This study aimed to assess the usefulness of a new chest X-ray scoring systemthe Brixia scoreto predict the risk of in-hospital mortality in hospitalized patients with coronavirus disease 2019 (COVID-19). Methods: Between March 4, 2020 and March 24, 2020, all CXR reports including the Brixia score were retrieved. We enrolled only hospitalized Caucasian patients with COVID-19 for whom the final outcome was available. For each patient, age, sex, underlying comorbidities, immunosuppressive therapies, and the CXR report containing the highest score were considered for analysis. These independent variables were analyzed using a multivariable logistic regression model to extract the predictive factors for inhospital mortality. Results: 302 Caucasian patients who were hospitalized for COVID-19 were enrolled. In the multivariable logistic regression model, only Brixia score, patient age, and conditions that induced immunosuppression were the significant predictive factors for in-hospital mortality. According to receiver operating characteristic curve analyses, the optimal cutoff values for Brixia score and patient age were 8 points and 71 years, respectively. Three different models that included the Brixia score showed excellent predictive power. Conclusions: Patients with a high Brixia score and at least one other predictive factor had the highest risk of in-hospital death.
Purpose To improve the risk stratification of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), an experimental chest X-ray (CXR) scoring system for quantifying lung abnormalities was introduced in our Diagnostic Imaging Department. The purpose of this study was to retrospectively evaluate correlations between the CXR score and the age or sex of Italian patients infected with SARS-CoV-2. Materials and methods Between March 4, 2020, and March 18, 2020, all CXR reports containing the new scoring system were retrieved. Only hospitalized patients with SARS-CoV-2 infection were enrolled. For each patient, age, sex, and the CXR report containing the highest score were considered for the analysis. Patients were also divided into seven groups according to age. Nonparametric statistical tests were used to examine the relationship between the severity of lung disease and the age or sex. Results 783 Italian patients (532 males and 251 females) with SARS-CoV-2 infection were enrolled. The CXR score was significantly higher in males than in females only in groups aged 50 to 79 years. A significant correlation was observed between the CXR score and age in both males and females. Males aged 50 years or older and females aged 80 years or older with coronavirus disease 2019 showed the highest CXR score (median ≥ 8). Conclusions Males aged 50 years or older and females aged 80 years or older showed the highest risk of developing severe lung disease. Our results may help to identify the highest-risk patients and those who require specific treatment strategies.
The much-heralded second wave of coronavirus disease has arrived in Italy. Right now, one of the main questions about COVID-19 in Italy is whether the second wave will be less severe than the rst.Currently, the answer to this question remains open.According to the Italian Ministry of Health website (COVID-19 -Situation in Italy), it would appear that in Italy the COVID-19 second wave is less severe and deadly than the rst one was.However, this difference could be affected by several factors, including the different number of swabs performed in the two waves, as it is approximately seven to eight times higher in the second wave. Therefore, it is not yet clear whether the COVID-19 second wave in Italy, speci cally in Lombardy, is less severe and deadly than the rst wave.In order to answer this challenging question, we decided to quantify the radiographic severity of COVID-19 pneumonia during the second wave and compare it with that of the rst wave. In addition, to further test whether the severity of the second wave is indeed lower than that of the rst one, we compared the use of mechanical ventilation between the two waves.
Purpose: To improve the risk stratification of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), an experimental chest x-ray (CXR) scoring system for quantifying lung abnormalities was introduced in our Diagnostic Imaging Department. The purpose of this study was to retrospectively evaluate correlations between the CXR score and the age or sex of Italian patients infected with SARS-CoV-2.Material and Methods: Between March 4, 2020 and March 18, 2020, all CXR reports containing the new scoring system were retrieved. Only hospitalized patients with SARS-CoV-2 infection were enrolled. For each patient, age, sex, and the CXR report containing the highest score were considered for the analysis. Patients were also divided into seven groups according to age. Non-parametric statistical tests were used to examine the relationship between the severity of lung disease and the age or sex.Results: 783 Italian patients (532 males and 251 females) with SARS-CoV-2 infection were enrolled.The CXR score was significantly higher in males than in females only in groups aged 50 to 79 years. A significant correlation was observed between the CXR score and age in both males and females.Males aged 50 years or older and females aged 80 years or older showed a significantly increased risk of developing severe coronavirus disease 2019 (COVID-19). Conclusions:Males aged 50 years or older and females aged 80 years or older showed the highest risk of developing severe lung disease. Our results may help to identify the highest-risk patients and those who require specific treatment strategies.
Persistent part-solid nodules (PSNs) with a solid component <6 mm usually represent minimally invasive adenocarcinomas and are significantly less aggressive than PSNs with a solid component ≥6 mm. However, not all PSNs with a small solid component behave in the same way: some nodules exhibit an indolent course, whereas others exhibit more aggressive behavior. Thus, predicting the future behavior of this subtype of PSN remains a complex and fascinating diagnostic challenge. The main purpose of this study was to apply open-source software to investigate which quantitative computed tomography (CT) features may be useful for predicting the behavior of a select group of PSNs. We retrospectively selected 50 patients with a single PSN with a solid component <6 mm and diameter <15 mm. Computerized analysis was performed using ImageJ software for each PSN and various quantitative features were calculated from the baseline CT images. The area, perimeter, mean Feret diameter, linear mass density, circularity and solidity were significantly related to nodule growth (p ≤ 0.031). Therefore, quantitative CT analysis was helpful for predicting the future behavior of a select group of PSNs with a solid component <6 mm and diameter <15 mm.
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