Ambient activity monitoring systems produce large amounts of data, which can be used for health monitoring. The problem is that patterns in this data reflecting health status are not identified yet. In this paper the possibility is explored of predicting the functional health status (the motor score of AMPS = Assessment of Motor and Process Skills) of a person from data of binary ambient sensors. Data is collected of five independently living elderly people. Based on expert knowledge, features are extracted from the sensor data and several subsets are selected. We use standard linear regression and Gaussian processes for mapping the features to the functional status and predict the status of a test person using a leave-oneperson-out cross validation. The results show that Gaussian processes perform better than the linear regression model, and that both models perform better with the basic feature set than with location or transition based features. Some suggestions are provided for better feature extraction and selection for the purpose of health monitoring. These results indicate that automated functional health assessment is possible, but some challenges lie ahead. The most important challenge is eliciting expert knowledge and translating that into quantifiable features.
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ObjectiveMany patients with coronavirus disease 2019 (COVID-19) infections were admitted to an intensive care unit (ICU). Physical impairments are common after ICU stays and are associated with clinical and patient characteristics. To date, it is unknown if physical functioning and health status are comparable between patients in the ICU with COVID-19 and patients in the ICU without COVID-19 3 months after ICU discharge. The primary objective of this study was to compare handgrip strength, physical functioning, and health status between patients in the ICU with COVID-19 and patients in the ICU without COVID-19 3 months after ICU discharge. The second objective was to identify factors associated with physical functioning and health status in patients in the ICU with COVID-19. Methods In this observational, retrospective chart review study, handgrip strength (handheld dynamometer), physical functioning (Patient-Reported Outcomes Measurement Information System Physical Function), and health status (EuroQol 5 Dimension 5 Level) were compared between patients in the ICU with COVID-19 and patients in the ICU without COVID-19 using linear regression. Multilinear regression analyses were used to investigate whether age, sex, body mass index, comorbidities in medical history (Charlson Comorbidity Index), and premorbid function illness (Identification of Seniors At Risk-Hospitalized Patients) were associated with these parameters in patients in the ICU with COVID-19. Results In total, 183 patients (N = 92 with COVID-19) were included. No significant between-group differences were found in handgrip strength, physical functioning, and health status 3 months after ICU discharge. The multilinear regression analyses showed a significant association between sex and physical functioning in the COVID-19 group, with better physical functioning in men compared with women. Conclusion Current findings suggest that handgrip strength, physical functioning, and health status are comparable for patients who were in the ICU with COVID-19 and patients who were in the ICU without COVID-19 3 months after ICU discharge. Impact Aftercare in primary or secondary care in the physical domain of postintensive care syndrome after ICU discharge in patients with COVID-19 and in patients without COVID-19 who had an ICU length of stay >48 hours is recommended. Lay Summary Patients who were in the ICU with and without COVID-19 had a lower physical status and health status than healthy people, thus requiring personalized physical rehabilitation. Outpatient aftercare is recommended for patients with an ICU length of stay >48 hours, and functional assessment is recommended 3 months after hospital discharge.
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Background Evidence about the impact of the COVID-19 pandemic on existing health inequalities is emerging. This study explored differences in mental health, sense of coherence (SOC), sense of community coherence (SOCC), sense of national coherence (SONC), and social support between low and high socioeconomic (SES) groups, and the predictive value of these predictors for mental health. participants and procedure A cross-sectional study was conducted using an online survey in the Netherlands in October 2021, comprising a total of 91 respondents (n = 41, low SES; n = 50, high SES). results There were no differences in mental health, SOC, SOCC, SONC, and social support between the groups. SOC was a predictor for mental health in both groups and SOCC for the low SES group. conclusions We found that both SOC and SOCC predict mental health during the pandemic. In the article we reflect on possible pathways for strengthening these resources for mental health.
