Agent-Based Model: Simulating a Virus Expansion Based on the Acceptance of Containment Measures (preprint)

Compartmental epidemiological models categorize individuals based on their disease status, such as the SEIRD model (Susceptible-Exposed-Infected-Recovered-Dead). These models determine the parameters that influence the magnitude of an outbreak, such as contagion and recovery rates. However, they don't account for individual characteristics or population actions, which are crucial for assessing mitigation strategies like mask usage in COVID-19 or condom distribution in HIV. Additionally, studies highlight the role of citizen solidarity, interpersonal trust, and government credibility in explaining differences in contagion rates between countries. Agent-Based Modeling (ABM) offers a valuable approach to study complex systems by simulating individual components, their actions, and interactions within an environment. ABM provides a useful tool for analyzing social phenomena. In this study, we propose an ABM architecture that combines an adapted SEIRD model with a decision-making model for citizens. In this paper, we propose an ABM architecture that allows us to analyze the evolution of virus infections in a society based on two components: 1) an adaptation of the SEIRD model and 2) a decision-making model for citizens. In this way, the evolution of infections is affected, in addition to the spread of the virus itself, by individual behavior when accepting or rejecting public health measures. We illustrate the designed model by examining the progression of SARS-CoV-2 infections in A Coru\~na, Spain. This approach makes it possible to analyze the effect of the individual actions of citizens during an epidemic on the spread of the virus.

Reliability and reproducibility of clinical phenotypes developed during the first wave of COVID-19: A validation study in critically ill patients from the second and third wave (preprint)

Background: During the first wave of the COVID-19 pandemic, different clinical phenotypes were published. However, none of them have been validated in subsequent waves, so their current validity is unknown. The aim of the study is to validate the unsupervised cluster model developed during the first pandemic wave in a cohort of critically ill patients from the second and third pandemic waves. Methods: Retrospective, multicentre, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 74 Intensive Care Units (ICU) in Spain. To validate our original phenotypes model, we assigned a phenotype to each patient of the validation cohort using the same medoids, the same number of clusters (n= 3), the same number of variables (n= 25) and the same discretisation used in the development cohort. The performance of the classification was determined by Silhouette analysis and general linear modelling. The prognostic models were validated, and their performance was measured using accuracy test and area under curve (AUC)ROC. Results: The database included a total of 2,033 patients (mean age 63[53-92] years, 1643(70.5%) male, median APACHE II score (12[9-16]) and SOFA score (4[3-6]) points. The ICU mortality rate was 27.2%. Although the application of unsupervised cluster analysis classified patients in the validation population into 3 clinical phenotypes. Phenotype A (n=1,206 patients, 59.3%), phenotype B (n=618 patients, 30.4%) and phenotype C (n=506 patients, 24.3%), the characteristics of patients within each phenotype were significantly different from the original population. Furthermore, the silhouette coefficients were close to or below zero and the inclusion of phenotype classification in a regression model did not improve the model performance (accuracy =0.78, AUC=0.78) with respect to a standard model (accuracy = 0.79, AUC=0.79) or even worsened when the model was applied to patients within each phenotype (accuracy = 0.80, AUC 0.77 for Phenotype A, accuracy=0.73, AUC= 0.67 for phenotype B and accuracy= 0.66 , AUC= 0.76 for phenotype C ) Conclusion:  Models developed using machine learning techniques during the first pandemic wave cannot be applied with adequate performance to patients admitted in subsequent waves without prior validation. Trial Registration: The study was retrospectively registered (NCT 04948242) on June 30, 2021

