Sarcopenia is a skeletal muscle disorder characterized by reduced muscle mass, strength, and performance. Muscle ultrasound can be helpful in assessing muscle mass, quality, and architecture, and thus possibly useful for diagnosing or screening sarcopenia. The objective of this study was to evaluate the reliability of ultrasound assessment of tibialis anterior muscle in sarcopenia diagnosis. We included subjects undergoing total or partial hip replacement, comparing measures with a healthy control group. We measured the following parameters: tibialis anterior muscle thickness, echogenicity, architecture, stiffness, skeletal muscle index (SMI), hand grip strength, and sarcopenia related quality of life evaluated through the SarQoL questionnaire. We included 33 participants with a mean age of 54.97 ± 23.91 years. In the study group we found reduced tibialis anterior muscle thickness compared to the healthy control group (19.49 ± 4.92 vs. 28.94 ± 3.63 mm, p < 0.05) with significant correlation with SarQoL values (r = 0.80, p < 0.05), dynamometer hand strength (r = 0.72, p < 0.05) and SMI (r = 0.76, p < 0.05). Moreover, we found reduced stiffness (32.21 ± 12.31 vs. 27.07 ± 8.04 Kpa, p < 0.05). AUC measures of ROC curves were 0.89 predicting reduced muscle strength, and 0.97 predicting reduced SMI for tibialis anterior muscle thickness, while they were 0.73 and 0.85, respectively, for muscle stiffness. Our findings showed that ultrasound assessment of tibialis anterior muscle might be considered a reliable measurement tool to evaluate sarcopenia.
Introduction. The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. Materials and Methods. In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients ( 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. Results. At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) ( 10.4; ), neutrophil-to-lymphocyte (NL) ratio ( 7.6; ), and platelet count ( 5.39; ), along with age ( 87.6; ) and gender ( 17.3; ), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a was characterized by an odds ratio for in-hospital (2.40-4.82), while the OR for a
Background: The studies about injury to the anterior talo-fibular ligament (ATFL) are focused mainly on chronic symptoms and chronic instability, and the literature about the accuracy of magnetic resonance imaging (MRI) in acute injuries is quite lacking. Methods: This systematic review with meta-analysis analyzes the diagnostic accuracy of MRI on acute ATFL injury. Relative studies were retrieved after searching three databases (MEDLINE, SCOPUS, and Cochrane Central Register of Controlled Trails). Eligible studies were summarized. The quality of the included articles was assessed using the revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Data were extracted to calculate pooled sensitivity and specificity of MRI. Results: Seven studies met our inclusion and exclusion criteria. For MRI, the pooled sensitivities and specificity in diagnosing acute ATFL injury were respectively 1.0 (95% CI: 0.58–1) and 0.9 (95% CI: 0.79–0.96). Pooled LR+ and LR− were respectively 10.4 (95% CI: 4.6–23) and 0 (95% CI: 0–0.82). Conclusion: This systematic review with meta-analysis investigated the accuracy of imaging for the diagnosis of acute ATFL injury. Our results demonstrated that MRI shows high diagnostic accuracy in the diagnosis of acute ATFL lesions. These results suggest that routine MRI in the case of suspected ATFL acute injury may be clinically useful, although this is not done in clinical practice due probably to high cost.
Background: In December 2019, a cluster of unknown etiology pneumonia cases occurred in Wuhan, China leading to identification of the responsible pathogen as SARS-coV-2. Since then, the coronavirus disease 2019 (COVID-19) has spread to the entire world. Computed Tomography (CT) is frequently used to assess severity and complications of COVID-19 pneumonia. The purpose of this study is to compare the CT patterns and clinical characteristics in intensive care unit (ICU) and non- ICU patients with COVID-19 pneumonia. Design and methods: This retrospective study included 218 consecutive patients (136 males; 82 females; mean age 63±15 years) with laboratory-confirmed SARS-coV-2. Patients were categorized in two different groups: (a) ICU patients and (b) non-ICU inpatients. We assessed the type and extent of pulmonary opacities on chest CT exams and recorded the information on comorbidities and laboratory values for all patients. Results: Of the 218 patients, 23 (20 males: 3 females; mean age 60 years) required ICU admission, 195 (118 males: 77 females, mean age 64 years) were admitted to a clinical ward. Compared with non-ICU patients, ICU patients were predominantly males (60% versus 83% p=0.03), had more comorbidities, a positive CRP (p=0.04) and higher LDH values (p=0.008). ICU patients’ chest CT demonstrated higher incidence of consolidation (p=0.03), mixed lesions (p=0.01), bilateral opacities (p<0.01) and overall greater lung involvement by consolidation (p=0.02) and GGO (p=0.001). Conclusions: CT imaging features of ICU patients affected by COVID-19 are significantly different compared with non-ICU patients. Identification of CT features could assist in a stratification of the disease severity and supportive treatment.
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 U 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. Out of 897 patients, the 229 (26%) patients who died during hospitalization had higher median pulmonary artery diameter (29.0 mm) than patients who survived (27.0 mm, p < 0.001) and higher median ascending aortic diameter (36.6 mm versus 34.0 mm, p < 0.001). SVM and MLP best models considered the same ten input features, yielding a 0.747 (precision 0.522, recall 0.800) and 0.844 (precision 0.680, recall 0.567) area under the curve, respectively. In this model integrating clinical and radiological data, pulmonary artery diameter was the third most important predictor after age and parenchymal involvement extent, contributing to reliable in-hospital mortality prediction, highlighting the value of vascular metrics in improving patient stratification.
Background: Patellar femoral chondropathy (FPC) is a common problem in patients undergoing anterior cruciate ligament reconstruction (ACL-R) surgery, which, if left untreated, predisposes to arthrosis. Magnetic resonance imaging (MRI) is the non-invasive gold standard for morphological evaluation of cartilage, while in recent years advanced MRI techniques (such as T2 mapping) have been developed to detect early cartilage biochemical changes. This study evaluates the different onset of early PFC between B-TP-B and HT through T2 mapping. Secondly, it aims to assess the presence of any concordance between self-reported questionnaires and qualitative MRI. Materials and methods: 19 patients enrolled were divided into two groups based on the type of intervention: B-PT-B and HT. After a median time of 54 months from surgery, patients were subjected to conventional MRI, T2 mapping, and clinical-functional evaluation through three self-reported questionnaires: Knee Injury and Osteoarthritis index (KOOS); Tegner Lysholm Knee Scoring Scale; International Knee Documentation Committee (IKDC). Results: There is not statistically significant difference in the comparison between the two MRI techniques and the two reconstructive techniques. KOOS and Tegner Lysholm scales showed significant agreement with MRI results on the grading of chondropathy. Conclusions: There are no differences between B-TP-B and HT techniques in the early development of PFC detectable through non-invasive methods. Due to the large reduction in the frequency of physical activity following ACL-R and the finding of mild PFC (grade I and II) in a substantial proportion of patients, after a relatively short period from ACL-R, all patients should undergo conservative treatment.