Causes of Death and Comorbidities in Patients with COVID-19

Infection by the new corona virus strain SARS-CoV-2 and its related syndrome COVID-19 has caused several hundreds of thousands of deaths worldwide. Patients of higher age and with preexisting chronic health conditions are at an increased risk of fatal disease outcome. However, detailed information on causes of death and the contribution of comorbidities to death yet is missing. Here, we report autopsy findings on causes of death and comorbidities of 26 decedents that had clinically presented with severe COVID-19. We found that septic shock and multi organ failure was the most common immediate cause of death, often due to suppurative pulmonary infection. Respiratory failure due to diffuse alveolar damage presented as the most immediate cause of death in fewer cases. Several comorbidities, such as hypertension, ischemic heart disease, and obesity were present in the vast majority of patients. Our findings reveal that causes of death were directly related to COVID-19 in the majority of decedents, while they appear not to be an immediate result of preexisting health conditions and comorbidities. We therefore suggest that the majority of patients had died of COVID-19 with only contributory implications of preexisting health conditions to the mechanism of death.

Olfactory transmucosal SARS-CoV-2 invasion as port of Central Nervous System entry in COVID-19 patients

The newly identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic respiratory disease presenting with fever, cough, and often pneumonia. Moreover, thromboembolic events throughout the body including the central nervous system (CNS) have been described. Given first indication for viral RNA presence in the brain and cerebrospinal fluid and in light of neurological symptoms in a large majority of COVID-19 patients, SARS-CoV-2-penetrance of the CNS is likely. By precisely investigating and anatomically mapping oro- and pharyngeal regions and brains of 32 patients dying from COVID-19, we not only describe CNS infarction due to cerebral thromboembolism, but also demonstrate SARS-CoV-2 neurotropism. SARS-CoV-2 enters the nervous system via trespassing the neuro-mucosal interface in the olfactory mucosa by exploiting the close vicinity of olfactory mucosal and nervous tissue including delicate olfactory and sensitive nerve endings. Subsequently, SARS-CoV-2 follows defined neuroanatomical structures, penetrating defined neuroanatomical areas, including the primary respiratory and cardiovascular control center in the medulla oblongata.

Cross-modality assessment and planning for pulmonary trunk treatment using CT and MRI imaging.

Congenital heart defect is the primary cause of death in newborns, due to typically complex malformation of the cardiac system. The pulmonary valve and trunk are often affected and require complex clinical management and in most cases surgical or interventional treatment. While minimal invasive methods are emerging, non-invasive imaging-based assessment tools become crucial components in the clinical setting. For advanced evaluation and therapy planning purposes, cardiac Computed Tomography (CT) and cardiac Magnetic Resonance Imaging (cMRI) are important non-invasive investigation techniques with complementary properties. Although, characterized by high temporal resolution, cMRI does not cover the full motion of the pulmonary trunk. The sparse cMRI data acquired in this context include only one 3D scan of the heart in the end-diastolic phase and two 2D planes (long and short axes) over the whole cardiac cycle. In this paper we present a cross-modality framework for the evaluation of the pulmonary trunk, which combines the advantages of both, cardiac CT and cMRI. A patient-specific model is estimated from both modalities using hierarchical learning-based techniques. The pulmonary trunk model is exploited within a novel dynamic regression-based reconstruction to infer the incomplete cMRI temporal information. Extensive experiments performed on 72 cardiac CT and 74 cMRI sequences demonstrated the average speed of 110 seconds and accuracy of 1.4mm for the proposed approach. To the best of our knowledge this is the first dynamic model of the pulmonary trunk and right ventricle outflow track estimated from sparse 4D cMRI data.

Scanning microprobe matrix-assisted laser desorption ionization (SMALDI) mass spectrometry: instrumentation for sub-micrometer resolved LDI and MALDI surface analysis.

A new instrument and method is described for laterally resolved mass spectrometric surface analysis. Fields of application are in both the life sciences and the material sciences. The instrument provides for imaging of the distribution of selected sample components from natural and artificial surfaces. Samples are either analyzed by laser desorption ionization (LDI) time-of-flight mass spectrometry or, after preparation with a suitable matrix, by matrix-assisted laser desorption ionization (MALDI) mass spectrometry. Areas of 100 x 100 microm are scanned with minimal increments of 0.25 microm, and between 10,000 and 160,000 mass spectra are acquired per image within 3 to 50 min (scan rate up to 50 pixels per s). The effective lateral resolution is in the range of 0.6 to 1.5 microm depending on sample properties, preparation methods and laser wavelength. Optical investigation of the same sample area by UV confocal scanning laser microscopy was found to be very attractive in combination with scanning MALDI mass analysis because pixel-identical images can be created with both techniques providing for a strong increase in analytical information. This article describes the method and instrumentation, including first applicational examples in elemental analysis, imaging of pine tree roots, and investigation of MALDI sample morphology in biomolecular analysis.