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IoT toward Efficient Analysis of Aging, Cardiometabolic, and Neurodegenerative Diseases—An eHealth Perspective
Published in Ricardo Armentano, Robin Singh Bhadoria, Parag Chatterjee, Ganesh Chandra Deka, The Internet of Things, 2017
Leandro Cymberknop, Parag Chatterjee, Diego Dujovne, Luis Romero, Ricardo Armentano
Cardiovascular diseases (CVD), cerebrovascular accidents, and cancer have always been prevalent largely in the elderly population. This includes an increasing incidence of chronic conditions, such as osteoarthritis, chronic airways disease, and diabetes combined with sedentary lifestyles (e.g., obesity). Thus, major health care challenges are posed, primarily focusing on prevention, early detection, and minimally invasive management of such diseases. As a result, new technologies are applied to assist in patient monitoring and care. Accordingly, wearable systems offer users the ability to interact with other tools and physical objects around them, being capable of continuously monitoring vital signs and electrical signals generated by heart and brain, including posture and physical activities (Andreu-Perez et al., 2015; Chan et al., 2012; Krohn et al., 2016). Here, IoT constitutes an emerging paradigm in which everyday objects, devices, and sensors exchange data with little to no human intervention, exploiting the advanced ways of connectivity and computing ability.
Communications
Published in Emmanuel Tsekleves, Rachel Cooper, Design for Health, 2017
Similarly, O’Halloran et al., (2004: 383) defines chronic diseases as ‘non-communicable illnesses that are prolonged in duration, do not resolve spontaneously and are rarely cured completely’. These characteristics may be tied to more specific criteria that sees chronic health as ‘characteristically a duration that has lasted, or is expected to last, at least six months; has a pattern of recurrence or deterioration; has a poor prognosis; and produces conditions that may lead to other related health issues that may be physical or mental and related to the initial chronic condition’ (O’Halloran et al., 2004: 384). Examples that fall within the National Centre for Disease Control and Prevention’s (2009) definition include heart disease, cancer, stroke, diabetes, oral conditions, obesity, respiratory conditions, arthritis and asthma.
Descriptive Analysis of High Utilizers
Published in Chengliang Yang, Chris Delcher, Elizabeth Shenkman, Sanjay Ranka, Data-Driven Approaches for Health care, 2019
Chengliang Yang, Chris Delcher, Elizabeth Shenkman, Sanjay Ranka
We investigated four specific chronic conditions prevalent in the Medicaid population of the United States: diabetes, COPD, asthma, and hypertension. The results showed that a large percentage of the top 10% in the cohort stayed in the top 10% in the next period. We calculated their average percentiles and standard deviation. The counterparts of Tables 4.3, 4.4, and 4.5 and Figures 4.3 and 4.4 for the diabetes cohort are shown in Tables 4.6, 4.7, and 4.8 and Figures 4.5 and 4.2, respectively. The results for patients with COPD, asthma, and hypertension are not presented here, but the scatterplots for these cohorts are similar to the diabetes cohort.
Characteristics of effective home-based resistance training in patients with noncommunicable chronic diseases: a systematic scoping review of randomised controlled trials
Published in Journal of Sports Sciences, 2021
Roseanne E Billany, Noemi Vadaszy, Courtney J Lightfoot, Matthew Pm Graham-Brown, Alice C Smith, Thomas J Wilkinson
A PRISMA flow diagram showing study screening and selection is shown in Figure 1. Our search identified 22 studies that met the inclusion criteria. (Bauldoff et al., 1996; Chen et al., 2018; Cheung et al., 2009; Cheville et al., 2013; Dracup et al., 2007; Fernandez et al., 2009; Hiraki et al., 2017; Howden et al., 2015; Huppertz et al., 2020; Husebo et al., 2014; Karjalainen et al., 2015; Krousel-Wood et al., 2008; Lubans et al., 2012; Morey et al., 2009; Mustian KM, Peppone L, Darling TV et al, 2009; O’Shea et al., 2007; Oka et al., 2000; Plotnikoff et al., 2010; Servantes et al., 2012; De Sousa Pinto et al., 2014; Uchiyama et al., 2019; Winkels et al., 2017) Two studies are secondary analyses. (Huppertz et al., 2020; Lubans et al., 2012) Table 1 shows the design characteristics of the included studies. Chronic conditions included cancer (n = 5), COPD (n = 5), cardiac (n = 4), diabetes (n = 4), and CKD (n = 4). In total, 986 participants were randomised into an intervention group (RT, aerobic training, or a combination of both), with sample sizes ranging from n = 10 to n = 319. The median (IQR) sample size was 27 (22 to 39). And, 943 participants were randomised into a non-exercise control group with sample sizes ranging from n = 10 to n = 322. The median (IQR) sample size was 23 (18 to 38). Three studies had total sample sizes of >100 participants. (Dracup et al., 2007; Karjalainen et al., 2015; Morey et al., 2009)
Stressors, allostatic load, and health outcomes among women hotel housekeepers: A pilot study
Published in Journal of Occupational and Environmental Hygiene, 2019
Marie-Anne S. Rosemberg, Yang Li, Daniel S. McConnell, Marjorie C. McCullagh, Julia S. Seng
These workers are a fairly young group (with a mean age of 40 years). Yet we found frequent reports of chronic conditions such as hypertension, diabetes, high cholesterol, pain, fatigue, and arthritis. Krause and colleagues recently reported high prevalence of hypertension among hotel housekeepers.[44] Previous studies have shown frequent reports of pain.[5,45,46] However, this is the first time that a study reported findings of self-reported history of high cholesterol and arthritis diagnoses among these workers.
Will the plant-based movement redefine physicians’ understanding of chronic disease?
Published in The New Bioethics, 2020
Treatment approaches for chronic conditions, such as cardiovascular disease, rheumatoid arthritis and diabetes, are often dominated by symptom control and risk factor management. This is, inter alia, the result of our current understanding of the terms ‘chronic disease’ and ‘chronic condition’. Although definitions appear inhomogeneous and vary tremendously in the academic literature (Bernell and Howard 2016), most include some common features.