ObjectiveTo develop a diagnostic model for superficial soft tissue lesions to differentiate epidermal cyst (EC) from other lesions based on ultrasound (US) features.Materials and MethodsThis retrospective study included 205 patients who had undergone US examinations for superficial soft tissue lesions and subsequent surgical excision. The study population was divided into the derivation set (n = 112) and validation set (n = 93) according to the imaging date. The following US features were analyzed to determine those that could discriminate EC from other lesions: more-than-half-depth involvement of the dermal layer, “submarine sign” (focal projection of the hypoechoic portion to the epidermis), posterior acoustic enhancement, posterior wall enhancement, morphology, shape, echogenicity, vascularity, and perilesional fat change. Using multivariable logistic regression, a diagnostic model was constructed and visualized as a nomogram. The performance of the diagnostic model was assessed by calculating the area under the curve (AUC) of the receiver operating characteristic curve and calibration plot in both the derivation and validation sets.ResultsMore-than-half-depth involvement of the dermal layer (odds ratio [OR] = 3.35; p = 0.051), “submarine sign” (OR = 12.2; p < 0.001), and morphology (OR = 5.44; p = 0.002) were features that outweighed the others when diagnosing EC. The diagnostic model based on these features showed good discrimination ability in both the derivation set (AUC = 0.888, 95% confidence interval [95% CI] = 0.825–0.950) and validation set (AUC = 0.902, 95% CI = 0.832–0.972).ConclusionMore-than-half-depth of involvement of the dermal layer, “submarine sign,” and morphology are relatively better US features than the others for diagnosing EC.

Intermittent manual measurement of vital signs may not rapidly predict sepsis development in febrile patients admitted to the emergency department (ED). We aimed to evaluate the predictive performance of a wireless monitoring device that continuously measures heart rate (HR) and respiratory rate (RR) and a machine learning analysis in febrile but stable patients in the ED. We analysed 468 patients (age, ≥18 years; training set, n = 277; validation set, n = 93; test set, n = 98) having fever (temperature >38 °C) and admitted to the isolation care unit of the ED. The AUROC of the fragmented model with device data was 0.858 (95% confidence interval [CI], 0.809–0.908), and that with manual data was 0.841 (95% CI, 0.789–0.893). The AUROC of the accumulated model with device data was 0.861 (95% CI, 0.811–0.910), and that with manual data was 0.853 (95% CI, 0.803–0.903). Fragmented and accumulated models with device data detected clinical deterioration in febrile patients at risk of septic shock 9 h and 5 h 30 min earlier, respectively, than those with manual data. Continuous vital sign monitoring using a wearable device could accurately predict clinical deterioration and reduce the time to recognise potential clinical deterioration in stable ED patients with fever.

Introduction The coronavirus disease (COVID-19) pandemic has delayed the management of other serious medical conditions. This study presents an efficient method to prevent the degradation of the quality of diagnosis and treatment of other critical diseases during the pandemic. Methods We performed a retrospective observational study. The primary outcome was ED length of stay (ED LOS). The secondary outcomes were the door-to-balloon time in patients with suspected ST-segment elevation myocardial infarction and door-to-brain computed tomography time for patients with suspected stroke. The outcome measures were compared between patients who were treated in the red and orange zones designated as the changeable isolation unit and those who were treated in the non-isolation care unit. To control confounding factors, we performed propensity score matching, following which, outcomes were analyzed for non-inferiority. Results The mean ED LOS for hospitalized patients in the isolation and non-isolation care units were 406.5 min (standard deviation [SD], 237.9) and 360.2 min (SD, 226.4), respectively. The mean difference between the groups indicated non-inferiority of the isolation care unit (p = 0.037) but not in the patients discharged from the ED (p>0.999). The mean difference in the ED LOS for patients admitted to the ICU between the isolation and non-isolation care units was -22.0 min (p = 0.009). The mean difference in the door-to-brain computed tomography time between patients with suspected stroke in the isolation and non-isolation care units was 7.4 min for those with confirmed stroke (p = 0.013), and -20.1 min for those who were discharged (p = 0.012). The mean difference in the door-to-balloon time between patients who underwent coronary angiography in the isolation and non-isolation care units was -2.1 min (p<0.001). Conclusions Appropriate and efficient handling of a properly planned ED plays a key role in improving the quality of medical care for other critical diseases during the COVID-19 outbreak.

Post contrast-acute kidney injury (PC-AKI) is defined as the deterioration of renal function after administration of iodinated contrast media. HMGB1 is known to play an important role in the development of acute kidney injury. The purpose of this study was to investigate the association between HMGB1 and PC-AKI and the protective effect of glycyrrhizin, a direct inhibitor of HMGB1, in rats. Rats were divided into three groups: control, PC-AKI and PC-AKI with glycyrrhizin. Oxidative stress was measured with MDA levels and H2DCFDA fluorescence intensity. The mRNA expressions of pro-inflammatory cytokines (IL-1α, IL-1β, IL-6 and TNF-α) and kidney injury markers (KIM-1, NGAL and IL-18) were assessed using RT-PCR and ELISA in kidney tissue. In addition, the serum and intracellular protein levels of HMGB1were analyzed with the enzyme-linked immunosorbent assay (ELISA) and western blotting. Histologic changes were assessed with H&E staining using the transmission electron microscope (TEM). Moreover, serum creatinine (SCr), blood urea nitrogen (BUN) and lactate dehydrogenase (LDH) levels were assessed. Oxidative stress, pro-inflammatory cytokines, kidney injury markers and LDH were significantly higher in PC-AKI compared to the controls, but were lower in PC-AKI with glycyrrhizin. Intracellular and serum HMGB1 levels significantly increased after contrast media exposure, whereas they markedly decreased after glycyrrhizin pretreatment. SCr and BUN also decreased in PC-AKI with glycyrrhizin compared to PC-AKI. In PC-AKI, we could frequently observe tubular dilatation with H&E staining and cytoplasmic vacuoles on TEM, whereas these findings were attenuated in PC-AKI with glycyrrhizin. Our findings indicate that HMGB1 plays an important role in the development of PC-AKI and that glycyrrhizin has a protective effect against renal injury and dysfunction by inhibiting HMGB1 and reducing oxidative stress.