Breast cancer and cervical cancer: a comparison of the period before and during the COVID-19 pandemic.

BACKGROUND: The coronavirus 2019 (COVID-19) pandemic impacted cancer health care in several countries, with delays in the detection and treatment of breast and cervical cancer. The objective of this study is to analyze and compare the screening, diagnosis and treatment of breast and cervical cancer in the pre-COVID period and during the COVID-19 period. METHODS: Cross-sectional study with secondary data collected from the Mortality Information System (SIM), Hospital Information System (SIH), Ambulatory Information System (SIA) and the Oncology Panel (PO) of breast cancer notifications with ICD C50.0 to C50.9 and cervix ICD C53.0 to C53.9, The analyzed period before the pandemic was from March 1 to October 1, 2019, and during the pandemic from March 1 to October 1, 2020. The period from 2013 to 2022 was also analyzed with the same information, including the number of diagnoses, treatments, and deaths from breast cancer and cervical cancer. The study population consisted of Brazilian women aged 25 to 70 years. In order to compare categorical variables between periods, the Chi-Square or Fisher's Exact tests, and Mann-Whitney U tests were applied, and the Poisson Regression model was applied to model the number of reported cases of COVID-19 and the amount of procedures. RESULTS: There was a decrease in the number of mammograms and cytopathological exams during COVID-19, as well as a decrease in cases of breast and cervical cancer. The Poisson regression showed that the increase in the number of COVID-19 cases caused a decrease in the number of breast cytopathological examinations, cervical-vaginal cytopathological examinations/microflora and screening, diagnosis, initiation of treatment for breast cancer and deaths from this disease. Meanwhile, in some regions of Brazil, as the number of Covid-19 increased, there was a significantly increase in the number of mammograms performed and cervical cancer diagnoses. CONCLUSIONS: The COVID-19 period in 2020 significantly impacted screening, diagnosis, treatment for breast and cervical cancer.

Bayesian Modeling and Estimation of Spatial Risk for Hospitalization and Mortality from Ischemic Heart Disease in Paraná, Brazil.

Objective: Despite significant advancements in understanding risk factors and treatment strategies, ischemic heart disease (IHD) remains the leading cause of mortality worldwide, particularly within specific regions in Brazil, where the disease is a burden. Therefore, the aim of this study was to estimate the risk of hospitalization and mortality from IHD in the state of Paraná (Brazil), using spatial analysis to identify areas with higher risk based on socioeconomic, demographic and health variables. Methods: This is an ecological study based on secondary and retrospective IHD hospitalization and mortality data obtained from the Brazilian Hospitalization and Mortality Information Systems during the 2010-2021 period. Data were analyzed for 399 municipalities and 22 health regions in the state of Paraná. To assess the spatial patterns of the disease and identify relative risk (RR) areas, we constructed a risk model by Bayesian inference using the R-INLA and SpatialEpi packages in R software. Results: A total of 333,229 hospitalizations and 73,221 deaths occurred in the analyzed period, and elevated RR of hospitalization (RR = 27.412, CI 21.801; 34.466) and mortality (RR = 15.673, CI 2.148; 114.319) from IHD occurred in small-sized municipalities. In addition, medium-sized municipalities also presented elevated RR of hospitalization (RR = 6.533, CI 1.748; 2.006) and mortality (RR = 6.092, CI 1.451; 2.163) from IHD. Hospitalization and mortality rates were higher in white men aged 40-59 years. A negative association was found between Municipal Performance Index (IPDM) and IHD hospitalization and mortality. Conclusion: Areas with increased risk of hospitalization and mortality from IHD were found in small and medium-sized municipalities in the state of Paraná, Brazil. These results suggest a deficit in health care attention for IHD cases in these areas, potentially due to a low distribution of health care resources.

Urbanization and scorpion stings in Manaus, the largest metropolis in the Brazilian Amazon.

This study analyzed a total of 260 confirmed scorpion stings reported in the city of Manaus, in the Brazilian Amazon, from 1990 to 2020. Cases were mapped according to the GPS location of their occurrence and plotted on a satellite image of the city. The stings generally occurred close to green areas, and the hotspots of stings moved north as city grew into that direction over time. Spatial analysis shows that scorpion stings mostly occur in poor, recently urbanized areas. The rapid and unplanned urbanization of originally forested areas, without offering adequate infrastructure and services, creates favorable conditions for infestation by scorpions and increases the risk of scorpion stings.

