To Örebro University

oru.seÖrebro University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Visual scoring of chest CT at hospital admission predicts hospitalization time and intensive care admission in Covid-19
Örebro University Hospital. Örebro University, School of Medical Sciences. Department of Medicine.ORCID iD: 0000-0003-1928-7518
Örebro University, School of Medical Sciences. Örebro University Hospital. Department of Infectious Diseases.ORCID iD: 0000-0003-3921-4244
Örebro University, School of Medical Sciences. Department of Anesthesiology and Intensive Care.
Faculty of Medicine and Health, Department of Infectious Diseases, Örebro University, Örebro, Sweden.
Show others and affiliations
2021 (English)In: Infectious Diseases, ISSN 2374-4235, E-ISSN 2374-4243, Vol. 53, no 8, p. 622-632Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Chest CT is prognostic in Covid-19 but there is a lack of consensus on how to report the CT findings. A chest CT scoring system, ÖCoS, was implemented in clinical routine on 1 April 2020, in Örebro Region, Sweden. The ÖCoS-severity score measures the extent of lung involvement. The objective of the study was to evaluate the ÖCoS scores as predictors of the clinical course of Covid-19.

METHODS: Population based study including data from all hospitalized patients with Covid-19 in Örebro Region during March to July 2020. We evaluated the correlations between CT scores at the time of admission to hospital and intensive care in relation to hospital and intensive care length of stay (LoS), intensive care admission and death. C-reactive protein and lymphocyte count were included as covariates in multivariate regression analyses.

RESULTS: In 381 included patients, the ÖCoS-severity score at admission closely correlated to hospital length of stay, and intensive care admission or death. At admission to intensive care, the ÖCoS-severity score correlated with intensive care length of stay. The ÖCoS-severity score was superior to basic inflammatory biomarkers in predicting clinical outcomes.

CONCLUSION: Chest CT visual scoring at admission to hospital predicted the clinical course of Covid-19 pneumonia.

Place, publisher, year, edition, pages
Taylor & Francis, 2021. Vol. 53, no 8, p. 622-632
Keywords [en]
Covid-19, chest CT, computed tomography, prediction models, visual scoring
National Category
Anesthesiology and Intensive Care Infectious Medicine
Identifiers
URN: urn:nbn:se:oru:diva-91044DOI: 10.1080/23744235.2021.1910727ISI: 000639690600001PubMedID: 33848219Scopus ID: 2-s2.0-85104447361OAI: oai:DiVA.org:oru-91044DiVA, id: diva2:1544165
Note

Funding Agency:

Region Örebro län, Sweden OLL-878081

Available from: 2021-04-14 Created: 2021-04-14 Last updated: 2024-01-10Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

Ahlstrand, ErikCajander, SaraCajander, PerLidén, Mats

Search in DiVA

By author/editor
Ahlstrand, ErikCajander, SaraCajander, PerLidén, Mats
By organisation
Örebro University HospitalSchool of Medical Sciences
In the same journal
Infectious Diseases
Anesthesiology and Intensive CareInfectious Medicine

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 714 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf