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Background: The aim of this study was to describe the prevalence of persistent symptoms of COVID in hospitalized pediatric population one year after admission compared to a control group. Method(s): Prospective observational study conducted in 2 hospitals. We included patients aged 0-18 years hospitalized for acute COVID-19 more than a year ago and controls, matched by age and sex, hospitalized for causes other than COVID-19, and who had never COVID-19 at recruitment or during the follow-up. Families were contacted and a standardized survey was conducted. Persistent COVID/disease was defined as the presence of symptoms with onset in the first 3 months after COVID-19 and with persistence for more than 2 months. Result(s): 50 cases and 46 controls were analyzed, 58.3% male, 36% <5 years. Families were interviewed a median of 1.89 years (interquartile range;1.25-2.07) after hospitalization. The definition of persistent COVID-19/disease was met in 34% of cases vs. 37% of controls (p=0.767). Symptoms persisted >=11 months in 24% (12/50) of cases vs. 13% (6/46) of controls (p=0.182), with no differences by age group. The most frequent symptoms at 1 year in cases were fatigue (8%), headache (6%), poor appetite (6%), abdominal pain (6%) and variations in heart rate (6%). In controls, persistent symptoms were mostly abdominal pain (6%) and poor appetite (6%). The number of readmissions was 11/50 (22%) and 6/46 (13%) (p=0.267), respectively. On emotional/behavioral items, 16/50 (32%) of cases reported that their emotional state was worse or much worse than before admission, compared to 16/46 (34.7%). No risk factors associated with the development of persistent symptoms were found, except the length of hospital admission (p=0.043). Conclusion(s): In this study, the prevalence of persistent symptoms was not different in patients with and without COVID-19. 1-year persistence was higher in COVID-19 cases but did not reach significance. Persistence correlated with length of hospitalization.
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Along with most economic sectors, the COVID-19 crisis has had a strong impact on start-up accelerators, forcing them to seek urgent and imaginative solutions to quickly adapt to a new environment. The enforced change brought challenges that have been exacerbated by the sudden slowdown in economic activity. Despite these difficulties, it has become clear that the accelerated digital transformation that emerged through a needs-must approach to engage with start-ups through remote means has also presented new opportunities for accelerators to improve their programmes. This article analyses the impact of the COVID crisis on the organisation and results obtained by a European accelerator, which delivers programmes for growth stage technology start-ups. For this purpose, two very similar programmes have been analysed and compared: one focused on industrial technologies (delivered in 2019–2020) and another one focused on products and services built on space technologies (2020–2021). The research has been undertaken using observational techniques, reinforced through the collection of primary and secondary data throughout the study duration. The result of the analysis point to a possible post-COVID accelerator model that blends online and remote delivery as a new way of improving the experience of start-ups and optimising the use of scarce resources. © 2023 by the authors.
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Gender classification is an important biometric task. It has been widely studied in the literature. Face modality is the most studied aspect of human -gender classification. Moreover, the task has also been investigated in terms of different face components such as irises, ears, and the periocular region. In this paper, we aim to investigate gender classification based on the oral region. In the proposed approach, we adopt a convolutional neural network. For experimentation, we extracted the region of interest using the RetinaFace algorithm from the FFHQ faces dataset. We achieved acceptable results, surpassing those that use the mouth as a modality or facial sub-region in geometric approaches. The obtained results also proclaim the importance of the oral region as a facial part lost in the Covid-19 context when people wear facial mask. We suppose that the adaptation of existing facial data analysis solutions from the whole face is indispensable to keep-up their robustness.
