Thirty to sixty per cent of older patients experience functional decline after hospitalisation, associated with an increase in dependence, readmission, nursing home placement and mortality. First step in prevention is the identification of patients at risk. The objective of this study is to develop and validate a prediction model to assess the risk of functional decline in older hospitalised patients.
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De zorg voor ouderen verandert en wordt steeds meer in de wijk georganiseerd. Mensen worden niet alleen ouder, ook de complexiteit van hun zorgbehoefte neemt toe. Dit geldt met name voor ouderen die meerdere chronische ziekten en aandoeningen hebben. Vaak zijn diverse disciplines tegelijkertijd betrokken bij deze doelgroep. Voor goede zorg en ondersteuning is interprofessionele samenwerking tussen professionals uit het medisch en sociaal domein in de wijk noodzakelijk. Om de samenwerking in de wijk te versterken, hebben de Hogeschool Utrecht, Universitair Medisch Centrum Utrecht en Stichting Volte, in cocreatie met het veld en de doelgroep (professionals in de wijk) een interprofessionele training ontwikkeld voor professionals in de wijk. De training wordt op wijkniveau aangeboden en omvat een mix tussen online, face-to-face en on the job leren. In dit artikel beschrijven we hoe de training in nauwe samenwerking met de praktijk en experts uit de verschillende domeinen is ontwikkeld.
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ABSTRACT Objective: To examine the associations between individual chronic diseases and multidimensional frailty comprising physical, psychological, and social frailty. Methods: Dutch individuals (N = 47,768) age ≥ 65 years completed a general health questionnaire sent by the Public Health Services (response rate of 58.5 %), including data concerning self-reported chronic diseases, multidimensional frailty, and sociodemographic characteristics. Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI). Total frailty and each frailty domain were regressed onto background characteristics and the six most prevalent chronic diseases: diabetes mellitus, cancer, hypertension, arthrosis, urinary incontinence, and severe back disorder. Multimorbidity was defined as the presence of combinations of these six diseases. Results: The six chronic diseases had medium and strong associations with total ((f2 = 0.122) and physical frailty (f2 = 0.170), respectively, and weak associations with psychological (f2 = 0.023) and social frailty (f2 = 0.008). The effects of the six diseases on the frailty variables differed strongly across diseases, with urinary incontinence and severe back disorder impairing frailty most. No synergetic effects were found; the effects of a disease on frailty did not get noteworthy stronger in the presence of another disease. Conclusions: Chronic diseases, in particular urinary incontinence and severe back disorder, were associated with frailty. We thus recommend assigning different weights to individual chronic diseases in a measure of multimorbidity that aims to examine effects of multimorbidity on multidimensional frailty. Because there were no synergetic effects of chronic diseases, the measure does not need to include interactions between diseases.
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Purpose: To examine the development of multidimensional frailty, including physical, psychological and socialcomponents, over a period of seven years. To determine the effects of sociodemographic factors (gender, age, marital status, education, income) on the development of frailty. Methods: : This longitudinal study was conducted in sample of 479 community-dwelling people aged ≥ 75 years living in the municipality of Roosendaal, the Netherlands. The Tilburg Frailty Indicator (TFI), a self-report questionnaire, was used to collect data about frailty. Frailty was assessed annually. Results: : Frailty increased significantly over seven years among the people who completed the entire TFI all years (n = 121), the average score was 3.75 (SD 2.80) at baseline and 5.05 (SD 3.18) after seven years. Regarding frailty transitions, most participants remained unchanged from their baseline status. The transition from non-frail to frail was present in 8.3% to 12.6% of the participants and 5.1% to 10.7% made a transition from frail to nonfrail. Gender (woman), age (≥80 years), marital status (not married/cohabiting), high level of education, and incomes from €601-€1800 were significantly associated with a higher frailty score. Conclusion: : This study showed that multidimensional frailty, assessed with the TFI, increased among Dutch community-dwelling people aged ≥75 years using a follow-up of seven years. Gender, age, marital status, education, and income were associated with frailty transitions. These findings provide healthcare professionals clues to identify people at increased risk of frailty, and target interventions which aim to prevent or delay frailty and its adverse outcomes, such as disability and mortality.
