Novel Ultrasound Scoring System Provides Accurate COVID-19 Diagnosis and Prognosis in Less Than 10 Minutes
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By HospiMedica International staff writers Posted on 14 Sep 2021 |

Illustration
A new study has found that the Lung Ultrasound Severity Index (LUSI), a novel ultrasound score designed to measure the quality and extent of lung involvement, in relation to COVID-19, can be a useful tool in diagnosing COVID-19 in patients with a high pretest probability to have the disease.
The study by researchers from the University of Ferrara (Ferrara, Italy) also found that among the patients diagnosed with COVID-19 who had a high pretest probability to have the disease, the LUSI could also identify those with worse prognosis diagnosis and in-hospital mortality of patients with respiratory distress admitted for suspected COVID-19.
Lung ultrasound is increasingly employed in clinical practice but a standard approach and data about its accuracy still needed. Lung ultrasound having an acknowledged role in the diagnosis and staging of many lung diseases, has been repeatedly evoked as a potentially useful tool in the context of the current pandemic and has been included in many clinical diagnostic pathways of SARS-CoV-2 pneumonia. However, published studies are generally based on score systems that do not consider the patchy ultrasound appearance of SARS-CoV-2 pneumonia, due to the different patterns displayed in the same area.
To resolve this issue, the researchers built a lung ultrasound model that could semi-quantitatively represent the extent of lung involvement and could include the typical patchy appearance of SARS-CoV-2 pneumonia, reporting clearly all data regarding the technical aspect of the lung ultrasound examination, all data regarding the accuracy of the model, and testing it only in regard to the RT-PCR results, the only universally accepted standard reference for the diagnosis of COVID-19. In their study, the team decided to propose and validate the LUSI, a novel ultrasound score designed to measure the quality and extent of lung involvement, in relation to COVID-19 diagnosis and in-hospital mortality of patients with respiratory distress admitted for suspected COVID-19.
Patients with respiratory distress and suspected COVID-19 consecutively admitted in the emergency medicine unit were enrolled for the study. Lung ultrasound examinations were performed blindly to clinical data. The outcomes were diagnosis of COVID-19 pneumonia and in-hospital mortality. The study involved 159 patients, out of which 66% were males and 63.5% had a final diagnosis of COVID-19. The researchers found that COVID-19 patients had a higher mortality rate (18.8% vs. 6.9%) and LUSI (16.14 [8.71] vs. 10.08 [8.92] as compared to non-COVID-19 ones. This model proved able to distinguish between positive cases from negative ones with an Area Under the Receiver Operating Characteristic (AUROC) equal to 0.72 (95% CI 0.64-0.78) and to predict in-hospital mortality with an AUROC equal to 0.81 (95% CI 0.74-0.86), in the whole population, and an AUROC equal to 0.76 (95% CI 0.66-0.84) in COVID-19 patients. The findings indicate that LUSI can be a useful tool in diagnosing COVID-19 in patients with a high pretest probability to have the disease and - among them - identify those with worse prognosis.
Related Links:
University of Ferrara
The study by researchers from the University of Ferrara (Ferrara, Italy) also found that among the patients diagnosed with COVID-19 who had a high pretest probability to have the disease, the LUSI could also identify those with worse prognosis diagnosis and in-hospital mortality of patients with respiratory distress admitted for suspected COVID-19.
Lung ultrasound is increasingly employed in clinical practice but a standard approach and data about its accuracy still needed. Lung ultrasound having an acknowledged role in the diagnosis and staging of many lung diseases, has been repeatedly evoked as a potentially useful tool in the context of the current pandemic and has been included in many clinical diagnostic pathways of SARS-CoV-2 pneumonia. However, published studies are generally based on score systems that do not consider the patchy ultrasound appearance of SARS-CoV-2 pneumonia, due to the different patterns displayed in the same area.
To resolve this issue, the researchers built a lung ultrasound model that could semi-quantitatively represent the extent of lung involvement and could include the typical patchy appearance of SARS-CoV-2 pneumonia, reporting clearly all data regarding the technical aspect of the lung ultrasound examination, all data regarding the accuracy of the model, and testing it only in regard to the RT-PCR results, the only universally accepted standard reference for the diagnosis of COVID-19. In their study, the team decided to propose and validate the LUSI, a novel ultrasound score designed to measure the quality and extent of lung involvement, in relation to COVID-19 diagnosis and in-hospital mortality of patients with respiratory distress admitted for suspected COVID-19.
Patients with respiratory distress and suspected COVID-19 consecutively admitted in the emergency medicine unit were enrolled for the study. Lung ultrasound examinations were performed blindly to clinical data. The outcomes were diagnosis of COVID-19 pneumonia and in-hospital mortality. The study involved 159 patients, out of which 66% were males and 63.5% had a final diagnosis of COVID-19. The researchers found that COVID-19 patients had a higher mortality rate (18.8% vs. 6.9%) and LUSI (16.14 [8.71] vs. 10.08 [8.92] as compared to non-COVID-19 ones. This model proved able to distinguish between positive cases from negative ones with an Area Under the Receiver Operating Characteristic (AUROC) equal to 0.72 (95% CI 0.64-0.78) and to predict in-hospital mortality with an AUROC equal to 0.81 (95% CI 0.74-0.86), in the whole population, and an AUROC equal to 0.76 (95% CI 0.66-0.84) in COVID-19 patients. The findings indicate that LUSI can be a useful tool in diagnosing COVID-19 in patients with a high pretest probability to have the disease and - among them - identify those with worse prognosis.
Related Links:
University of Ferrara
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