¿Docentes saludables y eficaces?

El equipo Cuidem-nos («Cuidémonos»), del ICE de la Universidad Autónoma de Barcelona, trabaja en proyectos orientados a ayudar a los docentes a desarrollar una vivencia positiva y saludable del trabajo en el ámbito de la educación

Prospective cohort study for assessment of integrated care with a triple aim approach: hospital at home as use case

Background: Applicability of comprehensive assessment of integrated care services in real world settings is an unmet need. To this end, a Triple Aim evaluation of Hospital at Home (HaH), as use case, was done. As ancillary aim, we explored use of the approach for monitoring the impact of adoption of integrated care at health system level in Catalonia (Spain). Methods: Prospective cohort study over one year period, 2017-2018, comparing hospital avoidance (HaH-HA) with conventional hospitalization (UC) using propensity score matching. Participants were after the first episode directly admitted to HaH-HA or the corresponding control group. Triple Aim assessment using multiple criteria decision analysis (MCDA) was done. Moreover, applicability of a Triple Aim approach at health system level was explored using registry data. Results: HaH-HA depicted lower: i) Emergency Room Department (ER) visits (p < .001), ii) Unplanned re-admissions (p = .012); and iii) costs (p < .001) than UC. The weighted aggregation of the standardized values of each of the eight outcomes, weighted by the opinions of the stakeholder groups considered in the MCDA: i) enjoyment of life; ii) resilience; iii) physical functioning; iv) continuity of care; v) psychological wellbeing; (vi) social relationships & participation; (vii) person-centeredness; and (viii) costs, indicated better performance of HaH-HA than UC (p < .05). Actionable factors for Triple Aim assessment of the health system with a population-health approach were identified. Conclusions: We confirmed health value generation of HaH-HA. The study identified actionable factors to enhance applicability of Triple Aim assessment at health system level for monitoring the impact of adoption of integrated care. Registration: ClinicalTrials.gov (26/04/2017; NCT03130283). Keywords: Chronic care, Health Delivery Assessment, Health Services Research, Hospital at Home, Implementation Science, Multiple Criteria Decision Analysis, Triple Ai

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Perspectiva escolar

Resumen de la revista en catalánLos autores hacen un repaso, según su experiencia, de lo que ha aportado en la escuela la incorporación de los maestros especialistas, y detallan un amplio abanico de repercusiones de la coexistencia de maestros especialistas con maestros generalistas.CataluñaES

¿Docentes saludables y eficaces?

El equipo Cuidem-nos («Cuidémonos»), del ICE de la Universidad Autónoma de Barcelona, trabaja en proyectos orientados a ayudar a los docentes a desarrollar una vivencia positiva y saludable del trabajo en el ámbito de la educación

Aula de innovación educativa

Este artículo pertenece a una sección de la revista dedicada a innovación educativa, en este número a salud laboralSe exponen los objetivos y propuestas de trabajo del equipo Cuidem-nos, del ICE de la Universidad Autónoma de Barcelona, con el fin de proporcionar recursos y métodos de trabajo al docente para favorecer el desarrollo positivo y saludable de su labor personal y profesional en el ámbito educativo. Se trata de que el docente sea capaz de adquirir una serie de competencias comunicativas básicas y de enfocar su percepciones, pensamientos y emociones hacia una visión positivista que promueva el cambio individual y, por ende, el colectivo..CataluñaConsejería de Educación, Ciencia e Investigación. Biblioteca; Avda. de la Fama, 15; 30006 Murcia; Tel. +34968279685; Fax +34968279835; [email protected]

Breaking the PFAS Chain: Piezocatalytic Decomposition of Forever Chemicals Using BaTiO3 Nanoparticles

Per- and polyfluoroalkyl substances (PFAS) pose significant environmental and health risks due to their ubiquitous presence and persistence in water systems. In this study, we investigate the efficacy of piezocatalysis using barium titanate (BTO) nanoparticles under ultrasound irradiation for the degradation and defluorination of perfluorooctane sulfonate (PFOS) in water. The research demonstrates a substantial 90.5% degradation and 29% defluorination of PFOS after six hours of treatment, highlighting the potential of piezocatalysis as a promising approach for PFAS degradation. Additionally, the quantification of degradation products elucidates the transformation pathways of PFOS, suggesting a stepwise chain-shortening mechanism. Our findings underscore the importance of continued research in optimizing piezocatalytic processes and exploring synergistic approaches with other advanced oxidation methods to effectively address PFAS contamination challenges. These efforts are essential for advancing sustainable water treatment strategies and mitigating the environmental and health hazards associated with PFAS contamination

Von Willebrand factor in the outcome of temporal arteritis

OBJECTIVE: To determine fluctuation in circulating von Willebrand factor (vWF) in the outcome of patients with temporal arteritis. METHODS: Plasma vWF antigen concentrations were measured in 65 patients with biopsy proven temporal arteritis at different disease activity stages, in 12 with isolated polymyalgia rheumatica, and in 16 controls. Fourteen temporal arteritis patients underwent serial determinations during the course of their disease. RESULTS: vWF concentrations were significantly raised in temporal arteritis (mean 220 [arbitrary units], range 96 to 720) and in polymyalgia rheumatica (mean 196, range 103 to 266) compared with healthy controls (mean 98, range 75 to 137) (P < 0.05). Although vWF values tended to be higher in temporal arteritis, no significant differences were found between temporal arteritis and polymyalgia rheumatica patients nor between temporal arteritis patients with ischaemic complications (mean 269, range 130 to 720) and those who presented with polymyalgia rheumatica or constitutional symptoms only (mean 179, range 140 to 220). The highest levels were obtained in patients with associated, mainly infectious, diseases (mean 631, range 240 to 1680). Raised vWF values found in active temporal arteritis patients (mean 220, range 96 to 720) persisted within the first two years after the beginning of treatment (mean 244, range 102 to 510) but tended to normalise in patients in long term remission (mean 143, range 50 to 260). CONCLUSIONS: Persistent elevation of vWF during early remission of temporal arteritis might represent an endothelial activation status induced by a remaining inflammatory microenvironment rather than a marker of endothelial cell injury. In long term remission, decreasing vWF concentrations might reflect progression of inflammatory lesions to a healing stage