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1.
Food Chem ; 366: 130589, 2022 Jan 01.
Artículo en Inglés | MEDLINE | ID: mdl-34311241

RESUMEN

Bioactive plant-derived molecules have emerged as therapeutic alternatives in the fight against the COVID-19 pandemic. In this investigation, principal bioactive compounds of the herbal infusion "horchata" from Ecuador were studied as potential novel inhibitors of the SARS-CoV-2 virus. The chemical composition of horchata was determined through a HPLC-DAD/ESI-MSn and GC-MS analysis while the inhibitory potential of the compounds on SARS-CoV-2 was determined by a computational prediction using various strategies, such as molecular docking and molecular dynamics simulations. Up to 51 different compounds were identified. The computational analysis of predicted targets reveals the compounds' possible anti-inflammatory (no steroidal) and antioxidant effects. Three compounds were identified as candidates for Mpro inhibition: benzoic acid, 2-(ethylthio)-ethyl ester, l-Leucine-N-isobutoxycarbonyl-N-methyl-heptyl and isorhamnetin and for PLpro: isorhamnetin-3-O-(6-Orhamnosyl-galactoside), dihydroxy-methoxyflavanone and dihydroxyphenyl)-5-hydroxy-4-oxochromen-7-yl]oxy-3,4,5-trihydroxyoxane-2-carboxylic acid. Our results suggest the potential of Ecuadorian horchata infusion as a starting scaffold for the development of new inhibitors of the SARS-CoV-2 Mpro and PLpro enzymes.


Asunto(s)
COVID-19 , Humanos , Simulación del Acoplamiento Molecular , Simulación de Dinámica Molecular , Pandemias , Inhibidores de Proteasas , SARS-CoV-2
2.
Ann Lab Med ; 42(1): 24-35, 2022 Jan 01.
Artículo en Inglés | MEDLINE | ID: mdl-34374346

RESUMEN

Background: Laboratory parameter abnormalities are commonly observed in COVID-19 patients; however, their clinical significance remains controversial. We assessed the prevalence, characteristics, and clinical impact of laboratory parameters in COVID-19 patients hospitalized in Daegu, Korea. Methods: We investigated the clinical and laboratory parameters of 1,952 COVID-19 patients on admission in nine hospitals in Daegu, Korea. The average patient age was 58.1 years, and 700 (35.9%) patients were men. The patients were classified into mild (N=1,612), moderate (N=294), and severe (N=46) disease groups based on clinical severity scores. We used chi-square test, multiple comparison analysis, and multinomial logistic regression to evaluate the correlation between laboratory parameters and disease severity. Results: Laboratory parameters on admission in the three disease groups were significantly different in terms of hematologic (Hb, Hct, white blood cell count, lymphocyte%, and platelet count), coagulation (prothrombin time and activated partial thromboplastin time), biochemical (albumin, aspartate aminotransferase, alanine aminotransferase, lactate, blood urea nitrogen, creatinine, and electrolytes), inflammatory (C-reactive protein and procalcitonin), cardiac (creatinine kinase MB isoenzyme and troponin I), and molecular virologic (Ct value of SARS-CoV-2 RdRP gene) parameters. Relative lymphopenia, prothrombin time prolongation, and hypoalbuminemia were significant indicators of COVID-19 severity. Patients with both hypoalbuminemia and lymphopenia had a higher risk of severe COVID-19. Conclusions: Laboratory parameter abnormalities on admission are common, are significantly associated with clinical severity, and can serve as independent predictors of COVID-19 severity. Monitoring the laboratory parameters, including albumin and lymphocyte count, is crucial for timely treatment of COVID-19.