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Introduction: Durvalumab received EMA approval as consolidation therapy (CT) for unresectable stage III NSCLC with PD-L1 ≥1% and who did not have progression after CRT. Our objective was to analyze in real clinical practice the effectiveness of durvalumab and explore the clinical factors that may be associated with the benefit from CT. Methods: Retrospective study was made at Hospital of Leon (Spain), including 37 patients with locally advanced NSCLC treated with durvalumab after CRT treatment between March 2018 and october 2021 (40.5% patients were included in the durvalumab early access program). The neutrophil-to-lymphocyte ratio (NLR) could identified after CRT as a factor that may be benefit from durvalumab. Results: Median age was 67 years (range 46-82 years). 40.5% of patients were ≥70 years old. 78.4% were male and 51.4% smokers. 54% had non-squamous histology. PD-L1 expression was <1% in 5% and not available in 8% patients. 2.7% ROS1 rearrangements, 5.4% KRAS mutations and not available in 43.2% patients. Stage IIIA, IIIB, IIIC disease were 24.3%, 54.1% and 21.6%, respectively. Median time from end of CRT to onset durvalumab was 44 days (range 13-120 days). Overall median CT duration was 214.8 days (range 69-399 days) with a median of 14 infusions (range 6-27 infusions). With a median follow up of 19.7 months (range 1.4-34.9 months);67.6% had stopped CT: 37.8% due to completing treatment, 16.2% disease progression, 10.8% adverse event and 2.7% due to COVID19 infection. Median real-world progression-free survival (rwPFS) was 17 months (95% CI, 11-23). Median real-world overall survival (rwOS) was 29.9 months (95% CI, 23.3-36.6). %rwOS at 6, 18 and 24 months were 100%, 86.9% and 74.5%, respectively. For patients with post-CRT NLR not exceeding the cohort median value of 6, receipt of durvalumab was associated with an improvement in rwOS (median not reached vs 25.7 months;p=0.025). 56.8% patients had any grade of radiation pneumonitis (median time from CRT start: 119 days [range 36-241 days]). Of these, 19% patients developed worsening of radiation pneumonitis with durvalumab. 54,1% developed immune-mediated toxicity, mostly G1-2 (85.1%). Conclusions: Our results demonstrate the effectiveness of durvalumab consolidation in this patients population in a real-life setting. We identified low NLR after CRT as a potentially predictive factor for the benefit of CT in locally advanced NSCLC. Keywords: DURVALUMAB, PACIFIC, REAL WORLD DATA
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Background: High disease activity, treatment with glucocorticoids (GC) and rituximab (RTX), have been related to worse outcomes of COVID-19. Objectives: To assess the clinical characteristics and severity of the SARS-CoV-2 infection in patients with rheumatoid arthritis (RA) included in the SAR-COVID registry and to identify factors associated with poor outcomes. Methods: SAR-COVID is a national, longitudinal and observational registry. Patients of ≥18 years old, with diagnosis of RA (ACR-EULAR criteria 2010) who had confrmed SARS-CoV-2 infection (RT-PCR or positive serology) were included between 13-8-20 and 31-7-21. Sociodemographic and clinical data, comorbidities, disease activity and treatment at the moment of the SARS-CoV-2 infection were collected. Additionally, infection symptoms, complications, medical interventions and treatments for COVID-19 were registered. Infection severity was assessed using the WHO-ordinal scale (WHO-OS)1. A cut-off value of ≥5 identifed patients with severe COVID-19 and those who died. Statistical analysis: Descriptive statistics. Chi2 or Fischer test, Student T test or Mann-Whitney and Kruskal Wallis or ANOVA, as appropriate. Multiple logistic regression model. Results: A total of 801 patients were included, with a mean age of 53.1 ± 12.9 years, most of them were female (84.5%) and the median (m) disease duration was 8 years (IQR 4-14). One third were in remission and 46.4% had comor-bidities, being the most frequent, hypertension (26.9 %), dyslipidemia (13.5 %), obesity (13.4 %) and diabetes (8.9%). Moreover, 3.2% had interstitial lung disease (ILD) associated with RA. At SARS-CoV-2 diagnosis, 42.5% were receiving glucocorticoids (GC), 73.9% conventional (c) disease modifying antirheumatic drugs (DMARD), 24% biologic (b) DMARD and 9.1% targeted synthetic (ts) DMARD. Among bDMARD, the most frequently used were TNF inhibitors (17%), followed by abatacept (2.8%), IL-6 inhibitors (2.4%) and rituximab (RTX) (2.1%). During the SARS-CoV-2 infection, 95.8% had symptoms, 27% required hospital-ization, 7.9% presented complications and 4.4% died due to COVID-19. Severe disease and death (WHO-OS≥5) was present in 7.5% of the patients. They were older (62.9±12.5 vs 52.2±12.7, p<0.001), and they had more frequently ILD (18.5% vs 2%, p<0.001), comorbidities (82.5% vs 43.7%, p<0.001), ≥2 comor-bidities (60.3% vs 25.8%, p<0.001), treatment with GC (61% vs 40.7%, p=0.04) and RTX (8.3% vs 1.6%, p=0.007). Conversely, the use of cDMARD and TNF inhibitors was more frequent in patients with WHO-OS<5, nevertheless this difference was not signifcant. Disease activity was comparable between groups. In multivariable analysis, older age, the presence of diabetes, ILD, the use of GC and RTX were signifcantly associated with WHO-OS≥5 (Figure 1). Furthermore, older age (65.7±10.8 vs 52.4±12.8, p<0.001), the presence of comor-bidities (87.9% vs 44.7%, p<0.001), chronic obstructive pulmonary disease (21.9% vs 5.2%, p=0.002), diabetes (30.3% vs 7.9%, p<0.001), hypertension (57.6% vs 25.6%, p<0.001), cardiovascular disease (15.6% vs 3.2%, p=0.005), cancer (9.1% vs 1.3%, p=0.001), ILD (23.3% vs 2.4%, p<0.001) and the use of GC (61.8% vs 41.4%, p=0.02) were associated with mortality. Older age [OR 1.1 IC95% 1.06-1.13] and the use of GC 5-10 mg/day [OR 4.6 IC95% 1.8-11.6] remained signifcantly associated with death due to COVID-19. Conclusion: Treatment with RTX and GC, as well as older age, the presence of diabetes and ILD were associated with poor COVID-19 outcomes in this national cohort of patients with RA. Older patients and those taking GC had a higher mortality rate.
