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 hippocampus of mammals and birds is critical for spatial memory. Neuroanatomical evidence indicates that the medial cortex (MC) of reptiles and the lateral pallium (LP) of ray-finned fishes could be homologous to the hippocampus of mammals and birds. In this work, we studied the effects of lesions to the MC of turtles and to the LP of goldfish in spatial memory. Lesioned animals were trained in place, and cue maze tasks and crucial probe and transfer tests were performed. In experiment 1, MC-lesioned turtles in the place task failed to locate the goal during trials in which new start positions were used, whereas sham animals navigated directly to the goal independently of start location. In contrast, no deficit was observed in cue learning. In experiment 2, LP lesion produced a dramatic impairment in goldfish trained in the place task, whereas medial and dorsal pallium lesions did not decrease accuracy. In addition, none of these pallial lesions produced deficits in cue learning. These results indicate that lesions to the MC of turtles and to the LP of goldfish, like hippocampal lesions in mammals and birds, selectively impair map-like memory representations of the environmental space. Thus, the forebrain structures of reptiles and teleost fish neuroanatomically equivalent to the mammalian and avian hippocampus also share a central role in spatial cognition. Present results suggest that the presence of a hippocampus-dependent spatial memory system is a primitive feature of the vertebrate forebrain that has been conserved through evolution.

Objectives Information on the recently COVID‐19‐associated pulmonary aspergillosis (CAPA) entity is scarce. We describe eight CAPA patients, compare them to colonised ICU patients with coronavirus disease 2019 (COVID‐19), and review the published literature from Western countries. Methods Prospective study (March to May, 2020) that included all COVID‐19 patients admitted to a tertiary hospital. Modified AspICU and European Organization for Research and Treatment of Cancer/Mycoses Study Group (EORTC/MSG) criteria were used. Results COVID‐19‐associated pulmonary aspergillosis was diagnosed in eight patients (3.3% of 239 ICU patients), mostly affected non‐immunocompromised patients (75%) with severe acute respiratory distress syndrome (ARDS) receiving corticosteroids. Diagnosis was established after a median of 15 days under mechanical ventilation. Bronchoalveolar lavage was performed in two patients with positive Aspergillus fumigatus cultures and galactomannan (GM) index. Serum GM was positive in 4/8 (50%). Thoracic CT scan findings fulfilled EORTC/MSG criteria in one case. Isavuconazole was used in 4/8 cases. CAPA‐related mortality was 100% (8/8). Compared with colonised patients, CAPA subjects were administered tocilizumab more often (100% vs. 40%, p = .04), underwent longer courses of antibacterial therapy (13 vs. 5 days, p = .008), and had a higher all‐cause mortality (100% vs. 40%, p = .04). We reviewed 96 similar cases from recent publications: 59 probable CAPA (also putative according modified AspICU), 56 putative cases and 13 colonisations according AspICU algorithm; according EORTC/MSG six proven and two probable. Overall, mortality in the reviewed series was 56.3%. Conclusions COVID‐19‐associated pulmonary aspergillosis must be considered a serious and potentially life‐threatening complication in patients with severe COVID‐19 receiving immunosuppressive treatment.

We propose a framework for the robust and fully-automatic segmentation of magnetic resonance (MR) brain images called "Multi-Atlas Label Propagation with Expectation-Maximisation based refinement" (MALP-EM). The presented approach is based on a robust registration approach (MAPER), highly performant label fusion (joint label fusion) and intensity-based label refinement using EM. We further adapt this framework to be applicable for the segmentation of brain images with gross changes in anatomy. We propose to account for consistent registration errors by relaxing anatomical priors obtained by multi-atlas propagation and a weighting scheme to locally combine anatomical atlas priors and intensity-refined posterior probabilities. The method is evaluated on a benchmark dataset used in a recent MICCAI segmentation challenge. In this context we show that MALP-EM is competitive for the segmentation of MR brain scans of healthy adults when compared to state-of-the-art automatic labelling techniques. To demonstrate the versatility of the proposed approach, we employed MALP-EM to segment 125 MR brain images into 134 regions from subjects who had sustained traumatic brain injury (TBI). We employ a protocol to assess segmentation quality if no manual reference labels are available. Based on this protocol, three independent, blinded raters confirmed on 13 MR brain scans with pathology that MALP-EM is superior to established label fusion techniques. We visually confirm the robustness of our segmentation approach on the full cohort and investigate the potential of derived symmetry-based imaging biomarkers that correlate with and predict clinically relevant variables in TBI such as the Marshall Classification (MC) or Glasgow Outcome Score (GOS). Specifically, we show that we are able to stratify TBI patients with favourable outcomes from non-favourable outcomes with 64.7% accuracy using acute-phase MR images and 66.8% accuracy using follow-up MR images. Furthermore, we are able to differentiate subjects with the presence of a mass lesion or midline shift from those with diffuse brain injury with 76.0% accuracy. The thalamus, putamen, pallidum and hippocampus are particularly affected. Their involvement predicts TBI disease progression.

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