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 aim of the study was to determine the incidence of viruses causing aseptic meningitis, meningoencephalitis, and encephalitis in Spain. This was a prospective study, in collaboration with 17 Spanish hospitals, including 581 cases (CSF from all and sera from 280): meningitis (340), meningoencephalitis (91), encephalitis (76), febrile syndrome (7), other neurological disorders (32), and 35 cases without clinical information. CSF were assayed by PCR for enterovirus (EV), herpesvirus (herpes simplex [HSV], varicella-zoster [VZV], cytomegalovirus [CMV], Epstein-Barr [EBV], and human herpes virus-6 [HHV-6]), mumps (MV), Toscana virus (TOSV), adenovirus (HAdV), lymphocytic choriomeningitis virus (LCMV), West Nile virus (WNV), and rabies. Serology was undertaken when methodology was available. Amongst meningitis cases, 57.1% were characterized; EV was the most frequent (76.8%), followed by VZV (10.3%) and HSV (3.1%; HSV-1: 1.6%; HSV-2: 1.0%, HSV non-typed: 0.5%). Cases due to CMV, EBV, HHV-6, MV, TOSV, HAdV, and LCMV were also detected. For meningoencephalitis, 40.7% of cases were diagnosed, HSV-1 (43.2%) and VZV (27.0%) being the most frequent agents, while cases associated with HSV-2, EV, CMV, MV, and LCMV were also detected. For encephalitis, 27.6% of cases were caused by HSV-1 (71.4%), VZV (19.1%), or EV (9.5%). Other positive neurological syndromes included cerebellitis (EV and HAdV), seizures (HSV), demyelinating disease (HSV-1 and HHV-6), myelopathy (VZV), and polyradiculoneuritis (HSV). No rabies or WNV cases were identified. EVs are the most frequent cause of meningitis, as is HSV for meningoencephalitis and encephalitis. A significant number of cases (42.9% meningitis, 59.3% meningoencephalitis, 72.4% encephalitis) still have no etiological diagnosis.

BK and JC polyomavirus infections are acquired commonly during childhood, mainly asymptomatically. These viruses are thought to remain latent in renal tissue after the primary infection and to reactivate under certain conditions. This reactivation leads to urinary excretion of virus particles, which can be detected by a range of methods. However, while this reactivation has been studied in depth in immunocompromised patients, little information is available about healthy individuals. The present study used PCR-based methods to examine urine samples from healthy individuals (51 adults and 15 children), and found that 62.7% of adults and 13.2% of children excreted polyomaviruses in the urine, mostly JC virus (41.2%). JC virus excretion was continuous, while BK virus excretion was mostly occasional.

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...