Evidence map›Paper›PMID 36397905›Full record

ArticleCureus2022

Interobserver Variability in CT Severity Scoring System in COVID-19 Positive Patients.

Yash Jakhotia, Kajal Mitra, Prashant Onkar, Avinash Dhok

Abstract read
In one paragraph

Article in Cureus, 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
–field-weighted citation impact
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

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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.

  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

4 authors.

Yash JakhotiaRadiodiagnosis, NKP Salve Institute of Medical Sciences and Research Centre (IMSRC) and Lata Mangeshkar Hospital, Nagpur, IND.
Kajal MitraRadiodiagnosis, NKP Salve Institute of Medical Sciences and Research Centre (IMSRC) and Lata Mangeshkar Hospital, Nagpur, IND.
Prashant OnkarRadiodiagnosis, NKP Salve Institute of Medical Sciences and Research Centre (IMSRC) and Lata Mangeshkar Hospital, Nagpur, IND.
Avinash DhokRadiodiagnosis, NKP Salve Institute of Medical Sciences and Research Centre (IMSRC) and Lata Mangeshkar Hospital, Nagpur, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChest CT scans are done in cases of coronavirus disease 2019 (COVID-19)-positive patients to understand the severity of the disease and plan treatment accordingly. Severity is determined according to a 25-point scoring system, however, there could be interobserver variability in using this scoring system thus leading to the different categorization of patients. We tried to look for this interobserver variability and thus find out its reliability.

methodsThe study was retrospective and was done in a designated COVID center. Some 100 patients were involved in the study who tested positive for COVID-19 disease. The research was conducted over six months (January 2021 to June 2021). Images were given to three radiologists with a minimum of 10 years of experience in thoracic imaging working in different setups at different places for interpretation and scoring further and their scores were compared. Before the study, the local ethics committee granted its approval.

resultsThere was no significant variability in the interobserver scoring system thus proving its reliability. The standard deviation between different observers was less than three. There was almost perfect agreement amongst all the observers (Fleiss' K=0.99 [95% confidence interval, CI: 0.995-0.998]). Maximum variations were observed in the moderate class.  Conclusion: There was minimum inter-observer variability in the 25-point scoring system thus proving its reliability in categorizing patients according to severity. There was no change in the class of the patient according to its severity. A 25-point scoring system hence can be used by clinicians to plan treatment and thus improve a patient's prognosis.

Indexed as

computed tomographycovid-19ct severity scorepandemicreverse transcriptase polymerase chain reaction

Identifiers

PMID36397905
PMCPMC9648989

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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.