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Background: On October 2020 the Health and Labor Departments of Argentina decreed workers with BMI ≥ 40 kg / m2, a risk group for serious forms of COVID infection, had to suspend attendance at the workplace. On November 2020, a virtual multi-component intervention weight loss program was implemented for workers of an oil and gas company reached by the decree. The primary objective was to achieve significant weight loss to reduce health risks associated to obesity. The secondary objective was to achieve the return to work of the employees. Methods: 89 employees with grade 3 obesity from different areas of Argentina, including remote areas (Patagonia and Yungas -mountain jungle-), were invited to participate in a 3-month weight loss program. The program consisted in weekly virtual workshops on diet, physical activity and behavior change;plus telemedicine consultations based on motivational interview with physician, nutritionist, psychologist, and nurse. A cell phone app was designed to promote self-management of the disease: recording of weight progression, physical activity and meals. It also gave participants access to recorded weekly workshops, and a reservation system for appointments. Results: Average initial BMI was 46.03 kg/m2. After 3 months of intervention, 52 participants (58%) achieved a decrease in BMI < 40 kg/m2 and returned to work. 31.4% participants achieved a decrease of ≥5% and 23.6% of ≥10% of their initial weight. In the 6-month longitudinal follow-up, 66% of participants achieved BMI < 40 kg / m2. Conclusions: The context of the Covid 19 pandemic was an opportunity to install obesity as a disease in the workplace and increased awareness of employers and employees on health risks associated to it. The implementation of a structured virtual weight loss program on the workplace setting can be an effective obesity approach, including remote areas.
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Global energy consumption is growing due to multiple reasons, such as the COVID-19 pandemic. In order to improve the efficiency of energy consumption and thus contribute to the protection of the environment, governments are implementing new energy efficiency policies. Prediction of energy consumption is one of the most important objectives in this regard. Forecasting algorithms based on machine learning approaches have proven to be a robust solution to provide predictions based on energy consumption data. In this paper, we present a comparative study of different forecasting approaches on an energy consumption dataset collected from a Paraguayan electricity distribution provider. In the analysis, historical windows, W, of {7, 14, 28, 84} days and a prediction horizon, h of one day were used. Models were evaluated using the coefficient of determination (R-2), the mean absolute error(MAE), the root mean squared error (RMSE), and the mean absolute percentage error (MAPE). The results achieved show that, among the techniques studied, Artificial Neural Networks are the best strategy to capture the complexity of the data. Furthermore, the performance of linear regression is outstanding, taking into account its simplicity.
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Background and Aims: We evaluated whether stroke severity, functional outcome and mortality are different in patients with ischemic stroke with or without COVID-19 infection. Methods: A prospective, observational, multicentre cohort study in Catalonia, Spain. Recruitment was consecutive from mid-March to mid-May 2020. Patients had had an acute ischemic stroke within 48 hours and a previous modified Rankin scale (mRS) score of 0 to 3. We collected demographic data, vascular risk factors, prior mRS score, NIHSS score, rate of reperfusion therapies, logistics and metrics. Primary end-point was functional outcome at 3 months. Favourable outcome was defined depending on the previous mRS score. Secondary outcome was mortality at 3 months. We performed mRS shift and multivariate analyses. Results: We evaluated 701 patients (mean age 72.3±13.3 years, 60.5% men), and 91 (13%) had COVID-19 infection. Median baseline NIHSS score was higher in COVID-19 patients compared to patients without COVID-19 [8 (3-18) vs 6 (2-14), p=0.049)]. Proportion of patients with a favourable functional outcome was 33.7% in the COVID-19 and 47% in the non-COVID-19 group. However, after a multivariate logistic regression analysis, COVID-19 infection did not increase the probability of unfavourable functional outcome. Mortality rate was 39.3% among COVID-19 patients and 16.1% in the non-COVID-19 group. In the multivariate logistic regression analysis, COVID-19 infection was a risk factor for mortality (HR 3.14 (95% CI, 2.10-4.71;p<0.001). Conclusions: Patients with ischemic stroke and COVID-19 infection have more severe strokes and higher mortality than stroke patients without COVID-19 infection. However, functional outcome is comparable in both groups.