Asunto(s)
COVID-19 , Análisis de Datos , Humanos , Laboratorios , Masculino , Persona de Mediana Edad , República de Corea/epidemiología , Estudios Retrospectivos , SARS-CoV-2
3.
Infectio ; 25(4): 262-269, oct.-dic. 2021. tab, graf
Artículo en Inglés | LILACS, COLNAL | ID: biblio-1286720

RESUMEN

Abstract Objective: To analyse the clinic characteristics, risk factors and evolution of the first cohort of hospitalised patients with confirmed infection by COVID-19 in 5 Colombian institutions. Materials and methods: Is a retrospective observational study of consecutive hospitalized patients with a diagnosis of COVID-19 confirmed from March 01 to May 30, 2020 in Colombia. Results: A total of 44 patients were included. The median age was 62 years. 43.2% had a history of smoking, while 69.8% were overweight or obese. 88.6% had at least one comorbidity and 52.3% had three or more comorbidities. Hypertension and dyslipidaemia were the most frequent comorbidities (40.9% and 34.1%, respectively). The 30-day mortality rate was 47.7% with a median of 11 days. The composite outcome occurred in the 36.4%. The biomarkers associated with mor tality risk included troponin higher than 14 ng/L (RR: 5.25; 95% CI 1.37-20.1, p = 0.004) and D-dimer higher than 1000 ng/ml (RR: 3.0; 95% CI 1.4-6.3, p = 0.008). Conclusions: The clinical course of SARS-CoV-2 infection in hospitalized Colombian was characterised by a more advanced stage of the infection.


Resumen Objetivo: Analizar las características, clínicas, factores de riesgo, y la evolución de pacientes hospitalizados con infección confirmada por COVID-19 en 5 Institu ciones de Colombia. Material y método: Es un estudio observacional retrospectivo de pacientes consecutivos hospitalizados con diagnóstico de COVID-19 confirmado entre 01 de Febrero de 2020 y 30 de Mayo de 2020 en Colombia. Resultados: Un total de 44 pacientes fueron incluidos. La mediana de edad fue de 62 años y la mayoría del sexo masculino. El 43.2% tenían historia de tabaquismo, mientras que el 69.8% tenían sobrepeso u obesidad. El 88.6% tenían al menos una comorbilidad y el 52.3% tenían tres o más comorbilidades. La hipertensión arterial fue la comorbilidad más frecuente (40.9%), seguido de la dislipidemia (34.1%). La tasa de letalidad a 30 días fue de 47.7% y ocurrió con una mediana de 11 días. El 36.4% presentó el desenlace compuesto. Los biomarcadores asociados con el riesgo de muerte fue troponina > 14 ng/mL (RR:5.25, IC95% 1.37-20.1, p=0.004) y dímero D mayor a 1000 mg/dL (RR: 3.0, IC95% 1.4-6.3, p=0.008). Conclusiones: El curso clínico de la infección por SARS-CoV-2 en colombianos hospitalizados fue un estadio más avanzado de la infección.


Asunto(s)
Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Biomarcadores , COVID-19 , Pacientes , Tabaquismo , Comorbilidad , Riesgo , Factores de Riesgo , Mortalidad , Colombia , Sobrepeso , Cursos , Infecciones , Obesidad
4.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21264356

RESUMEN

The impacts of COVID-19 outbreak on socio-economic status of countries across the globe cannot be overemphasized as we examine the role it played in various countries. A lot of people were out of jobs, many households were careful of their spending and a greater social fracture of the population in fourteen different countries has emerged. We considered periods of infection spread during the first and second wave in Organization for Economic Co-operation and Development (OECD) countries and countries in Africa, that is developed and developing countries alongside their social-economic data. We established a mathematical and statistical relationship between Theil and Gini index, then we studied the relationship between the data from epidemiology and socio-economic determinants using several machine learning and deep learning methods. High correlations were observed between some of the socio-economic and epidemiologic parameters and we predicted three of the socio-economic variables in order to validate our results. These result shows a sharp difference between the first and second wave of the pandemic confirming the real dynamics of the spread of the outbreak in several countries and ways by which it was mitigated.

5.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21264273

RESUMEN

IntroductionTo retrospectively assess the accuracy of a mathematical modelling study that projected the rate of COVID-19 diagnoses for 72 locations worldwide in 2021, and to identify predictors of model accuracy. MethodsBetween June and August 2020, an agent-based model was used to project rates of COVID-19 infection incidence and cases diagnosed as positive from 15 September to 31 October 2020 for 72 geographic settings. Five scenarios were modelled: a baseline scenario where no future changes were made to existing restrictions, and four scenarios representing small or moderate changes in restrictions at two intervals. Post hoc, upper and lower bounds for number of diagnosed Covid-19 cases were compared with actual data collected during the prediction window. A regression analysis with 17 covariates was performed to determine correlates of accurate projections. ResultsThe actual data fell within the lower and upper bounds in 27 settings and out of bounds in 45 settings. The only statistically significant predictor of actual data within the predicted bounds was correct assumptions about future policy changes (OR = 15.04; 95%CI 2.20-208.70; p=0.016). ConclusionsFor this study, the accuracy of COVID-19 model projections was dependent on whether assumptions about future policies are correct. Frequent changes in restrictions implemented by governments, which the modelling team was not always able to predict, in part explains why the majority of model projections were inaccurate compared with actual outcomes and supports revision of projections when policies are changed as well as the importance of policy experts collaborating on modelling projects.

6.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21264749

RESUMEN

BackgroundThe COVID-19 pandemic has brought about significant behavioural changes, one of which is increased time spent at home. Although official lockdowns were typically short-term and allowed people to leave their homes for exercise and essential activities, some individuals did not leave their home for prolonged periods due to a range of factors including clinical vulnerability. This study aimed to explore longitudinal patterns of such home confinement across different stages of the COVID-19 pandemic in the UK, and its associated predictors and mental health outcomes. MethodsData were from the UCL COVID -19 Social Study. The analytical sample consisted of 25,390 adults in England who were followed up for 17 months from March 2020 to July 2021. Data were analysed using growth mixture models. ResultsOur analyses identified three classes of growth trajectories, including one class showing a high level of persistent home confinement (24.8%), one changing class with clear alignment with national containment policy/advice (32.0%), and one class with a persistently low level of confinement (43.1%). A range of factors were found to be associated the class membership of home confinement trajectories, such as age, gender, income, employment status, social relationships and health. The class with a high level of confinement had the highest number of depressive and anxiety symptoms at the end of the follow-up independent of potential confounders. ConclusionsThere was substantial heterogeneity in longitudinal patterns of home confinement during the COVID-19 pandemic. However, a striking proportion of our sample maintained a high level of home confinement over the course of 17 months, even during periods when containment measures were eased or removed and when infection rates were low. They also had the worst mental health outcomes. This group warrants special attention in addressing the mental health impact of the COVID-19 pandemic.

7.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21264545

RESUMEN

Advanced age is a main risk factor for severe COVID-19 and thus elderly were often prioritized for vaccination. However, low vaccination efficacy and accelerated waning immunity have been reported in this age group. To elucidate age-related differences in immunogenicity, we analysed cellular, serological and salivary SARS-CoV-2 spike glycoprotein-specific immune responses to BNT162b2 COVID-19 vaccine in old (69-92 years) and middle-aged (24-57 years) vaccinees compared to natural infection (COVID-19 convalescents of 21-55 years). Serological humoral responses to vaccination exceeded those of convalescents but salivary anti-spike subunit 1 (S1) IgA and neutralizing capacity were less durable in vaccinees. In old vaccinees, we observed that pre-existing spike-specific CD4+ T cells correlated with efficient induction of serological anti-S1 IgG and neutralizing capacity after vaccination. Our results highlight the role of pre-existing cross-reactive CD4+ T cells with respect to SARS-CoV-2 vaccination particularly in old individuals, in whom their presence predicted efficient COVID-19-vaccine-induced humoral immune responses.