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Background: Geriatric rehabilitation positively influences health outcomes in older adults after acute events. Integrating mobile health (mHealth) technologies with geriatric rehabilitation may further improve outcomes by increasing therapy time and independence, potentially enhancing functional recovery. Previous reviews have highlighted positive outcomes but also the need for further investigation of populations receiving geriatric rehabilitation. Objective: Our main objective was to assess the effects of mHealth applications on the health status of older adults after acute events. A secondary objective was to examine the structure and process elements reported in these studies. Methods: Systematic review, including studies from 2010 to January 2024. Studies were eligible if they involved older adults’ post-acute care and used mHealth interventions, measured health outcomes and compared intervention and control groups. The adjusted Donabedian Structure-Process-Outcome (SPO) framework was used to present reported intervention processes and structures. Results: After initial and secondary screenings of the literature, a total of nine studies reporting 26 health outcomes were included. mHealth interventions ranged from mobile apps to wearables to web platforms. While most outcomes showed improvement in both the intervention and control groups, a majority favored the intervention groups. Reporting of integration into daily practice was minimal. Conclusion: While mHealth shows positive effects on health status in geriatric rehabilitation, the variability in outcomes and methodologies among studies, along with a generally high risk of bias, suggest cautious interpretation. Standardized measurement approaches and co-created interventions are needed to enhance successful uptake into blended care and keep geriatric rehabilitation accessible and affordable.
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The aim of this study was to gain insight into the nutritional status, dietary intake and muscle health of older Dutch hip fracture patients to prevent recurrent fractures and to underpin rehabilitation programs. This cross-sectional study enrolled 40 hip fracture patients (mean ± SD age 82 ± 8.0 years) from geriatric rehabilitation wards of two nursing homes in the Netherlands. Assessments included nutritional status (Mini Nutritional Assessment), dietary intake on three non-consecutive days which were compared with Dietary Reference Intake values, and handgrip strength. Muscle mass was measured using Bioelectrical Impedance Analysis and ultrasound scans of the rectus femoris. Malnutrition or risk of malnutrition was present in 73% of participants. Mean energy, protein, fibre and polyunsaturated fat intakes were significantly below the recommendations, while saturated fat was significantly above the UL. Protein intake was
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In deze literatuurstudie werden vier databanken doorzocht met behulp van trefwoorden zoals chronic disease, e-health, factors en suggested interventions. Kwalitatieve, kwantitatieve en mixed methods-studies werden meegenomen. Uit de data van de 22 artikelen die werden geïncludeerd in de studie, blijken leeftijd, geslacht, inkomen, opleidingsniveau, etnische achtergrond en woonplaats (stad of platteland) in meer of mindere mate van invloed te zijn op het gebruik van e-health. Het artikel is een Nederlandstalige samenvatting van het artikel: Reiners, Sturm, Bouw & Wouters (2019) uit Int J Environ Res Public Health 2019;16(4)
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Objective: The aim of this study was to assess the relationship between frailty syndrome and the nutritional status of older patients. Material and methods: This cross-sectional study was conducted in a sample of 120 patients hospitalized at the Geriatric Clinic between January 2017 and May 2017. The research tools were the Frailty Instrument of the Survey of Health, Ageing and Retirement in Europe (SHARE-FI), including relevant anthropometric measurements and muscle strength measurement, and the Mini Nutritional Assessment (MNA). All the calculations were performed using the Statistica 10.0 program. The p-values lower than 0.05 were considered as statistically significant. Results: The mean age of the participants was 71 years (SD=9.03). Most participants were from urban areas. More than half of the participants (53.3%) were women. Based on the SHARE-FI, the frailty syndrome was found in 33.3% of the participants. The mean value in the MNA scale was 24.4 points (SD=3.4). The frailty syndrome was significantly correlated to gender (p<0.025), financial status (p=0.036) and MNA (p<0.01) score. A statistically significant difference was observed between gender (p=0.026), financial status (p=0.016), place of living (p=0.046) and MNA score. Conclusion: This study confirmed significant correlations between the frailty syndrome and the nutritional status of older adults. In terms of prevention and clinical application, it seems important to control the nutritional status of older people and the frailty syndrome. The above-mentioned scales should be used to evaluate patients, analyze the risk and plan the intervention for that group of patients.
