BACKGROUND: Chest physiotherapy is widely used in people with cystic fibrosis in order to clear mucus from the airways.OBJECTIVES: To determine the effectiveness and acceptability of chest physiotherapy compared to no treatment or spontaneous cough alone to improve mucus clearance in cystic fibrosis.SEARCH METHODS: We searched the Cochrane Cystic Fibrosis and Genetic Disorders Group Trials Register which comprises references identified from comprehensive electronic database searches and handsearches of relevant journals and abstract books of conference proceedings.Date of the most recent search of the Group's Cystic Fibrosis Trials Register: 04 February 2013.SELECTION CRITERIA: Randomised or quasi-randomised clinical studies in which a form of chest physiotherapy (airway clearance technique) were taken for consideration in people with cystic fibrosis compared with either no physiotherapy treatment or spontaneous cough alone.DATA COLLECTION AND ANALYSIS: Both authors independently assessed study eligibility, extracted data and assessed study quality. There was heterogeneity in the published outcomes, with variable reporting which meant pooling of the data for meta-analysis was not possible.MAIN RESULTS: The searches identified 144 studies, of which eight cross-over studies (data from 96 participants) met the inclusion criteria. There were differences between studies in the way that interventions were delivered, with several of the intervention groups combining more than one treatment modality. One included study looked at autogenic drainage, six considered conventional chest physiotherapy, three considered oscillating positive expiratory pressure, seven considered positive expiratory pressure and one considered high pressure positive expiratory pressure. Of the eight studies, six were single-treatment studies and in two, the treatment intervention was performed over two consecutive days (once daily in one, twice daily in the other). This enormous heterogeneity in the treatment interventions prevented any meta-analyses from being performed.Four studies, involving 28 participants, reported a higher amount of expectorated secretions during chest physiotherapy as compared to a control. One study, involving 18 participants, reported no significant differences in sputum weight. In five studies radioactive tracer clearance was used as an outcome variable. In three of these (28 participants) it was reported that chest physiotherapy, including coughing, increased radioactive tracer clearance as compared to the control period. One study (12 participants) reported increased radioactive tracer clearance associated with all interventions compared to control, although this was only reported to have reached significance for postural drainage with percussion and vibrations; and the remaining study (eight participants) reported no significant difference in radioactive tracer clearance between chest physiotherapy, without coughing, compared to the control period. Three studies, involving 42 participants reported no significant effect on pulmonary function variables following intervention; but one further study did report significant improvement in pulmonary function following the intervention in some of the treatment groups.AUTHORS' CONCLUSIONS: The results of this review show that airway clearance techniques have short-term effects in the terms of increasing mucus transport. No evidence was found on which to draw conclusions concerning the long-term effects.
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Chest imaging plays a pivotal role in screening and monitoring patients, and various predictive artificial intelligence (AI) models have been developed in support of this. However, little is known about the effect of decreasing the radiation dose and, thus, image quality on AI performance. This study aims to design a low-dose simulation and evaluate the effect of this simulation on the performance of CNNs in plain chest radiography. Seven pathology labels and corresponding images from Medical Information Mart for Intensive Care datasets were used to train AI models at two spatial resolutions. These 14 models were tested using the original images, 50% and 75% low-dose simulations. We compared the area under the receiver operator characteristic (AUROC) of the original images and both simulations using DeLong testing. The average absolute change in AUROC related to simulated dose reduction for both resolutions was <0.005, and none exceeded a change of 0.014. Of the 28 test sets, 6 were significantly different. An assessment of predictions, performed through the splitting of the data by gender and patient positioning, showed a similar trend. The effect of simulated dose reductions on CNN performance, although significant in 6 of 28 cases, has minimal clinical impact. The effect of patient positioning exceeds that of dose reduction.
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Chest physical therapy (CPT) is a widely used intervention for patients with airway diseases. The main goal is to facilitate secretion transport and thereby decrease secretion retention in the airways. Historically, conventional CPT has consisted of a combination of forced expirations (directed cough or huff), postural drainage, percussion, and/or shaking. CPT improves mucus transport, but it is not entirely clear which groups of patients benefit from which CPT modalities. In general, the patients who benefit most from CPT are those with airways disease and objective signs of secretion retention (eg, persistent rhonchi or decreased breath sounds) or subjective signs of difficulty expectorating sputum, and with progression of disease that might be due to secretion retention (eg, recurrent exacerbations, infections, or a fast decline in pulmonary function). The most effective and important part of conventional CPT is directed cough. The other components of conventional CPT add little if any benefit and should not be used routinely. Alternative airway clearance modalities (eg, high-frequency chest wall compression, vibratory positive expiratory pressure, and exercise) are not proven to be more effective than conventional CPT and usually add little benefit to conventional CPT. Only if cough and huff are insufficiently effective should other CPT modalities be considered. The choice between the CPT alternatives mainly depends on patient preference and the individual patient's response to treatment.