Use of machine learning to identify protective factors for death from COVID-19 in the ICU: a retrospective study.

Background: Patients in serious condition due to COVID-19 often require special care in intensive care units (ICUs). This disease has affected over 758 million people and resulted in 6.8 million deaths worldwide. Additionally, the progression of the disease may vary from individual to individual, that is, it is essential to identify the clinical parameters that indicate a good prognosis for the patient. Machine learning (ML) algorithms have been used for analyzing complex medical data and identifying prognostic indicators. However, there is still an urgent need for a model to elucidate the predictors related to patient outcomes. Therefore, this research aimed to verify, through ML, the variables involved in the discharge of patients admitted to the ICU due to COVID-19. Methods: In this study, 126 variables were collected with information on demography, hospital length stay and outcome, chronic diseases and tumors, comorbidities and risk factors, complications and adverse events, health care, and vital indicators of patients admitted to an ICU in southern Brazil. These variables were filtered and then selected by a ML algorithm known as decision trees to identify the optimal set of variables for predicting patient discharge using logistic regression. Finally, a confusion matrix was performed to evaluate the model's performance for the selected variables. Results: Of the 532 patients evaluated, 180 were discharged: female (16.92%), with a central venous catheter (23.68%), with a bladder catheter (26.13%), and with an average of 8.46- and 23.65-days using bladder catheter and submitted to mechanical ventilation, respectively. In addition, the chances of discharge increase by 14% for each additional day in the hospital, by 136% for female patients, 716% when there is no bladder catheter, and 737% when no central venous catheter is used. However, the chances of discharge decrease by 3% for each additional year of age and by 9% for each other day of mechanical ventilation. The performance of the training data presented a balanced accuracy of 0.81, sensitivity of 0.74, specificity of 0.88, and the kappa value was 0.64. The test performance had a balanced accuracy of 0.85, sensitivity 0.75, specificity 0.95, and kappa value of 0.73. The McNemar test found that there were no significant differences in the error rates in the training and test data, suggesting good classification. This work showed that female, the absence of a central venous catheter and bladder catheter, shorter mechanical ventilation, and bladder catheter duration were associated with a greater chance of hospital discharge. These results may help develop measures that lead to a good prognosis for the patient.

Mapa de Evidências - Estratégias em programas e políticas de alimentação e nutrição

O Mapa apresenta uma visão geral das evidências sobre os efeitos de ações e estratégias para promover a nutrição e a alimentação saudável nas diretrizes previstas na Política Nacional de Alimentação e Nutrição (PNAN). A partir de uma ampla busca bibliográfica para as nove diretrizes da PNAN e “Programas e Políticas de Nutrição e Alimentação”, foram incluídas 101 revisões sistemáticas (RS). O mapa representa graficamente 640 associações entre 82 tipos de intervenções distribuídos em 5 categorias e 119 desfechos distribuídos em 8 categorias, com o efeito reportado para cada associação: positivo, potencialmente positivo, inconclusivo, sem efeito ou negativo. Principais Achados: ● As RS abordaram cinco, das nove diretrizes da PNAN: Organização da Atenção Nutricional; Promoção da Alimentação Adequada e Saudável; Qualificação da Força de Trabalho; Controle e Regulação dos Alimentos; e Cooperação e articulação para a Segurança Alimentar e Nutricional. ● As 82 intervenções analisadas nas revisões foram categorizadas em: Atenção Nutricional, Alimentação Saudável, Força de Trabalho, Controle e Regulação, Segurança Alimentar. ● Os 119 desfechos foram distribuídos em oito categorias: Aleitamento materno; Educação e conhecimento; Hábito alimentar; Indicador de Saúde; Problema de Saúde; Qualidade dos alimentos; Segurança alimentar; Venda e publicidade.

Mortality in Women with Coronary Artery Disease in Paraná State, Brazil: A Bayesian Spatiotemporal Analysis.

