Evidence map›Paper›PMID 37173883›Full record

ArticleCancers2023

Comparison of Computed Tomography Scoring Systems in Patients with COVID-19 and Hematological Malignancies.

Marta Hałaburda-Rola, Joanna Drozd-Sokołowska, Magdalena Januszewicz, Laretta Grabowska-Derlatka

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
–field-weighted citation impact, top 66% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 1 institution in 1 country.

Marta Hałaburda-RolaIInd Department of Clinical Radiology, Medical University of Warsaw, 01-445 Warsaw, Poland.
Joanna Drozd-SokołowskaDepartment of Hematology, Transplantation and Internal Diseases, Medical University of Warsaw, 01-445 Warsaw, Poland.ORCID 0000-0002-4562-6264
Magdalena JanuszewiczIInd Department of Clinical Radiology, Medical University of Warsaw, 01-445 Warsaw, Poland.
Laretta Grabowska-DerlatkaIInd Department of Clinical Radiology, Medical University of Warsaw, 01-445 Warsaw, Poland.
Medical University of Warsaw · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNumerous computed tomography (CT) scales have been proposed to assess lung involvement in COVID-19 pneumonia as well as correlate radiological findings with patient outcomes.

objectiveComparison of different CT scoring systems in terms of time consumption and diagnostic performance in patients with hematological malignancies and COVID-19 infection. MATERIALS AND

methodsRetrospective analysis included hematological patients with COVID-19 and CT performed within 10 days of diagnosis of infection. CT scans were analyzed in three different semi-quantitative scoring systems, Chest CT Severity Score (CT-SS), Chest CT Score(CT-S), amd Total Severity Score (TSS), as well as qualitative modified Total Severity Score (m-TSS). Time consumption and diagnostic performance were analyzed.

resultsFifty hematological patients were included. Based on the ICC values, excellent inter-observer reliability was found among the three semi-quantitative methods with ICC > 0.9 (

conclusionsChest CT score and chest CT severity score have very high sensitivity and specificity in terms of diagnostic accuracy. The highest AUC values and the shortest median time of analysis in chest CT severity score indicate this method as preferred for semi-quantitative assessment of chest CT in hematological patients with COVID-19.

Indexed as

computed tomographyCOVID-19hematological malignanciesimagingpneumonia

Identifiers

PMID37173883
PMCPMC10177556
OpenAlexW4366828430

What OpenQuestion holds

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LicenceCC BY
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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.