Bij de richtlijn horen 1) een wetenschappelijke onderbouwing en 2) een samenvattingskaart. Deze richtlijn beoogt ggz-professionals - in het bijzonder verpleegkundigen - te ondersteunen bij de somatische screening op gezondheidsproblemen bij mensen met een ernstige psychische aandoening, en ondersteuning te bieden bij de planning en uitvoering van vervolgactiviteiten voor preventie en tijdige diagnostiek en behandeling van somatische problemen. Gerichte leefstijlinterventies kunnen risicofactoren voor bepaalde somatische aandoeningen gunstig beïnvloeden. De richtlijn richt zich op volwassen patiënten (18-65 jaar) met een ernstige psychische aandoening of een verhoogd risico. De aanbevelingen zijn ook toepasbaar voor de POH-ggz. Medeauteurs: Marieke van Piere, Maarten Bak, Merlijn Bakkenes, Digna van der Kellen, Sonja van Hamersveld, Ronald van Gool, Katie Dermout, Titia Feldmann, Anneriek Risseeuw, Anneke Wijtsma-van der Kolk, Ingrid van Vuuren, Matthijs Rümke, Evelyn Sloots-Jongen, Paul de Heij, Richard Starmans, Cilia Daatselaar, Christine van Veen en Marleen Hermens (Werkgroep Richtlijnontwikkeling Algemene somatische screening & Leefstijl)
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Aims and objectives: To examine the predictive properties of the brief Dutch National Safety Management Program for the screening of frail hospitalised older patients (VMS) and to compare these with the more extensive Maastricht Frailty Screening Tool for Hospitalised Patients (MFST-HP). Background: Screening of older patients during admission may help to detect frailty and underlying geriatric conditions. The VMS screening assesses patients on four domains (i.e. functional decline, delirium risk, fall risk and nutrition). The 15-item MFST-HP assesses patients on three domains of frailty (physical, social and psychological). Design: Retrospective cohort study. Methods: Data of 2,573 hospitalised patients (70+) admitted in 2013 were included, and relative risks, sensitivity and specificity and area under the receiver operating characteristic (AUC) curve of the two tools were calculated for discharge destination, readmissions and mortality. The data were derived from the patients nursing files. A STARD checklist was completed. Results: Different proportions of frail patients were identified by means of both tools: 1,369 (53.2%) based on the VMS and 414 (16.1%) based on the MFST-HP. The specificity was low for the VMS, and the sensitivity was low for the MFST-HP. The overall AUC for the VMS varied from 0.50 to 0.76 and from 0.49 to 0.69 for the MFST-HP. Conclusion: The predictive properties of the VMS and the more extended MFST-HP on the screening of frailty among older hospitalised patients are poor to moderate and not very promising. Relevance to clinical practice: The VMS labels a high proportion of older patients as potentially frail, while the MFST-HP labels over 80% as nonfrail. An extended tool did not increase the predictive ability of the VMS. However, information derived from the individual items of the screening tools may help nurses in daily practice to intervene on potential geriatric risks such as delirium risk or fall risk.