Background: Mortality resulting from coronary artery disease (CAD) among women is a complex issue influenced by many factors that encompass not only biological distinctions but also sociocultural, economic, and healthcare-related components. Understanding these factors is crucial to enhance healthcare provisions. Therefore, this study seeks to identify the social and clinical variables related to the risk of mortality caused by CAD in women aged 50 to 79 years old in Paraná state, Brazil, between 2010 and 2019. Methods: This is an ecological study based on secondary data sourced from E-Gestor, IPARDES, and DATASUS. We developed a model that integrates both raw and standardized coronary artery disease (CAD) mortality rates, along with sociodemographic and healthcare service variables. We employed Bayesian spatiotemporal analysis with Markov Chain Monte Carlo simulations to assess the relative risk of CAD mortality, focusing specifically on women across the state of Paraná. Results: A total of 14,603 deaths from CAD occurred between 2010 and 2019. Overall, temporal analysis indicates that the risk of CAD mortality decreased by around 22.6% between 2010 (RR of 1.06) and 2019 (RR of 0.82). This decline was most prominent after 2014. The exercise stress testing rate, accessibility of cardiology centers, and IPARDES municipal performance index contributed to the reduction of CAD mortality by approximately 4%, 8%, and 34%, respectively. However, locally, regions in the Central-West, Central-South, Central-East, and Southern regions of the Central-North parts of the state exhibited risks higher-than-expected. Conclusion: In the last decade, CAD-related deaths among women in Paraná state decreased. This was influenced by more exercise stress testing, better access to cardiology centers, improved municipal performance index. Yet, elevated risks of deaths persist in certain regions due to medical disparities and varying municipal development. Therefore, prioritizing strategies to enhance women's access to cardiovascular healthcare in less developed regions is crucial.

The Impact of Time, Region, and Income Level on Stillbirth and Neonatal Mortality in Brazil, 2000-2019.

OBJECTIVE: To describe trends in perinatal loss across Brazil, a country that transitioned in 2006 from a lower-middle income to an upper-middle income country, from 2000 to 2019 and analyze the effect of municipal wealth status on perinatal outcomes. STUDY DESIGN: We conducted an ecological cohort study, based on publicly available data from the Brazilian Ministry of Health's data repository on live births and deaths. The Atlas of Human Development in Brazil was used to associate each region with a World Bank income classification. RESULTS: The national neonatal mortality rate (NMR) for infants born at ≥22 weeks of gestation decreased from 21.2 in 2000 to 12.4 in 2019. The stillbirth rate (SBR) decreased from 12.0 to 10.2 during this period. For infants born between 22 and 27 weeks of gestation, worsening perinatal outcomes were seen after 2012. In 2019, the median rates of neonatal mortality and stillbirth were both 4 points higher in lower- to middle-income municipalities compared with high-income municipalities (P < .01). CONCLUSION: Brazil has made significant progress in neonatal mortality and stillbirth from 2000 to 2019, yet inequity in perinatal outcomes remains and is correlated with municipal economic status. Nationally, ongoing improvement is needed for infants <28 weeks of gestation, and closer exploration is needed into why there are increasing rates of negative perinatal outcomes among infants born at 22-27 weeks of gestation after 2012.

Antivenom access impacts severity of Brazilian snakebite envenoming: A geographic information system analysis.

BACKGROUND: Snakebite envenoming (SBE) is a neglected tropical disease capable of causing both significant disability and death. The burden of SBE is especially high in low- and middle-income countries. The aim of this study was to perform a geospatial analysis evaluating the association of sociodemographics and access to care indicators on moderate and severe cases of SBE in Brazil. METHODS: We conducted an ecological, cross-sectional study of SBE in Brazil from 2014 to 2019 using the open access National System Identification of Notifiable Diseases (SINAN) database. We then collected a set of indicators from the Brazil Census of 2010 and performed a Principal Component Analysis to create variables related to health, economics, occupation, education, infrastructure, and access to care. Next, a descriptive and exploratory spatial analysis was conducted to evaluate the geospatial association of moderate and severe events. These variables related to events were evaluated using Geographically Weighted Poisson Regression. T-values were plotted in choropleth maps and considered statistically significant when values were <-1.96 or >+1.96. RESULTS: We found that the North region had the highest number of SBE cases by population (47.83/100,000), death rates (0.18/100,000), moderate and severe rates (22.96/100,000), and proportion of cases that took more than three hours to reach healthcare assistance (44.11%). The Northeast and Midwest had the next poorest indicators. Life expectancy, young population structure, inequality, electricity, occupation, and more than three hours to reach healthcare were positively associated with greater cases of moderate and severe events, while income, illiteracy, sanitation, and access to care were negatively associated. The remaining indicators showed a positive association in some areas of the country and a negative association in other areas. CONCLUSION: Regional disparities in SBE incidence and rates of poor outcomes exist in Brazil, with the North region disproportionately affected. Multiple indicators were associated with rates of moderate and severe events, such as sociodemographic and health care indicators. Any approach to improving snakebite care must work to ensure the timeliness of antivenom administration.

