Search

R E S U M O O novo coronavírus se espalhou rapidamente, logo após seu primeiro caso ser registrado em dezembro de 2019. Demonstrando a necessidade de estudos que auxiliassem nas ações de prevenção feitas por órgãos públicos da saúde. Neste contexto, o Programa de Extensão Geosaúde do Instituto Federal do Rio Grande do Sul, buscando atender a demandas da Secretaria do Município da Saúde do Rio Grande, analisou a relação entre os casos confirmados de Covid-19 e sua proximidade a estabelecimentos comerciais. Utilizou-se, assim, dados da fiscalização realizada em janeiro de 2021 pela Vigilância Sanitária a estabelecimentos da localidade São Miguel, região do município com grande número de contaminados. Os locais que não atendiam aos protocolos de contenção da Covid-19 foram utilizados na análise. Desta forma, aplicou-se a técnica de Densidade de Kernel, para os casos confirmados nos meses de dezembro (2020), janeiro (2021) e fevereiro (2021), correspondendo ao mês anterior, durante e após a fiscalização. Além disso, utilizou-se a ferramenta “distância para o ponto central mais próximo” do QGIS, objetivando medir as distâncias médias entre os casos e os estabelecimentos. Obteve-se como resultado uma redução gradual da densidade de casos confirmados após as visitas da Vigilância Sanitária. Assim como, verificou-se que, ao longo dos três meses os casos ficavam mais próximo dos estabelecimento, podendo inferir que houve uma redução na disseminação de contaminados. Portanto, entende-se que as ações foram eficientes, pois podem ter auxiliado na redução da densidade de casos, bem como influenciado na diminuição da transmissão do vírus pelos estabelecimentos comerciais. Palavras-Chaves: Mapa de Calor, Gestão Municipal, Pandemia. A B S T R A C T The new coronavirus spread quickly, after its first case was reported in December 2019. Demonstrating need for studies to assist in prevention actions carried out by public health agencies. In this context, Geosaúde Extension Program of Federal Institute of Rio Grande do Sul, seeking to meet the demands of Secretary of the Municipality of Health of Rio Grande, analyzed the relationship between confirmed cases of Covid-19 and their proximity to commercial establishments. Thus, data from the inspection carried out in January 2021 by Sanitary Surveillance of establishments in São Miguel, a region of the municipality with a large number of contaminated people, were used. Sites that did not meet Covid-19 containment protocols were used in analysis. In this way, Kernel Density technique was applied to cases confirmed in december (2020), january (2021) and february (2021), corresponding to previous month, during and after inspection. In addition, the “distance to the nearest central point” tool of QGIS was used, aiming to measure average distances between cases and establishments. The result was a gradual reduction in density of confirmed cases after visits by Health Surveillance. As well, it was found that, over three months, the cases were closer to establishment, which can infer that there was a reduction in spread of contaminated. Therefore, it is understood that actions were efficient, as they may have helped to reduce density of cases, as well as influenced reduction of transmission of virus by commercial establishments. Keywords: Heat Map, Municipal Management, Pandemic.

Background: This study investigated whether a machine-learning-based combination of radiomics and clinical parameters was superior to the use of clinical parameters alone in predicting therapy response after three months, and overall survival after six and twelve months, in stage-IV malignant melanoma patients undergoing immunotherapy with PD-1 checkpoint inhibitors and CTLA-4 checkpoint inhibitors. Methods: A random forest model using clinical parameters (demo-graphic variables and tumor markers = baseline model) was compared to a random forest model using clinical parameters and radiomics (extended model) via repeated 5-fold cross-validation. For this purpose, the baseline computed tomographies of 262 stage-IV malignant melanoma patients treated at a tertiary referral center were identified in the Central Malignant Melanoma Registry, and all visible metastases were three-dimensionally segmented (n = 6404). Results: The extended model was not significantly superior compared to the baseline model for survival prediction after six and twelve months (AUC (95% CI): 0.664 (0.598, 0.729) vs. 0.620 (0.545, 0.692) and AUC (95% CI): 0.600 (0.526, 0.667) vs. 0.588 (0.481, 0.629), respectively). The extended model was not significantly superior compared to the baseline model for response prediction after three months (AUC (95% CI): 0.641 (0.581, 0.700) vs. 0.656 (0.587, 0.719)). Conclusion: The study indicated a potential, but non-significant, added value of radiomics for six-month and twelve-month survival prediction of stage-IV melanoma patients undergoing immunotherapy.