HEALTH RELATED SOCIAL NEEDS IN THE TIME OF COVID-19 AMONG ADULT MEN - NEEDS ASSESSMENT AND RESPONSE

BACKGROUND: Health care systems are screening patients for unmet social risk factors and needs though there is variation in patients' interest in receiving assistance from health care systems in response to identified social risk. Understanding this variation would allow health systems to respond to patients' social and health needs more effectively. Our objective is to report findings from a large community outreach effort spurred by the COVID-19 epidemic. This effort sought to identify and meet the needs of men in our community and close the loop by documenting connections with resources. METHODS: We surveyed adult men who had previously participated in at least one community-focused annual health fair in Cleveland, Ohio. In this descriptive cohort study, we spoke with men up to three times (i.e. phases) from May - October 2020 by email and phone. Phase 1 was a needs assessment survey. Phase 2 was to outreach to those who identified a need to provide a resource. Phase 3 was to determine whether the resource met the individuals' needs. We described the demographic characteristics of the survey respondents, the percentage of men reporting a need and wanting a resource. Finally, we report whether that resource resolved their need. RESULTS: Of the 768 individuals contacted for the needs assessment, 275 men who lived in the state of Ohio completed the survey (36% response rate). The majority of respondents were 50-69 years old, African American, had at least a bachelor's degree, were employed, had a health care provider and health insurance, and reported good or higher health status. Eighty-five percent identified food, employment, financial, or health needs. Wellness, financial, and health care access were among the top reported needs. Among those that identified a need, 35%(n=82) respondents were interested in a referral. The remaining respondents were not interested in a referral (n=51) or were not able to be reached (n=100). Among those referred for an employment need (n=17), 70% connected with a resource, but none reported the resource meeting their need. Similarly, men with behavioral health, oral health, vision, substance use disorder, or wellness needs also felt the referred resources did not meet their need. A handful of respondents reported having their personal hygiene/food, financial, health care access, annual health screening, and medication needs resolved. CONCLUSIONS: Our needs assessment found that the vast majority of respondents identified food, employment, financial, or health needs. However, only a fraction of men were interested in a referral to a resource, and far fewer connected with a resource that resolved his need. A greater understanding of the effectiveness of social need screening and referrals for social needs by healthcare systems is warranted.

REDIRECTION: Generating drug repurposing hypotheses using link prediction with DISNET data (preprint)

In the recent years and due to COVID-19 pandemic, drug repurposing or repositioning has been placed in the spotlight. Giving new therapeutic uses to already existing drugs, this discipline allows to streamline the drug discovery process, reducing the costs and risks inherent to de novo development. Computational approaches have gained momentum, and emerging techniques from the machine learning domain have proved themselves as highly exploitable means for repurposing prediction. Against this backdrop, one can find that biomedical data can be represented in terms of graphs, which allow depicting in a very expressive manner the underlying structure of the information. Combining these graph data structures with deep learning models enhances the prediction of new links, such as potential disease-drug connections. In this paper, we present a new model named REDIRECTION, which aim is to predict new disease-drug links in the context of drug repurposing. It has been trained with a part of the DISNET biomedical graph, formed by diseases, symptoms, drugs, and their relationships. The reserved testing graph for the evaluation has yielded to an AUROC of 0.93 and an AUPRC of 0.90. We have performed a secondary validation of REDIRECTION using RepoDB data as the testing set, which has led to an AUROC of 0.87 and a AUPRC of 0.83. In the light of these results, we believe that REDIRECTION can be a meaningful and promising tool to generate drug repurposing hypotheses.

Timing of Intubation and ICU Mortality in Covid-19 Patients: A Preplanned Retrospective Analysis of 4198 Critically Ill Patients (preprint)

