Introduction: To optimally target physiotherapy treatment, knowledge of the pre- and postoperative course of functional status in patients undergoing esophagectomy is required. The aim of this prospective longitudinal study was to investigate the course of functional status in patients with esophageal cancer before and after esophagectomy. Materials and methods: Functional status outcome measures of patients with esophageal cancer who underwent surgery between March 2012 and June 2016 were prospectively measured at 3 months and at 1 day before surgery and at 1 week and at 3 months after surgery. Analysis of repeated measurements with the mixed model approach was used to study changes over time. Results: Hundred fifty-five patients were measured at 3 months and at 1 day before surgery, of which 109 (70.3%) at 1 week and 60 (38.7%) at 3 months after surgery. Mean (SD) age at surgery was 63.5 years (9.3), and 122 patients (78.7%) were male. The incidence of postoperative complications was 83 (53.5%). Three months postoperatively, functional status measures returned to baseline levels, except from handgrip strength (beta [95% CI] −6.2 [-11.3 to −1.1]; P = 0.02) and fatigue (4.7 [0.7to 8.7]; P = 0.02). No differences were observed in the course of functional status between patients with and without postoperative complications. Conclusion: Functional status of patients undergoing esophagectomy returned to baseline values three months after surgery, despite the high incidence of postoperative complications. This requires rethinking the concept of prehabilitation, where clearly not all patients benefit from high functional status to prevent postoperative complications.
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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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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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PURPOSE: To evaluate the functional status of patients within the first week of discharge from an intensive care unit (ICU), and to identify predictors and explanatory factors of functional status.METHODS: A prospective, observational, cohort study was conducted with consecutive ICU patients who had stayed in a mixed, closed-format, university-level ICU for longer than 48 h.RESULTS: Between 3 and 7 days of discharge from the ICU, functional status (as primary outcome), walking ability, muscle strength, and sensory and cognitive functioning were assessed in 69 survivors. The overall functional status was poor (median Barthel Index 6). In their ability to perform basic activities of daily living, 67% percent were severely dependent, 15% were moderately dependent, and 9% were slightly dependent on other people. Independent walking was impossible for 73% of participants, grip strength was reduced for 50%, and 30% had cognitive impairments. Duration of ventilation was associated with functional status after ICU discharge. Reduced grip strength and walking ability were identified as explanatory factors for poorer functional status shortly after discharge from the ICU.CONCLUSION: In the first week after discharge from the ICU, the majority of the patients had substantial functional disabilities in activities of daily living. These disabilities were more severe in patients who experienced ventilation for a longer period of time. There is a need for prospective studies focusing on functional recovery to support informed decision-making concerning the care of critically ill patients after ICU discharge.
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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: To obtain insight into (a) the prevalence of nursing staff–experienced barriers regarding the promotion of functional activity among nursing home residents, and (b) the association between these barriers and nursing staff–perceived promotion of functional activity. Method: Barriers experienced by 368 nurses from 41 nursing homes in the Netherlands were measured with the MAastrIcht Nurses Activity INventory (MAINtAIN)-barriers; perceived promotion of functional activities was measured with the MAINtAIN-behaviors. Descriptive statistics and hierarchical linear regression analyses were performed. Results: Most often experienced barriers were staffing levels, capabilities of residents, and availability of resources. Barriers that were most strongly associated with the promotion of functional activity were communication within the team, (a lack of) referral to responsibilities, and care routines. Discussion: Barriers that are most often experienced among nursing staff are not necessarily the barriers that are most strongly associated with nursing staff–perceived promotion of functional activity.
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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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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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