2023
DOI: 10.1002/ird3.23
|View full text |Cite
|
Sign up to set email alerts
|

Prognostic and discriminatory abilities of imaging scoring systems in predicting COVID‐19 adverse outcomes

Omneya Kandil,
Anas Elgenidy,
Patrick Saba
et al.

Abstract: Background To evaluate the discriminatory ability of imaging modalities' scoring systems in the prediction of COVID‐19 adverse outcomes like ICU admission, ventilatory support, or mortality. Methods We searched PUBMED, EBSCO, WEB OF SCIENCE, and SCOPUS. Two authors independently screened the resulting papers for fulfillment criteria. Meta‐DiSc version 1.4, RevMan version 5.4, and MedCalc version 19.1 were used for test accuracy analysis, sensitivity and specificity analysis, and pooling Area under the curve fo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 70 publications
0
1
0
Order By: Relevance
“…In addition, the absolute volume of the altered lung volume was derived by the total lung volume software [21]. In all cases a semi-quantitative CT severity score was calculated considering the extent of anatomic involvement as follows: 0, no involvement; 1, <5% involvement; 2, 5-25% involvement; 3, 26-50% involvement; 4, 51-75% involvement; and 5, >75% involvement, using the classification proposed by Pan et al [22] and by Kandil et al [23].…”
Section: Analysis Of Ct Imagesmentioning
confidence: 99%
“…In addition, the absolute volume of the altered lung volume was derived by the total lung volume software [21]. In all cases a semi-quantitative CT severity score was calculated considering the extent of anatomic involvement as follows: 0, no involvement; 1, <5% involvement; 2, 5-25% involvement; 3, 26-50% involvement; 4, 51-75% involvement; and 5, >75% involvement, using the classification proposed by Pan et al [22] and by Kandil et al [23].…”
Section: Analysis Of Ct Imagesmentioning
confidence: 99%