8.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21264569

RESUMEN

During the COVID-19 pandemic, West Virginia developed an aggressive SARS-CoV-2 testing strategy which included utilizing pop-up mobile testing in locations anticipated to have near-term increases in SARS-CXoV-2 infections. In this study, we describe and compare two methods for predicting near-term SARS-CoV-2 incidence in West Virginia counties. The first method, Rt Only, is solely based on producing forecasts for each county using the daily instantaneous reproductive numbers, Rt. The second method, ML+ Rt, is a machine learning approach that uses a Long Short-Term Memory network to predict the near-term number of cases for each county using epidemiological statistics such as Rt, county population information, and time series trends including information on major holidays, as well as leveraging statewide COVID-19 trends across counties and county population size. Both approaches used daily county-level SARS-CoV-2 incidence data provided by the West Virginia Department Health and Human Resources beginning April 2020. The methods are compared on the accuracy of near-term SARS-CoV-2 increases predictions by county over 17 weeks from January 1, 2021-April 30, 2021. Both methods performed well (correlation between forecasted number of cases and the actual number of cases week over week is 0.872 for the ML+Rt method and 0.867 for the Rt Only method) but differ in performance at various time points. Over the 17-week assessment period, the ML+Rt method outperforms the Rt Only method in identifying larger spikes. We also find that both methods perform adequately in both rural and non-rural predictions. Finally, we provide a detailed discussion on practical issues regarding implementing forecasting models for public health action based on Rt, and the potential for further development of machine learning methods that are enhanced by Rt.

9.
BMC Public Health ; 21(1): 1830, 2021 Oct 09.
Artículo en Inglés | MEDLINE | ID: mdl-34627208

RESUMEN

BACKGROUND: Generalized Anxiety Disorder (GAD) is a common but urgent mental health problem during disease outbreaks. Resilience buffers against the negative impacts of life stressors on common internalizing psychopathology such as GAD. This study assesses the prevalence of GAD and examines the protective or compensatory effect of resilience against worry factors during the COVID-19 outbreak. METHODS: A cross-sectional online survey was conducted among Chinese citizens aged ≥18 years from January 31 to February 2, 2020. A total of 4827 participants across 31 provinces and autonomous regions of the mainland of China participated in this study. The Generalized Anxiety Disorder scale (GAD-7), the Connor-Davidson Resilience Scale (CD-RISC), and a self-designed worry questionnaire were used to asses anxiety disorder prevalence, resilience level, and anxiety risk factors. Multivariable logistic regression was used to identify the associations of resilience and worry factors with GAD prevalence after controlling for other covariates. RESULTS: The prevalence of anxiety disorder was 22.6% across the 31 areas, and the highest prevalence was 35.4% in Hubei province. After controlling for covariates, the results suggested a higher GAD prevalence among participants who were worried about themselves or family members being infected with COVID-19 (adjusted odds ratio, AOR 3.40, 95%CI 2.43-4.75), worried about difficulty obtaining masks (AOR 1.92, 95%CI 1.47-2.50), worried about difficulty of distinguishing true information (AOR 1.65, 95%CI 1.36-2.02), worried about the prognosis of COVID-19 (AOR 2.41, 95%CI 1.75-3.33), worried about delays in working (AOR 1.71, 95%CI 1.27-.31), or worried about decreased income (AOR 1.45, 95%CI 1.14-1.85) compared with those without such worries. Additionally, those with a higher resilience level had a lower prevalence of GAD (AOR 0.59, 95%CI 0.51-0.70). Resilience also showed a mediating effect, with a negative influence on worry factors and thereby a negative association with GAD prevalence. CONCLUSION: It may be beneficial to promote public mental health during the COVID-19 outbreak through enhancing resilience, which may buffer against adverse psychological effects from worry factors.

10.
Artículo en Inglés | MEDLINE | ID: mdl-34627709

RESUMEN

OBJECTIVE: Noninvasive positive-pressure ventilation (NPPV) emerged as an efficient tool for treatment of COVID-19 pneumonia. The factors influencing NPPV failure still are elusive. The aim of the study was to investigate the relationships between semiquantitative chest computed tomography (CT) scoring and NPPV failure and mortality in patients with COVID-19. DESIGN: Observational study. SETTING: Nonintensive care setting. PARTICIPANTS: A total of 112 patients consecutively admitted for COVID-19 pneumonia. INTERVENTIONS: Usual care including various degrees of respiratory support. MEASUREMENTS AND MAIN RESULTS: The semiquantitative CT score was calculated at hospital admission. Subgroups were identified according to the ventilation strategy used (oxygen delivered by Venturi mask n = 53; NPPV-responder n = 38; NPPV-failure n = 21). The study's primary endpoint was the use of NPPV. The secondary endpoints were NPPV failure and in-hospital death, respectively. CT score progressively increased among groups (six v nine v 14, p < 0.05 among all). CT score was an independent predictor of all study endpoints (primary endpoint: 1.25 [95% confidence interval {CI} 1.1-1.4], p = 0.001; NPPV failure: 1.41 [95% CI 1.18-1.69], p < 0.001; in-hospital mortality: 1.21 [95% CI 1.07-1.38], p = 0.003). According to receiver operator characteristics curve analysis, CT score was the most accurate variable for prediction of NPPV failure (area under the curve 0.862 with p < 0.001; p < 0.05 v other variables). CONCLUSIONS: The authors reported the common and effective use of NPPV in patients with COVID-19 pneumonia. In the authors' population, a semiquantitative chest CT analysis at hospital admission accurately identified those patients responding poorly to NPPV.

