Clinical and Laboratory Data Up on Hospital Admission are Predictors of New-Onset Atrial Fibrillation in Patients Hospitalized Due to COVID-19 Pneumonia. / Variáveis Clínicas e Laboratoriais na Admissão Hospitalar são Preditores de Fibrilação Atrial Nova em Pacientes Internados com Pneumonia por COVID-19.

BACKGROUND: New-onset atrial fibrillation (NOAF) occurs in patients hospitalized due to COVID-19. It is still unknown whether clinical and laboratory data assessed upon hospital admission have predictive value for NOAF. OBJECTIVES: To analyze, upon hospital admission, variables with predictive potential for the occurrence of NOAF in patients with COVID-19 pneumonia. METHODS: Observational, retrospective, case-control study. Electronic medical reports of consecutive patients, 60 years of age or older, hospitalized due to COVID-19 pneumonia between March 1st and July 15th, 2020, were reviewed. Non-paired Student or chi-squared tests compared variables. A Cox proportional hazard model was employed to identify independent predictors of NOAF. P value < 0.05 was considered statistically significant. RESULTS: Among 667 patients hospitalized due to COVID-19, 201 (30.1%) fulfilled the inclusion criteria. NOAF was documented in 29 patients (14.4%), composing group 1. Group 2 was composed of 162 patients without NOAF. Ten patients were excluded due to the AF rhythm upon hospital admission. In groups 1 and 2, there were differences in overall in-hospital survival rate (24.1 % vs. 67.9%; p<0.001), length of stay in ICU (11.1 ± 10.5 days vs. 4.9 ± 7.5 days; p=0.004) and need for mechanical ventilation rate (82.9% vs. 32.7%; p<0.001). In the Cox model, age > 71 y/o (HR=6.8; p<0.001), total leukocyte count ≤ 7,720 cels.µL-¹ (HR=6.6; p<0.001), serum [Na+] ≤ 137 mEq.L-¹ (HR=5.0; p=0.001), SAPS3 score > 55 (HR=5.6; p=0.002), and disorientation (HR=2.5; p=0.04) on admission were independent predictors of NOAF. CONCLUSION: NOAF is a common arrhythmia in elderly hospitalized patients with COVID-19 pneumonia. Clinical and laboratory parameters evaluated on admission have a predictive value for the occurrence of NOAF during hospitalization.

FUNDAMENTO: Fibrilação atrial nova (FAN) ocorre em pacientes internados por COVID-19. Há controvérsias quanto ao valor preditivo de dados clínicos e laboratoriais à admissão hospitalar para ocorrência de FAN. OBJETIVOS: Analisar, à admissão hospitalar, variáveis com potencial preditivo para ocorrência de FAN em pacientes com pneumonia por COVID-19. MÉTODO: Estudo observacional, retrospectivo, caso-controle. Foram avaliados prontuários eletrônicos de pacientes consecutivos ≥ 60 anos, hospitalizados com pneumonia por COVID-19 entre 1º de março e 15 de julho de 2020. Comparações feitas pelos testes `t' de Student ou qui-quadrado. Foi empregado modelo de risco proporcional de Cox para identificação de preditores de FAN. Considerou-se o valor de p < 0,05 como estatisticamente significativo. RESULTADOS: Entre 667 pacientes internados por COVID-19, 201 (30,1%) foram incluídos. FAN foi documentada em 29 pacientes (14,4%) (grupo 1). Grupo 2 foi composto por 162 pacientes que não apresentaram FAN. Dez pacientes excluídos por estarem em FA na admissão hospitalar. Houve diferenças entre os grupos 1 e 2, respectivamente, no tempo de permanência em UTI (11,1±10,5 dias vs. 4,9±7,5 dias; p=0,004), necessidade de ventilação invasiva (82,9% e 32,7%; p<0,001) e mortalidade hospitalar (75,9% vs. 32,1%; p<0,001). No modelo de Cox, idade > 71 anos (hazard ratio [HR]=6,8; p<0,001), leucometria ≤ 7.720 cels.µL-1 (HR=6,6; p<0,001), natremia ≤ 137 mEq.L-1 (HR=5,0; p=0,001), escore SAPS3 > 55 (HR=5,6; p=0,002) e desorientação (HR=2,5; p=0,04) foram preditores independentes de FAN. CONCLUSÕES: FAN é uma arritmia comum em idosos hospitalizados com pneumonia por COVID-19. Parâmetros clínicos e laboratoriais avaliados na admissão são preditores de FAN durante internação.

