PurposeThe aim of this study was to evaluate and compare the diagnostic performance of grayscale ultrasonography (US), US elastography, and US computer-aided diagnosis (US-CAD) in the differential diagnosis of breast masses.MethodsA total of 193 breast masses in 175 consecutive women (mean age, 46.4 years) from June to August 2015 were included. US and elastography images were obtained and recorded. A US-CAD system was applied to the grayscale sonograms, which were automatically analyzed and visualized in order to generate a final assessment. The final assessments of breast masses were based on the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories, while elasticity scores were assigned using a 5-point scoring system. The diagnostic performance of grayscale US, elastography, and US-CAD was calculated and compared. ResultsOf the 193 breast masses, 120 (62.2%) were benign and 73 (37.8%) were malignant. Breast masses had significantly higher rates of malignancy in BI-RADS categories 4c and 5, elastography patterns 4 and 5, and when the US-CAD assessment was possibly malignant (all P<0.001). Elastography had higher specificity (40.8%, P=0.042) than grayscale US. US-CAD showed the highest specificity (67.5%), positive predictive value (PPV) (61.4%), accuracy (74.1%), and area under the curve (AUC) (0.762, all P<0.05) among the three diagnostic tools. ConclusionUS-CAD had higher values for specificity, PPV, accuracy, and AUC than grayscale US or elastography. Computer-based analysis based on the morphologic features of US may be very useful in improving the diagnostic performance of breast US.

Background:The Clinical Frailty Scale (CFS) is a representative frailty assessment tool in medicine. This systematic review and meta-analysis aimed to examine whether frailty defined based on the CFS could adequately predict short-term mortality in emergency department (ED) patients. Methods:The PubMed, EMBASE, and Cochrane libraries were searched for eligible studies until December 23, 2021. We included studies in which frailty was measured by the CFS and short-term mortality was reported for ED patients. All studies were screened by two independent researchers. Sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) values were calculated based on the data extracted from each study. Additionally, the diagnostic odds ratio (DOR) was calculated for effect size analysis, and the area under the curve (AUC) of summary receiver operating characteristics was calculated. Outcomes were in-hospital and 1month mortality rate for patients with the CFS scores of ≥5, ≥6, and ≥7. Results:Overall, 17 studies (n = 45,022) were included. Although there was no evidence of publication bias, a high degree of heterogeneity was observed. For the CFS score of ≥5, the PLR, NLR, and DOR values for in-hospital mortality were 1.446 (95% confidence interval [CI] 1.325-1.578), 0.563 (95% CI 0.355-0.893), and 2.728 (95% CI 1.872-3.976), respectively. In addition, the pooled statistics for 1-month mortality were 1.566 (95% CI 1.241-1.976), 0.582 (95% CI 0.430-0.789), and 2.696 (95% CI 1.673-4.345), respectively. Subgroup analysis of trauma patients revealed that the CFS score of ≥5 could adequately predict in-hospital mortality (PLR 1.641, NLR 0.580, DOR 2.883,. The AUC values represented sufficient to good diagnostic accuracy. Conclusions:Evidence that is published to date suggests that the CFS is an accurate and reliable tool for predicting short-term mortality in emergency patients.