Built environment influence on the incidence of elderly pedestrian collisions in a medium-large city in southern Brazil: a spatial analysis.

Trauma disproportionately affects vulnerable road users, especially the elderly. We analyzed the spatial distribution of elderly pedestrians struck by vehicles in the urban area of Maringa city, from 2014 to 2018. Hotspots were obtained by kernel density estimation and wavelet analysis. The relationship between spatial relative risks (RR) of elderly run-overs and the built environment was assessed through Qualitative Comparative Analysis (QCA). Incidents were more frequent in the central and southeast regions of the city, where the RR was up to 2.58 times higher. The QCA test found a significant association between elderly pedestrian victims and the presence of traffic lights, medical centers/hospitals, roundabouts and schools. There is an association between higher risk of elderly pedestrians collisions and specific elements of built environments in Maringa, providing fundamental data to help guide public policies to improve urban mobility aimed at protecting vulnerable road users and planning an age-friendly city.

River dataset as a potential fluvial transportation network for healthcare access in the Amazon region.

Remote areas, such as the Amazon Forest, face unique geographical challenges of transportation-based access to health services. As transportation to healthcare in most of the Amazon Forest is only possible by rivers routes, any travel time and travel distance estimation is limited by the lack of data sources containing rivers as potential transportation routes. Therefore, we developed an approach to convert the geographical representation of roads and rivers in the Amazon into a combined, interoperable, and reusable dataset. To build the dataset, we processed and combined data from three data sources: OpenStreetMap, HydroSHEDS, and GloRiC. The resulting dataset can consider distance metrics using the combination of streets and rivers as a transportation route network for the Amazon Forest. The created dataset followed the guidelines and attributes defined by OpenStreetMap to leverage its reusability and interoperability possibilities. This new data source can be used by policymakers, health authorities, and researchers to perform time-to-care analysis in the International Amazon region.

Emergency unit capacity in Northern Tanzania: a cross-sectional survey.

INTRODUCTION: Emergency medicine (EM) is a growing field in Sub-Saharan Africa. Characterising the current capacity of hospitals to provide emergency care is important in identifying gaps and future directions of growth. This study aimed to characterise the ability of emergency units (EU) to provide emergency care in the Kilimanjaro region in Northern Tanzania. METHODS: This was a cross-sectional study conducted at 11 hospitals with emergency care capacity in three districts in the Kilimanjaro region of Northern Tanzania assessed in May 2021. An exhaustive sampling approach was used, whereby all hospitals within the three-district area were surveyed. Hospital representatives were surveyed by two EM physicians using the Hospital Emergency Assessment tool developed by the WHO; data were analysed in Excel and STATA. RESULTS: All hospitals provided emergency services 24 hours a day. Nine had a designated area for emergency care, four had a core of fixed providers assigned to the EU, two lacked a protocol for systematic triage. For Airway and Breathing interventions, oxygen administration was adequate in 10 hospitals, yet manual airway manoeuvres were only adequate in six and needle decompression in two. For Circulation interventions, fluid administration was adequate in all facilities, yet intraosseous access and external defibrillation were each only available in two. Only one facility had an ECG readily available in the EU and none was able to administer thrombolytic therapy. For trauma interventions, all facilities could immobilise fractures, yet lacked interventions such as cervical spinal immobilisation and pelvic binding. These deficiencies were primarily due to lack of training and resources. CONCLUSION: Most facilities perform systematic triage of emergency patients, though major gaps were found in the diagnosis and treatment of acute coronary syndrome and initial stabilisation manoeuvres of patients with trauma. Resource limitations were primarily due to equipment and training deficiencies. We recommend the development of future interventions in all levels of facilities to improve the level of training.