An online platform for COVID-19 diagnostic screening using a machine learning algorithm.

OBJECTIVE: COVID-19 has brought emerging public health emergency and new challenges. It configures a complex panorama that has been requiring a set of coordinated actions and has innovation as one of its pillars. In particular, the use of digital tools plays an important role. In this context, this study presents a screening algorithm that uses a machine learning model to assess the probability of a diagnosis of COVID-19 based on clinical data. METHODS: This algorithm was made available for free on an online platform. The project was developed in three phases. First, an machine learning risk model was developed. Second, a system was developed that would allow the user to enter patient data. Finally, this platform was used in teleconsultations carried out during the pandemic period. RESULTS: The number of accesses during the period was 4,722. A total of 126 assistances were carried out from March 23, 2020, to June 16, 2020, and 107 satisfaction survey returns were received. The response rate to the questionnaires was 84.92%, and the ratings obtained regarding the satisfaction level were higher than 4.8 (on a 0-5 scale). The Net Promoter Score was 94.4. CONCLUSION: To the best of our knowledge, this is the first online application of its kind that presents a probabilistic assessment of COVID-19 using machine learning models exclusively based on the symptoms and clinical characteristics of users. The level of satisfaction was high. The integration of machine learning tools in telemedicine practice has great potential.

Sensors Network as an Added Value for the Characterization of Spatial and Temporal Air Quality Patterns at the Urban Scale.

Within the scope of the Aveiro STEAM City project, an air quality monitoring network was installed in the city of Aveiro (Portugal), to evaluate the potential of sensors to characterize spatial and temporal patterns of air quality in the city. The network consists of nine sensors stations with air quality sensors (PM10, PM2.5, NO2, O3 and CO) and two meteorological stations, distributed within selected locations in the city of Aveiro. The analysis of the data was done for a one-year measurement period, from June 2020 to May 2021, using temporal profiles, statistical comparisons with reference stations and Air Quality Indexes (AQI). The analysis of sensors data indicated that air quality variability exists for all pollutants and stations. The majority of the study area is characterized by good air quality, but specific areas-associated with hotspot traffic zones-exhibit medium, poor and bad air quality more frequently. The daily patterns registered are significantly different between the affected and non-affected road traffic sites, mainly for PM and NO2 pollutants. The weekly profile, significative deltas are found between week and weekend: NO2 is reduced on the weekends at traffic sites, but PM10 is higher in specific areas during winter weekends, which is explained by residential combustion sources.

Immunohistochemical Expression of Tensin-4/CTEN in Squamous Cell Carcinoma in Dogs.

C-terminal tensin-like (tensin-4/TNS4/CTEN) is the fourth member of the tensin family, frequently described as displaying oncological functions, including cellular migration, invasion, adhesion, growth, metastasis, epithelial to mesenchymal transition, and apoptosis, in several different types of cancer. To investigate, for the first time, the clinical significance of CTEN in squamous cell carcinoma (SCC) of dogs, we studied a total of 45 SCC sections from various dog breeds. The mean age of the affected dogs was 8.9 ± 3.6 years. Immunohistochemistry confirmed strong cytoplasmatic CTEN expression in the basal layer of the epidermis next to the tumor. We detected high CTEN expression associated with the highest grade of the tumor (grade III) and observed 100% of immunopositivity for this tumor grading (p < 0.0001). These data suggest that CTEN is an oncogene in SCC of dogs and a promising biomarker and a therapeutic target for dogs affected by SCC.

Investigating the association between ambient particulate matter (PM10) exposure and blood pressure values: Results from the link between the Portuguese Health Examination Survey and air quality data.