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Voor u ligt de wetenschappelijke onderbouwing van de Richtlijn Somatische screening bij patiënten met een ernstige psychische aandoening (2015). Het doel van deze richtlijn is om met name verpleegkundigen te ondersteunen bij de algemene somatische screening van patiënten in de ggz met een ernstige psychische aandoening (EPA) en de te ondernemen vervolgactiviteiten. Somatische screening is zowel klinisch als maatschappelijk zeer relevant, omdat de gezondheidsproblemen van deze patiënten groot zijn en het zorgaanbod er maar beperkt op aansluit. De richtlijn is ontwikkeld voor beroepsgroepen die zorg verlenen aan mensen met een ernstige psychische aandoening: verpleegkundigen, verpleegkundig specialisten, sociaal-psychiatrisch verpleegkundigen (SPV’en), consultatief-psychiatrisch verpleegkundigen, psychologen, psychiaters, klinisch geriaters, artsen somatisch werkzaam in de ggz, internisten in de ggz, huisartsen, POH-ggz, physician assistants in de ggz, psychomotorisch therapeuten, fysiotherapeuten, diëtisten, sociotherapeuten, ergotherapeuten en ggz-agogen. Dit rapport biedt achtergrondinformatie voor alle zorgprofessionals, zorgmanagers, kwaliteitsmedewerkers en alle anderen die betrokken zijn bij de algemene somatische zorg voor mensen met een ernstige psychische aandoening en die meer willen weten over de totstandkoming van deze richtlijn. In deze onderbouwing is beschikbare wetenschappelijke kennis samengevat en wordt aangegeven welke overige overwegingen, onder meer vanuit praktijkkennis en voorkeuren vanuit patiënten- en familieperspectief, van belang waren bij het formuleren van de richtlijnaanbevelingen. Deze richtlijn is gebaseerd op wetenschappelijke evidentie, grijze literatuur, de praktijkkennis van professionals en voorkeuren vanuit patiënten- en familieperspectief. Het ontwikkeltraject bestond uit een knelpuntanalyse, een systematische inventarisatie van bestaande richtlijnen, een veldinventarisatie van beschikbare interventies, een transparant literatuuronderzoek, diverse commentaarrondes onder de werkgroep- en klankbordgroepleden en een praktijktoets. Bij de richtlijn werden een indicatorenset en een stroomschema ontwikkeld. De indicatoren worden beschreven in dit rapport. De richtlijn zelf is apart uitgegeven (Meeuwissen et al., 2015a).
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This study evaluates the concurrent validity of five malnutrition screening tools to identify older hospitalized patients against the Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria as limited evidence is available. The screening tools Short Nutritional Assessment Questionnaire (SNAQ), Malnutrition Universal Screening Tool (MUST), Malnutrition Screening Tool (MST), Mini Nutritional Assessment—Short Form (MNA-SF), and the Patient-Generated Subjective Global Assessment—Short Form (PG-SGA-SF) with cut-offs for both malnutrition (conservative) and moderate malnutrition or risk of malnutrition (liberal) were used. The concurrent validity was determined by the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the level of agreement by Cohen’s kappa. In total, 356 patients were included in the analyses (median age 70 y (IQR 63–77); 54% male). The prevalence of malnutrition according to the GLIM criteria without prior screening was 42%. The conservative cut-offs showed a low-to-moderate sensitivity (32–68%) and moderate-to-high specificity (61–98%). The PPV and NPV ranged from 59 to 94% and 67–86%, respectively. The Cohen’s kappa showed poor agreement (k = 0.21–0.59). The liberal cut-offs displayed a moderate-to-high sensitivity (66–89%) and a low-to-high specificity (46–95%). The agreement was fair to good (k = 0.33–0.75). The currently used screening tools vary in their capacity to identify hospitalized older patients with malnutrition. The screening process in the GLIM framework requires further consideration.
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PURPOSE OF REVIEW: With the shifts in society, healthcare and the profile of the malnourished individual, a re-consideration of the goal of nutritional risk screening is needed: screening for malnutrition, or screening for risk of malnutrition? In this review article, we reflect on the role of nutritional risk screening in relation to prevention and treatment of malnutrition.RECENT FINDINGS: Within the Global Leadership Initiative on Malnutrition (GLIM) Initiative, modified Delphi studies are currently being conducted to reach global consensus on the conceptual definition and operationalization of 'risk of malnutrition'. This is necessary because various studies have demonstrated that different nutritional screening tools identify different individuals, due to variability in screening tool criteria, which influences GLIM outcomes. Upon screening, three different situations can be distinguished: having risk factors for malnutrition without clear signs of presence of malnutrition, having mild signs of malnutrition (malnutrition in progress), or having obvious signs of malnutrition.SUMMARY: The outcomes of the studies on 'risk of malnutrition' will guide the screening step within the GLIM process, and will help professionals to make informed choices regarding screening policy and screening tool(s).