Cutaneous melanoma (CM) is potentially the most dangerous form of skin tumor and causes 90% of skin cancer mortality. A unique collaboration of multi-disciplinary experts from the European Dermatology Forum (EDF), the European Association of Dermato-Oncology (EADO) and the European Organization for Research and Treatment of Cancer (EORTC) was formed to make recommendations on CM diagnosis and treatment, based on systematic literature reviews and the experts' experience. The diagnosis of melanoma can be made clinically and shall always be confirmed with dermatoscopy. If a melanoma is suspected, a histopathological examination is always required. Sequential digital dermatoscopy and full body photography can be used in high-risk patients to improve the detection of early melanoma. Where available, confocal reflectance microscopy can also improve clinical diagnosis in special cases. Melanoma shall be classified according to the 8th version of the American Joint Committee on Cancer classification. Thin melanomas up to 0.8 mm tumor thickness do not require further imaging diagnostics. From stage IB onwards, examinations with lymph node sonography are recommended, but no further imaging examinations. From stage IIC onwards whole-body examinations with computed tomography (CT) or positron emission tomography CT (PET-CT) in combination with brain magnetic resonance imaging are recommended. From stage III and higher, mutation testing is recommended, particularly for BRAF V600 mutation. It is important to provide a structured follow-up to detect relapses and secondary primary melanomas as early as possible. There is no evidence to define the frequency and extent of examinations. A stage-based follow-up scheme is proposed which, according to the experience of the guideline group, covers the optimal requirements, but further studies may be considered. This guideline is valid until the end of 2024. © 2022 Elsevier Ltd

Highlights • Risk of distress/burnout amongst oncology professionals continues to worsen since COVID-19 despite improved job performance. • Female and younger (≤40 years old) colleagues continue to be at higher risk of poor well-being and feeling burnout. • Job demands have increased, with nearly half now feeling overwhelmed with workload. • Concerns regarding career development/training, job security, and international fellowship opportunities remain high. • A quarter of oncology professionals reported considering changing their career, including leaving the oncology profession. Background COVID-19 has had a significant impact on the well-being and job performance of oncology professionals globally. The European Society for Medical Oncology (ESMO) Resilience Task Force collaboration set out to investigate and monitor well-being since COVID-19 in relation to work, lifestyle and support factors in oncology professionals 1 year on since the start of the pandemic. Methods An online, anonymous survey was conducted in February/March 2021 (Survey III). Key outcome variables included risk of poor well-being or distress (expanded Well-Being Index), feeling burnout (single item from expanded Well-Being Index), and job performance since COVID-19. Longitudinal analysis of responses to the series of three surveys since COVID-19 was carried out, and responses to job demands and resources questions were interrogated. SPSS V.26.0/V.27.0 and GraphPad Prism V9.0 were used for statistical analyses. Results Responses from 1269 participants from 104 countries were analysed in Survey III: 55% (n = 699/1269) female, 54% (n = 686/1269) >40 years, and 69% (n = 852/1230) of white ethnicity. There continues to be an increased risk of poor well-being or distress (n = 464/1169, 40%) and feeling burnout (n = 660/1169, 57%) compared with Survey I (25% and 38% respectively, P < 0.0001), despite improved job performance. Compared with the initial period of the pandemic, more participants report feeling overwhelmed with workload (45% versus 29%, P < 0.0001). There remain concerns about the negative impact of the pandemic on career development/training (43%), job security (37%). and international fellowship opportunities (76%). Alarmingly, 25% (n = 266/1086) are considering changing their future career with 38% (n = 100/266) contemplating leaving the profession. Conclusion Oncology professionals continue to face increased job demands. There is now significant concern regarding potential attrition in the oncology workforce. National and international stakeholders must act immediately and work closely with oncology professionals to draw up future-proof recovery plans.