Background: Coronavirus disease 2019 (COVID-19) can manifest as a viral-induced hyperinflammation with multiorgan involvement. Such patients often experience rapid deterioration and need for mechanical ventilation. Currently, no prospectively validated biomarker of impending respiratory failure is available. Objective: We aimed to identify and prospectively validate biomarkers that allow the identification of patients in need of impending mechanical ventilation. Methods: Patients with COVID-19 who were hospitalized from February 29 to April 9, 2020, were analyzed for baseline clinical and laboratory findings at admission and during the disease. Data from 89 evaluable patients were available for the purpose of analysis comprising an initial evaluation cohort (n 5 40) followed by a temporally separated validation cohort (n 5 49). Results: We identified markers of inflammation, lactate dehydrogenase, and creatinine as the variables most predictive of respiratory failure in the evaluation cohort. Maximal IL-6 level before intubation showed the strongest association with the need for mechanical ventilation, followed by maximal CRP level. The respective AUC values for IL-6 and CRP levels in the evaluation cohort were 0.97 and 0.86, and they were similar in the validation cohort (0.90 and 0.83, respectively). The calculated optimal cutoff values during the course of disease from the evaluation cohort (IL-6 level > 80 pg/mL and CRP level > 97 mg/L) both correctly classified 80% of patients in the validation cohort regarding their risk of respiratory failure. Conclusion: The maximal level of IL-6, followed by CRP level, was highly predictive of the need for mechanical ventilation. This suggests the possibility of using IL-6 or CRP level to guide escalation of treatment in patients with COVID-19-related hyperinflammatory syndrome.

Key Question 1. What are the causative microorganisms of community-acquired bacterial meningitis in specific groups (neonates, children, adults and immunocompromised patients)?

We describe the first public data release of the Dark Energy Survey, DES DR1, consisting of reduced single-epoch images, co-added images, co-added source catalogs, and associated products and services assembled over the first 3 yr of DES science operations. DES DR1 is based on optical/near-infrared imaging from 345 distinct nights (2013 August to 2016 February) by the Dark Energy Camera mounted on the 4 m Blanco telescope at the Cerro Tololo Inter-American Observatory in Chile. We release data from the DES wide-area survey covering ∼5000 deg 2 of the southern Galactic cap in five broad photometric bands, grizY. DES DR1 has a median delivered point-spread function of = g 1.12, r=0.96, i=0.88, z=0.84, and Y=0 90 FWHM, a photometric precision of <1% in all bands, and an astrometric precision of 151 mas. The median co-added catalog depth for a 1 95 diameter aperture at signal-to-noise ratio (S/N)=10 is g=24.33, r=24.08, i=23.44, z=22.69, and Y=21.44 mag. DES DR1 includes nearly 400 million distinct astronomical objects detected in ∼10,000 co-add tiles of size 0.534 deg 2 produced from ∼39,000 individual exposures. Benchmark galaxy and stellar samples contain ∼310 million and ∼80 million objects, respectively, following a basic object quality selection. These data are accessible through a range of interfaces, including query web clients, image cutout servers, jupyter notebooks, and an interactive co-add image visualization tool. DES DR1 constitutes the largest photometric data set to date at the achieved depth and photometric precision.

We derive cosmological constraints using a galaxy cluster sample selected from the 2500 deg 2 SPT-SZ survey. The sample spans the redshift range 0.25<z<1.75 and contains 343 clusters with SZ detection significance ξ>5. The sample is supplemented with optical weak gravitational lensing measurements of 32 clusters with 0.29<z<1.13 (from Magellan and Hubble Space Telescope) and X-ray measurements of 89 clusters with 0.25<z<1.75 (from Chandra). We rely on minimal modeling assumptions: (i) weak lensing provides an accurate means of measuring halo masses, (ii) the mean SZ and X-ray observables are related to the true halo mass through power-law relations in mass and dimensionless Hubble parameter E(z) with a priori unknown parameters, and (iii) there is (correlated, lognormal) intrinsic scatter and measurement noise relating these observables to their mean relations. We simultaneously fit for these astrophysical modeling parameters and for cosmology. Assuming a flat νΛCDM model, in which the sum of neutrino masses is a free parameter, we measure Ω m =0.276±0.047, σ 8 =0.781±0.037, and σ 8 (Ω m /0.3) 0.2 =0.766±0.025. The redshift evolutions of the X-ray Y X-mass and M gas-mass relations are both consistent with self-similar evolution to within 1σ. The mass slope of the Y X-mass relation shows a 2.3σ deviation from self-similarity. Similarly, the mass slope of the M gas-mass relation is steeper than self-similarity at the 2.5σ level. In a νwCDM cosmology, we measure the dark energy equation-of-state parameter w=−1.55±0.41 from the cluster data. We perform a measurement of the growth of structure since redshift z∼1.7 and find no evidence for tension with the prediction from general relativity. This is the first analysis of the SPT cluster sample that uses direct weak-lensing mass calibration and is a step toward using the much larger weak-lensing data set from DES. We provide updated redshift and mass estimates for the SPT sample.