Structure-Aware Combinatorial Group Testing: A New Method for Pandemic Screening

Combinatorial group testing (CGT) is used to identify defective items from a set of items by grouping them together and performing a small number of tests on the groups. Recently, group testing has been used to design efficient COVID-19 testing, so that resources are saved while still identifying all infected individuals. Due to test waiting times, a focus is given to non-adaptive CGT, where groups are designed a priori and all tests can be done in parallel. The design of the groups can be done using Cover-Free Families (CFFs). The main assumption behind CFFs is that a small number d of positives are randomly spread across a population of n individuals. However, for infectious diseases, it is reasonable to assume that infections show up in clusters of individuals with high contact (children in the same classroom within a school, households within a neighbourhood, students taking the same courses within a university, people seating close to each other in a stadium). The general structure of these communities can be modeled using hypergraphs, where vertices are items to be tested and edges represent clusters containing high contacts. We consider hypergraphs with non-overlapping edges and overlapping edges (first two examples and last two examples, respectively). We give constructions of what we call structure-aware CFF, which uses the structure of the underlying hypergraph. We revisit old CFF constructions, boosting the number of defectives they can identify by taking the hypergraph structure into account. We also provide new constructions based on hypergraph parameters.

The Impact of Maintenance Immunosuppressive Regimen on COVID-19 Outcomes Among Kidney Transplant Patients

Purpose: Compared to azathioprine (AZA), mycophenolate (MPA) is implicated in an increased risk of several viral infections. Contrariwise, mTOR inhibitors (mTORi) are protective. Therefore, the study proposal is to evaluate the Covid-19 outcomes among kidney transplants (KT) patients under different maintenance immunosuppressive regimens. Method(s): We analyzed 90-day outcomes after Covid-19 infection using nationalwide Brazilian cohort data. RT-PCR positive patients tested between Mar/20 and Apr/21 (before immunization) were included. Patients using calcineurin-inhibitors (CNI)-free regimens were excluded. Result(s): 1,833 patients from 44 centers were analyzed, divided into three groups: CNI-AZA (n=389), CNI-MPA (n=1,258), and CNI-mTORi (n=186). Except for donor source, time after KT, and diabetes, demographics were similar among groups (Table1). The main outcomes are shown in Table 1. Considering CNI-AZA as the reference group, center-adjusted multivariable Cox regression showed that the CNIMPA group was associated with higher 30-day fatality (HR 1.65, 95% CI 1.17-2.33, p=0.004), effected also demonstrated in 90-day fatality (HR 1.43, 95%CI 1.06-1.93, p=0.020). CNI-mTORi was neutral for the 30-day fatality (HR 0.75, 95%CI 0.43- 1.29, p=0.296), but protective for the 90-day (HR 0.56, 95%CI 0.34-0.94, p=0.027). Conclusion(s): This data suggests that maintenance immunosuppressive drugs impact Covid-19 outcomes in kidney transplant patients. While MPA is associated with poor prognosis, mTORi seems to be protective. (Figure Presented).

The Prevalence of Anti-SARS-CoV-2 Antibodies After COVID-19 is Similar in Kidney Transplant Recipients to Non-Transplanted Patients, and the Clinical Severity is a Predictor of Seroconversion