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BackgroundA key factor in successfully preventing falls, is early identification of elderly with a high risk of falling. However, currently there is no easy-to-use pre-screening tool available; current tools are either not discriminative, time-consuming and/or costly. This pilot investigates the feasibility of developing an automatic gait-screening method by using a low-cost optical sensor and machinelearning algorithms to automatically detect features and classify gait patterns.MethodParticipants (n = 204, age 27 ± 7 yrs.) performed a gait test under two conditions: control and with distorted depth perception (induced by wearing special goggles). Each test consisted of 4x 3m walking at comfortable speed. Full-body 3D kinematics were captured using an optical sensor (Microsoft Xbox One Kinect). Tests were conducted in a public space to establish relatively 'natural' conditions. Data was processed in Matlab and common spatiotemporal variables were calculated per gait section. The 3D-time series data of the centre of mass for each section was used as input for a neural network, that was trained to discriminate between the two conditions.ResultsWearing the goggles affected the gait pattern significantly: gait velocity and step length decreased, and lateral sway increased compared to the control condition. A 2-layer neural network could correctly classify 79% of the gait segments (i.e. with or without distorted vision).ConclusionsThe results show that gait patterns of healthy people with distorted vision could automatically be classified with the proposed approach. Future work will focus on adapting this model for identification of specific physical risk-factors in elderly.
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In a class or group of twenty children, - statistically - one child has a developmental language disorder (DLD). For children with DLD it is very difficult to keep up at school. The problems in the language also easily lead to miscommunication, which can cause behavioral problems. The timely recognition of a DLD is of great importance for early treatment. This way you can prevent or reduce problems at school, at home and in the children's leisure time. At the moment, children with DLD are not always identified early.Problems in language development can be identified early, for example at the age of two by child health workers. Parents, kindergarten teachers and elementary school teachers can also identify problems in children's language development. This requires a language screening instrument that can easily determine whether a child's language is 'at risk' or 'not at risk'. Early identification of language problems is important, but until today children are still missed. In this dissertation I present a new instrument for the identification of problems in the language development of children from one to six years old, the Early Language Scale (ELS). I also describe the development of the milestones in the language development of children, how good the current screening at the age of two at the health care office is and what parents think of this language screening. The ELS appears to detect DLD in young children well and can therefore make an important contribution to the detection of these problems at the primary health care.
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Amsterdam Airport Schiphol has faced capacity constraints, particularly during peak periods. At the security screening checkpoint, this is due to the growing number of passengers and a shortage of security staff. To improve operating performance, there is a need to integrate newer technologies that improve passing times. This research presents a discrete event simulation (DES) model for the inclusion of a shoe scanner at the security screening checkpoint at Amsterdam Airport Schiphol. Simulation is a frequently used method to assess the influence of process changes, which, however, has not been applied for the inclusion of shoe scanners in airport security screenings yet. The simulation model can be used to assess the implementation and potential benefits of an optical shoe scanner, which is expected to lead to significant improvements in passenger throughput and a decrease in the time a passenger spends during the security screening, which could lead to improved passenger satisfaction. By leveraging DES as a tool for analysis, this study provides valuable insights for airport authorities and stakeholders aiming to optimize security screening operations and enhance passenger satisfaction.
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If brief and easy to use self report screening tools are available to identify frail elderly, this may avoid costs and unnecessary assessment of healthy people. This study investigates the predictive validity of three self-report instruments for identifying community-dwelling frail elderly.
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In recent years, there has been an exponential increase in the use of health and sports-related smartphone applications (apps). This is also reflected in App-stores, which are stacked with thousands of health- and sports-apps, with new apps launched each day. These apps have great potential to monitor and support people’s physical activity and health. For users, however, it is difficult to know which app suits their needs. In this paper, we present an online tool that supports the decision-making process for choosing an appropriate app. We constructed and validated a screening instrument to assess app content quality, together with the assessment of users’ needs. Both served as input for building the tool through various iterations with prototypes and user tests. This resulted in an online tool which relies on app content quality scores to match the users’ needs with apps that score high in the screening instrument on those particular needs. Users can add new apps to the database via the screening instrument, making the tool self-supportive and future proof. A feedback loop allows users to give feedback on the recommended app and how well it meets their needs. This feedback is added to the database and used in future filtering and recommendations. The principles used can be applied to other areas of sports, physical activity and health to help users to select an app that suits their needs. Potentially increasing the long-term use of apps to monitor and to support physical activity and health.
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