Evidence map›Paper›PMID 32914853›Full record

ArticleThe Journal of infectious diseases2020

Postmortem Findings in Italian Patients With COVID-19: A Descriptive Full Autopsy Study of Cases With and Without Comorbidities.

Laura Falasca, Roberta Nardacci, Daniele Colombo, Eleonora Lalle, Antonino Di Caro, Emanuele Nicastri, Andrea Antinori, Nicola Petrosillo, Luisa Marchioni, Gianluigi Biava and 7 more

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 125 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
125citing papers in PubMed, 6 pooled it
4.7field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

125 citing papers in PubMed, 6 syntheses or guidelines pooled it, 201 citations in OpenAlex.

  1. COVID-19-Associated cardiac pathology at the postmortem evaluation: a collaborative systematic review.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2022
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65 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 3 institutions in 2 countries.

Laura FalascaNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Roberta NardacciNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Daniele ColomboNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Eleonora LalleNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Antonino Di CaroNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Emanuele NicastriNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Andrea AntinoriNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Nicola PetrosilloNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Luisa MarchioniNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Gianluigi BiavaNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Gianpiero D'OffiziNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Fabrizio PalmieriNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Delia GolettiNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Alimuddin ZumlaDepartment of Infection, Division of Infection and Immunity, University College London, London, United Kingdom.
Giuseppe IppolitoNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Mauro PiacentiniNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Franca Del NonnoNational Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy.
Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani · ITNational Health Service · GBUniversity of Rome Tor Vergata · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDescriptions of the pathological features of coronavirus disease-2019 (COVID-19) caused by the novel zoonotic pathogen severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emanate from tissue biopsies, case reports, and small postmortem studies restricted to the lung and specific organs. Whole-body autopsy studies of COVID-19 patients have been sparse.

methodsTo further define the pathology caused by SARS-CoV-2 across all body organs, we performed autopsies on 22 patients with COVID-19 (18 with comorbidities and 4 without comorbidities) who died at the National Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS Hospital, Rome, Italy. Tissues from the lung, heart, liver, kidney, spleen, and bone marrow (but not the brain) were examined. Only lung tissues were subject to transmission electron microscopy.

resultsCOVID-19 caused multisystem pathology. Pulmonary and cardiovascular involvement were dominant pathological features. Extrapulmonary manifestations included hepatic, kidney, splenic, and bone marrow involvement, and microvascular injury and thrombosis were also detected. These findings were similar in patients with or without preexisting medical comorbidities.

conclusionsSARS-CoV-2 infection causes multisystem disease and significant pathology in most organs in patients with and without comorbidities.

Indexed as

AdultAgedAged, 80 and overAutopsyBone MarrowComorbidityCOVID-19FemaleHumansItalyKidneyLiverLungMaleMiddle AgedSpleenautopsycomorbiditiesCOVID-19pathologySARS-CoV-2

Identifiers

PMID32914853
PMCPMC7543426
OpenAlexW3085434206

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.