Snakebite envenoming in Brazilian children: clinical aspects, management and outcomes.

Snakebite envenoming is currently considered a neglected tropical disease, which affects over 5 million people worldwide, and causes almost 150 000 deaths every year, as well as severe injuries, amputations and other sequelae. Snakebite envenoming in children, although proportionally less frequent, is generally more severe, and represents an important challenge for pediatric medicine, since they often result in worse outcomes. In Brazil, given its ecological, geographic and socioeconomic characteristics, snakebites are considered an important health problem, presenting approximately 30 000 victims per year, approximately 15% of them in children. Even with low snakebite incidence, children tend to have higher snakebite severity and complications due to the small body mass and same venom volume inoculated in comparison to adults, even though, due to the lack of epidemiological information about pediatric snakebites and induced injuries, it is difficult to measure the treatment effectiveness, outcomes and quality of emergency medical services for snakebites in children. In this review, we report how Brazilian children are affected by snakebites, describing the characteristics of this affected population, clinical aspects, management, outcomes and main challenges.

Antivenom access impacts severity of Brazilian snakebite envenoming: a geographic information system analysis

Background Snakebite envenoming (SBE) is a neglected tropical disease capable of causing both significant disability and death. The burden of SBE is especially high in low- and middle-income countries. The aim of this study was to perform a geospatial analysis evaluating the association of sociodemographics and access to care indicators on moderate and severe cases of SBE in Brazil. Methods We conducted an ecological, cross-sectional study of SBE in Brazil from 2014 to 2019 using the open access National System Identification of Notifiable Diseases (SINAN) database. We then collected a set of indicators from the Brazil Census of 2010 and performed a Principal Component Analysis to create variables related to health, economics, occupation, education, infrastructure, and access to care. Next, a descriptive and exploratory spatial analysis was conducted to evaluate the geospatial association of moderate and severe events. These variables related to events were evaluated using Geographically Weighted Poisson Regression. T-values were plotted in choropleth maps and considered statistically significant when values were <-1.96 or >+1.96. Results We found that the North region had the highest number of SBE cases by population (47.83/100,000), death rates (0.18/100,000), moderate and severe rates (22.96/100,000), and proportion of cases that took more than three hours to reach healthcare assistance (44.11%). The Northeast and Midwest had the next poorest indicators. Life expectancy, young population structure, inequality, electricity, occupation, and more than three hours to reach healthcare were positively associated with greater cases of moderate and severe events, while income, illiteracy, sanitation, and access to care were negatively associated. The remaining indicators showed a positive association in some areas of the country and a negative association in other areas. Conclusion Regional disparities in SBE incidence and rates of poor outcomes exist in Brazil, with the North region disproportionately affected. Multiple indicators were associated with rates of moderate and severe events, such as sociodemographic and health care indicators. Any approach to improving snakebite care must work to ensure the timeliness of antivenom administration.

River dataset as a potential fluvial transportation network for healthcare access in the amazon region

Remote areas, such as the Amazon Forest, face unique geographical challenges of transportation-based access to health services. As transportation to healthcare in most of the Amazon Forest is only possible by rivers routes, any travel time and travel distance estimation is limited by the lack of data sources containing rivers as potential transportation routes. Therefore, we developed an approach to convert the geographical representation of roads and rivers in the Amazon into a combined, interoperable, and reusable dataset. To build the dataset, we processed and combined data from three data sources: OpenStreetMap, HydroSHEDS, and GloRiC. The resulting dataset can consider distance metrics using the combination of streets and rivers as a transportation route network for the Amazon Forest. The created dataset followed the guidelines and attributes defined by OpenStreetMap to leverage its reusability and interoperability possibilities. This new data source can be used by policymakers, health authorities, and researchers to perform time-to-care analysis in the International Amazon region.

Ergonomic assessment of postal workers' pain symptoms and musculoskeletal risks related to parcel processing activity for delivery.

