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A COVID-19-association-dependent categorization of death causes in 100 autopsy cases

From March through December 2020, 100 autopsies were performed (Semmelweis University, Budapest, Hungary), with chart review, of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection demonstrated by real-time reverse-transcription polymerase chain reaction testing (mea...

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Autores principales: Danics, Krisztina, Pesti, Adrián, Törő, Klára, Kiss-Dala, Noémi, Szlávik, János, Lakatos, Botond, Radnai, Andrea, Balázs, Tamás, Bacskai, Miklós, Dobi, Deján, Várkonyi, Tibor, Glasz, Tibor, Lotz, Gábor, Kiss, András, Schaff, Zsuzsa, Vályi-Nagy, István
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8435112/
https://www.ncbi.nlm.nih.gov/pubmed/34510338
http://dx.doi.org/10.1007/s11357-021-00451-w
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author Danics, Krisztina
Pesti, Adrián
Törő, Klára
Kiss-Dala, Noémi
Szlávik, János
Lakatos, Botond
Radnai, Andrea
Balázs, Tamás
Bacskai, Miklós
Dobi, Deján
Várkonyi, Tibor
Glasz, Tibor
Lotz, Gábor
Kiss, András
Schaff, Zsuzsa
Vályi-Nagy, István
author_facet Danics, Krisztina
Pesti, Adrián
Törő, Klára
Kiss-Dala, Noémi
Szlávik, János
Lakatos, Botond
Radnai, Andrea
Balázs, Tamás
Bacskai, Miklós
Dobi, Deján
Várkonyi, Tibor
Glasz, Tibor
Lotz, Gábor
Kiss, András
Schaff, Zsuzsa
Vályi-Nagy, István
author_sort Danics, Krisztina
collection PubMed
description From March through December 2020, 100 autopsies were performed (Semmelweis University, Budapest, Hungary), with chart review, of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection demonstrated by real-time reverse-transcription polymerase chain reaction testing (mean age, 74.73 years, range 40–102 years; 50 males, mean age 71.96 years, and 50 females, mean age 77.5 years). Classified by the date of death, 21 cases were from the pandemic’s “first wave” (March through July) and 79 from the “second wave” (August through December). Three mortality categories were defined by relevance of SARS-CoV-2 infection: (1) “strong” association (n=57), in which COVID-19 was primary responsible for death; (2) “contributive” association (n=27), in which a pre-existing condition independent of COVID-19 was primary responsible for death, albeit with substantial COVID-19 co-morbidity; (3) “weak” association (n=16), in which COVID-19 was minimally or not at all responsible for death. Distributions among categories differed between the first wave, in which the “contributive” association cases dominated (strong: 24%, contributive: 48%, weak: 28%), and the second wave, in which the “strong” association cases dominated (strong: 66%, contributive: 21%, weak: 13%). Charted co-morbidities included hypertension (85 %), cardiovascular diseases (71 %), diabetes (40 %), cerebrovascular diseases (31 %), chronic respiratory diseases (30 %), malignant tumors (20 %), renal diseases (19 %), diseases of the central nervous system (15 %), and liver diseases (6 %). Autopsy evaluation analyzed alterations on macroscopy as well as findings on microscopy of scanned and scored sections of formalin-fixed, paraffin-embedded tissue samples (50–80 blocks/case). Severity of histological abnormalities in the lung differed significantly between “strong” and “contributive” (p<0.0001) and between “strong” and “weak” categories (p<0.0001). Abnormalities included diffuse alveolar damage, macrophage infiltration, and vascular and alveolar fibrin aggregates (lung), with macro- and microvascular thrombi and thromboemboli (lung, kidney, liver). In conclusion, autopsies clarified in what extent COVID-19 was responsible for death, demonstrated the pathological background of clinical signs and symptoms, and identified organ alterations that led to the death. Clinicopathologic correlation, with conference discussions of severity of co-morbidities and of direct pathological signs of disease, permitted accurate categorization of cause of death and COVID-19 association as “strong,” “contributive,” or “weak.” Lung involvement, with reduced ventilatory capacity, was the primary cause of death in the “strong” and “contributive” categories. Shifts in distribution among categories, with “strong” association between COVID-19 and death dominating in the second wave, may reflect improved clinical management of COVID-19 as expertise grew. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11357-021-00451-w.