Purpose: To evaluate the seroconversion rate in kidney transplant recipients (KTR), compared to two non-transplanted groups of patients, and identify predictors of seroconversion in COVID-19 convalescent patients. Method(s): A retrospective cohort study enrolled RT-PCR COVID-19 diagnosed patients (Mar/20 and Oct/2020) of three groups: 601 KTR, 211 health care workers (HCW), and 170 non-transplanted inhabitants (INH) in a countryside city in the state of Sao Paulo - Brazil. At least 14 days after diagnosis, all survivors underwent antibody testing by chemiluminescent microparticle immunoassay (titter expressed in RLU). The primary outcome was seroconversion. The group-adjusted multivariable model for the probability of seroconversion was built by generalized linear mixed models with binary logistic regression and the discrimination performance by AUC-ROC. Result(s): Several differences were observed among groups regarding demographic data and COVID-19 clinical presentation. Of note, KTR were older (54.0 years old vs. 37.0 in HCW vs. 42.0 in INH, P<0.001), more frequently had comorbidities (P<0.001), and severe COVID-19 (P<0.001). Compared to HCW and INH, respectively, admission to ICU (44.9% vs. 0% vs. 1.8%), MV requirement (32.3% vs. 0% vs. 1.8%), and death (28.8% vs. 0% vs. 1.2%) were significantly more frequent in KTR (P<0.001). On the other hand, the seroconversion rate was not different among survivors: 76.2% for KTR, 74.9% for HCW, and 82.2% for INH (P=0.35). The IgG anti-SARS-CoV-2 was slightly higher among INH: 5.8 RLU vs. 5.4 for KTR and 4.4 for HCW (P=0.009). Seroconversion was associated with a shorter time between infection and blood sample collection (OR for each day= 0.986;P<0.001) and increased by 64% if the fever was a COVID-19 symptom (OR=1.737;P=0.017), 78% if the cough was present (OR=1.785;P=0.005) and 98% if the ventilatory support was required (OR=1.981;P=0.017). This predictive model achieved an AU-ROC of 0.730 (P<0.001). Conclusion(s): As expected, the rates of clinical deterioration to ICU admission, MV requirement, and death were significantly higher among KTR. However, among the survivors, KTR had a similar rate of seroconversion, associated with clinical severity parameters and a shorter time of blood sample collection.

Delivery of Neurocritical Care Servicesto Critically Ill Patients with Altered Mental Status Before and During the COVID-19 Pandemic: A Single Center Study

Objective: Compare neurocritical care delivery and outcomes in patients with altered mental status before and during the COVID-19 pandemic. Background: Reduced utilization of inpatient radiology and routine diagnostic procedures has been reported during the COVID-19 pandemic. We hypothesized there was a reduction in the use of neurologic diagnostic procedures for patients with altered mental status. Design/Methods: Single-center retrospective study of critically-ill patients (age ≥18 years) at a large academic center in the United States. ICD-10 codes for altered mental status were used to identify eligible patients: 339 in pre COVID-19 period (June-December 2019);145 in the first wave (April-July 2020);279 in the second wave (April-July 2020). CPT codes were used to quantify neurocritical care procedures: head CTs, brain MRIs, lumbar punctures, and long-term monitoring EEGs. Results: There were no significant differences in gender, race, Comorbidity Index, or length of stay comparing the pre-COVID-19 period to each COVID-19 wave. Patients in the pre-COVID period were older (median age 64 years vs 60 years in each COVID phase;p=0.0001). There was no significant change in the frequency of head CT or MRIs, and long-term EEGs performed in patients with altered mental status across the three periods. The frequency of LPs decreased;8% in the pre-COVID period vs 6% and 4% (p=0.025) in the respective COVID periods. There was no significant difference in in-hospital mortality for patients with altered mental status across the three periods (OR 0.95 [0.78-1.08] p=0.31).Conclusions: In a large academic center the frequency of neurocritical care radiologic procedures and continuous EEG were not significantly impacted by the pandemic. Additional analysis is indicated to determine if the reduction in diagnostic LPs can be explained by differences in etiology of altered mental status across the three periods. Larger studies can determine whether the pandemic has differentially impacted neurocritical care delivery across varying resource settings.

Bibliometric Analysis Of Research on Coronavirus Infection and Patient Safety in Health Care

Objective: The study aimed at analyzing the international scientific publications on coronavirus infection and patient safety in health care. Methods: This research is a bibliometric study carried out by searching published articles in theISIWebofKnowledge/WebofScience database and analyzing the results through bibliometric analysis software HistCite. The selected time frame was between 1970 and 2020, and we used the following descriptors: “coronavirus infection” OR “severe acute respiratory syndrome” OR “COVID-19/SARS-CoV-2”. Results: We found 5,434 publications in 1,491 different journals;they are written by 18,274 authors linked to 4,064 institutions, which are located in 104 countries. In the citations analysis, the h-index was 155, and the average of citations each article received was 30.79. Conclusion: During the studied period, the Web of Science database showed two peaks of publications on coronavirus infections.The first comprised 768 articles published between 2003 and 2004 when a new coronavirus caused an outbreak of severe acute respiratory failure. The second consisted of 576 articles published between 2019 and 2020, during the period of the COVID-19 pandemic COVID-19. The knowledge on coronavirus infection should be widely shared so that new studies can be designed and the world scientific community can contribute to improving patient safety in healthcare and preventing new pandemics of severe acute respiratory infection caused by coronaviruses. © 2021 Nascimento et al.