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Objective: Many patients with COVID-19 infections were admitted to an intensive care unit (ICU). Physical impairments are common after ICU stays and are associated with clinical and patient characteristics. To date, it is unknown if physical functioning and health status are comparable between patients in the ICU with COVID-19 and patients in the ICU without COVID-19 3 months after ICU discharge. The primary objective of this study was to compare handgrip strength, physical functioning, and health status between patients in the ICU with COVID-19 and patients in the ICU without COVID-19 3 months after ICU discharge. The second objective was to identify factors associated with physical functioning and health status in patients in the ICU with COVID-19. Methods: In this observational, retrospective chart review study, handgrip strength (handheld dynamometer), physical functioning (Patient-Reported Outcomes Measurement Information System Physical Function), and health status (EuroQol 5 Dimension 5 Level) were compared between patients in the ICU with COVID-19 and patients in the ICU without COVID-19 using linear regression. Multilinear regression analyses were used to investigate whether age, sex, body mass index, comorbidities in medical history (Charlson Comorbidity Index), and premorbid function illness (Identification of Seniors At Risk-Hospitalized Patients) were associated with these parameters in patients in the ICU with COVID-19. Results: In total, 183 patients (N = 92 with COVID-19) were included. No significant between-group differences were found in handgrip strength, physical functioning, and health status 3 months after ICU discharge. The multilinear regression analyses showed a significant association between sex and physical functioning in the COVID-19 group, with better physical functioning in men compared with women. Conclusions: Current findings suggest that handgrip strength, physical functioning, and health status are comparable for patients who were in the ICU with COVID-19 and patients who were in the ICU without COVID-19 3 months after ICU discharge. Impact: Aftercare in primary or secondary care in the physical domain of postintensive care syndrome after ICU discharge in patients with COVID-19 and in patients without COVID-19 who had an ICU length of stay >48 hours is recommended.
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The aim of this systematic review was to examine the association between malnutrition and oral health in older people (≥ 60 years of age). A comprehensive systematic literature search was performed in four databases (PubMed, CINAHL, Dentistry and Oral Sciences Source, and Embase) for literature from January 2000 to May 2020. Both observational and intervention studies were screened for eligibility. Two reviewers independently screened the search results to identify potential eligible studies, and assessed the methodological quality of the full-text studies. A total of 3240 potential studies were identified. After judgement for relevance, 10 studies (cross-sectional (n = 9), prospective cohort (n = 1)) met the inclusion criteria. Three studies described malnourished participants as having fewer teeth, or functional (tooth) units (FTUs), compared to well-nourished participants. Four studies reported soft tissue problems in malnourished participants, including red tongue with blisters, and dry or cracked lips. Subjective oral health was the topic in six studies, with poorer oral health and negative self-perception of oral health in malnourished elderly participants. There are associations between (at risk of) malnutrition and oral health in older people, categorized in hard and soft tissue conditions of the mouth, and subjective oral health. Future research should be focused on longitudinal cohort studies with proper determination of malnutrition and oral health assessments, in order to evaluate the actual association between malnutrition and oral health in older people.
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Introduction: This study evaluates the course of physical fitness and nutritional status during curative therapy for esophageal cancer, after implementation of a prehabilitation program. Additionally, the impact of baseline physical fitness level and severe postoperative complications on the course of individual patients were explored. Materials and methods: This multicenter, observational cohort study included patients with esophageal cancer following curative treatment. Prehabilitation, consisting of supervised exercise training and nutritional counseling was offered as standard care to patients after neoadjuvant therapy, prior to surgery. Primary outcome measures included change of exercise capacity, hand grip strength, self-reported physical functioning, Body Mass Index, and malnutrition risk from diagnosis to 2–6 months postoperatively. Analyses over time were performed using linear mixed models, and linear mixed regression models to investigate the impact of baseline level and severe postoperative complications. Results: Hundred sixty-eight patients were included (mean age 65.9 ± 8.6 years; 78.0 % male). All parameters (except for malnutrition risk) showed a decline during neoadjuvant therapy (p < .05), an improvement during prehabilitation (p < .005) and a decline postoperatively (p < .001), with a high heterogeneity between patients. Change in the outcomes from baseline to postoperatively was not different for patients with or without a severe complication. Better baseline physical fitness and nutritional status were significantly associated with a greater decline postoperatively (p < .001). Conclusion: This study demonstrates a notable decline during neoadjuvant therapy, that fully recovers during prehabilitation, and a subsequent long lasting decline postoperatively. The heterogeneity in the course of physical fitness and nutritional status underlines the importance of individualized monitoring.
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