INTRODUCTION AND OBJECTIVES: High blood pressure (BP) remains a major modifiable cardiovascular (CV) risk factor. Several epidemiologic studies have been performed to assess the association between air pollution exposure and this CV risk factor but results remain inconsistent. This study aims to estimate the effect of short-term PM10 exposure (average previous three-day concentration) on diastolic (DBP) and systolic (SBP) blood pressure values of the resident mainland Portuguese population. METHODS: Our study was based on available DBP and SBP data from 2272 participants from the first Portuguese Health Examination Survey (INSEF, 2015) living within a 30 km radius of at least one air quality monitoring station, with available measurements of particulate matter with an aerodynamic equivalent diameter ≤10 µm (PM10). We used data from the air quality monitoring network of the Portuguese Environment Agency to obtain the individual allocated PM10 concentrations. Generalized linear models were used to assess the effect of PM10 exposure on DBP and SBP values. RESULTS: No statistically significant association was found between PM10 exposure and both DBP and SBP values (0.42% DBP change per 10 µg/m3 of PM10 increment (95% confidence interval (CI): -0.85; 1.70) and 0.47% SBP change per 10 µg/m3 of PM10 increment (95% CI: -0.86; 1.79)). Results remain unchanged after restricting the analysis to hypertensive or obese participants or changing the PM10 assessment methodology. CONCLUSIONS: In view of the PM10 levels observed in 2015, our results suggests that exposure to PM10 concentrations have a small or no effect on the blood pressure values. Other air pollutants and mixtures of pollutants that were not included in our study should considered in future studies.

Air pollution and tourism growth relationship: exploring regional dynamics in five European countries through an EKC model.

The present study intends to explore the relationship between tourism growth and air pollution at a regional level for five important tourism European destinations: France, Spain, Greece, Portugal, and Italy. Most of the studies found in the literature examine this relationship on a national scale and focus only on the CO2 pollutant, which is a greenhouse gas but not a critical pollutant in terms of air quality and human exposure. This research focuses on a regional basis (NUTS 2 classification) and takes into account the main critical pollutants in terms of urban air pollution (namely: NOx, PM10, and PM2.5), and considers 10 years, from 2009 until 2018. This work aims to investigate evidence of a tourism-induced Environmental Kuznets Curve (EKC) for the countries through the construction of five panels, one for each country, including different variables: the Gross Domestic Product, the energy consumption, and the number of nights spent at tourist accommodation establishments from both domestic and foreign tourists. The Levin-Lin-Chu unit root test proves the variables to be stationary, while the Pedroni cointegration test shows that they are integrated. The pooled OLS estimator is employed throughout the countries to check the relationship among the variables. Results reveal that the tourism-induced EKC hypothesis is not validated for any of the countries. The findings also show that in Portugal, Italy, and Greece, there is a negative relationship between economic growth and environmental pollution, while mixed evidence is found for France and Spain. Moreover, differences in the impacts of international and domestic tourists on air pollution are found: foreign tourists negatively impact emissions, while domestic ones increase them. This result is clear for Spain, Greece, and Italy. The Granger panel causality test is then conducted to see the causality among the variables.

An online platform for COVID-19 diagnostic screening using a machine learning algorithm

SUMMARY OBJECTIVE: COVID-19 has brought emerging public health emergency and new challenges. It configures a complex panorama that has been requiring a set of coordinated actions and has innovation as one of its pillars. In particular, the use of digital tools plays an important role. In this context, this study presents a screening algorithm that uses a machine learning model to assess the probability of a diagnosis of COVID-19 based on clinical data. METHODS: This algorithm was made available for free on an online platform. The project was developed in three phases. First, an machine learning risk model was developed. Second, a system was developed that would allow the user to enter patient data. Finally, this platform was used in teleconsultations carried out during the pandemic period. RESULTS: The number of accesses during the period was 4,722. A total of 126 assistances were carried out from March 23, 2020, to June 16, 2020, and 107 satisfaction survey returns were received. The response rate to the questionnaires was 84.92%, and the ratings obtained regarding the satisfaction level were higher than 4.8 (on a 0-5 scale). The Net Promoter Score was 94.4. CONCLUSION: To the best of our knowledge, this is the first online application of its kind that presents a probabilistic assessment of COVID-19 using machine learning models exclusively based on the symptoms and clinical characteristics of users. The level of satisfaction was high. The integration of machine learning tools in telemedicine practice has great potential.

A Recreational Swimming Intervention during the Whole School Year Improves Fitness and Cardiometabolic Risk in Children and Adolescents with Overweight and Obesity.

