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The pandemic caused by COVID-19 meant an important change in the approach to teaching-learning strategies at all educational levels, since the face-to-face model had to be forcedly adapted to other hybrid or online models. Different national and international reports advocated carrying out this transformation for the benefit of all students, regardless of health measures. This research aims to analyze the variability of teaching methodologies of Compulsory Secondary Education and Baccalaureate teachers in face-to-face format with the didactic actions undertaken for the development of online activities during the confinement period of the 2019-2020 academic year in centers of the Community of Madrid. For this, a questionnaire was designed that, online, was sent to all the centers in which the students of the Master's Degree in Teacher Training (UCM) carried out their curricular practices, obtaining a total of 226 responses. For data analysis, a descriptive analytical model was carried out, using a cross-sectional design to determine differences between the members of the sample. The conclusions show that the low use of digital resources in the classroom on a regular basis is related to the increase in difficulties and discomfort of teachers in facing virtual teaching situations. In turn, the difficulties and discomfort of the younger teachers is similar to that of the older teachers, so some years of experience in the educational center are necessary to implement virtual teaching. © 2023, AUFOP. All rights reserved.
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BACKGROUND AND AIMS: To explore the association between body mass index (BMI) and adverse outcomes in a large cohort of patients with coronavirus disease 2019 (COVID-19). METHODS: This is a secondary analysis of a 37-site, nationwide, multicenter, retrospective cohort study that investigated the clinical and neurological outcomes of adult patients with confirmed COVID-19 admitted from February to December 15, 2020. RESULTS: We analyzed 4,463 patients with BMI and outcome data. A total of 790 (17.7%) and 710 (15.9%) had the primary outcome of in-hospital mortality and need for invasive mechanical ventilation (IMV), respectively. There was no significant association between WHO BMI groups and these outcomes. Using Asia-Pacific cutoffs showed a significant association between obesity and in-hospital mortality risk (P = 0.012). Being underweight was an independent predictor of prolonged IMV requirement regardless of BMI criteria used (P < 0.01). Obesity correlated with the need for intensive care unit admission using Asia-Pacific cutoffs (P = 0.029). There was a significant association between any BMI abnormality and odds of severe/critical COVID-19 (P < 0.05). Obese patients with concomitant acute neurological presentation/diagnosis during their COVID-19 admission were shown to have lower odds of neurologic recovery (P < 0.05). CONCLUSIONS: We found BMI abnormalities to be associated with several adverse clinical and neurologic outcomes, although such associations may be more evident with the use of race-specific BMI criteria.
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COVID-19 , Adult , Body Mass Index , Humans , Obesity/complications , Philippines , Retrospective StudiesABSTRACT
Two eucalyptol derivatives, namely 1,3,3-trimethyl-2-oxabicycle[2.2.2]oct-5-yl acetate (4) and 1,3,3trimethyl-2-oxabicycle[2.2.2]oct-5,8-yl acetate (6) have been synthesized and characterized. Their crystal structures have been solved by single-crystal X-ray diffraction methods indicating that the molecular conformation of both compounds is stabilized by intramolecular C-H center dot center dot center dot O bonds between the H-atoms of the methyl group from the eucalyptol moiety and the O-atom of the acetoxy group. In addition, we have performed a detailed investigation of the intermolecular interactions that stabilize the crystal packing of both structures by using Hirshfeld surface analysis and their associated two-dimensional fingerprint plots. The analysis reveals that the solid-state structure of compounds 4 and 6 is mainly stabilized by C-H center dot center dot center dot O hydrogen bonds and H center dot center dot center dot H bonding interactions. These interactions have also been described and studied energetically using DFT calculations. The nature and strength of these intermolecular contacts have been rationalized by using several computational tools including molecular electrostatic potential (MEP) surfaces, natural bond orbital analysis (NBO), Bader's theory of atoms in molecules (QTAIM) and non-covalent interaction plot (NCI plot) index methods. Furthermore, the intermolecular contacts observed in the crystal lattice of both compounds were experimentally studied through vibrational (IR and Raman) and H-1 and C-13 NMR spectra. The computational molecular docking analysis of the compounds has been carried out against five potential leishmanial drug targets and the main protease of SARS-CoV-2.
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Background: In response to the pandemic, closure of daycare facilities has been implemented as part of infection control, jeopardizing children's education. Whether these measures proved effective, remains up for discussion. This study aimed at understanding how the behavior of families influenced the probability of acquiring the virus in children with chronic cardiovascular (CV) health conditions. Method: The “COVID-19 Child Health Investigation of Latent Disease” study screened 6,113 children of less than 18 years in pediatric hospitals and among healthy volunteers in Hamburg from May 9 to June 30, 2020. Participants were tested for SARS-CoV-2 infection by nasopharyngeal PCR. Of them, 4,657 participants were tested for antibodies against SARS-CoV-2. The family's social and psychological situation and medical history were assessed via questionnaire. Results: A total of 6,113 (age 7.7 ± 5.1 years) patients were included in the study of which 27.3% had at least one chronic health condition. Also, 219 children (16.2%) had a CV disease. While no active infection on PCR was detected, seropositivity rate amounted to 1.3%. The seropositivity rate did not differ between the population with chronic health conditions and the healthy population (1.0 vs.1.4%, p = 0.271). Parents of children with chronic health conditions more often reported worries regarding the health risk of the virus to their children (30.9 vs. 12.6%, OR = 3.1 [2.7-3.6], p < 0.001) and were less likely to have sent their children to an educational institution 14 days before the testing (48.3 vs. 67.2%, age-adjusted OR = 0.38 [0.33-0.43], p < 0.001). We did not observe increased odds of seropositivity when visiting educational institutions in the 14 days before testing (age-adjusted OR = 1.03 [0.61-1.76], p = 0.902). Increased physical burden of the caregiver and their assessment of their child's worse well-being correlated with increased seropositivity (OR = 2.7 [1.4-5.3], p = 0.004, and 3.3 [1.2-9.5], p = 0.021). Conclusion: The prevalence of SARS-CoV-2 in children with and without chronic health conditions is similar. Still, the anxiety in parents of sick children is higher, which leads to a reduced attendance of daycare facilities. Attendance at a daycare facility does not increase the risk of seropositivity in children with health conditions. Caregivers' assessment of the physical well-being in their child is a good predictor of seropositivity. In summary, the spread of SARS-CoV-2 seems to be limited in daycare facilities even in chronically sick children with CV disease.