The parcel delivery activity is carried out all over the world and workers in this sector have suffered from musculoskeletal disorders (MSDs) due to the strong demand for work generated by the recent increase in e-commerce. This study aimed to evaluate postal workers' pain symptoms, movements and identify MSDs risks related to the parcel processing activity for delivery, proposing preventive measures. A sample of thirty-two workers was evaluated with the application of sociodemographic and Nordic questionnaires and electrical bioimpedance. The motion capture sensors were used to evaluate right/left shoulder joints, segment C7-T1 (Cervical) and segment L5-S1 (Lumbar) of three postal workers (percentiles of anthropometric data: 5, 50, and 95) during four real work activities that are part of the parcel processing. The analyzed workers presented musculoskeletal complaints in practically all body regions, with a greater prevalence in shoulders, hands, lower back, and knees. According to the Body Mass Index (BMI), they were on average overweight (27.8 ± 3.7 kg/m2). In the movement analysis, we identified risks related to cervical protrusion, anterior trunk flexion, and shoulder flexion, in addition to repetitive movements. In some activities, the higher stature showed an increase in lumbar and cervical anterior flexion. The set of evaluations showed that the activity of processing orders for delivery offers musculoskeletal risks. We identify that ergonomic adaptations are necessary to adapt the heights of the work environment to the statures of the postal workers. Relevance to industry: The activity of processing orders for delivery is carried out practically all over the world generating jobs and income for its employees. Nonetheless, there are still situations of ergonomic disadvantage that can generate musculoskeletal risks. The findings elucidate ergonomic risks and provide useful information for future ergonomic interventions in the postal/delivery workplace environment.

Experiences of COVID-19 infection in North Carolina: A qualitative analysis.

BACKGROUND AND AIM: It has been demonstrated that marginalized populations across the U.S. have suffered a disproportionate burden of the coronavirus disease 2019 (COVID-19) pandemic, illustrating the role that social determinants of health play in health outcomes. To better understand how these vulnerable and high-risk populations have experienced the pandemic, we conducted a qualitative study to better understand their experiences from diagnosis through recovery. METHODS: We conducted a qualitative study of patients in a North Carolina healthcare system's registry who tested positive for COVID-19 from March 2020 through February 2021, identified from population-dense outbreaks of COVID-19 (hotspots). We conducted semi-structured phone interviews in English or Spanish, based on patient preference, with trained bilingual study personnel. Each interview was evaluated using a combination of deductive and inductive content analysis to determine prevalent themes related to COVID-19 knowledge, diagnosis, disease experience, and long-term impacts. FINDINGS: The 10 patients interviewed from our COVID-19 hotspot clusters were of equal distribution by sex, predominantly Black (70%), aged 22-70 years (IQR 45-62 years), and more frequently publicly insured (50% Medicaid/Medicare, vs 30% uninsured, vs 20% private insurance). Major themes identified included prior knowledge of COVID-19 and patient perceptions of their personal risk, the testing process in numerous settings, the process of quarantining at home after a positive diagnosis, the experience of receiving medical care during their illness, and difficulties with long-term recovery. DISCUSSION: Our findings suggest areas for targeted interventions to reduce COVID-19 transmission in these high-risk communities, as well as improve the patient experience throughout the COVID-19 illness course.

Emergency Care Gap in Brazil: Geographical Accessibility as a Proxy of Response Capacity to Tackle COVID-19.

Background: The new coronavirus disease (COVID-19) has claimed thousands of lives worldwide and disrupted the health system in many countries. As the national emergency care capacity is a crucial part of the COVID-19 response, we evaluated the Brazilian Health Care System response preparedness against the COVID-19 pandemic. Methods: A retrospective and ecological study was performed with data retrieved from the Brazilian Information Technology Department of the Public Health Care System. The numbers of intensive care (ICU) and hospital beds, general or intensivist physicians, nurses, nursing technicians, physiotherapists, and ventilators from each health region were extracted. Beds per health professionals and ventilators per population rates were assessed. A health service accessibility index was created using a two-step floating catchment area (2SFCA). A spatial analysis using Getis-Ord Gi* was performed to identify areas lacking access to high-complexity centers (HCC). Results: As of February 2020, Brazil had 35,682 ICU beds, 426,388 hospital beds, and 65,411 ventilators. In addition, 17,240 new ICU beds were created in June 2020. The South and Southeast regions have the highest rates of professionals and infrastructure to attend patients with COVID-19 compared with the northern region. The north region has the lowest accessibility to ICUs. Conclusions: The Brazilian Health Care System is unevenly distributed across the country. The inequitable distribution of health facilities, equipment, and human resources led to inadequate preparedness to manage the COVID-19 pandemic. In addition, the ineffectiveness of public measures of the municipal and federal administrations aggravated the pandemic in Brazil.