The benefits of swimming as a treatment for overweight children are undefined. We investigated the effects of recreational swimming on cardiometabolic risk in children/adolescents with normal and excess weight. Participants (n = 49, 26 girls, 10.3 ± 1.8 y) were grouped as 'eutrophic swimming' (EU-Swim, n = 14); 'excess weight swimming' (EW-Swim, n = 20) with an 'obese swimming' subgroup (OB-Swim, n = 10); and 'excess weight sedentary' (EW-Sed, n = 15) with an 'obese sedentary' subgroup (OB-Sed, n = 11). Swimming (50 min, twice/week, moderate-vigorous intensity) was an extra activity during the school year (6 + 3 months with a 3-month school break). Nutritional status, blood pressure (BP), physical activity, cardiorespiratory fitness, biochemical variables, autonomic modulation, endothelial function, abdominal fat, and carotid thickness were assessed at baseline, 6, and 12 months. Greater improvements (p < 0.05) occurred in EW-Swim vs. EW-Sed in body mass index (z-BMI, -16%, d+ 0.52), waist-to-height ratio (W/H, -8%, d+ 0.59-0.79), physical activity (37-53%, d+ 1.8-2.2), cardiorespiratory fitness (30-40%, d+ 0.94-1.41), systolic BP (SBP, -6-8%, d+ 0.88-1.17), diastolic BP (DBP, -9-10%, d+ 0.70-0.85), leptin (-14-18%, d+ 0.29-0.41), forearm blood flow (FBF, 26-41%, d+ 0.53-0.64), subcutaneous fat (SAT, -6%, d+ 0.18), and intra-abdominal fat (VAT, -16%, d+ 0.63). OB-Swim showed improvements vs. OB-Sed in TNFα (-17%, d+ 1.15) and adiponectin (22%, d+ 0.40). Swimming improved fitness and cardiometabolic risk in children/adolescents with overweight/obesity. (TCTR20220216001).

Multi-sectoral impact assessment of an extreme African dust episode in the Eastern Mediterranean in March 2018.

In late March 2018, a large part of the Eastern Mediterranean experienced an extraordinary episode of African dust, one of the most intense in recent years, here referred to as the "Minoan Red" event. The episode mainly affected the Greek island of Crete, where the highest aerosol concentrations over the past 15 yeas were recorded, although impacts were also felt well beyond this core area. Our study fills a gap in dust research by assessing the multi-sectoral impacts of sand and dust storms and their socioeconomic implications. Specifically, we provide a multi-sectoral impact assessment of Crete during the occurrence of this exceptional African dust event. During the day of the occurrence of the maximum dust concentration in Crete, i.e. March 22nd, 2018, we identified impacts on meteorological conditions, agriculture, transport, energy, society (including closing of schools and cancellation of social events), and emergency response systems. As a result, the event led to a 3-fold increase in daily emergency responses compare to previous days associated with urban emergencies and wildfires, a 3.5-fold increase in hospital visits and admissions for Chronic Obstructive Pulmonary Disease (COPD) exacerbations and dyspnoea, a reduction of visibility causing aircraft traffic disruptions (eleven cancellations and seven delays), and a reduction of solar energy production. We estimate the cost of direct and indirect effects of the dust episode, considering the most affected socio-economic sectors (e.g. civil protection, aviation, health and solar energy production), to be between 3.4 and 3.8 million EUR for Crete. Since such desert dust transport episodes are natural, meteorology-driven and thus to a large extent unavoidable, we argue that the efficiency of actions to mitigate dust impacts depends on the accuracy of operational dust forecasting and the implementation of relevant early warning systems for social awareness.

The Importance of Radiological Patterns and Small Airway Disease in Long-Term Follow-Up of Postacute COVID-19: A Preliminary Study.

