Evidence map›Paper›PMID 35160121›Full record

ArticleJournal of clinical medicine2022

Inter-Observer Agreement between Low-Dose and Standard-Dose CT with Soft and Sharp Convolution Kernels in COVID-19 Pneumonia.

Ivan Blokhin, Victor Gombolevskiy, Valeria Chernina, Maxim Gusev, Pavel Gelezhe, Olga Aleshina, Alexander Nikolaev, Nicholas Kulberg, Sergey Morozov, Roman Reshetnikov

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 47% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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

10 authors at 4 institutions in 1 country.

Ivan BlokhinResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.ORCID 0000-0002-2681-9378
Victor GombolevskiyArtificial Intelligence Research Institute (AIRI), 105064 Moscow, Russia.ORCID 0000-0003-1816-1315
Valeria CherninaResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.
Maxim GusevMoscow Polytechnic University, 107023 Moscow, Russia.ORCID 0000-0001-8864-8722
Pavel GelezheResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.
Olga AleshinaCity Clinical Hospital No. 13 of the Moscow Health Care Department, 115280 Moscow, Russia.
Alexander NikolaevResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.ORCID 0000-0001-5151-4579
Nicholas KulbergFederal Research Center "Computer Science and Control" of Russian Academy of Sciences, 119333 Moscow, Russia.ORCID 0000-0001-7046-7157
Sergey MorozovResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.
Roman ReshetnikovResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.ORCID 0000-0002-9661-0254
City Clinical Hospital · RUMoscow Polytechnic University · RURussian Academy of Sciences · RUSechenov University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computed tomography (CT) has been an essential diagnostic tool during the COVID-19 pandemic. The study aimed to develop an optimal CT protocol in terms of safety and reliability. For this, we assessed the inter-observer agreement between CT and low-dose CT (LDCT) with soft and sharp kernels using a semi-quantitative severity scale in a prospective study (Moscow, Russia). Two consecutive scans with CT and LDCT were performed in a single visit. Reading was performed by ten radiologists with 3-25 years' experience. The study included 230 patients, and statistical analysis showed LDCT with a sharp kernel as the most reliable protocol (percentage agreement 74.35 ± 43.77%), but its advantage was marginal. There was no significant correlation between radiologists' experience and average percentage agreement for all four evaluated protocols. Regarding the radiation exposure, CTDI

Indexed as

COVID-19pneumoniaSARS-CoV-2tomographyX-ray computed

Identifiers

PMID35160121
PMCPMC8836391
OpenAlexW4210469115

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.