12.
Int J Infect Dis ; 2021 Oct 07.
Artículo en Inglés | MEDLINE | ID: mdl-34628020

RESUMEN

OBJECTIVES: The effective reproduction number (Rt) is critical for assessing the effectiveness of countermeasures during the coronavirus disease 2019 (COVID-19) pandemic. Conventional methods using reported incidence are unable to provide Rt timely due to the delay from infection to reporting. Here, we aim to develop a framework to predict the Rt in real-time using timely accessible data, i.e., human mobility, temperature, and risk awareness. METHODS: A linear regression model to predict Rt was designed and embedded in the renewal process. Four prefectures of Japan with high incidence in the first wave were selected for model fitting and validation. Predictive performance was assessed by comparing the observed and predicted incidence using cross-validation, by testing on a separate dataset in two other prefectures with distinct geographical settings from the four prefectures. RESULTS: The predicted mean values of Rt and 95% uncertainty intervals well traced the overall trend of incidence, while predictive performance was diminished when Rt abruptly changed potentially due to superspreading events and when stringent countermeasures were implemented. CONCLUSIONS: The described model can potentially be used for monitoring the transmission dynamics of COVID-19 ahead of the formal estimates subject to delay, providing essential information for timely planning and assessment of countermeasures.

14.
Sci China Life Sci ; 2021 Oct 08.
Artículo en Inglés | MEDLINE | ID: mdl-34632536

RESUMEN

Triage management plays important roles in hospitalized patients for disease severity stratification and medical burden analysis. Although progression risks have been extensively researched for numbers of diseases, other crucial indicators that reflect patients' economic and time costs have not been systematically studied. To address the problems, we developed an automatic deep learning based Auto Triage Management (ATM) Framework capable of accurately modelling patients' disease progression risk and health economic evaluation. Based on them, we can first discover the relationship between disease progression and medical system cost, find potential features that can more precisely aid patient triage in resource allocation, and allow treatment plan searching that has cured patients. Applying ATM in COVID-19, we built a joint model to predict patients' risk, the total length of stay (LoS) and cost when at-admission, and remaining LoS and cost at a given hospitalized time point, with C-index 0.930 and 0.869 for risk prediction, mean absolute error (MAE) of 5.61 and 5.90 days for total LoS prediction in internal and external validation data.

15.
Work ; 2021 Oct 05.
Artículo en Inglés | MEDLINE | ID: mdl-34633339

RESUMEN

BACKGROUND: Dentistry is one of the highest risk occupations that face COVID-19, especially in countries that are severely affected by the pandemic, such as Indonesia. OBJECTIVE: The purpose of the study was to determine factors influencing job satisfaction among dentists during the new normal of COVID-19 pandemic in Indonesia by utilizing the Structural Equation Modeling (SEM) approach. METHODS: A total of 310 Indonesian dentists voluntary completed an online questionnaire, which contained 58 questions. Several latent variables such as perceived severity of COVID-19, staff cooperation and management commitment, personal protective equipment, job stress, working hours, income, and overall job satisfaction were analyzed simultaneously. RESULTS: SEM revealed perceived severity of COVID-19 had significant effects on job stress (ß:0.394, p = 0.025) and the utilization of personal protective equipment (ß:0.757, p = 0.001). Subsequently, job stress (ß:-0.286, p = 0.001), working hours (ß:0.278, p = 0.018), income (ß:0.273, p = 0.003), personal protective equipment (ß:0.145, p = 0.038), and staff cooperation & management commitment (ß:0.091, p = 0.002) were found to have significant effects on overall job satisfaction. In addition, management & staff cooperation was found to have a significant association with job stress reduction (ß:-0.319, p = 0.003) which subsequently led to higher satisfaction. CONCLUSIONS: The current study is one of the first that analyzed job satisfaction among dentists in Indonesia during the global COVID-19 pandemic. The integrated latent variables can be applied and extended to evaluate job satisfaction among dentists during the COVID-19 pandemic in other countries. Finally, this study contributed as a theoretical foundation for policymakers to enhance the job satisfaction of dentists during the COVID-19 pandemic.

