ABSTRACT
Coronavirus infection 2019 (COVID-19) has become a challenge for the health care system around the world due to the progressive increase in the number of cases with severe manifestations of the disease. Autopsy findings are fundamental and critical to better understanding how infection affects the human body. These data are needed to improve diagnostic and treatment methods, as well as to stratify risk groups. The purpose of the review is to analyze and summarize the pathological data available to date related to COVID-19. In COVID-19, the lungs are usually severe and swollen. Histologically, the most frequent is the detection of both exudative and proliferative diffuse alveolar injury with the formation of hyaline membranes, inflammatory cell infiltration, and stagnant small vessels. There is also evidence that SARS-CoV-2 causes endothelial dysfunction. There is still insufficient data to reflect the complete pathophysiological picture of SARS-CoV-2 infection. Almost all of the articles reviewed in this review focused on pulmonary macro- and microscopic changes;there is little data on the features of the virus affecting other organs and its systemic effect. Despite the tremendous attention and investment in the fight against the new coronavirus infection, diagnosis of most of the deaths associated with COVID-19 is difficult. It is necessary to conduct further pathological studies, the purpose of which should be the development of a standardized diagnostic method, as well as the isolation of pathognomonic signs of the disease. © Authors, 2022.
ABSTRACT
Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pneumopathy is characterized by a complex clinical picture and heterogeneous pathological lesions, both involving alveolar and vascular components. The severity and distribution of morphological lesions associated with SARS-CoV-2 and how they relate to clinical, laboratory, and radiological data have not yet been studied systematically. The main goals of the present study were to objectively identify pathological phenotypes and factors that, in addition to SARS-CoV-2, may influence their occurrence. Lungs from 26 patients who died from SARS-CoV-2 acute respiratory failure were comprehensively analysed. Robust machine learning techniques were implemented to obtain a global pathological score to distinguish phenotypes with prevalent vascular or alveolar injury. The score was then analysed to assess its possible correlation with clinical, laboratory, radiological, and tissue viral data. Furthermore, an exploratory random forest algorithm was developed to identify the most discriminative clinical characteristics at hospital admission that might predict pathological phenotypes of SARS-CoV-2. Vascular injury phenotype was observed in most cases being consistently present as pure form or in combination with alveolar injury. Phenotypes with more severe alveolar injury showed significantly more frequent tracheal intubation; longer invasive mechanical ventilation, illness duration, intensive care unit or hospital ward stay; and lower tissue viral quantity (p < 0.001). Furthermore, in this phenotype, superimposed infections, tumours, and aspiration pneumonia were also more frequent (p < 0.001). Random forest algorithm identified some clinical features at admission (body mass index, white blood cells, D-dimer, lymphocyte and platelet counts, fever, respiratory rate, and PaCO2 ) to stratify patients into different clinical clusters and potential pathological phenotypes (a web-app for score assessment has also been developed; https://r-ubesp.dctv.unipd.it/shiny/AVI-Score/). In SARS-CoV-2 positive patients, alveolar injury is often associated with other factors in addition to viral infection. Identifying phenotypical patterns at admission may enable a better stratification of patients, ultimately favouring the most appropriate management. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.