BackgroundOptimal time to intubate patients with SARS-CoV-2 pneumonia is controversial. Whereas some authors recommend trying noninvasive respiratory support before intubate, others argue that delaying intubation can cause patient-self-induced lung injury and worsen the prognosis. We hypothesized that delayed intubation would increase the risk mortality in COVID-19 patients.MethodsThis preplanned retrospective observational study used prospectively collected data from adult patients with COVID-19 and respiratory failure admitted to 73 intensive care units between February 2020 and March 2021. Patients with limitations on life support and those with missing data were excluded.We collected demographic, laboratory, clinical variables and outcomes.Intubation was classified as 1) Very early: before or at ICU admission; 2) Early: < 24 hours after ICU admission; or 3) Late: ≥24 hours after ICU admission. We compared the early group versus those intubated late, using chi-square tests for categorical variables and the Mann-Whitney U for continuous variables. To assess the relationship between early versus late intubation and mortality, we used multivariable binary logistic regression. Statistical significance was set at p<0.05.Results We included 4198 patients [median age, 63 (54‒71) years; 70.8% male; median SOFA score, 4 (3‒7); median APACHE score, 13 (10‒18)], and median PaO2/FiO2, 131 (100‒190)]; intubation was very early in 2024 (48.2%) patients, early in 928 (22.1%), and late in 441 (10.5%). ICU mortality was 30.2% and median ICU stay was 14 (7‒28) days. Although patients in the late group were younger [62 vs. 64, respectively, p<0.05] and had less severe disease [APACHE II (13 vs. 14, respectively, p<0.05) and SOFA (3 vs. 4, respectively, p<0.05) scores], and higher PaO2/FiO2 at admission (116 vs. 100, respectively, p<0.05), mortality was higher in the late group than in the early group (36.9% vs. 31.6%, p<0.05). Late intubation was independently associated with mortality (OR1.83; 95%CI 1.35‒2.47).ConclusionsDelaying intubation beyond the first 24 hours of admission in patients with COVID-19 pneumonia increases the risk of mortality. Trial registration: The study was retrospectively registered at Clinical-Trials.gov (NCT 04948242) on the 30th June 2021.

ICU-Acquired Pneumonia is a Risk Factor of a Poor Health Post-Covid-19 Syndrome (preprint)

Background: . Some patients who had previously presented with COVID-19 have been reported to develop persistent COVID-19 symptoms. Whilst this information has been adequately recognised and extensively published with respect to non-critically ill patients, less is known about the prevalence and risk factors and characteristics of persistent COVID_19 . On other hand these patients have very often intensive care unit-acquired pneumonia (ICUAP). A second infectious hit after COVID increases the length of ICU stay and mechanical ventilation and could have an influence in the poor health post-Covid 19 syndrome in ICU discharged patients Methods: This prospective, multicentre and observational study was done across 40 selected ICUs in Spain. Consecutive patients with COVID-19 requiring ICU admission were recruited and evaluated three months after hospital discharge. Results: A total of 1,255 ICU patients were scheduled to be followed up at 3 months; however, the final cohort comprised 991 (78.9%) patients. A total of 315 patients developed ICUAP (97% of them had ventilated ICUAP) Patients requiring invasive mechanical ventilation had persistent, post-COVID-19 symptoms than those who did not require mechanical ventilation. Female sex, duration of ICU stay, and development of ICUAP were independent risk factors for persistent poor health post-COVID-19. Conclusions: : Persistent, post-COVID-19 symptoms occurred in more than two-thirds of patients. Female sex, duration of ICU stay and the onset of ICUAP comprised all independent risk factors for persistent poor health post-COVID-19. Prevention of ICUAP could have beneficial effects in poor health post-Covid 19

A Differential Therapeutic Consideration for use of Corticosteroids According to Established COVID-19 Clinical Phenotypes in Critically Ill Patients (preprint)