The Impact of Violence on the Anxiety Levels of Healthcare Personnel During the COVID-19 Pandemic.

Introduction: The COVID-19 pandemic stressed the importance of healthcare personnel. However, there is evidence of an increase in violence against them, which brings consequences, such as anxiety. The aim of this study was to analyze the anxiety levels of health professionals who have or not suffered violence during the COVID-19 pandemic, and verify the variables associated with the risk of starting to take medication for anxiety. Methods: We assessed the anxiety profile of health professionals in Brazil through an online questionnaire, using the Generalized Anxiety Disorder 7-item Scale (GAD-7), in relation to groups of participants who have or not suffered violence during the COVID-19 pandemic. We used Cronbach's alpha reliability coefficient to check the consistency of the responses, and the effect size using the r coefficient. Principal Component Analysis was used to verify the differences in anxiety scores between the two groups. Logistic regression analysis was also used to verify the variables associated with the risk of starting medication for anxiety and considered statistically significant when p < 0.05. Results: A total of 1,166 health professionals participated in the study, in which 34.13% had a normal anxiety profile, 40.14% mild, 15.78% moderate, and 9.95% severe. The mean score of the sum of the GAD-7 was 7.03 (SD 5.20). The group that suffered violence had a higher mean (8.40; SD 5.42) compared to the group that did not (5.70; SD 4.60). In addition, the median between both groups was significantly different (7.0 vs. 5.0; p < 0.01). Approximately 18.70% of the participants reported having started taking medication to treat anxiety during the pandemic. The factors that increased the chances of these professionals starting medication for anxiety p < 0.05 were having suffered violence during the pandemic (OR 1.97; 95% CI 1.42-2.77), being nurses (OR 1.61; 95% CI 1.04-2.47) or other types of health professionals (OR 1.58; 95% CI 1.04-2.38), and having a mild (OR 2.11; 95% CI 1.37-3.34), moderate (OR 4.05; 95% CI 2.48-6.71) or severe (OR 9.08; 95% CI 5.39-15.6) anxiety level. Conclusion: Brazilian healthcare professionals who have suffered violence during the pandemic have higher anxiety scores and higher risk to start taking anxiety medication.

Detection of Group B Streptococcus in vaginal swabs, without prior enrichment, by qPCR.

Group B Streptococcus (GBS) infection in newborns during childbirth can result in death. We described a method to detect GBS from vaginal swabs in pregnant women, without prior enrichment, using real-time polymerase chain reaction (qPCR), and compared its results to the culture method. The qPCR outperforms culture method.

A hybrid methodology for breast screening and cancer diagnosis using thermography.

Breast cancer is the second most common cancer in the world. Early diagnosis and treatment increase the patient's chances of healing. The temperature of cancerous tissues is generally different from that of healthy neighboring tissues, making thermography an option to be considered in the fight against cancer because it does not use ionizing radiation, venous access, or any other invasive process, presenting no damage or risk to the patient. In this paper, we propose a hybrid computational method using the Dynamic Infrared Thermography (DIT) and Static Infrared Thermography (SIT) for abnormality screening and diagnosis of malignant tumor (cancer), applying supervised and unsupervised machine learning techniques. We use the area under receiver operating characteristic curve, sensitivity, specificity, and accuracy as performance measures to compare the hybrid methodology with previous work in the literature. The K-Star classifier achieved accuracy of 99% in the screening phase using DIT images. The Support Vector Machines (SVM) classifier applied on SIT images yielded accuracy of 95% in the diagnosis of cancer. The results confirm the potential of the proposed approaches for screening and diagnosis of breast cancer.