Can We Apply Snyder's Arthroscopic Classification to Ultrasound for Evaluating Rotator Cuff Tears? A Comparative Study with MR Arthrography.

We aimed to demonstrate the applicability of Snyder's arthroscopic classification of rotator cuff tears (RCT) in shoulder ultrasound (US) and to compare it with MR arthrography (MRA). Forty-six patients (34 males; mean age:34 ± 14 years) underwent shoulder US and MRA. Two radiologists (R1 = 25 years of experience; R2 = 2 years of experience) assigned A1-4, B1-4, or C1-4 values depending on the extent of RCT in both US and MRA. Inter-reader intra-modality and intra-reader inter-modality agreement were calculated using Cohen's kappa coefficient. US sensitivity and specificity of both readers were calculated using MRA as the gold standard. Patients were divided into intact cuff vs. tears, mild (A1/B1) vs. moderate (A2-3/B2-3) tears, mild-moderate (A2/B2) vs. high-moderate (A3/B3) cuff tears, moderate (A2-3/B2-3) vs. advanced (A4/B4) and full-thickness (C) tears. The highest agreement values in inter-reader US evaluation were observed for mild-moderate vs. high-moderate RCT (K = 0.745), in inter-reader MRA evaluation for mild vs. moderate RCT (K = 0.821), in R1 inter-modality (US-MRA) for mild-moderate vs. high-moderate and moderate vs. advanced/full-thickness RCT (K = 1.000), in R2 inter-modality (US-MRA) for moderate vs. advanced/full-thickness RCT (K = 1.000). US sensitivity ranged from 88.89%(R1)-84.62%(R2) to 100% (both readers), while specificity from 77.78%(R1)-90.00%(R2) to 100% (both readers). Snyder's classification can be used in US to ensure the correct detection and characterization of RCT.

Detection Rate and Variability in Measurement of Mandibular Incisive Canal on Cone-Beam Computed Tomography: A Study of 220 Dentate Hemi-Mandibles from Italy.

The mandibular incisive canal (MIC) is a small bony channel located in the interforaminal region; it represents the anterior continuation of the mandibular canal. Cone-beam computed tomography (CBCT) is the most commonly utilized radiological technique for assessing the MIC. The main purpose of this study was to evaluate the detectability and variability in measurements of the MIC on CBCT. A total of 220 dentate hemi-mandibles were retrospectively selected for this study. For each hemi-mandible, the detectability, diameter, and distance of the MIC from anatomical landmarks (cortical plates and tooth apices) were evaluated in consensus by two observers. The analysis was performed at four different levels (first premolar, canine, lateral incisor, and central incisor) and was repeated after one month. The variability of MIC measurements was expressed as the coefficient of repeatability (CR), obtained from the Bland-Altman analysis. The MIC detection rate reduced from the first premolar to the central incisor (from 82.3% to 0.5%). The CR of MIC measurements (diameter and distances from anatomical landmarks) was ≤0.74 mm. Although the MIC is difficult to detect in a non-negligible percentage of cases, the limited variability in measurements confirms that CBCT is an effective technique for the assessment of the MIC.

Lombardy, Northern Italy: COVID-19 second wave less severe and deadly than the first? A preliminary investigation.

BACKGROUND: The much-heralded second wave of coronavirus disease (COVID-19) has arrived in Italy. Right now, one of the main questions about COVID-19 is whether the second wave is less severe and deadly than the first wave. In order to answer this challenging question, we decided to evaluate the chest X-ray (CXR) severity of COVID-19 pneumonia, the mechanical ventilation (MV) use, the patient outcome, and certain clinical/laboratory data during the second wave and compare them with those of the first wave. METHODS: During the two COVID-19 waves two independent groups of hospitalised patients were selected. The first group consisted of the first 100 COVID-19 patients admitted to our hospital during the first wave. The second group consisted of another 100 consecutive COVID-19 patients admitted to our hospital during the second wave. We enlisted only Caucasian male patients over the age of fifty for whom the final outcome was available. For each patient, the CXR severity of COVID-19 pneumonia, the MV use, the patient outcome, comorbidities, corticosteroid use, and C-reactive protein (CRP) levels were considered. Nonparametric statistical tests were used to compare the data obtained from the two waves. RESULTS: The CXR severity of COVID-19 pneumonia, the in-hospital mortality, and CRP levels were significantly higher in the first wave than in the second wave (p ≤ .041). Although not statistically significant, the frequency of MV use was higher in the first wave. CONCLUSIONS: This preliminary investigation seems to confirm that the COVID-19 second wave is less severe and deadly than the first wave.

Chest X-ray severity index as a predictor of in-hospital mortality in coronavirus disease 2019: A study of 302 patients from Italy.

OBJECTIVES: This study aimed to assess the usefulness of a new chest X-ray scoring system - the Brixia score - to 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 in-hospital 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.