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“KITT, activate super pursuit mode!” Actiefilms zijn kenmerkend vanwege de hoeveelheid stunts die erin voorkomen. Auto’s die crashen of elkaar net missen ontbreken hierin niet. Momenteel worden de stunts nog gedaan door getrainde stuntprofessionals wat de nodige risico’s met zich meebrengt. Naast de veiligheidsrisico’s spelen inschattingsfouten en menselijke communicatie een grote rol. Daarom is vanuit het mkb actief in de filmindustrie de vraag ontstaan hoe (gevaarlijke) stunts met voertuigen & beweegbare objecten veiliger, accurater en nauwkeuriger uitgevoerd kunnen worden. In deze KIEM worden de mogelijkheden van technologische toepassingen vanuit de Mobiliteit / Automotive Branche, zoals teleoperatie (het op afstand besturen van een voertuig) en autonome applicaties voor het mkb actief in de filmindustrie onderzocht. De vraag die centraal staat luidt daarom: “Wat is de potentie van technologieën als teleoperatie en autonomie binnen de Nederlandse Filmindustrie voor het uitvoeren van gevaarlijke en nauwkeurige voertuigstunts?” De vraag wordt beantwoord door zowel op schaal als op 1:1 voertuigen teleoperatie & autonome applicaties te ontwikkelen voor een specifieke stunt. Door te werken aan 1 scenario, te weten het net missen van twee voertuigen die op een kruispunt afrijden, bouwen we kennis op over de geschiktheid van teleoperatie en autonomie voor het mkb in de stuntindustrie. De resultaten van deze KIEM zullen worden vastgelegd en gepubliceerd en kunnen de basis vormen voor vervolg onderzoeken zoals een RAAK-mkb onderzoek.
Collaborative networks for sustainability are emerging rapidly to address urgent societal challenges. By bringing together organizations with different knowledge bases, resources and capabilities, collaborative networks enhance information exchange, knowledge sharing and learning opportunities to address these complex problems that cannot be solved by organizations individually. Nowhere is this more apparent than in the apparel sector, where examples of collaborative networks for sustainability are plenty, for example Sustainable Apparel Coalition, Zero Discharge Hazardous Chemicals, and the Fair Wear Foundation. Companies like C&A and H&M but also smaller players join these networks to take their social responsibility. Collaborative networks are unlike traditional forms of organizations; they are loosely structured collectives of different, often competing organizations, with dynamic membership and usually lack legal status. However, they do not emerge or organize on their own; they need network orchestrators who manage the network in terms of activities and participants. But network orchestrators face many challenges. They have to balance the interests of diverse companies and deal with tensions that often arise between them, like sharing their innovative knowledge. Orchestrators also have to “sell” the value of the network to potential new participants, who make decisions about which networks to join based on the benefits they expect to get from participating. Network orchestrators often do not know the best way to maintain engagement, commitment and enthusiasm or how to ensure knowledge and resource sharing, especially when competitors are involved. Furthermore, collaborative networks receive funding from grants or subsidies, creating financial uncertainty about its continuity. Raising financing from the private sector is difficult and network orchestrators compete more and more for resources. When networks dissolve or dysfunction (due to a lack of value creation and capture for participants, a lack of financing or a non-functioning business model), the collective value that has been created and accrued over time may be lost. This is problematic given that industrial transformations towards sustainability take many years and durable organizational forms are required to ensure ongoing support for this change. Network orchestration is a new profession. There are no guidelines, handbooks or good practices for how to perform this role, nor is there professional education or a professional association that represents network orchestrators. This is urgently needed as network orchestrators struggle with their role in governing networks so that they create and capture value for participants and ultimately ensure better network performance and survival. This project aims to foster the professionalization of the network orchestrator role by: (a) generating knowledge, developing and testing collaborative network governance models, facilitation tools and collaborative business modeling tools to enable network orchestrators to improve the performance of collaborative networks in terms of collective value creation (network level) and private value capture (network participant level) (b) organizing platform activities for network orchestrators to exchange ideas, best practices and learn from each other, thereby facilitating the formation of a professional identity, standards and community of network orchestrators.
Craft your own audience: How can a technology-driven company use online gaming communities, like Minecraft, to reach and engage a young audience? This project creates a context in which reality is simulated, by having students work together for a real client in an international context. In this project we explore innovative ways in which Samsung can engage younger audiences through Minecraft, the world's best-selling game with almost 140 million monthly players (2023). This project is focused on on educating, researching and developing playable prototypes within Minecraft that demonstrate how online gaming communities can be used to connect technology companies with a new generation of users. Societal issueInclusion of different ages around technology literacy and education (21st century skills).Benefit to societyGlobal inclusive community around education and R&D, higher cultural awareness.Collaborative partnersManchester Metropolitan University; Samsung Benelux.