Postacute COVID-19 has become a relevant public health problem, and radiological and pulmonary function tests are tools that help physicians in decision-making. The objectives of this study are to characterize the findings and patterns on a chest radiograph (CXR) and computed tomography (CT) that are most important in the postacute phase and to evaluate how these changes correlate with clinical data, spirometry, and impulse oscillometry (IOS). This was a retrospective study of 29 patients who underwent CXR, CT, spirometry, and IOS. The inclusion criteria were age >18 years and persistent respiratory symptoms after four weeks. The exclusion criteria were radiological exams with low technical quality and non-COVID-19 acute lung diseases. The inferential analysis was carried out with the chi-square (χ 2) or Fisher's exact test to evaluate the interrelationships between the clinical and COVID-19 variables according to spirometry, IOS, CT, and CXR. In our sample, 19 patients were women (65.5%). The predominance of abnormal spirometry was associated with CT's moderate/severe degree of involvement (p = 0.017; 69.2%, CI 95%: 44.1%-94.3%). There was no significant association between IOS and tomographic and radiographic parameters. A significant association was found between the classifications of the moderate/severe and normal/mild patterns on CT and CXRs (p = 0.003; 93.3%, CI 95%: 77.8%-100%). Patients with moderate/severe impairment on CXR were associated with a higher frequency of hospitalization (p = 0.033; 77.8%, CI 95%: 58.6%-97.0%) and had significantly more moderate/severe classifications in the acute phase than the subgroup with normal/mild impairment on CXR (p = 0.017; 88.9%, CI 95%: 74.4%-100%). In conclusion, the results of this study show that CXR is a relevant examination and may be used to detect nonspecific alterations during the follow-up of post-COVID-19 patients. Small airway disease is an important finding in postacute COVID-19 syndrome, and we postulate a connection between this pattern and the persistently low-level inflammatory state of the lung.

Evaluation of the experience with the use of telemedicine in a home dialysis program-a qualitative and quantitative study.

INTRODUCTION: Assisted home hemodialysis is a therapeutic modality for patients diagnosed with end-stage renal disease who require dialysis replacement therapy and have concomitant health limitations that prevent them from attending a satellite dialysis unit or performing their own treatment. OBJECTIVE: The main objective of this study was to evaluate whether telemedicine provided through telemonitoring can improve the ongoing relationship between the doctor, the nurse and the patient. METHOD: This prospective longitudinal, qualitative and quantitative study analyzes the impact of telemedicine through an evaluation of the experiences of patients and nurses. During the study, we performed remote weekly monitoring for 6 months. RESULTS: A total of 17 patients and 12 nurses were included. We observed that the patients and nurses had positive experiences with telemonitoring and highlighted feelings of being cared for and improved confidence, although they indicated that telemonitoring does not replace face-to-face visits. CONCLUSION: Telemonitoring is a useful tool to increase satisfaction with and confidence in home hemodialysis.

PM10 exposure interacts with abdominal obesity to increase blood triglycerides: a cross-sectional linkage study.

BACKGROUND: Blood lipids and glucose levels dysregulation represent potential mechanisms intermediating the adverse cardiovascular effects of ambient particulate matter (PM) exposure. This study aims to estimate the effect of long-term PM10 exposure on blood lipids and glucose levels and to assess the potential mediation and/or modification action of abdominal obesity (AO) (waist-to-height ratio). METHODS: Our study was based on 2,390 participants of the first Portuguese Health Examination Survey (INSEF, 2015) with available data on blood lipids and glucose parameters and living within a 30-km radius of an air quality monitoring station with available PM10 measurements. PM10 concentrations were acquired from the air quality monitoring network of the Portuguese Environment Agency. Generalized linear models were used to assess the effect of 1-year PM10 exposure on blood lipids and glucose levels. An interaction term was introduced in the models to test the modification action of AO. RESULTS: We found an association between PM10 and non-fasting blood triglycerides (TG) after adjustment for age, sex, education, occupation, lifestyles-related variables and temperature but only in participants with AO. Per each 1 µg/m3 PM10 increment, there was a 1.84% (95% confidence interval: 0.02-3.69) increase in TG. For the remaining blood lipid and glucose parameters, no associations were found. CONCLUSIONS: Our study demonstrates that even at low levels of exposure, long-term PM10 exposure interacts with AO to increase blood TG. Our findings suggest that reducing both AO prevalence and PM10 below current standards would result in additional health benefits for the population.

Association between respiratory hospital admissions and air quality in Portugal: A count time series approach.

