Publications by authors named "Roberto Arioli"
Introduction: Computer-Aided Lung Informatics for Pathology Evaluation and Ratings (CALIPER) software has already been widely used in the evaluation of interstitial lung diseases (ILD) but has not yet been tested in patients affected by COVID-19. Our aim was to use it to describe the relationship between Coronavirus Disease 2019 (COVID-19) outcome and the CALIPER-detected pulmonary vascular-related structures (VRS).
Materials And Methods: We performed a multicentric retrospective study enrolling 570 COVID-19 patients who performed a chest CT in emergency settings in two different institutions.
Pulmonary parenchymal and vascular damage are frequently reported in COVID-19 patients and can be assessed with unenhanced chest computed tomography (CT), widely used as a triaging exam. Integrating clinical data, chest CT features, and CT-derived vascular metrics, we aimed to build a predictive model of in-hospital mortality using univariate analysis (Mann-Whitney test) and machine learning models (support vectors machines (SVM) and multilayer perceptrons (MLP)). Patients with RT-PCR-confirmed SARS-CoV-2 infection and unenhanced chest CT performed on emergency department admission were included after retrieving their outcome (discharge or death), with an 85/15% training/test dataset split.
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- The study focuses on understanding the varied prognosis of COVID-19 by identifying clinical and laboratory indicators that can predict poor outcomes in hospitalized patients.
- Researchers analyzed data from 664 COVID-19 patients in Northern Italy, discovering that factors like red cell distribution width (RDW), neutrophil-to-lymphocyte (NL) ratio, and platelet count are significant predictors of in-hospital mortality.
- The results suggest that using simple blood tests could help in classifying the severity of COVID-19, ultimately guiding treatment and monitoring strategies for better patient management.
Article Synopsis
- - In December 2019, COVID-19 emerged in Wuhan, leading to a global pandemic and prompting studies to analyze its effects, particularly through CT imaging of pneumonia severity.
- - A retrospective study examined 218 patients with confirmed COVID-19, dividing them into ICU and non-ICU groups to assess chest CT patterns and related clinical data, revealing distinct differences in demographics and health conditions.
- - ICU patients showed more severe CT findings like consolidation and bilateral opacities, alongside higher rates of comorbidities and abnormal lab results, indicating that CT features can help evaluate disease severity and inform treatment.
Background Lower muscle mass is a known predictor of unfavorable outcomes, but its prognostic impact on patients with COVID-19 is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in patients with COVID-19. Materials and Methods Clinical or laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed SARS-CoV-2 infection, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020.
View Article and Find Full Text PDFClinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods.
View Article and Find Full Text PDFObjectives: The goal of this study was to assess chest computed tomography (CT) diagnostic accuracy in clinical practice using RT-PCR as standard of reference.
Methods: From March 4th to April 9th 2020, during the peak of the Italian COVID-19 epidemic, we enrolled a series of 773 patients that performed both non-contrast chest CT and RT-PCR with a time interval no longer than a week due to suspected SARS-CoV-2 infection. The diagnostic performance of CT was evaluated according to sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy, considering RT-PCR as the reference standard.
Purpose: To quantitatively compare the artefact reduction between standard and metallic artefact reduction (MAR) fast spin echo (FSE) T2 sequences in a low-field magnetic resonance imaging (MRI) scanner (0.3 T) in patients with titanium volar wrist plating.
Materials And Methods: Sixteen patients with fractures of the distal radius, treated with titanium volar wrist plating and screws, were examined using a dedicated 0.