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Emotions play an important role in learning. As a part of our research efforts on algorithm education, we planned to evaluate the impact of an educational system to experiment with algorithms on students' emotions. The advent of the COVID-19 pandemic changed both the educational context and the educational process. We redesigned our study to inquire two research questions: (a) what is the emotional level of students in the current situation?, and (b) what is the emotional impact of OptimEx on students of an algorithm course? We planned an evaluation in a lab session under mixed conditions, i.e. students could choose between attending physically or virtually. We used the PANAS questionnaire, which allows assessing 20 emotions, classified into positive and negative. The outcomes show that students experienced higher emotional levels for positive emotions than negative. Furthermore, students who attended face-to-face scored stronger emotions. After the session, all students decreased their negative emotional levels, with the students who attended physically also experiencing an increase in positive emotions. Due to the pandemic situation, the study was conducted with less control than we intended, therefore it is better qualified as an exploratory study. © 2021 IEEE.
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This article presents a double evaluation carried out in the subject Didactics of Computer Science and Technology, corresponding to the Master's degree teacher training in secondary education, baccalaureate, vocational training and languages taught by Universidad Rey Juan Carlos. Students of the subject had to learn how to prepare simple web pages, using HTML, CSS and JavaScript programming languages. To this end, flipped classroom technique was used to present the necessary contents, combined with an adaptation of Aronson's cooperative learning puzzle technique, used to carry out a group practice that reflected the knowledge acquired. It is worth mentioning, as a complement to the two techniques used, the use of an adapted assessment rubric, which was provided to the students at the beginning of the teaching block. The evaluation was carried out during two consecutive academic years, 2018/2019 and 2019/2020. There were important differences between the two studies: in the first study, students' previous self-assigned level was much higher (2.8 points as opposed to 1.4 points on a scale of 1 to 5). The other difference, even more relevant, was that in the second year all teaching was done at home, in a non-attendance format, on a mandatory basis, due to the period of confinement decreed by the state of alarm at that moment, because of the pandemic caused by the SARS-CoV-2 virus, popularly known as coronavirus. It is remarkable that, despite these differences, the students expressed their satisfaction with the learning acquired and with the tasks performed in both cases. The techniques used were well-appreciated, in first year more than in the second, and especially flipped classroom. Scores obtained were, in addition, always very relevant.
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Background: SARS-CoV2 infection severity during pregnancy and posible consequences for exposed newborns information is still unknown. The objective of this study is to analyse clinical and epidemiological characteristics of a SARS-CoV2 infected women during pregnancy and their newborns cohort. Methods: Multicentric observational study from the Spanish GENEO-COVID cohort (participating in RECLIP). Infected pregnant women and their newborns born from 15 March to 31 July with a 15 days follow up were included. Data regarding epidemiological, clinical, virological and immunological characteristics of the patients was collected. Results: Globally, 105 pregnant women with a median age of 34 (IQR: 29-37) years old and 107 newborns were included in the study. Median gestational age at diagnosis was 36.9 (IQR-33.4-39.2) weeks, and 6.7% os women were diagnosed in the second trimester. More than 34% of the women presented at least one comorbidity and almost 65% of women had COVID19 symptoms and 43% of them were treated for the infection. Overall, 30.8% had COVID-19 pneumonia and 4.8% were admitted to the intensive care unit (ICU) needing invasive mechanical ventilation. The rate of positive RT-PCR at delivery was 61.9%. There was a 36.2% rate of caesarean sections, associated with pneumonia during pregnancy OR:4.2 (95% CI 1.5,12.0) and lower gestational age at delivery OR:0.7 (95% CI: 0.6,0.9). Regarding newborns, 46.7% were male, 66.4% breastfed, with median Apgar 1' of 9 and Apgar 5' of 10. Almost 6% were small for gestational age and 16.8% needed admission to the neonatal ICU. Oxygen was needed by 12.1% and surfactant by 5.6% newborns. Prematurity rate was 20.6%, associated with pneumonia during gestation OR:7.0 (95% CI: 2.3,22.8) and with a positive RT-PCR at delivery OR:6.5 (95% CI: 1.8,31.8). No associations were found with age, comorbidities or blood group. No vertical transmission was reported but one newborn was horizontally infected. Two newborns died, one due to prematurity causes and another of unexpected sudden death during early skin-to-skin contact after delivery. Conclusion: Even there is no vertical transmission reported in this cohort, we found a case of horizontal transmission. SARS-CoV2 infection could produce COVID19 pneumonia during pregnancy, that increases caesarean sections and prematurity rates worsening exposed newborns prognosis. (Figure Presented).