Background: The steroids are currently used as standard treatment for severe COVID-19. However, the evidence is weak. Our aim is to determine if the use of corticosteroids was associated with Intensive Care Unit (ICU) mortality among whole population and pre-specified clinical phenotypes.Methods: A secondary analysis derived from multicenter, observational study of adult critically ill patients with confirmed COVID-19 disease admitted to 63 ICUs in Spain. Three phenotypes were derived by non-supervised clustering analysis from whole population and classified as (A: severe, B: critical and C: life-threatening). The primary outcome was ICU mortality. We performed a Multivariate analysis after propensity score full matching (PS), Cox proportional hazards (CPH), Cox covariate time interaction (TIR), Weighted Cox Regression (WCR) and Fine-Gray analysis(sHR) to assess the impact of corticosteroids on ICU mortality according to the whole population and distinctive patient clinical phenotypes. Results:  A total of 2,017 patients were analyzed, 1171(58%) with corticosteroids. After PS, corticosteroids were shown not to be associated with ICU mortality (OR:1.0,95%CI:0.98-1.15). Corticosteroids were administered in 298/537(55.5%) patients of “A” phenotype and their use was not associated with ICU mortality (HR=0.85[0.55-1.33]). A total of 338/623(54.2%) patients in “B” phenotype received corticosteroids. The CPH (HR =0.65 [0.46-0.91]) and TIR regression (1- 25 day tHR=0.56[0.39-0.82] and >25 days tHR=1.53[1.03-7.12]) showed a biphasic effect of corticosteroids due to proportional assumption violation. No effect of corticosteroids on ICU mortality was observed when WCR was performed (wHR=0.72[0.49-1.05]). Finally, 535/857(62.4%) patients in “C” phenotype received corticosteroids. The CPH (HR=0.73[0.63-0.98]) and TIR regression (1- 25 day tHR=0.69[ 0.53-0.89] and >25 days tHR=1.30[ 1.14-3.25]) showed a biphasic effect of corticosteroids and proportional assumption violation. However, wHR (0.75[0.58-0.98]) and sHR (0.79[0.63-0.98]) suggest a protective effect of corticosteroids on ICU mortality.     Conclusion: Our finding warns against the widespread use of corticosteroids in all critically ill patients with COVID-19 at moderate-high dose. Only patients with the highest severity could benefit from steroid treatment although this effect on clinical outcome was minimized during ICU stay. 

Global impact of COVID-19 on stroke care.

BACKGROUND: The COVID-19 pandemic led to profound changes in the organization of health care systems worldwide. AIMS: We sought to measure the global impact of the COVID-19 pandemic on the volumes for mechanical thrombectomy, stroke, and intracranial hemorrhage hospitalizations over a three-month period at the height of the pandemic (1 March-31 May 2020) compared with two control three-month periods (immediately preceding and one year prior). METHODS: Retrospective, observational, international study, across 6 continents, 40 countries, and 187 comprehensive stroke centers. The diagnoses were identified by their ICD-10 codes and/or classifications in stroke databases at participating centers. RESULTS: The hospitalization volumes for any stroke, intracranial hemorrhage, and mechanical thrombectomy were 26,699, 4002, and 5191 in the three months immediately before versus 21,576, 3540, and 4533 during the first three pandemic months, representing declines of 19.2% (95%CI, -19.7 to -18.7), 11.5% (95%CI, -12.6 to -10.6), and 12.7% (95%CI, -13.6 to -11.8), respectively. The decreases were noted across centers with high, mid, and low COVID-19 hospitalization burden, and also across high, mid, and low volume stroke/mechanical thrombectomy centers. High-volume COVID-19 centers (-20.5%) had greater declines in mechanical thrombectomy volumes than mid- (-10.1%) and low-volume (-8.7%) centers (p < 0.0001). There was a 1.5% stroke rate across 54,366 COVID-19 hospitalizations. SARS-CoV-2 infection was noted in 3.9% (784/20,250) of all stroke admissions. CONCLUSION: The COVID-19 pandemic was associated with a global decline in the volume of overall stroke hospitalizations, mechanical thrombectomy procedures, and intracranial hemorrhage admission volumes. Despite geographic variations, these volume reductions were observed regardless of COVID-19 hospitalization burden and pre-pandemic stroke/mechanical thrombectomy volumes.

Addressing COVID-19 health disparities through a regional community health response.

To combat racial/ethnic and socioeconomic health disparities associated with COVID-19 in our surrounding communities, the Cleveland Clinic Community Health & Partnership team developed a comprehensive program focused on connecting and communicating with local officials, faith-based organizations, and individual community members. Since March of 2020, our team has donated resources (e.g., personal protective equipment) to local organizations, referred thousands of community members to community or clinical resources, and partnered with federally-qualified health centers to support community COVID-19 testing. Future work will include the use of these networks to deploy the COVID-19 vaccine.

Assesment of SARS-CoV-2 infection-in dentists and supporting staff at a university dental hospital in Argentina.