Although regulatory improvements for air quality in the European Union have been made, air pollution is still a pressing problem and, its impact on health, both mortality and morbidity, is a topic of intense research nowadays. The main goal of this work is to assess the impact of the exposure to air pollutants on the number of daily hospital admissions due to respiratory causes in 58 spatial locations of Portugal mainland, during the period 2005-2017. To this end, INteger Generalised AutoRegressive Conditional Heteroskedastic (INGARCH)-based models are extensively used. This family of models has proven to be very useful in the analysis of serially dependent count data. Such models include information on the past history of the time series, as well as the effect of external covariates. In particular, daily hospitalisation counts, air quality and temperature data are endowed within INGARCH models of optimal orders, where the automatic inclusion of the most significant covariates is carried out through a new block-forward procedure. The INGARCH approach is adequate to model the outcome variable (respiratory hospital admissions) and the covariates, which advocates for the use of count time series approaches in this setting. Results show that the past history of the count process carries very relevant information and that temperature is the most determinant covariate, among the analysed, for daily hospital respiratory admissions. It is important to stress that, despite the small variability explained by air quality, all models include on average, approximately two air pollutants covariates besides temperature. Further analysis shows that the one-step-ahead forecasts distributions are well separated into two clusters: one cluster includes locations exclusively in the Lisbon area (exhibiting higher number of one-step-ahead hospital admissions forecasts), while the other contains the remaining locations. This results highlights that special attention must be given to air quality in Lisbon metropolitan area in order to decrease the number of hospital admissions.

Chest computed tomography in COVID-19 pneumonia: a retrospective study of 155 patients at a university hospital in Rio de Janeiro, Brazil.

OBJECTIVE: To define diagnostic criteria for coronavirus disease 2019 (COVID-19) on computed tomography (CT); to study the correlation between CT and polymerase chain reaction (PCR) testing for infection with severe acute respiratory syndrome coronavirus 2; and to determine whether the extent of parenchymal involvement and the need for mechanical ventilation are associated with the CT findings and clinical characteristics of patients with COVID-19. MATERIALS AND METHODS: This was a retrospective study of 155 patients with COVID-19 treated between March and May 2020. We attempted to determine whether the CT findings correlated with age and clinical variables, as well as whether the need for mechanical ventilation correlated with the extent of the pulmonary involvement. RESULTS: On average, the patients with COVID-19 were older than were those without (mean age, 54.8 years vs. 45.5 years; p = 0.031). The most common CT finding (seen in 88.6%) was ground-glass opacity, which correlated significantly with a diagnosis of COVID-19 (p = 0.0001). The CT findings that correlated most strongly with the need for mechanical ventilation were parenchymal bands (p = 0.013), bronchial ectasia (p = 0.046), and peribronchovascular consolidations (p = 0.012). The presence of one or more comorbidities correlated significantly with more extensive parenchymal involvement (p = 0.023). For the diagnosis of COVID-19, CT had a sensitivity of 84.3%, a specificity of 36.7%, and an accuracy of 73.5% (p = 0.012 vs. PCR). CONCLUSION: The patterns of CT findings are useful for the diagnosis of COVID-19 and the evaluation of disease severity criteria. The presence of any comorbidity is associated with greater severity of COVID-19.

OBJETIVO: Definir os critérios diagnósticos da COVID-19 na tomografia computadorizada (TC), estudar a concordância entre a TC e o PCR e determinar a associação da extensão do envolvimento parenquimatoso e ventilação mecânica com os achados tomográficos e características clínicas da amostra. MATERIAIS E MÉTODOS: Estudo de 155 pacientes com COVID-19 atendidos entre março e maio de 2020. Tentamos determinar se os achados da TC se correlacionavam com a idade e variáveis clínicas, bem como se a necessidade de ventilação mecânica se correlacionava com a extensão do envolvimento pulmonar. RESULTADOS: A faixa etária dos pacientes com COVID-19 (54,8 anos) foi maior do que a dos pacientes sem a doença (45,5 anos) (p = 0,031). Opacidades em vidro fosco foram as alterações mais frequentes (88,6%; p = 0,0001). Bandas parenquimatosas (p = 0,013), ectasia brônquica (p = 0,046) e consolidações peribroncovasculares (p = 0,012) foram mais frequentes nos pacientes que necessitaram de ventilação mecânica. Pacientes com comorbidades apresentaram envolvimento parenquimatoso mais extenso (p = 0,023). A TC apresentou sensibilidade de 84,3%, especificidade de 36,7% e acurácia de 73,5% (p = 0,012). CONCLUSÃO: Os padrões de TC são úteis para o diagnóstico de COVID-19 e avaliação dos critérios de gravidade da doença. Pacientes com comorbidades estão associados a condições clínicas mais graves.

