Browsing by Author "Rojas, Hugo"
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Item BIG barrio: Arena de innovación y diseño / BIG barrio: Innovation and design arena(Universidad del Desarrollo. Facultad de Diseño, 2023-06) Rojas, HugoEste documento plantea la iniciativa BIG barrio, desde un proceso investigativo-proyectual, orientado a la transformación digital de los territorios, articulándose como una estrategia viable para la innovación social y pública en la ciudad, cercana a las necesidades, que, de modo latente, se expresan en las comunidades de usuarios y residentes de los barrios, dentro de un nuevo ciclo sociotecnológico del habitar, y una nueva relación con el espacio y tiempo, post experiencia de confinamiento. Esta arena de innovación que es el barrio, convoca el hacer de diversos actores: académicos, públicos, privados y a la comunidad barrial, en un modelo de trabajo conjunto de codiseño, transdisciplinario y transectorial, bajo un formato de operación de laboratorio vivo urbano. BIG barrio funciona como una plataforma de gestión inteligente barrial, que permite mitigar la desigualdad socio-territorial local, impulsando un desarrollo policéntrico de ciudad cercana y, a la vez, ingrávida desde su interoperabilidad en red digital; poniendo en el centro a los ciudadanos y sus intereses, para potenciar su asociatividad y relación con lo común y lo público; en un diseño de ciudad que amplía el valor de uso de su infraestructura existente, dotándola de prestaciones ampliadas de naturaleza físico-digital, habilitante de oportunidades para los ciudadanos. This document proposes the BIG barrio initiative from a research-project process. It is oriented towards the digital transformation of the territories as a viable strategy for social and public innovation in the city. An approach focused on the needs that, in a latent way, are expressed in the communities of users and residents of the neighbourhoods within a new socio-technological cycle of inhabiting. A new relationship with space and time after the experience of confinement. The neighbourhood as an innovation arena brings together different actors: academic, public, private and the neighbourhood community, in a joint work model of transdisciplinary and cross-sectorial co-design, under the operation format of an urban living laboratory. BIG barrio is an intelligent neighbourhood management platform that mitigates local socio-territorial inequality. It promotes a polycentric development of a close and weightless city through its interoperability in a digital network, placing citizens and their interests at the centre to enhance their associativity and relationship with the common and the public. A city design that expands the use value of its existing infrastructure, providing it with expanded physical-digital services which enable opportunities for citizens.Item Prospective validation of the ultrasound based TIRADS (Thyroid Imaging Reporting And Data System) classification: results in surgically resected thyroid nodules(Springer, 2017) Horvath, Eleonora; Silva, Claudio; Majlis, Sergio; Rodriguez, Ignacio; Skoknic, Velimir; Castro, Alex; Rojas, Hugo; Niedmann, Juan Pablo; Madrid, Arturo; Capdeville, Felipe; Whittle, Carolina; Rossi, Ricardo; Dominguez, Miguel; Tala, HernánOBJECTIVE: To assess performance of TIRADS classification on a prospective surgical cohort, demonstrating its clinical usefulness. METHODS: Between June 2009 and October 2012, patients assessed with pre-operative ultrasound (US) were included in this IRB-approved study. Nodules were categorised according to our previously described TIRADS classification. Final pathological diagnosis was obtained from the thyroidectomy specimen. Sensitivity, specificity, positive/negative predictive values and likelihood ratios were calculated. RESULTS: The study included 210 patients with 502 nodules (average: 2.39 (±1.64) nodules/patient). Median size was 7 mm (3-60 mm). Malignancy was 0 % (0/116) in TIRADS 2, 1.79 % (1/56) in TIRADS 3, 76.13 % (185/243) in TIRADS 4 [subgroups: TIRADS 4A 5.88 % (1/17), TIRADS 4B 62.82 % (49/78), TIRADS 4C 91.22 % (135/148)], and 98.85 % (86/87) in TIRADS 5. With a cut-off point at TIRADS 4-5 to perform FNAB, we obtained: sensitivity 99.6 % (95 % CI: 98.9-100.0), specificity 74.35 % (95 % CI: 68.7-80.0), PPV 82.1 % (95 % CI: 78.0-86.3), NPV 99.4 % (95 % CI: 98.3-100.0), PLR 3.9 (95 % CI: 3.6-4.2) and an NLR 0.005 (95 % CI: 0.003-0.04) for malignancy. CONCLUSION: US-based TIRADS classification allows selection of nodules requiring FNAB and recognition of those with a low malignancy risk. KEY POINTS: • TIRADS classification allows accurate selection of thyroid nodules requiring biopsy (TIRADS 4-5). • The recognition of benign/possibly benign patterns can avoid unnecessary procedures. • This classification and its sonographic patterns are validated using surgical specimens.Item Tumor Desmoides en una Paciente Post Parto(Sociedad de Cirujanos de Chile, 2016) Salazar, Victor; Guiñez, Gonzalo; Vial, Gustavo; Aguayo, Juan; Vivanco, Marcelo; Rojas, HugoDescripción de caso con imágenes.