INTRODUCTION: Oral healthcare professionals are at increased risk of infection by SARS-CoV-2. The aim of this study was to evaluate the prevalence of COVID-19 in a population of workers who provided services during the COVID-19 pandemic at a dental care and educational institution in the Buenos Aires Metropolitan Area. MATERIALS AND METHODS: This was a descriptive, cross-sectional study including 358 workers who provided essential services during the first 180 days of the COVID-19 pandemic at the Dental Hospital at Buenos Aires University School of Dentistry (FOUBA). Following epidemiological data, these workers underwent diagnostic testing for COVID-19 (1- nasal or throat swab tests; 2- blood test for enzyme-linked immunosorbent assays [ELISA]; 3- commercial rapid serology test). RESULTS: Three diagnostic tests were implemented. Rapid tests were performed on 290 subjects, with 255 negative results (88%; CI95: 84%-91%) and 35 positive (12%; CI95: 9%-16%); ELISA on 317 subjects, with 308 negative (97%; CI95: 95%-98%) and 9 positive (3%; CI95: 2%-5%); and PCR on 204 subjects, with 196 negative (96%; CI95: 92%-98%) and 8 positive (4%; CI95: 2%-8%). There were 358 subjects who were evaluated by ELISA or PCR, with 342 negative results (96%; CI95: 93%-97%) and 16 positives (4%; CI95: 3%-7%). CONCLUSION: For this sample of dentists, dental assistants and nonclinical personnel, the weighted prevalence of COVID-19 was 4%. Similar studies should be conducted at other dental care facilities in order to evaluate the worldwide impact of COVID-19 on the dental care community.

Stroke etiologies in patients with COVID-19: the SVIN COVID-19 multinational registry.

BACKGROUND AND PURPOSE: Coronavirus disease 2019 (COVID-19) is associated with a small but clinically significant risk of stroke, the cause of which is frequently cryptogenic. In a large multinational cohort of consecutive COVID-19 patients with stroke, we evaluated clinical predictors of cryptogenic stroke, short-term functional outcomes and in-hospital mortality among patients according to stroke etiology. METHODS: We explored clinical characteristics and short-term outcomes of consecutively evaluated patients 18 years of age or older with acute ischemic stroke (AIS) and laboratory-confirmed COVID-19 from 31 hospitals in 4 countries (3/1/20-6/16/20). RESULTS: Of the 14.483 laboratory-confirmed patients with COVID-19, 156 (1.1%) were diagnosed with AIS. Sixty-one (39.4%) were female, 84 (67.2%) white, and 88 (61.5%) were between 60 and 79 years of age. The most frequently reported etiology of AIS was cryptogenic (55/129, 42.6%), which was associated with significantly higher white blood cell count, c-reactive protein, and D-dimer levels than non-cryptogenic AIS patients (p

Fructose, a modifiable key factor in the pathogenic basis of metabolic syndrome, NAFLD and obesity Frutose, um fator chave modificável na patogênese da síndrome metabólica, esteatose hepática e obesidade