16.
Nat Commun ; 12(1): 5877, 2021 Oct 07.
Artículo en Inglés | MEDLINE | ID: mdl-34620860

RESUMEN

Several COVID-19 vaccines have recently gained authorization for emergency use. Limited knowledge on duration of immunity and efficacy of these vaccines is currently available. Data on other coronaviruses after natural infection suggest that immunity to SARS-CoV-2 might be short-lived, and preliminary evidence indicates waning antibody titers following SARS-CoV-2 infection. In this work, we model the relationship between immunogenicity and protective efficacy of a series of Ad26 vectors encoding stabilized variants of the SARS-CoV-2 Spike protein in rhesus macaques and validate the analyses by challenging macaques 6 months after immunization with the Ad26.COV2.S vaccine candidate that has been selected for clinical development. We show that Ad26.COV2.S confers durable protection against replication of SARS-CoV-2 in the lungs that is predicted by the levels of Spike-binding and neutralizing antibodies, indicating that Ad26.COV2.S could confer durable protection in humans and immunological correlates of protection may enable the prediction of durability of protection.

17.
Artículo en Inglés | MEDLINE | ID: mdl-34622441

RESUMEN

BACKGROUND: The prediction of in-hospital mortality for ICU patients with COVID-19 is fundamental to treatment and resource allocation. The main purpose was to develop an easily implemented score for such prediction. METHODS: This was an observational, multicenter, development and validation study on a national critical care dataset of COVID-19 patients. A systematic literature review was performed to determine variables possibly important for COVID-19 mortality prediction. Using a logistic multivariable model with a LASSO penalty, we developed the Rapid Evaluation of Coronavirus Illness Severity (RECOILS) score and compared its performance against published scores. RESULTS: Our development (validation) cohort consisted of 1480 (937) adult patients from 14 (11) Dutch ICUs admitted between March 2020 and April 2021. Median age was 65 (65) years, 31% (26%) died in hospital, 74% (72%) were males, average length of ICU stay was 7.83 (10.25) days and average length of hospital stay was 15.90 (19.92) days. Age, platelets, PaO2/FiO2 ratio, pH, blood urea nitrogen, temperature, PaCO2, Glasgow Coma Scale (GCS) score measured within +/- 24 hours of ICU admission were used to develop the score. The AUROC of RECOILS score was 0.75 (CI 0.71-0.78) which was higher than that of any previously reported predictive scores (0.68 (CI 0.64-0.71), 0.61 (CI 0.58-0.66), 0.67 (CI 0.63-0.70), 0.70 (CI 0.67-0.74) for ISARIC 4C Mortality Score, SOFA, SAPS-III, and age, respectively). CONCLUSIONS: Using a large dataset from multiple Dutch ICUs, we developed a predictive score for mortality of COVID-19 patients admitted to ICU, which outperformed other predictive scores reported so far.

