Background Information about incidence, clinical characteristics, and outcomes of HIV-infected individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is scarce. We characterised individuals with COVID-19 among a cohort of HIV-infected adults in Madrid. Methods In this observational prospective study, we included all consecutive HIV-infected individuals (aged ≥18 years) who had suspected or confirmed COVID-19 as of April 30, 2020, at the Hospital Universitario Ramón y Cajal (Madrid, Spain). We compared the characteristics of HIV-infected individuals with COVID-19 with a sample of HIV-infected individuals assessed before the COVID-19 pandemic, and described the outcomes of individuals with COVID-19. Findings 51 HIV-infected individuals were diagnosed with COVID-19 (incidence 1•8%, 95% CI 1•3-2•3). Mean age of patients was 53•3 years (SD 9•5); eight (16%) were women, and 43 (84%) men. 35 (69%) cases of co-infection had laboratory confirmed COVID-19, and 28 (55%) required hospital admission. Age and CD4 cell counts in 51 patients diagnosed with COVID-19 were similar to those in 1288 HIV-infected individuals without; however, 32 (63%) with COVID-19 had at least one comorbidity (mostly hypertension and diabetes) compared with 495 (38%) without COVID-19 (p=0•00059). 37 (73%) patients had received tenofovir before COVID-19 diagnosis compared with 487 (38%) of those without COVID-19 (p=0•0036); 11 (22%) in the COVID-19 group had previous protease inhibitor use (mostly darunavir) compared with 175 (14%; p=0•578). Clinical, analytical, and radiological presentation of COVID-19 in HIV-infected individuals was similar to that described in the general population. Six (12%) individuals were critically ill, two of whom had CD4 counts of less than 200 cells per µL, and two (4%) died. SARS-CoV-2 RT-PCR remained positive after a median of 40 days from symptoms onset in six (32%) individuals, four of whom had severe disease or low nadir CD4 cell counts.Interpretation HIV-infected individuals should not be considered to be protected from SARS-CoV-2 infection or to have lower risk of severe disease. Generally, they should receive the same treatment approach applied to the general population.

Objectives To analyse the characteristics and predictors of death in hospitalized patients with coronavirus disease 2019 (COVID-19) in Spain. Methods A retrospective observational study was performed of the first consecutive patients hospitalized with COVID-19 confirmed by real-time PCR assay in 127 Spanish centres until 17 March 2020. The follow-up censoring date was 17 April 2020. We collected demographic, clinical, laboratory, treatment and complications data. The primary endpoint was all-cause mortality. Univariable and multivariable Cox regression analyses were performed to identify factors associated with death. Results Of the 4035 patients, male subjects accounted for 2433 (61.0%) of 3987, the median age was 70 years and 2539 (73.8%) of 3439 had one or more comorbidity. The most common symptoms were a history of fever, cough, malaise and dyspnoea. During hospitalization, 1255 (31.5%) of 3979 patients developed acute respiratory distress syndrome, 736 (18.5%) of 3988 were admitted to intensive care units and 619 (15.5%) of 3992 underwent mechanical ventilation. Virus- or host-targeted medications included lopinavir/ritonavir (2820/4005, 70.4%), hydroxychloroquine (2618/3995, 65.5%), interferon beta (1153/3950, 29.2%), corticosteroids (1109/3965, 28.0%) and tocilizumab (373/3951, 9.4%). Overall, 1131 (28%) of 4035 patients died. Mortality increased with age (85.6% occurring in older than 65 years). Seventeen factors were independently associated with an increased hazard of death, the strongest among them including advanced age, liver cirrhosis, low age-adjusted oxygen saturation, higher concentrations of C-reactive protein and lower estimated glomerular filtration rate. Conclusions Our findings provide comprehensive information about characteristics and complications of severe COVID-19, and may help clinicians identify patients at a higher risk of death.

The outbreak of coronavirus disease 2019 (COVID-19) prompted people to face a distressing and unexpected situation. Uncertainty and social distancing changed people's behaviors, impacting on their feelings, daily habits, and social relationships, which are core elements in human well-being. In particular, restrictions due to the quarantine increased feelings of loneliness and anxiety. Within this context, the use of digital technologies has been recommended to relieve stress and anxiety and to decrease loneliness, even though the overall effects of social media consumption during pandemics still need to be carefully addressed. In this regard, social media use evidence risk and opportunities. In fact, according to a compensatory model of Internet-related activities, the online environment may be used to alleviate negative feelings caused by distressing life circumstances, despite potentially leading to negative outcomes. The present study examined whether individuals who were experiencing high levels of loneliness during the forced isolation for COVID-19 pandemic were more prone to feel anxious, and whether their sense of loneliness prompted excessive social media use. Moreover, the potentially mediating effect of excessive social media use in the relationship between perceived loneliness and anxiety was tested. A sample of 715 adults (71.5% women) aged between 18 and 72 years old took part in an online survey during the period of lockdown in Italy. The survey included self-report measures to assess perceived sense of loneliness, excessive use of social media, and anxiety. Participants reported that they spent more hours/day on social media during the pandemic than before the pandemic. We found evidence that perceived feelings of loneliness predicted both excessive social media use and anxiety, with excessive social media use also increasing anxiety levels. These findings suggest that isolation probably reinforced the individuals' sense of loneliness, strengthening the need to be part of virtual communities. However, the facilitated and prolonged access to social media during the COVID-19 pandemic risked to further increase anxiety, generating a vicious cycle that in some cases may require clinical attention.

Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...

The COVID‐19 pandemic has disproportionally affected men. 1 Men infected with SARS‐CoV‐2 are more than twice as likely to be admitted to the intensive care unit (ICU). 2 This disparity in ICU admissions suggests the important role of androgens in COVID‐19 severity. 3 Previously, we reported that among 122 men hospitalized due to COVID‐19, 79% were diagnosed with androgenetic alopecia (AGA), 4 which is commonly treated with anti‐androgens. Anti‐androgens commonly used in the treatment of AGA such as finasteride, dutasteride, spironolactone, and bicalutamide could improve outcomes among men infected by SARS‐CoV‐2.

In contemporary society, social media use has become a widespread daily activity, especially among adolescents, who are often engaged in visual content sharing. Taking and posting selfies on social media is one of the most popular activities associated with teens' social media use, representing a useful tool to increase their self-presentation via others' approval. However, higher exposure to visual content on social media might lead to more social comparisons and appearance concerns reinforcement. Therefore, body image-based digital activities might allow dissatisfied individuals with their appearance to create and manage their best online selfpresentation, leading to potentially problematic social media use. The present study evaluated the unexplored predictive role of selfie-expectancies and social appearance anxiety on problematic social media use (referred to by some scholars as 'social media addiction'), as well as examining the possible gender differences between boys and girls. A total of 578 adolescents (mean age 16.1 years) participated in the study. Results showed that boys' anxiety concerning self-appearance and the expectancy that selfies could improve their self-confidence were both predictors of their problematic social media use. On the contrary, despite a higher level of social appearance anxiety among girls, it did not influence their social media use. The study demonstrated novel findings concerning new gender-related associations in relation to problematic social media use, social appearance anxiety, and teens' expectancies underlying selfie behavior.

Despite the increasing evidence of the benefit of corticosteroids for the treatment of moderate-severe coronavirus disease 2019 (COVID-19) patients, no data are available about the potential role of high doses of steroids for these patients. We evaluated the mortality, the risk of need for mechanical ventilation (MV), or death and the risk of developing a severe acute respiratory distress syndrome (ARDS) between high (HD) and standard doses (SD) among patients with a severe COVID-19. All consecutive confirmed COVID-19 patients admitted to a single center were selected, including those treated with steroids and an ARDS. Patients were allocated to the HD (≥ 250 mg/day of methylprednisolone) of corticosteroids or the SD (≤ 1.5 mg/kg/day of methylprednisolone) at discretion of treating physician. Five hundred seventy-three patients were included: 428 (74.7%) men, with a median (IQR) age of 64 (54-73) years. In the HD group, a worse baseline respiratory situation was observed and male gender, older age, and comorbidities were significantly more common. After adjusting by baseline characteristics, HDs were associated with a higher mortality than SD (adjusted OR 2.46, 95% CI 1.59-3.81, p < 0.001) and with an increased risk of needing MV or death (adjusted OR 2.35, p = 0.001). Conversely, the risk of developing a severe ARDS was similar between groups. Interaction analysis showed that HD increased mortality exclusively in elderly patients. Our real-world experience advises against exceeding 1-1.5 mg/kg/day of corticosteroids for severe COVID-19 with an ARDS, especially in older subjects. This reinforces the rationale of modulating rather than suppressing immune responses in these patients.

Men infected with SARS‐CoV‐2 are more likely to be admitted to the intensive care unit (ICU) compared to women. 1 Previously, we have reported that among hospitalized men with COVID‐19, 79% presented with androgenetic alopecia (AA) compared to 31‐53% that would be expected in a similar aged match population. 2 AA is known to be mediated by variations in the androgen receptor (AR) gene. 3 In addition, the only known promoter of the enzyme implicated in SARS‐CoV‐2 infectivity, TMPRSS2, is regulated by an androgen response element. 4 The polyglutamine repeat (CAG repeat) located in the AR gene is associated with androgen sensitivity and AA. 3 These observations led us to hypothesize that variations in the AR gene may predispose male COVID‐19 patients to increased disease severity.