Resumen: En esta revisión se resume el rol específico que el exceso de consumo de fructosa más allá de sus calorías puede tener en el desarrollo del síndrome metabólico, la esteatosis hepática no alcohólica y su asociación con la obesidad. Se desglosan los efectos de la fructosa (en comparación con la glucosa) en la esteatosis hepática, lo que genera la insulino-resistencia y la hipertrigliceridemia. Por su metabolismo hepático mayoritario y la falta de regulación, los flujos altos de fructosa consumen ATP generando ácido úrico, producen metabolitos tóxicos, como ceramidas y metilglioxal, y activan la síntesis de lípidos. Además, se analizan los efectos en el tejido adiposo, la activación del cortisol y las hormonas involucradas en el control de la saciedad, todas las cuales se ven afectadas por el consumo de fructosa. La insulino-resistencia hepática inicial se complica con insulino-resistencia sistémica, que genera leptino-resistencia y un ciclo de hiperfagia. Estos resultados subrayan la necesidad de intervenciones clínicas y educativas dentro de la población para regular o reducir el consumo de fructosa, especialmente en niños y adolescentes, sus principales consumidores. Summary: This review summarizes the specific role that excess fructose consumption (beyond its calories) may have in the development of MetS, NAFLD and its association with obesity. The effects of fructose (compared to glucose) on hepatic steatosis are discussed as well as their consequence: insulin resistance and hypertriglyceridemia. Unlike glucose, more than 80% ingested fructose stays in the liver, and due to lack of fine metabolic regulation, high fructose flows consume ATP generating uric acid, produce toxic metabolites such as ceramides and methylglyoxal and activate lipid synthesis. In addition, the study analyzes the effects of fructose on adipose tissue, cortisol activation and hormones involved in satiety control, all of which are affected by fructose consumption. The initial hepatic insulin resistance is complicated by systemic insulin resistance, which generates leptin resistance and a hyperphagia cycle. These results underscore the need for clinical and educational interventions within the population to regulate / reduce fructose consumption, especially in children and adolescents, their main consumers. Resumo: No momento vivemos uma pandemia causada pelo vírus SARS-CoV-2, COVID-19, sendo o mais recomendado ficar em casa para reduzir o contágio e que este seja reduzido ao mínimo possível. No século 21, a tecnologia está mais presente do que nunca e faz parte do nosso dia a dia. Tendo em vista que há significativo abuso da mesma, principalmente por adolescentes, na nossa perspectiva que promove o movimento e a redução do comportamento sedentário, propomos o uso de videogames ativos em substituição aos videogames convencionais. Para isso, fizemos uma revisão dos principais benefícios que estas podem trazer, tanto para a população mais jovem como para os idosos. Esta última faixa etária é uma das mais afetadas pela pandemia e, portanto, há uma forte recomendação para que fiquem em casa. No entanto, é recomendável usá-lo com responsabilidade e não investir tempo excessivo que possa causar danos.

Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2,022 critically ill patients with COVID-19 in Spain (preprint)

Background: The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. Methods: Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 Intensive Care Units(ICU) in Spain. The objective was to utilize an unsupervised clustering analysis to derive clinical COVID-19 phenotypes and to analyze patient’s factors associated with mortality risk. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves. Results: : The database included a total of 2,022 patients (mean age 64[IQR5-71] years, 1423(70.4%) male, median APACHE II score (13[IQR10-17]) and SOFA score (5[IQR3-7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the A(mild) phenotype (537;26.7%) included older age (<65 years), fewer abnormal laboratory values and less development of complications, B (moderate) phenotype (623,30.8%) had similar characteristics of A phenotype but were more likely to present shock. The C(severe) phenotype was the most common (857;42.5%) and was characterized by the interplay of older age (>65 years), high severity of illness and a higher likelihood of development shock. Crude ICU mortality was 20.3%, 25% and 45.4% for A, B and C phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications. Conclusion: The presented machine learning model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a “one-size-fits-all” model in practice .

Fructose, a modifiable key factor in the pathogenic basis of metabolic syndrome, NAFLD and obesity Frutose, um fator chave modificável na patogênese da síndrome metabólica, esteatose hepática e obesidade

