UNASSIGNED: We recruited 82 inpatients with LC from the Department of Gastroenterology at the First Affiliated Hospital of Guangxi Medical University between January 2018 and December 2019 for this diagnostic investigation. All patients underwent endoscopy, ultrasound, computed tomography, and routine laboratory investigations. For the study, we evaluated and compared the diagnostic accuracy of PSR, PSVR, SZ, and their combinations.
UNASSIGNED: There were significant differences in the area under the receiver operating characteristic (ROC) curve (AUC) in the prediction of severe and moderate/severe EV for all the variables. PSR+PSVR had the highest AUC at 0.735 (95% CI: 0.626-0.826) and 0.765 (95% CI: 0.659-0.852) for predicting severe and moderate/severe EV, respectively. There were statistically significant differences in the AUCs (95% CI) for PSR, PSVR, and PSR+PSVR in predicting the existence of EV. As per the overall model quality chart, the combination of PSR+PSVR was the best indicator for detecting the presence of EV (AUC, 0.696; 95% CI: 0.584-0.792).
UNASSIGNED: In our study, we found that these noninvasive parameters could predict the extent of severity of EV in patients with LC. We anticipate the use of a combination of PSR + PSVR to emerge as the superior indicator as studies progress.
■我们招募了2018年1月至2019年12月在广西医科大学第一附属医院消化内科住院的82例LC患者。所有患者均行内镜检查,超声,计算机断层扫描,和常规实验室调查。对于这项研究,我们评估并比较了PSR的诊断准确性,PSVR,SZ,和他们的组合。
■对于所有变量,在重度和中度/重度EV的预测中,受试者工作特征(ROC)曲线下面积(AUC)存在显着差异。PSR+PSVR在预测重度和中度/重度EV方面的AUC最高,分别为0.735(95%CI:0.626-0.826)和0.765(95%CI:0.659-0.852)。分别。PSR的AUC(95%CI)差异有统计学意义,PSVR,和PSR+PSVR预测EV的存在。根据整体模型质量图,PSR+PSVR的组合是检测EV存在的最佳指标(AUC,0.696;95%CI:0.584-0.792)。
■在我们的研究中,我们发现,这些无创参数可以预测LC患者EV的严重程度.随着研究的进展,我们预计PSR+PSVR的组合将成为更好的指标。