Chest computed tomography in COVID-19 pneumonia: a retrospective study of 155 patients at a university hospital in Rio de Janeiro, Brazil / Tomografia computadorizada de tórax na pneumonia por COVID-19: estudo retrospectivo de 155 pacientes em um hospital universitário no Rio de Janeiro, Brasil

Abstract Objective: To define diagnostic criteria for coronavirus disease 2019 (COVID-19) on computed tomography (CT); to study the correlation between CT and polymerase chain reaction (PCR) testing for infection with severe acute respiratory syndrome coronavirus 2; and to determine whether the extent of parenchymal involvement and the need for mechanical ventilation are associated with the CT findings and clinical characteristics of patients with COVID-19. Materials and Methods: This was a retrospective study of 155 patients with COVID-19 treated between March and May 2020. We attempted to determine whether the CT findings correlated with age and clinical variables, as well as whether the need for mechanical ventilation correlated with the extent of the pulmonary involvement. Results: On average, the patients with COVID-19 were older than were those without (mean age, 54.8 years vs. 45.5 years; p = 0.031). The most common CT finding (seen in 88.6%) was ground-glass opacity, which correlated significantly with a diagnosis of COVID-19 (p = 0.0001). The CT findings that correlated most strongly with the need for mechanical ventilation were parenchymal bands (p = 0.013), bronchial ectasia (p = 0.046), and peribronchovascular consolidations (p = 0.012). The presence of one or more comorbidities correlated significantly with more extensive parenchymal involvement (p = 0.023). For the diagnosis of COVID-19, CT had a sensitivity of 84.3%, a specificity of 36.7%, and an accuracy of 73.5% (p = 0.012 vs. PCR). Conclusion: The patterns of CT findings are useful for the diagnosis of COVID-19 and the evaluation of disease severity criteria. The presence of any comorbidity is associated with greater severity of COVID-19.

Resumo Objetivo: Definir os critérios diagnósticos da COVID-19 na tomografia computadorizada (TC), estudar a concordância entre a TC e o PCR e determinar a associação da extensão do envolvimento parenquimatoso e ventilação mecânica com os achados tomográficos e características clínicas da amostra. Materiais e Métodos: Estudo de 155 pacientes com COVID-19 atendidos entre março e maio de 2020. Tentamos determinar se os achados da TC se correlacionavam com a idade e variáveis clínicas, bem como se a necessidade de ventilação mecânica se correlacionava com a extensão do envolvimento pulmonar. Resultados: A faixa etária dos pacientes com COVID-19 (54,8 anos) foi maior do que a dos pacientes sem a doença (45,5 anos) (p = 0,031). Opacidades em vidro fosco foram as alterações mais frequentes (88,6%; p = 0,0001). Bandas parenquimatosas (p = 0,013), ectasia brônquica (p = 0,046) e consolidações peribroncovasculares (p = 0,012) foram mais frequentes nos pacientes que necessitaram de ventilação mecânica. Pacientes com comorbidades apresentaram envolvimento parenquimatoso mais extenso (p = 0,023). A TC apresentou sensibilidade de 84,3%, especificidade de 36,7% e acurácia de 73,5% (p = 0,012). Conclusão: Os padrões de TC são úteis para o diagnóstico de COVID-19 e avaliação dos critérios de gravidade da doença. Pacientes com comorbidades estão associados a condições clínicas mais graves.

The impact of COVID-19 on air quality levels in Portugal: A way to assess traffic contribution.

The pandemic caused by coronavirus COVID-19 is having a worldwide impact that affects health, the economy and indirectly affects the air pollution in cities. In Portugal, the number of cases increased continually (32700 confirmed cases as of May 31, 2020), which has affected the health system and caused movement restrictions which in turn affects the air pollution in the country. This article analyses the indirect effect produced by this pandemic on air pollution in Portugal, by comparison of data from a period of movement restriction of the citizens by the government - COVID lockdown period (March-May 2020) with data from baseline conditions (mean of the mirrored periods from the five previous years (March-May from 2015 to 2019)). Air quality data - in particular NO2 and PM10 hourly concentration - from more than 20 monitoring stations spread over mainland Portugal was used to perform this evaluation. The mean reduction observed on pollutant concentrations was higher for NO2 (41%) than for PM10 (18%). For NO2, mean reductions were more significant in traffic (reaching values higher than 60% in some monitoring stations) and background urban sites than in rural stations. The reduction of NO2 concentration observed in traffic sites were compared to the estimation of traffic contribution by the incremental method, suggesting that this latter approach is not consistent (lower in same sites and higher in others) and alerting to the careful use of this approach in future works.