Resumen: En esta revisión se resume el rol específico que el exceso de consumo de fructosa más allá de sus calorías puede tener en el desarrollo del síndrome metabólico, la esteatosis hepática no alcohólica y su asociación con la obesidad. Se desglosan los efectos de la fructosa (en comparación con la glucosa) en la esteatosis hepática, lo que genera la insulino-resistencia y la hipertrigliceridemia. Por su metabolismo hepático mayoritario y la falta de regulación, los flujos altos de fructosa consumen ATP generando ácido úrico, producen metabolitos tóxicos, como ceramidas y metilglioxal, y activan la síntesis de lípidos. Además, se analizan los efectos en el tejido adiposo, la activación del cortisol y las hormonas involucradas en el control de la saciedad, todas las cuales se ven afectadas por el consumo de fructosa. La insulino-resistencia hepática inicial se complica con insulino-resistencia sistémica, que genera leptino-resistencia y un ciclo de hiperfagia. Estos resultados subrayan la necesidad de intervenciones clínicas y educativas dentro de la población para regular o reducir el consumo de fructosa, especialmente en niños y adolescentes, sus principales consumidores. Summary: This review summarizes the specific role that excess fructose consumption (beyond its calories) may have in the development of MetS, NAFLD and its association with obesity. The effects of fructose (compared to glucose) on hepatic steatosis are discussed as well as their consequence: insulin resistance and hypertriglyceridemia. Unlike glucose, more than 80% ingested fructose stays in the liver, and due to lack of fine metabolic regulation, high fructose flows consume ATP generating uric acid, produce toxic metabolites such as ceramides and methylglyoxal and activate lipid synthesis. In addition, the study analyzes the effects of fructose on adipose tissue, cortisol activation and hormones involved in satiety control, all of which are affected by fructose consumption. The initial hepatic insulin resistance is complicated by systemic insulin resistance, which generates leptin resistance and a hyperphagia cycle. These results underscore the need for clinical and educational interventions within the population to regulate / reduce fructose consumption, especially in children and adolescents, their main consumers. Resumo: No momento vivemos uma pandemia causada pelo vírus SARS-CoV-2, COVID-19, sendo o mais recomendado ficar em casa para reduzir o contágio e que este seja reduzido ao mínimo possível. No século 21, a tecnologia está mais presente do que nunca e faz parte do nosso dia a dia. Tendo em vista que há significativo abuso da mesma, principalmente por adolescentes, na nossa perspectiva que promove o movimento e a redução do comportamento sedentário, propomos o uso de videogames ativos em substituição aos videogames convencionais. Para isso, fizemos uma revisão dos principais benefícios que estas podem trazer, tanto para a população mais jovem como para os idosos. Esta última faixa etária é uma das mais afetadas pela pandemia e, portanto, há uma forte recomendação para que fiquem em casa. No entanto, é recomendável usá-lo com responsabilidade e não investir tempo excessivo que possa causar danos.

Deploying Machine Learning to Validate Clinical Phenotypes and Factors Associated with Mortality Risk in 2,022 Critically Ill Patients with COVID-19 in Spain (preprint)

Background: The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. The objective was to analyze patient’s factors associated with mortality risk and utilize a Machine Learning(ML) to derive clinical COVID-19 phenotypes.Methods: Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 Intensive Care Units(ICU) in Spain. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. An unsupervised clustering analysis was applied to determine presence of phenotypes. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves.Findings: The database included a total of 2,022 patients (mean age 64[IQR5-71] years, 1423(70·4%) male, median APACHE II score (13[IQR10-17]) and SOFA score (5[IQR3-7]) points. The ICU mortality rate was 32·6%. Of the 3 derived phenotypes, the C(severe) phenotype was the most common (857;42·5%) and was characterized by the interplay of older age (>65 years), high severity of illness and a higher likelihood of development shock. The A(mild) phenotype (537;26·7%) included older age (>65 years), fewer abnormal laboratory values and less development of complications and B (moderate) phenotype (623,30·8%) had similar characteristics of A phenotype but were more likely to present shock. Crude ICU mortality was 45·4%, 25·0% and 20·3% for the C, B and A phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications.Interpretation: The presented ML model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a “one-size-fits-all” model in practice.Funding Statement: This study was supported by the Spanish Intensive Care Society(SEMICYUC) and Ricardo Barri Casanovas Foundation.Declaration of Interests: All authors declare that they have no conflicts of interest.Ethics Approval Statement: The study was approved by the reference institutional review board at Joan XXIII University Hospital (IRB# CEIM/066/2020) and each participating site with a waiver of informed consent. All data values were anonymized prior to the phenotyping which consisted of clustering clinical variables on their association with COVID-19 mortality.

