The lung ultrasound “Rule of 7” in the prognosis of COVID-19 patients: Results from a prospective multicentric study

Tung‐Chen, Yale; Gil‐Rodrigo, Adriana; Algora-Martín, Ana; Llamas-Fuentes, Rafael; Rodríguez-Fuertes, Pablo; Marín-Baselga, Raquel; Alonso-Martínez, Blanca; Rodríguez, Elena Sanz; Soriano, Pere Llorens; Ramos-Rincón, José-Manuel

doi:10.1016/j.medcle.2021.07.024

Cited by 1 publication

(2 citation statements)

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“…In COVID-19 diagnosis, a meta-analysis pointed out that CT is sensitive and moderately specific while chest X-ray is moderately sensitive and specific, and Ultrasound is sensitive but not specific, thus chest CT and ultrasound are more useful for ruling out COVID-19 infection [3]. Several studies have discussed the use of one of the imaging scoring systems in prediction of COVID-19's outcomes but no meta-analysis had compared between them in predicting COVID's outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…Several studies and meta-analyses have been done on the role of different imaging modalities such as X-ray, computed tomography (CT), and ultrasound in COVID-19 diagnosis. COVID 19 imaging findings have been reported in lots of studies; however, the use of a combined prognostic and triage tool has not been explored yet [3]. The prognostic importance of imaging modalities and their role in the risk stratification of patients already diagnosed with COVID- 19 have not yet been established.…”

Section: Introductionmentioning

confidence: 99%

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

Kandil,

Elgenidy,

Saba

et al. 2023

iRADIOLOGY

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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 < 0.001, I2 = 74.86%, p = 0.019] while the pooled area under ROC for CT severity score was [AUC = 0.855, 95% CI 0.78–0.93; p < 0.001, I2 = 93.73%, p < 0.001]. Regarding adverse outcomes prediction, the LUS had a slightly higher specificity of [78%; 95% CI 0.75–0.80] and PLR of [3.60; 95% CI 2.28–5.68] compared to CT score. The pooled AUC using LUS was (0.77, 95% CI 0.719–0.832; p < 0.001), while using CT severity score was (0.843, 95% CI 0.787–0.898; p < 0.001), and using X‐ray scores was (0.814, 95% CI 0.751–0.878; p < 0.001). Conclusion CT severity score showed a better discriminatory ability in predicting COVID‐19 adverse outcomes, as in‐hospital mortality, ICU admission, and need for ventilatory support compared to LUS and X‐RAY scores, while the LUS, being more specific, had a slightly better prognostic value.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%