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spelling pubmed-84351122021-09-13 A COVID-19-association-dependent categorization of death causes in 100 autopsy cases Danics, Krisztina Pesti, Adrián Törő, Klára Kiss-Dala, Noémi Szlávik, János Lakatos, Botond Radnai, Andrea Balázs, Tamás Bacskai, Miklós Dobi, Deján Várkonyi, Tibor Glasz, Tibor Lotz, Gábor Kiss, András Schaff, Zsuzsa Vályi-Nagy, István GeroScience Original Article From March through December 2020, 100 autopsies were performed (Semmelweis University, Budapest, Hungary), with chart review, of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection demonstrated by real-time reverse-transcription polymerase chain reaction testing (mean age, 74.73 years, range 40–102 years; 50 males, mean age 71.96 years, and 50 females, mean age 77.5 years). Classified by the date of death, 21 cases were from the pandemic’s “first wave” (March through July) and 79 from the “second wave” (August through December). Three mortality categories were defined by relevance of SARS-CoV-2 infection: (1) “strong” association (n=57), in which COVID-19 was primary responsible for death; (2) “contributive” association (n=27), in which a pre-existing condition independent of COVID-19 was primary responsible for death, albeit with substantial COVID-19 co-morbidity; (3) “weak” association (n=16), in which COVID-19 was minimally or not at all responsible for death. Distributions among categories differed between the first wave, in which the “contributive” association cases dominated (strong: 24%, contributive: 48%, weak: 28%), and the second wave, in which the “strong” association cases dominated (strong: 66%, contributive: 21%, weak: 13%). Charted co-morbidities included hypertension (85 %), cardiovascular diseases (71 %), diabetes (40 %), cerebrovascular diseases (31 %), chronic respiratory diseases (30 %), malignant tumors (20 %), renal diseases (19 %), diseases of the central nervous system (15 %), and liver diseases (6 %). Autopsy evaluation analyzed alterations on macroscopy as well as findings on microscopy of scanned and scored sections of formalin-fixed, paraffin-embedded tissue samples (50–80 blocks/case). Severity of histological abnormalities in the lung differed significantly between “strong” and “contributive” (p<0.0001) and between “strong” and “weak” categories (p<0.0001). Abnormalities included diffuse alveolar damage, macrophage infiltration, and vascular and alveolar fibrin aggregates (lung), with macro- and microvascular thrombi and thromboemboli (lung, kidney, liver). In conclusion, autopsies clarified in what extent COVID-19 was responsible for death, demonstrated the pathological background of clinical signs and symptoms, and identified organ alterations that led to the death. Clinicopathologic correlation, with conference discussions of severity of co-morbidities and of direct pathological signs of disease, permitted accurate categorization of cause of death and COVID-19 association as “strong,” “contributive,” or “weak.” Lung involvement, with reduced ventilatory capacity, was the primary cause of death in the “strong” and “contributive” categories. Shifts in distribution among categories, with “strong” association between COVID-19 and death dominating in the second wave, may reflect improved clinical management of COVID-19 as expertise grew. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11357-021-00451-w. Springer International Publishing 2021-09-11 /pmc/articles/PMC8435112/ /pubmed/34510338 http://dx.doi.org/10.1007/s11357-021-00451-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Danics, Krisztina
Pesti, Adrián
Törő, Klára
Kiss-Dala, Noémi
Szlávik, János
Lakatos, Botond
Radnai, Andrea
Balázs, Tamás
Bacskai, Miklós
Dobi, Deján
Várkonyi, Tibor
Glasz, Tibor
Lotz, Gábor
Kiss, András
Schaff, Zsuzsa
Vályi-Nagy, István
A COVID-19-association-dependent categorization of death causes in 100 autopsy cases
title A COVID-19-association-dependent categorization of death causes in 100 autopsy cases
title_full A COVID-19-association-dependent categorization of death causes in 100 autopsy cases
title_fullStr A COVID-19-association-dependent categorization of death causes in 100 autopsy cases
title_full_unstemmed A COVID-19-association-dependent categorization of death causes in 100 autopsy cases
title_short A COVID-19-association-dependent categorization of death causes in 100 autopsy cases
title_sort covid-19-association-dependent categorization of death causes in 100 autopsy cases
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8435112/
https://www.ncbi.nlm.nih.gov/pubmed/34510338
http://dx.doi.org/10.1007/s11357-021-00451-w
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