18.
Health Soc Work ; 2021 Oct 08.
Artículo en Inglés | MEDLINE | ID: mdl-34624076

RESUMEN

The relationship between chronic medical conditions and PTSD within-race in Black adults is not well understood and there exists a dearth of empirical research investigating the gender differences. Cross-sectional data from the National Survey of American Life were used to examine the relationship between PTSD and obesity, hypertension, diabetes, heart disease, and asthma (five of the most commonly identified COVID-19 underlying medical conditions) among Black adults in the United States. Results from modified Poisson regression analyses revealed that Black adults across all three groups (overall, male, and female samples) who reported two or more chronic medical conditions had a higher prevalence of PTSD than those who reported zero or one. Black men with obesity, diabetes, or heart disease and Black women with asthma had a higher prevalence of PTSD than those who did not report obesity, diabetes, heart disease, or asthma. Findings from this study underscore the need to alert social workers to the potential relationship between obesity, diabetes, or heart disease and PTSD for Black men and asthma and PTSD for Black women to help develop culturally appropriate biopsychosocial-spiritual assessments, with a measured focus on Black men based on their comparatively worse health status.

19.
Autism Res ; 2021 Oct 09.
Artículo en Inglés | MEDLINE | ID: mdl-34626164

RESUMEN

Adults with autism spectrum disorder (ASD) experience high rates of both unemployment and depression. Though job loss predicts increased risk of depression in the general population, studies have yet to directly examine this relationship among individuals with ASD. With the backdrop of rising unemployment due to COVID-19, we used a longitudinal design to examine whether employment changes predicted increasing depressive symptoms among young adults with ASD. Online surveys were collected from young adults with ASD at two times: just before widespread social distancing measures were adopted in the United States, and again 10 weeks later. Both time points included measurement of depressive symptoms (Beck Depression Inventory-2). At Time 2, COVID-related employment changes and the perceived impact of those changes on well-being were collected. Of the young adults who were employed at Time 1 (n = 144), over one-third (37.5%) reported employment changes during the first 2 months of COVID-19. Most of this change was job loss or reductions in hours or pay ("job loss/reduction"). Controlling for Time 1 depressive symptoms, young adults who experienced job loss/reduction had significantly higher depressive symptoms at Time 2 than those without an employment change. Individuals' perceived impact of employment change also predicted depressive symptoms. These findings suggest that losing a job or experiencing reductions in hours or pay leads to worsening depressive symptoms among adults with ASD. Better supporting autistic adults in the workplace may not only decrease the likelihood of job loss, but also combat the exceedingly high rates of depression in this group. LAY SUMMARY: Though unemployment has been linked to mental health problems in the general population, this relationship is seldom considered among adults with autism. In this study, we found that adults on the autism spectrum who lost their jobs or experienced reductions in pay or hours during the first 2 months of COVID-19 had worsening depression compared to adults who did not have job changes. Our findings suggest that increasing access to employment may help alleviate poor mental health among autistic adults.

20.
Med Clin (Barc) ; 2021 Jul 29.
Artículo en Inglés, Español | MEDLINE | ID: mdl-34635318

RESUMEN

INTRODUCTION: SARS-CoV-2 infection is frequently associated with hyponatremia (plasma sodium<135mmol/L), being associated with a worse prognosis. The incidence of hyponatremia is estimated to be 20-37% according to the series, but there are no data on the prognosis after correction of hyponatremia. Therefore, our objectives were: to analyze the incidence and severity of hyponatremia at hospital admission, and to determine the association of this hyponatremia with the prognosis of COVID-19. MATERIAL AND METHOD: Observational and retrospective cohort study. Patients who were admitted with a diagnosis of COVID-19 infection and hyponatremia, in the period March-May 2020, were included. We recorded epidemiological, demographic, clinical, biochemical, and radiological variables of SARS-CoV-2 infection and hyponatremia at the time of diagnosis and during hospitalization. The clinical follow-up ranged from admission to death or discharge. RESULTS: 91 patients (21.8%) of the 414 admitted for SARS-CoV-2 infection presented hyponatremia (81.32% mild hyponatremia, 9.89% moderate and 8.79% severe). The absence of correction of hyponatremia 72-96h after hospital admission was associated with higher mortality in patients with COVID-19 (Odds Ratio .165; 95% confidence interval: .018-.686; P=.011). 19 patients (20.9%) died. An increase in mortality was observed in patients with severe hyponatremia compared with moderate and mild hyponatremia during hospital admission (37.5% versus 11.1% versus 8.1%, P=.041). CONCLUSIONS: We conclude that persistence of hyponatremia at 72-96h of hospital admission was associated with higher mortality in patients with SARS-CoV-2.

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