Objective To evaluate the application of different anesthetic drugs—remimazolam(RM)and propofol(PPF)—in anesthesia for pediatric adenoidectomy and tonsillectomy and its effect on emergence agitation.Methods A total of 120 children undergoing elective adenoidectomy and tonsillectomy under general anesthesia in Xinhua Hospital,Huainan Xinhua Medical Group between December 2022 and August 2024 were enrolled.With a random number table,they were assigned to a PPF group receiving PPF and remifentanil and a RM group receiving RM and remifentanil,with 60 cases in each group.The primary and secondary outcome indicators of the two groups were compared.The primary outcome indicator was the incidence of emergence agitation.Secondary outcome indicators included anesthesia-related parameters,changes in mean arterial pressure(MAP)and heart rate(HR)at different time points during surgery,changes in pediatric anesthesia emergence delirium(PAED)scores at different time points after recovery,changes in Ramsay sedation scores and Face,Legs,Activity,Cry,Consolability(FLACC)pain scores at 2,4,12,and 24 hours after surgery,incidence of negative postoperative behavioral changes(NPOBCs)at 7 and 14 days,and adverse events during anesthesia.Results The incidence rate of emergence agitation was lower in the RM group than that of the PPF group(5.00%vs.18.33%,P<0.05).The RM group also demonstrated significantly shorter anesthesia time,extubation time,wake-up time,and postanesthesia care unit(PACU)than those in the PPF group(P<0.05).HR and MAP in the RM group were higher than those in the PPF group at 3 min after induction,at the time of tracheal intubation,during tonsillectomy,and at the end of surgery,with the difference being statistically significant(P<0.05).The PAED scores at different time points after recovery,Ramsay sedation scores and FLACC scores at 2,4 and 12 hours after surgery,the incidence of NPOBCs at 7 days after surgery,and the incidence of adverse reactions during anesthesia were lower in the RM group than those in the PPF group,with the difference being statistically significant(P<0.05).Conclusion RM improves the anesthesia effect and recovery quality of children undergoing adenoidectomy and tonsillectomy,relieves the severity of emergence agitation,reduces the incidence of agitation,and demonstrates good safety.

Objective To investigate the value of CT radiomics for predicting effect of neoadjuvant chemotherapy(NACT)for locally advanced gastric cancer(LAGC).Methods Totally 325 LAGC patients who received NACT were retrospectively enrolled,among them 247 were taken as training set,while the rest 78 were taken as validation set.Tumor regression scale(TRG)was evaluated according to postoperation pathology after NACT,and the efficacy of NACT was evaluated.Univariate logistic regression was used to analyze and screen clinical predictors of effect of NACT,and clinical model was constructed.Radiomics features were extracted based on venous phase enhanced CT pre-and post-NACT,and Delta radiomics features(i.e.the ratio of the difference of pre-and post-NACT radiomics features and pre-NACT radiomics features)were calculated.The best features were screened based on pre-NACT,post-NACT and Delta radiomics features to construct radiomics labels,the optimal label was screened and used to construct combined model through combining clinical model.Receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate predicting efficiency of the above models.Decision curve analysis(DCA)was performed to explore the clinical value of each model.Results In training set,significant effect was found in 67 cases,but not in 180 cases,while in validation set,significant effect was found in 18 cases but not in 60 cases.Borrmann classification of LAGC before NACT was the clinical predictor(P=0.031),and clinical model was constructed,which had AUC of 0.577 and 0.520 in training and validation sets,respectively.Based on pre-NACT,post-NACT and Delta radiomics features,19,14 and 17 best features were selected,and AUC of the established radiomics labels of Pre-Rad,Post-Rad and Delta-Rad in training set was 0.672,0.796 and 0.789,while in validation set was 0.558,0.805 and 0.666,respectively.Post-Rad was the optimal label,which was used to construct combined model.AUC of the obtained combined model in training and validation sets was 0.824 and 0.818,respectively,both higher than that of clinical model(both P＜0.001)but not different with that of Post-Rad(both P＞0.05).Taken 0.4 to 0.7 as the threshold,the combined model had higher clinical net benefit than the other two.Conclusion Venous CT radiomics could effectively predict effect of NACT for LAGC.Combining with clinical features could improve its predictive efficacy.

Objective To investigate the value of CT radiomics for predicting effect of neoadjuvant chemotherapy(NACT)for locally advanced gastric cancer(LAGC).Methods Totally 325 LAGC patients who received NACT were retrospectively enrolled,among them 247 were taken as training set,while the rest 78 were taken as validation set.Tumor regression scale(TRG)was evaluated according to postoperation pathology after NACT,and the efficacy of NACT was evaluated.Univariate logistic regression was used to analyze and screen clinical predictors of effect of NACT,and clinical model was constructed.Radiomics features were extracted based on venous phase enhanced CT pre-and post-NACT,and Delta radiomics features(i.e.the ratio of the difference of pre-and post-NACT radiomics features and pre-NACT radiomics features)were calculated.The best features were screened based on pre-NACT,post-NACT and Delta radiomics features to construct radiomics labels,the optimal label was screened and used to construct combined model through combining clinical model.Receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate predicting efficiency of the above models.Decision curve analysis(DCA)was performed to explore the clinical value of each model.Results In training set,significant effect was found in 67 cases,but not in 180 cases,while in validation set,significant effect was found in 18 cases but not in 60 cases.Borrmann classification of LAGC before NACT was the clinical predictor(P=0.031),and clinical model was constructed,which had AUC of 0.577 and 0.520 in training and validation sets,respectively.Based on pre-NACT,post-NACT and Delta radiomics features,19,14 and 17 best features were selected,and AUC of the established radiomics labels of Pre-Rad,Post-Rad and Delta-Rad in training set was 0.672,0.796 and 0.789,while in validation set was 0.558,0.805 and 0.666,respectively.Post-Rad was the optimal label,which was used to construct combined model.AUC of the obtained combined model in training and validation sets was 0.824 and 0.818,respectively,both higher than that of clinical model(both P＜0.001)but not different with that of Post-Rad(both P＞0.05).Taken 0.4 to 0.7 as the threshold,the combined model had higher clinical net benefit than the other two.Conclusion Venous CT radiomics could effectively predict effect of NACT for LAGC.Combining with clinical features could improve its predictive efficacy.