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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Background: Over the years, a plethora of frailty assessment tools has been developed. These instruments can be basically grouped into two types of conceptualizations – unidimensional, based on the physical–biological dimension – and multidimensional, based on the connections among the physical, psychological, and social domains. At present, studies on the comparison between uni- and multidimensional frailty measures are limited. Objective: The aims of this paper were: 1) to compare the prevalence of frailty obtained using a uni- and a multidimensional measure; 2) to analyze differences in the functional status among individuals captured as frail or robust by the two measures; and 3) to investigate relations between the two frailty measures and disability.
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Maintaining independence is the most important goal of the majority of older people. The onset of disability in activities of daily living is one of the greatest threats to the ability of older people to live independently. Older people with a low socioeconomic status (SES) are at high risk of functional decline. It is unclear what predicts functional decline in older people with a low SES. The aim of this study was to determine predictors of 12-month functional decline in community-living older people with low SES in the Netherlands. Functional decline was defined as the inability to perform (instrumental) activities of daily living. A prognostic multicentre study was conducted, using data from The Dutch Older Persons and Informal Caregivers Survey Minimum DataSet. A multivariable logistic regression model was fitted, using a stepwise backward selection process. Performance of the model was expressed by discrimination, calibration and accuracy. A total of 4.370 participants were included. The mean age of the participants was 80 years and 58.9% were female. Functional decline was present in 1486 participants (34.0%). Ten predictors were independently associated with the outcome. Dementia was the strongest predictor (OR 1.83, 95% CI 1.04–3.23). Other predictors were age, education, poor health, quality of life rate, arthrosis/arthritis, hearing problems, anxiety/panic disorder, pain and less social activities. The final model showed an acceptable discrimination (C-statistic 0.69, 95% CI 0.67–0.70), calibration (Hosmer-Lemeshow p-value 0.33) and accuracy (Brier score 0.20). Further research is needed to examine how functional decline can be ameliorated in this population.
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Wireless sensor networks are becoming popular in the field of ambient assisted living. In this paper we report our study on the relationship between a functional health metric and features derived from the sensor data. Sensor systems are installed in the houses of nine people who are also quarterly visited by an occupational therapist for functional health assessments. Different features are extracted and these are correlated with a metric of functional health (the AMPS). Though the sample is small, the results indicate that some features are better in describing the functional health in the population, but individual differences should also be taken into account when developing a sensor system for functional health assessment.
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A growing number of older patients undergo cardiac surgery. Some of these patients are at increased risk of post-operative functional decline, potentially leading to reduced quality of life and autonomy, and other negative health outcomes. First step in prevention is to identify patients at risk of functional decline. There are no current published tools available to predict functional decline following cardiac surgery. The objective was to validate the identification of seniors at risk—hospitalised patients (ISAR-HP), in older patients undergoing cardiac surgery. A multicenter cohort study was performed in cardiac surgery wards of two university hospitals with follow-up 3 months after hospital admission. Inclusion criteria: consecutive cardiac surgery patients, aged ≥65. Functional decline was defined as a decline of at least one point on the Katz ADL Index at follow-up compared with preadmission status.
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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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Preoperative functional status is a risk factor for developing postoperative complications (POC) in major abdominal and thoracic surgery, but this has hardly been evaluated in esophageal cancer patients undergoing esophagectomy. The aim of this prospective cohort study was to determine if preoperative functional status in esophageal cancer patients is associated with POC. From March 2012 to October 2014, esophageal cancer patients scheduled for esophagectomy at the outpatient clinic of a large tertiary referral center were eligible for the study. We measured inspiratory muscle strength, hand grip strength, physical activities, and health related quality of life as indicators of functional status one day before surgery. POC were scored according to the Clavien-Dindo Classification. We used univariate and multivariate backward regression analysis to determine the association between functional status and POC. We included 94 patients in the study and esophagectomy was performed in 90 patients from which 55 developed POC (61.1%). After multivariate analysis, none of the indicators of preoperative functional status were independently associated with POC (inspiratory muscle strength [OR 1.00; P = 0.779], hand grip strength [OR 0.99; P = 0.250], physical activities [OR 1.00; P = 0.174], and health related quality of life [OR 1.02; P = 0.222]). We concluded that preoperative functional status in our study cohort is not associated with POC after esophagectomy.
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OBJECTIVE: The prevalence of osteoarthritis (OA) increases, but the impact of the disorder on peoples' functional capacity is not known. Therefore, the objective of this study was to compare self-reported health status and functional capacity of subjects with early OA of hip and/or knee to reference data of healthy working subjects and to assess whether this capacity is sufficient to meet physical job demands.METHODS: Self-reported health status and functional capacity of 93 subjects from the Cohort Hip and Cohort Knee (CHECK) were measured using the Short-Form 36 Health Survey and 6 tests of the Work Well Systems Functional Capacity Evaluation. Results were compared with reference data from 275 healthy workers, using t-tests. To compare the functional capacity with job demands, the proportions of subjects with OA performing lower than the p(5) of reference data were calculated.RESULTS: Compared to healthy workers, the subjects (mean age 56) from CHECK at baseline reported a significantly worse physical health status, whereas the women (n = 78) also reported a worse mental health status. On the FCE female OA subjects performed significantly lower than their healthy working counterparts on all 6 tests. Male OA subjects performed lower than male workers on 3 tests. A substantial proportion of women demonstrated functional capacities that could be considered insufficient to perform jobs with low physical demands.CONCLUSIONS: Functional capacity and self-reported health of subjects with early OA of the hips and knees were worse compared to healthy ageing workers. A substantial proportion of female subjects did not meet physical job demands.
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Background: The concept of Functional Independence (FI), defined as ‘functioning physically safe and independent from other persons, within one’s context”, plays an important role in maintaining the functional ability to enable well-being in older age. FI is a dynamic and complex concept covering four clinical outcomes: physical capacity, empowerment, coping flexibility, and health literacy. As the level of FI differs widely between older adults, healthcare professionals must gain insight into how to best support older people in maintaining their level of FI in a personalized manner. Insight into subgroups of FI could be a first step in providing personalized support This study aims to identify clinically relevant, distinct subgroups of FI in Dutch community-dwelling older people and subsequently describe them according to individual characteristics. Results: One hundred fifty-three community-dwelling older persons were included for participation. Cluster analysis identified four distinctive clusters: (1) Performers – Well-informed; this subgroup is physically strong, well-informed and educated, independent, non-falling, with limited reflective coping style. (2) Performers – Achievers: physically strong people with a limited coping style and health literacy level. (3) The reliant- Good Coper representing physically somewhat limited people with sufficient coping styles who receive professional help. (4) The reliant – Receivers: physically limited people with insufficient coping styles who receive professional help. These subgroups showed significant differences in demographic characteristics and clinical FI outcomes. Conclusions: Community-dwelling older persons can be allocated to four distinct and clinically relevant subgroups based on their level of FI. This subgrouping provides insight into the complex holistic concept of FI by pointing out for each subgroup which FI domain is affected. This way, it helps to better target interventions to prevent the decline of FI in the community-dwelling older population.
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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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