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Background: Dependency in activities of daily living (ADL) might be caused by multidimensional frailty. Prevention is important as ADL dependency might threaten the ability to age in place. Therefore, this study aimed to assess whether protective factors, derived from a systematic literature review, moderate the relationship between multidimensional frailty and ADL dependency, and whether this differs across age groups. Methods: A longitudinal study with a follow–up after 24 months was conducted among 1027 communitydwelling people aged ≥65 years. Multidimensional frailty was measured with the Tilburg Frailty Indicator, and ADL dependency with the ADL subscale from the Groningen Activity Restriction Scale. Other measures included socio-demographic characteristics and seven protective factors against ADL dependency, such as physical activity and non-smoking. Logistic regression analyses with interaction terms were conducted. Results: Frail older people had a twofold risk of developing ADL dependency after 24 months in comparison to non-frail older people (OR=2.12, 95% CI=1.45–3.00). The selected protective factors against ADL dependency did not significantly moderate this relationship. Nonetheless, higher levels of physical activity decreased the risk of becoming ADL dependent (OR=0.67, 95% CI=0.46–0.98), as well as having sufficient financial resources (OR=0.49, 95% CI=0.35–0.71). Conclusion: Multidimensional frail older people have a higher risk of developing ADL dependency. The studied protective factors against ADL dependency did not significantly moderate this relationship.
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Background: Due to differences in the definition of frailty, many different screening instruments have been developed. However, the predictive validity of these instruments among community-dwelling older people remains uncertain. Objective: To investigate whether combined (i.e. sequential or parallel) use of available frailty instruments improves the predictive power of dependency in (instrumental) activities of daily living ((I)ADL), mortality and hospitalization. Design, setting and participants: A prospective cohort study with two-year followup was conducted among pre-frail and frail community-dwelling older people in the Netherlands. Measurements: Four combinations of two highly specific frailty instruments (Frailty Phenotype, Frailty Index) and two highly sensitive instruments (Tilburg Frailty Indicator, Groningen Frailty Indicator) were investigated. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for all single instruments as well as for the four combinations, sequential and parallel. Results: 2,420 individuals participated (mean age 76.3 ± 6.6 years, 60.5% female) in our study. Sequential use increased the levels of specificity, as expected, whereas the PPV hardly increased. Parallel use increased the levels of sensitivity, although the NPV hardly increased. Conclusions: Applying two frailty instruments sequential or parallel might not be a solution for achieving better predictions of frailty in community-dwelling older people. Our results show that the combination of different screening instruments does not improve predictive validity. However, as this is one of the first studies to investigate the combined use of screening instruments, we recommend further exploration of other combinations of instruments among other study populations.
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INLEIDING In deze module worden behandeladviezen gegeven voor de Post-COVID-19 ambulante behandeling in de geriatrische revalidatie gericht op somatische-, functionele- en psychische status. Deze module is een onderdeel van het behandeladvies post-COVID-19 (geriatrische) revalidatie-Verenso. Deze module is in een zeer korte tijd tot stand gekomen en heeft de status van groeidocument. Zorgvuldigheid is betracht om zowel de (beperkte) ervaringskennis, als de actuele stand van de wetenschappelijke literatuur hierin te betrekken. Voor dit behandeladvies is gebruik gemaakt van het door GRZPLUS ontwikkeld ambulant revalidatieprogramma CO FIT+. Bij GRZPLUS is een doorontwikkeling gemaakt op basis van de update behandeladvies post-COVID-19 geriatrische revalidatie van Verenso (Verenso, 19-05-2020) welke is gebaseerd op de principes van longrevalidatie zoals vertaald in het Behandelprogramma geriatrische COPD-revalidatie (van Damvan Isselt et al.) en het Behandelprogramma COVID-19 Post IC, van Revalidatiecentrum de Hoogstraat (Brouwers, de Graaf). Dit is aangevuld met behandeladviezen en leidraden vanuit de beroepsverenigingen en kennis uit wetenschappelijk onderzoek (long-revalidatie) en vanuit het REACH netwerk (REhabilitation After Critical illness and Hospital discharge). De komende maanden zullen zowel de nieuwe wetenschappelijke literatuur als de ervaringen uit de praktijk gebruikt worden om de handreiking te verbeteren en zo nodig aan te vullen. Dat zullen wij doen met specialisten ouderengeneeskunde, revalidatieartsen, klinisch-geriaters, paramedici, longartsen, verpleegkundigen, infectie deskundigen, en andere betrokken beroepsgroepen. De revalidatie van ambulante post-COVID-19 patiënten vereist vooral afstemming binnen de multidisciplinaire zorg. De complexiteit en ernst van de problematiek en de interactie van beperkingen op diverse domeinen maakt dat interdisciplinaire behandeling essentieel is.
