Evidence map›Paper›PMID 39348359›Full record

ArticlePloS one2024

Chest X-ray findings of COVID-19 pneumonia in children: Experiences in a multicenter study in Thailand.

Aunya Kulbun, Prakarn Tovichien, Chanapai Chaiyakulsil, Araya Satdhabudha, Harutai Kamalaporn, Kanokkarn Sunkonkit, Rattapon Uppala, Watit Niyomkarn, Vasinee Norasettekul, Kanokpan Ruangnapa and 9 more

Abstract readMulticenter Study
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

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

19 authors.

Aunya KulbunFaculty of Medicine, Department of Pediatrics, Her Royal Highness Maha Chakri Sirindhorn Medical Center, Srinakharinwirot University, Nakhon Nayok, Thailand.ORCID 0000-0002-8897-2925
Prakarn TovichienFaculty of Medicine Siriraj Hospital, Department of Pediatrics, Division of Pulmonology, Mahidol University, Bangkok, Thailand.ORCID 0000-0002-5000-9930
Chanapai ChaiyakulsilFaculty of Medicine, Department of Pediatrics, Thammasat University Hospital, Thammasat University, Pathumthani, Thailand.ORCID 0000-0003-4677-4223
Araya SatdhabudhaFaculty of Medicine, Department of Pediatrics, Thammasat University Hospital, Thammasat University, Pathumthani, Thailand.
Harutai KamalapornFaculty of Medicine, Department of Pediatrics, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Kanokkarn SunkonkitFaculty of Medicine, Department of Pediatrics, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0003-2725-4636
Rattapon UppalaFaculty of Medicine, Department of Pediatrics, Khon Kaen University, Khon Kaen, Thailand.
Watit NiyomkarnFaculty of Medicine, Department of Pediatrics, Chulalongkorn University, Bangkok, Thailand.
Vasinee NorasettekulDepartment of Pediatrics, Charoenkrung Pracharak Hospital, Bangkok, Thailand.
Kanokpan RuangnapaFaculty of Medicine, Department of Pediatrics, Prince of Songkla University, Songkhla, Thailand.
Chutima SmathakaneeDepartment of Pediatrics, Hat Yai Hospital, Songkhla, Thailand.
Bararee ChoursamranDepartment of Pediatrics, Sawanpracharak Hospital, Nakhon Sawan, Thailand.
Rasintra JaroenyingFaculty of Medicine, Department of Pediatrics, Phramongkutklao Hospital, Bangkok, Thailand.
Tidarat SriboonyongFaculty of Medicine, Department of Pediatrics, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Phanthila SitthikarnkhaFaculty of Medicine, Department of Pediatrics, Khon Kaen University, Khon Kaen, Thailand.
Koonkoaw RoekworachaiDepartment of Pediatrics, Nakornping Hospital, Chiangmai, Thailand.
Thanyarat RatanavongkosolDepartment of Pediatrics, Charoenkrung Pracharak Hospital, Bangkok, Thailand.
Chutima ThongnualDepartment of Pediatrics, Hat Yai Hospital, Songkhla, Thailand.
Jitladda DeerojanawongFaculty of Medicine, Department of Pediatrics, Chulalongkorn University, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAlthough chest X-ray is commonly used to diagnose COVID-19 pneumonia, few studies have explored findings in pediatric patients. This study aimed to reveal chest X-ray characteristics in children with COVID-19 pneumonia and compare between non-severe and severe cases.

methodsThis multicenter, nationwide retrospective study included all children aged 0 to 15 years who were admitted to 13 medical facilities throughout Thailand with COVID-19 pneumonia between January 2020 and October 2021. We analyzed the demographics, clinical features, and chest X-ray results of these children, and compared differences between the non-severe and severe groups.

resultsDuring the study period, 1018 children (52% male, median age 5 years) were admitted with COVID-19 pneumonia. Most chest radiographic findings showed bilateral (51%) patchy/ground glass opacities (61%) in the central area (64%). Only 12% of the children exhibited typical classification for COVID-19 pneumonia, whereas 74% of chest radiographs were categorized as indeterminate. Comorbidities including chronic lung diseases [adjusted OR (95%CI): 14.56 (3.80-55.75), P-value <0.001], cardiovascular diseases [adjusted OR (95%CI): 7.54 (1.44-39.48), P-value 0.017], genetic diseases [adjusted OR (95%CI): 28.39 (4.55-177.23), P-value <0.001], clinical dyspnea [adjusted OR (95%CI): 12.13 (5.94-24.77), P-value <0.001], tachypnea [adjusted OR (95%CI): 3.92 (1.79-8.55), P-value 0.001], and bilateral chest X-ray infiltrations [adjusted OR (95%CI): 1.99 (1.05-3.78), P-value 0.036] were factors associated with severe COVID-19 pneumonia.

conclusionMost children with COVID-19 pneumonia had indeterminate chest X-rays according to the previous classification. We suggest using chest X-rays in conjunction with clinical presentation to screen high-risk patients for early detection of COVID-19 pneumonia.

Indexed as

COVID-19Radiography, ThoracicAdolescentChildChild, PreschoolComorbidityFemaleHumansInfantInfant, NewbornLungMaleRetrospective StudiesSARS-CoV-2Thailand

Identifiers

PMID39348359
PMCPMC11441654

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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.