Climate-Change Adaptation Framework for Multiple Urban Areas in Northern Portugal.

Climate change is increasingly exerting pressure with intensified impacts in the short-, medium-, and long-term. Cities are highly vulnerable to the impacts of climate change, and it is recognized that they play a significant role in the European Strategy on adaptation to climate change. This study intends to develop a climate adaptation framework to identify effective measures that will be evaluated using a multi-urban area located in the north of Portugal, as a case study. The climate adaptation framework was developed following the Urban Adaptation Support Tool (AST), adapted to the Portuguese reality. The Weather Research and Forecasting (WRF) model was used to provide future projections with a high level of spatial resolution over the study area, increasing the accuracy of the identification of future climatic vulnerabilities. The results show a tendency for an increase of extreme weather events associated with the increase of both temperature and annual accumulated precipitation variables. A set of both urban and rural measures to promote a sustainable development path to climate adaptability and increase cities resilience to climate change are presented and discussed.

Impact of harbour activities on local air quality: A review.

Several harbour activities cause negative environmental impacts in the harbours' surrounding areas, namely the degradation of air quality. This paper intends to comprehensively review the status of the air quality measured in harbour areas. The published studies show a limited number of available air quality monitoring data in harbours areas, mostly located in Europe (71%). Measured concentrations of the main air pollutants were compiled and intercompared, for different countries worldwide allowing a large spatial representativeness. The higher NO2 and PM10 concentrations were found in Europe - ranging between 12 and 107 µg/m3 and 2-50 µg/m3, respectively, while the higher concentrations of PM2.5 were found in Asia (25-70 µg/m3). In addition, the lower levels of SO2 monitored in recent years suggest that current mitigation strategies adopted across Europe were very efficient in promoting the reduction of SO2 concentrations. Part of the reviewed studies also estimated the contributions from ship emissions to PM concentration through the application of source apportionment methods, with an average of 5-15%. In some specific harbour areas in Asia, ships can contribute up to 7-26% to the local fine particulate matter concentrations. This review confirms that emissions from the maritime transport sector should be considered as a significant source of particulate matter in harbour areas, since this pollutant concentrations are frequently exceeding the established standard legal limit values. Therefore, the results from this review boost the implementation of mitigation measures, aiming to reduce, in particular, particulate matter emissions.

Telecardiology on the diagnostic support of chest pain in twenty-two Emergency Care Units (UPA 24h) in the State of Rio de Janeiro / Telecardiology on the diagnostic support of chest pain in twenty-two Emergency Care Units (UPA 24h) in the State of Rio de Janeiro

Background: Telecardiology may be a useful support in diagnosis and management of chest pain. Objective: Evaluate the application of telecardiology to support the differential diagnosis of chest pain in patients admitted to Emergency Care Units. Method: Observational, retrospective and documental study of 5,816 patients admitted with supposedly cardiological chest pain in twenty two Emergency Care Units in the state of Rio de Janeiro. Data were tabulated and analyzed by Excel® software, using simple descriptive statistics, from the database of the Cardiology Consultancy Nucleus. Results: Diagnostic disagreement was found in 1,593 (27.39%) cases. Of these, 1,477 (92.72%) were diagnosed locally as non-ST-elevation myocardial infarction (non-STEMI), 74 (4.64%) as acute myocardial infarction with ST-segment elevation (STEMI), 40 (2.52%) as acute pulmonary edema (APE) and 2 (0.12%) as tachyarrhythmia. Intensive care referral was requested to 100% of these patients. After telecardiology, the diagnoses were: 385 (24.17%) unstable angina, 289 (18.14%) congestive heart failure, 212 (13.31%) APE, 174 (10.92%) STEMI, 152 (9.54%) hypertensive emergency, 113 (7.09%) acute chronic renal failure, 89 (5.59%) non-STEMI, 89 (5.59%) pneumonia, 39 (2.45%) sepsis, 26 (1.63 %) myopericarditis, 20 (1.26%) tachyarrhythmia and 5 (0.31%) orovalvar disease. The outcome after telecardiology was 1,178 discharges (73.94%), 338 (21.21%) referrals, 62 (3.90%) deaths and 15 (0.95%) unknown. Conclusion: Telecardiology was effective in chest pain diagnosis and management, optimizing hospital admission in the public health system