COVID-19: Clinical Presentation and Prognostic Factors of Severe Disease and Mortality in the Oldest-old Population. A Cohort Study. (preprint)

INTRODUCTION The oldest-old population (80 years or older) has the highest lethality from COVID-19. There is little information on the clinical presentation and specific prognostic factors for this group. This trial evaluated the clinical presentation and prognostic factors of severe disease and mortality in the oldest-old population.METHODS Ambispective cohort study of oldest-old patients hospitalized for respiratory infection associated with COVID-19 and with a positive test by real-time polymerase chain reaction. The clinical presentation and the factors associated with severe disease and mortality were evaluated (logistic regression). All patients were followed until discharge or death.RESULTS A total of 103 patients (59.2% female) were included. The most frequent symptoms were fever (68.9%), dyspnoea (60.2%), and cough (39.8%), and 11.7% presented confusion. Fifty-nine patients (57.3%) presented severe disease, and 59 died, with 43 patients (41.7%) presenting both of these. In the multivariate analysis, male sex (OR 0.31, 95% confidence interval [95% CI] 0.13-0.73, p 0.0074) and serum lactate dehydrogenase (LDH) (OR 2.55, 95% CI 1.21-5.37, p 0.0139) were associated with severe disease, and serum sodium was associated with mortality (OR 3.12, 95% CI 1.18-8.26, p 0.0222). No chronic disease or pharmacological treatment was associated with worse outcomes.CONCLUSIONS The typical presenting symptoms of respiratory infection in COVID-19 are less frequent in the oldest-old population. Male sex and LDH level are associated with severe disease, and serum sodium level is associated with mortality in this population.

Matched Cohort Study on the Efficacy of Tocilizumab in Patients with COVID-19 (preprint)

Background: Tocilizumab has been proposed as a treatment for the new disease COVID-19, however, there is not enough scientific evidence to support this treatment. The objective of this study is to analyze whether the use of tocilizumab is associated with respiratory improvement and a shorter time to discharge in patients with COVID-19 and lung involvement.Methods: Observational study on a cohort of 418 patients, admitted to three county hospitals in Catalonia (Spain). Patients admitted consecutively were included and followed until discharge or up to 30 days of admission. A sub-cohort of patients treated with tocilizumab and a sub-cohort of control patients were identified, matched by a large number of risk factors and clinical variables. Sub-cohorts were also matched by the number of other treatments for COVID-19 that patients received. Increment in SAFI (inspired oxygen fraction / saturation) 48 hours after the start of treatment, and time to discharge, were the primary outcomes. Mortality, which was a secondary outcome, was analyzed in the total cohort, by using logistic regression models, adjusted by confounders.Results: There were 96 patients treated with tocilizumab. Of them, 22 patients could be matched with an equivalent number of control patients. The increment in SAFI from baseline to 48 hours of treatment, was not significantly different between groups (tocilizumab: -0.04; control: 0.09; p=0.636). Also, no difference in time to discharge was found between the two sub-cohorts (logrank test: p=0.472). The logistic regression models, did not show an effect of tocilizumab on mortality (OR 0.99; p=0.990)Conclusions: We did not find a clinical benefit associated with the use tocilizumab, in terms of respiratory function at 48 hours of treatment, or time to discharge. 

Identification of Potential Inhibitors of SARS-CoV-2 Main Protease via a Rapid In-Silico Drug Repurposing Approach (preprint)

An in-silico drug repurposing study was carried out to search for potential COVID-19 antiviral agents. A dataset of 1615 FDA-approved drugs was docked in the active site of SARS CoV-2 Main protease. A subset of the top scoring hit compounds was subjected to follow-up molecular dynamics simulations to further characterise the predicted binding modes. The main findings are that the drugs Aliskiren, Capreomycin, Isovuconazonium, emerge as novel potential inhibitors. We also observed that Ceftolozane, Cobicistat, Carfilzomib and Saquinavir are well-ranked by our protocol, in agreement with other recent in silico drug repurposing studies, however MD simulations shows only potential for the three first, as Saquinavir exhibited an unstable binding mode. As many HIV-protease inhibitors has been reported as active and not active, Atazanavir and Lopinavir were included in the data set in order to rationalize the findings. In addition, our protocol ranked favourably Dronedarone suggesting that this recently reported SARS-CoV-2 inhibitor targets SARS-CoV-2 Main protease.