IMPLEMENTATION OF ACTIVE METHODOLOGIES AS AN ASSESSMENT TOOL IN THE PLANT PHYSIOLOGY DISCIPLINE IN PANDEMIC TIMES: EXPERIENCES AND CHALLENGES

In view of the pandemic scenario of the new coronavirus, SARS-CoV2, educational units invested in remote education by adapting and reinventing the teaching-learning process amid uncertainties and limitations of different orders. The present study aimed to evaluate the use of some alternative methodologies such as Google forms, Conceptual map, Kahoot and Short film. It was observed that the Google forms form as well as the Short film had an acceptance of 90% of the students, 60% stated that the concept map improved the understanding of the content energy metabolism and 90,9% scored above the average 7 during the Kahoot. Therefore, the implementation of alternative methodologies as an evaluation method in order to stimulate student protagonism during remote teaching proved to be positive, allowing undergraduates to exercise autonomy in the elaboration and execution of activities in the construction of their knowledge and that of other colleagues, thus providing the experience teaching practice during graduation.

A Novel Approach to Differentiate COVID-19 Pneumonia in Chest X-ray

Radiological chest examinations like chest X-ray play a fundamental role in the fight against the outbreak of COVID-19 pneumonia, caused by the coronavirus strain SARS-Cov-2. This study aims to investigate classification models to differentiate chest X-ray images of COVID-19-based and typical pneumonia using hand-crafted radiomic features, understanding the distinctive radiographic features of COVID-19. A total of 136 segmented chest X-rays from two public databases were used to train and evaluate the classification methods. The PyRadiomics library was used to extract first and second-order statistical texture features in the right (R), left (L), and in superior, middle and bottom lung zones for each lung side. For performing feature selection, data was split in training (80%) and test (20%) sets. Stratified K-folds (K=5) was used within the training dataset for cross-validation. The most relevant radiomic features were selected after measuring validation accuracy and relative feature importance. Support vector machines (SVM), random forest (RF), AdaBoost (AB), and logistic regression (LR) were analyzed as potential classifiers. The AB model was the best discriminant method between features related to COVID-19-based when compared to typical pneumonia, using a model of lung segmentation in six distinct lung zones (AUC = 0.98). Our study shows a predominance of radiomic feature selection in the right lung, with a tendency to the upper lung zone.

COVID-19 classification in X-ray chest images using a new convolutional neural network: CNN-COVID

Purpose: COVID-19 causes lung inflammation and lesions, and chest X-ray and computed tomography images are remarkably suitable for differentiating the new disease from patients with other lung diseases. In this paper, we propose a computer model to classify X-ray images of patients diagnosed with COVID-19. Chest X-ray exams were chosen over computed tomography scans because they are low cost, results are quickly obtained, and X-ray equipment is readily available. Methods: A new CNN network, called CNN-COVID, has been developed to classify X-ray patient’s images. Images from two different datasets were used. The images of Dataset I is originated from the COVID-19 image data collection and the ChestXray14 repository, and the images of Dataset II belong to the BIMCV COVID-19+ repository. To assess the accuracy of the network, 10 training and testing sessions were performed in both datasets. A confusion matrix was generated to evaluate the model’s performance and calculate the following metrics: accuracy (ACC), sensitivity (SE), and specificity (SP). In addition, Receiver Operating Characteristic (ROC) curves and Areas Under the Curve (AUCs) were also considered. Results: After running 10 tests, the average accuracy for Dataset I and Dataset II was 0.9787 and 0.9839, respectively. Since the weights of the best test results were applied in the validation, it was obtained the accuracy of 0.9722 for Dataset I and 0.9884 for Dataset II. Conclusions: The results showed that the CNN-COVID is a promising tool to help physicians classify chest images with pneumonia, considering pneumonia caused by COVID-19 and pneumonia due to other causes. © 2021, Sociedade Brasileira de Engenharia Biomedica.

Migratory pattern of the coronavirus disease 2019 and high fatality rates among kidney transplant recipients: report from the Brazilian Multicenter Cohort Study

INTRODUCTION: The unprecedented coronavirus disease 2019 (COVID-19) pandemic has affected kidney transplant (KT) recipients, with worldwide fatality rates around 25%. Considering the well-known Brazilian socio-demographic disparities, this report describes for the first time the main outcomes of COVID-19 in KT recipients according to Brazilian geographic regions. METHODS: This multicenter national retrospective analysis included data from KT recipients with confirmed COVID-19 between March and November 2020. RESULTS: Thirty-five of the 81 centers (57% of KT activity in Brazil) reported 1,680 patients with COVID-19. The Northeast was the first to reach the peak in the number of infections. The Southeast, due to its population density, contributed with the largest number of patients. Patients had a median age of 52 years, 76% had hypertension and 34% diabetes, 75% were recipients of a deceased donor, and the time interval between diagnosis and transplantation was 5.9 years. In 53% of patients, immunosuppression was adjusted, and clinical support varied according to geographic region. Hospitalization was required for 65% of the patients, 35% of them needed intensive care, 25% mechanical ventilation, and 23% renal replacement therapy. The 90-day overall fatality was 21%, being 23% in the Southeast, 16% in the Northeast, and 19% in the Central-west and South regions. CONCLUSION: The migratory pattern of the pandemic among KT recipients followed that of the general population and the outcomes were influenced by regional features. COVID-19 in KT recipients was associated with high utilization of health-care resources and higher fatality rates than those reported in the general population.

Intersectional experiences of violence in a vulnerable and peripheral territory

Violence is a socio-cultural phenomenon that violates rights and accentuates social inequalities with noticeable implications in the health and daily life of the population. This article discusses forms of violence produced at the intersection of gender, race and class in a peripheral and highly vulnerable community located in the city of Cubatao, state of Sao Paulo. The research was guided by the theoretical framework of intersectionality and socio-historical psychology. Data were obtained using three surveys conducted from June, 2017 to November, 2020, partially during COVID-19 pandemic. Interviews and field diaries were conducted, analyzed according to Depth Hermeneutics. The material collected from four community leaders served as the basis for this article. The results point to a structural violence articulated to race, class and gender, expressed in the inaccessibility to decent conditions of housing, food and basic income. The violence against women emphasized as a result appears intermediated by the State or the organized drug trafficking. The data suggest that these forms of violence are aggravated by the inefficiency of the public policy operationalization in promoting care for the mostly black and poor population, indicating that intersectionality can be an essential tool for analysis and confrontation of social inequalities.

Pulmonary thromboembolism in conjunction with intracavitary thrombus caused by severe acute respiratory syndrome coronavirus-2 infection in a patient living with human immunodeficiency virus

Approximately one-third of patients with coronavirus disease 2019 (COVID-19) present with coagulation disorders and hematological changes. However, the clinical manifestations of COVID-19 and prognoses of people living with human immunodeficiency virus (HIV) remain controversial. This study reports the case of a 27-year-old HIV-infected man who regularly used antiretroviral medications, had no other comorbidities and was admitted for acute respiratory distress syndrome caused by COVID-19. Complementary examinations during hospitalization revealed a diagnosis of pulmonary thromboembolism in association with an intracavitary thrombus.

Intersectional experiences of violence in a vulnerable and peripheral territory

Violence is a socio-cultural phenomenon that violates rights and accentuates social inequalities with noticeable implications in the health and daily life of the population. This article discusses forms of violence produced at the intersection of gender, race and class in a peripheral and highly vulnerable community located in the city of Cubatão, state of São Paulo. The research was guided by the theoretical framework of intersectionality and socio-historical psychology. Data were obtained using three surveys conducted from June, 2017 to November, 2020, partially during COVID-19 pandemic. Interviews and field diaries were conducted, analyzed according to Depth Hermeneutics. The material collected from four community leaders served as the basis for this article. The results point to a structural violence articulated to race, class and gender, expressed in the inaccessibility to decent conditions of housing, food and basic income. The violence against women emphasized as a result appears intermediated by the State or the organized drug trafficking. The data suggest that these forms of violence are aggravated by the inefficiency of the public policy operationalization in promoting care for the mostly black and poor population, indicating that intersectionality can be an essential tool for analysis and confrontation of social inequalities.