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The aim of this study was to assess the predictive ability of the frailty phenotype (FP), Groningen Frailty Indicator (GFI), Tilburg Frailty Indicator (TFI) and frailty index (FI) for the outcomes mortality, hospitalization and increase in dependency in (instrumental) activities of daily living ((I)ADL) among older persons. This prospective cohort study with 2-year follow-up included 2420 Dutch community-dwelling older people (65+, mean age 76.3±6.6 years, 39.5% male) who were pre-frail or frail according to the FP. Mortality data were obtained from Statistics Netherlands. All other data were self-reported. Area under the receiver operating characteristic curves (AUC) was calculated for each frailty instrument and outcome measure. The prevalence of frailty, sensitivity and specifcity were calculated using cutoff values proposed by the developers and cutoff values one above and one below the proposed ones (0.05 for FI). All frailty instruments poorly predicted mortality, hospitalization and (I)ADL dependency (AUCs between 0.62–0.65, 0.59–0.63 and 0.60–0.64, respectively). Prevalence estimates of frailty in this population varied between 22.2% (FP) and 64.8% (TFI). The FP and FI showed higher levels of specifcity, whereas sensitivity was higher for the GFI and TFI. Using a different cutoff point considerably changed the prevalence, sensitivity and specifcity. In conclusion, the predictive ability of the FP, GFI, TFI and FI was poor for all outcomes in a population of pre-frail and frail community-dwelling older people. The FP and the FI showed higher values of specifcity, whereas sensitivity was higher for the GFI and TFI.
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Background: In frail older people with natural teeth factors like polypharmacy, reduced salivary flow, a decrease of oral self-care, general healthcare issues, and a decrease in dental care utilization contribute to an increased risk for oral complications. On the other hand, oral morbidity may have a negative impact on frailty. Objective: This study explored associations between oral health and two frailty measures in community-dwelling older people. Design: A cross-sectional study. Setting: The study was carried out in a Primary Healthcare Center (PHC) in The Netherlands. Participants: Of the 5,816 persons registered in the PHC, 1,814 persons were eligible for participation at the start of the study. Measurements: Two frailty measures were used: 1. Being at risk for frailty, using Electronical Medical Record (EMR) data, and: 2. Survey-based frailty using ‘The Groningen Frailty Indicator’ (GFI). For oral health measures, dental-record data (dental care utilization, dental status, and oral health information) and self-reported oral problems were recorded. Univariate regression analyses were applied to determine the association between oral health and frailty, followed by age- and sex-adjusted multivariate logistic regressions. Results: In total 1,202 community-dwelling older people were included in the study, 45% were male and the mean age was 73 years (SD=8). Of all participants, 53% was at risk for frailty (638/1,202), and 19% was frail based on the GFI (222/1,202). A dental emergency visit (Odds Ratio (OR)= 2.0, 95% Confidence Interval (CI)=1.33;3.02 and OR=1.58, 95% CI=1.00;2.49), experiencing oral problems (OR=2.07, 95% CI=1.52;2.81 and OR=2.87, 95% CI= 2.07;3.99), and making dietary adaptations (OR=2.66, 95% CI=1.31;5.41 and OR=5.49, 95% CI= 3.01;10.01) were associated with being at risk for frailty and surveybased frailty respectively. Conclusions: A dental emergency visit and self-reported oral health problems are associated with frailty irrespective of the approach to its measurement. Healthcare professionals should be aware of the associations of oral health and frailty in daily practice.
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Abstract Purpose To determine the predictive value of quality of life for mortality at the domain and item levels. Methods This longitudinal study was carried out in a sample of 479 Dutch people aged 75 years or older living independently, using a follow-up of 7 years. Participants completed a self-report questionnaire. Quality of life was assessed with the WHOQOL-BREF, including four domains: physical health, psychological, social relationships, and environment. The municipality of Roosendaal (a town in the Netherlands) indicated the dates of death of the individuals. Results Based on mean, all quality of life domains predicted mortality adjusted for gender, age, marital status, education, and income. The hazard ratios ranged from 0.811 (psychological) to 0.933 (social relationships). The areas under the curve (AUCs) of the four domains were 0.730 (physical health), 0.723 (psychological), 0.693 (social relationships), and 0.700 (environment). In all quality of life domains, at least one item predicted mortality (adjusted). Conclusion Our study showed that all four quality of life domains belonging to the WHOQOL-BREF predict mortality in a sample of Dutch community-dwelling older people using a follow-up period of 7 years. Two AUCs were above threshold (psychological, physical health). The findings offer health care and welfare professionals evidence for conducting interventions to reduce the risk of premature death.
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