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

Autor: Omneya Kandil, Anas Elgenidy, Patrick Saba, Mohamed Tarek Hasan, Kenneth Galbraith, Mark Spooner, Demi Ajao, Omar Yaipen, Elyas Ayad, Abdelrahman Nassar, Khalil Hamka, Walaa Hasan, Jaffer Shah, Ahmed Shawkat, Diaa Hakim, Hani Aiash
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: iRADIOLOGY, Vol 1, Iss 2, Pp 128-140 (2023)
Druh dokumentu: article
ISSN: 2834-2879
2834-2860
DOI: 10.1002/ird3.23
Popis: 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 for discriminatory assessment, respectively. Results Regarding mortality prediction, the computed tomography (CT) showed significantly higher sensitivity [80%; 95% CI 0.74–0.85] and positive likelihood ratio (PLR) [4.41 95% CI 2.94–6.61] relative to the Lung Ultrasound Score (LUS) approach, while the LUS approached the CT scan with specificity of 81% [95% CI 0.78–0.83] and negative likelihood ratio (NLR) of [0.32; 95% CI 0.16–0.64]. The pooled area under ROC for LUS was [AUC = 0.777, 95% CI 0.701–0.852; p
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