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Coronavirus disease 2019 (COVID-19) pneumonia is associated with a high rate of pulmonary embolism (PE). In patients with contraindications for CT pulmonary angiography (CTPA) or non-diagnostic on CTPA, perfusion single photon emission computed tomography/computed tomography (Q-SPECT/CT) is a diagnosis option. The goal of this work is to develop an Intelligent Radiomic system for the detection of PE in COVID-19 patients from the analysis of Q-SPECT/CT scans. Our Intelligent Radiomic System for identification of patients with PE (with/without pneumonia) is based on a local analysis of SPECT-CT volumes that considers both CT and SPECT values for each volume point. We present an hybrid approach that uses radiomic features extracted from each scan as input to a siamese classification network trained to discriminate among 4 different types of tissue: no pneumonia without PE (control group), no pneumonia with PE, pneumonia without PE and pneumonia with PE. The proposed radiomic system has been tested on 133 patients, 63 with COVID-19 (26 with PE, 22 without PE, 15 indeterminate-PE) and 70 without COVID-19 (31 healthy/control, 39 with PE). The per-patient recall for the detection of COVID-19 pneumonia and COVID-19 pneumonia with PE was, respectively, 91% and 81% with an area under the receiver operating characteristic curves equal to 0.99 and 0.87.
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INTRODUCTION: COVID-19 pneumonia is associated with a high rate of pulmonary embolism (PE) and its diagnosis can be changeling. In patients with contraindications for CT pulmonary angiography (CTPA) or nondiagnostic on CTPA, perfusion single photon emission computed tomography/computed tomography (Q-SPECT/CT) is a diagnosis option in patients with COVID-19 disease. Our aim was to develop an artificial intelligence (AI) model based on QSPECT/ CT images of patients during the COVID-19 pandemic which is able to classify lung lesions to optimize PE diagnosis. METHODS: Single center study with a prospective observational branch with patients who tested positive for COVID-19 and underwent a perfusion SPECT-CT study for diagnosis of PE, from April to September 2020. The second branch is retrospective, with patients in pre-pandemic period who underwent Q-SPECT/CT for diagnosis of PE from January to December 2018. For each patient, a Q-SPECT/CT based on intravenous administration of 6 mCi (222MBq) of 99mTC-macroaggregates of human-albumin (99mTC-MAA) was performed, with the subsequent tomoscintigraphy (SPECT) and a CT. The entire image pre-processing (volume exploration, segmentation analysis, registration analysis) was conducted with MATLAB. The final diagnosis for each patient and the different tissue type segments were analyzed and validated by two senior nuclear physicians. Our Intelligent Radiomic System for the identification of patients with PE (with or without pneumonia) is based on a local analysis of SPECT-CT volumes that considers both CT and SPECT values for each volume point. Volumes are first co-registered and their intensity is normalized in [0, 1] to account for differences due to acquisition. A support vector machine (SVM) model was trained to discriminate among 4 different types of tissue: no pneumonia without PE (control group), no pneumonia with PE, pneumonia without PE and pneumonia with PE. We followed a k-fold (with k=30) scheme for statistical analysis of results. RESULTS: We collected 133 patients, 63 in prospective branch (26 with PE, 22 without PE, 15 indeterminate- PE) and 70 in retrospective branch (31 healthy/control, 39 PE). Concerning the local analysis, for all cases we obtain an average sensitivity and positive predictive value over 92%. CONCLUSION: This study represents a first step towards a complete intelligent radiomic system to optimize the diagnosis of PE by Q-SPECT/CT. The capability to detect alterations in perfusion for COVID-19 pneumonia encourages developing a tool in the cloud for clinical use and further investigates if it can also predict long term complications.
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Purpose: Romance fraud refers to situations where an individual is deceived for financial gain by someone with whom the victim perceives to be in a romantic relationship. With the increase in internet use, the growth in loneliness and the increasing engagement in online dating sites during COVID-19, opportunities for romance fraud may have suffered an important increase. This paper aims to analyse changes in romance fraud, loneliness and internet use during the pandemic. Design/methodology/approach: Data about romance fraud reported to the police in the UK, and survey data recorded by the Understanding Society longitudinal survey, are used to address our research questions. Auto regressive integrated moving average (ARIMA) modelling is used to analyse whether temporal changes observed are an effect of social changes associated with lockdown and stay-at-home orders. Findings: The analysis shows that cyber-enabled romance fraud experienced a large increase after April 2020, which is greatly above any expected crime variation considering known pre-COVID trends. The increase in romance fraud was more abrupt among young adults than older persons. The results also indicate that only young adults experienced a significant increase in loneliness, while older adults reported a large increase in internet use during COVID. Originality/value: To the best of the authors’ knowledge, this is a first-of-its-kind paper analysing the effect of rapid social changes on a growing type of cyber-enabled fraud. It is likely that the growth in romance fraud during COVID is due to a combined effect of an increase in internet use and growing loneliness rates experienced by many people during the pandemic. © 2020, Emerald Publishing Limited.