Evidence map›Paper›PMID 33572122›Full record

ArticleDiagnostics (Basel, Switzerland)2021

Quantitative Evaluation of COVID-19 Pneumonia Lung Extension by Specific Software and Correlation with Patient Clinical Outcome.

Andrea Daniele Annoni, Edoardo Conte, Maria Elisabetta Mancini, Carlo Gigante, Cecilia Agalbato, Alberto Formenti, Giuseppe Muscogiuri, Saima Mushtaq, Marco Guglielmo, Andrea Baggiano and 4 more

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

8 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Quantitative Analysis for Lung Disease on Thin-Section CT.Diagnostics (Basel, Switzerland) · 2023
    Review
  6. Article
  7. Article
  8. Article
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

14 authors at 2 institutions in 1 country.

Andrea Daniele AnnoniCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0001-5271-4353
Edoardo ConteCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Maria Elisabetta ManciniCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Carlo GiganteCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0003-2266-0344
Cecilia AgalbatoCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Alberto FormentiCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Giuseppe MuscogiuriCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Saima MushtaqCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Marco GuglielmoCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Andrea BaggianoCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Alice BonomiCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Mauro PepiCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0003-2524-6288
Gianluca PontoneCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0002-1339-6679
Daniele AndreiniCentro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Centro Cardiologico Monzino · ITUniversity of Milan · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung infection named as COVID-19 is an infectious disease caused by the most recently discovered coronavirus 2 (SARS-CoV-2). CT (computed tomography) has been shown to have good sensitivity in comparison with RT-PCR, particularly in early stages. However, CT findings appear to not always be related to a certain clinical severity. The aim of this study is to evaluate a correlation between the percentage of lung parenchyma volume involved with COVID-19 infection (compared to the total lung volume) at baseline diagnosis and correlated to the patient's clinical course (need for ventilator assistance and or death). All patients with suspected COVID-19 lung disease referred to our imaging department for Chest CT from 24 February to 6 April 2020were included in the study. Specific CT features were assessed including the amount of high attenuation areas (HAA) related to lung infection. HAA, defined as the percentage of lung parenchyma above a predefined threshold of -650 (HAA%, HAA/total lung volume), was automatically calculated using a dedicated segmentation software. Lung volumes and CT findings were correlated with patient's clinical course. Logistic regressions were performed to assess the predictive value of clinical, inflammatory and CT parameters for the defined outcome. In the overall population we found an average infected lung volume of 31.4 ± 26.3% while in the subgroup of patients who needed ventilator assistance and who died as well as the patients who died without receiving ventilator assistance the volume of infected lung was significantly higher 41.4 ± 28.5 and 72.7 ± 36.2 (

Indexed as

computed tomographycoronavirus infectionslungpneumonia

Identifiers

PMID33572122
PMCPMC7915160
OpenAlexW3127573282

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.