 2024
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.
Background: Use of health applications (apps) to support healthy lifestyles has intensified. Different app features may support effectiveness, including gamification defined as the use of game elements in a non-game situation. Whether health apps with gamification can impact behaviour change and cardiometabolic risk factors remains unknown.
View Article and Find Full Text PDFWorld J Clin Cases
January 2025
Department of Gastroenterology, Laiko General Hospital, National and Kapodistrian University of Athens, Athens 11527, Greece.
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 .
View Article and Find Full Text PDFPatient Prefer Adherence
January 2025
Division of Hypertension, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Introduction: Self-care practices are crucial for optimizing blood pressure control and are influenced by multilevel factors.
Objective: To examine the influences of multilevel factors on hypertension self-care practices among individuals with uncontrolled hypertension and to determine the relationship between hypertension self-care practices and blood pressure.
Methods: The study was conducted in primary, secondary, and tertiary care settings in Bangkok, selected for convenience, where individuals with uncontrolled hypertension were recruited using a convenience sampling method based on specific inclusion criteria.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!