Objective: To explore the clinical safety and efficacy of a single-position robot-assisted radical nephroureterectomy (RRUN) in the treatment of upper tract urothelial carcinoma (UTUC). Methods: A retrospective study was conducted on 136 UTUC patients who underwent RRUN (n=35) and laparoscopic radical nephroureterectomy (LRUN，n=101) in our hospital during Dec.2020 and Aug.2023.The perioperative and safety indicators of the two groups were compared.The intravesical recurrence-free survival (IVRFS)，recurrence-free survival (RFS)，and overall survival (OS) of the two groups were compared using Kaplan-Meier method. Results: There were no significant differences in the baseline data between the two groups (P>0.05).All surgeries were successfully completed without conversion to open surgery.RRUN demonstrated superior perioperative outcomes compared to LRUN in overall postoperative complication rate [37.1%(13/35) vs. 56.4%(57/101)]，postoperative hospital stay [6(5,7) days vs. 7(6,8) days]，and catheter indwelling time [3(2，4) days vs. 4(3，5) days]，with statistically significant differences (P<0.05).Safety indicators of both surgical approaches were similar (P>0.05).Survival analysis showed no significant difference in oncological outcomes between the two groups [IVRFS (1 year：92.1%，2 years：85.2%)，RFS (1 year:82.4%，2 years:74.9%)，OS (1 year:90.6%，2 years:84.2%)] (P>0.05). Conclusion: Compared with retroperitoneal LRUN，single-position RRUN for UTUC demonstrates comparable safety and oncological efficacy，while offering significant advantages in perioperative outcomes such as reducing postoperative complication rate and shortening hospital stay.

Objective To develop an instrument for predicting postoperative constipation risks in patients with osteoporotic thoracolumbar fracture(OTLF)who have undergone percutaneous kyphoplasty(PKP).Methods A total of 858 OTLF patients who underwent PKP surgery between January 2020 and December 2024 were enrolled.The patients were randomly assigned to a training set(n=600)and a validation set(n=258)in a 7∶3 ratio.According to whether the patients had postoperative constipation,the training set was divided into a constipation group(n=205)and a non-constipation group(n=395),and the validation set was divided into a constipation group(n=90)and a non-constipation group(n=168).Logistic regression analysis was conducted to analyze the factors influencing postoperative constipation in OTLF patients after PKP,and a nomogram model was constructed accordingly.The receiver operating characteristic(ROC)curve and the calibration curve of the model were plotted,and the Hosmer-Lemeshow test for goodness of fit was performed.Results A total of 205 OTLF patients(34.17%)in the training set and 90 OTLF patients(34.88%)in the validation set experienced constipation after PKP.Univariate analysis revealed significant differences between the constipation and non-constipation groups in terms of operative time,postoperative water intake,time to first postoperative meal,postoperative bed rest time,the levels of Bifidobacterium,Lactobacillus,Enterococcus,and Enterobacter,the Nutrition Risk Screening 2002(NRS-2002)score,and the levels of sodium,potassium,and HbA1c(P<0.05).Least absolute shrinkage and selection operator(LASSO)regression was performed and operative time,time to first postoperative meal,the levels of Bifidobacterium,Lactobacillus,Enterococcus,and Enterobacter,the NRS-2002 score,and the levels of sodium,potassium,and HbA1c were identified as candidate predictors.Multivariate logistic analysis showed that the time to first postoperative meal,the levels of Bifidobacterium and Lactobacillus,the NRS-2002 score,and the levels of sodium and HbA1c were influencing factors of postoperative constipation in OTLF patients(P<0.05).The ROC curves showed that the area under the curve(AUC)of the training set was 0.842(95%CI:0.793-0.892),while that of the validation set was 0.860(95%CI:0.830-0.889).The calibration curves demonstrated good agreement between the prediction curve and the standard curve in both the training set and the validation set.Conclusion The time to the first postoperative meal,the NRS2002 score,and the levels of Bifidobacterium,Lactobacillus,sodium,and HbA1c are influencing factors of post-PKP constipation in OTLF patients.The nomogram model built based on these factors exhibited good predictive performance.

Objective To construct a radiomics model for predicting hematoma enlargement in early hypertensive intracerebral hemorrhage and explore its predictive value.Methods A retrospective collection of 212 patients with hypertensive intracerebral hemorrhage within 6 h of onset,admitted to our hospital from February 2010 to August 2018,was performed.CT examination was performed within half an hour of admission.CT re-examination was performed 24 h after admission to determine whether there was hematoma enlargement.The regions of interest were delineated on the first CT,and 431 image indicators were extracted from the Matlab software.The LASSO regression model was used to screen out the most predictive imaging features,and the selected features and support vector machine classifier (SVM) were used to build the prediction model.Receiver operating characteristic (ROC) curve was used to evaluate the predicted effect of the model.Results After 24 h of admission,the incidence of hematoma enlargement was 18.9％ (40/212).Eighteen imaging ensemble features (including 4 first-order statistics features:standard deviation,kurtosis,uniformity,and variance;one shape-and size-based feature:surface to volume ratio;7 textual features:long run low grey level emphasis,inertia,correlation-angle 90,short run emphasis,correlation-all direction,long run emphasis,and inverse difference moment;6 wavelet features:autocorrelation-3,informational measure of correlation2-3,long run high gray level emphasis-4,short run high gray level emphasis-4,short run low gray level emphasis-7,and sum variance-3) were combined with SVM to establish a prediction model by LASSO regression model.The area under ROC curve was 0.928,enjoying sensitivity and specificity of 92.5％ and 83.5％,respectively.Conclusion The constructed radiomics model is helpful in predicting the expansion of hypertensive cerebral hemorrhage.