1. Study on the application of dexmedetomidine combined with remifentanil in dressing change of conscious patients with non-intubation in burn intensive care unit
Zhibin YANG ; Jiangyong SHEN ; Kede MI ; Qiang MA ; Yinsheng WU ; Ming YAO
Chinese Journal of Burns 2018;34(10):707-713
Objective:
To observe the analgesic and sedative effect and safety of application of dexmedetomidine combined with remifentanil in dressing change of conscious patients with non-intubation in burn intensive care unit.
Methods:
Forty patients conforming to the study criteria hospitalized in our burn intensive care unit from April 2015 to April 2017 were selected. Prospective, randomized, and double-blind method was used for the design. Patients were divided into dexmedetomidine group and dexmedetomidine+ remifentanil group according to the random number table, with 20 cases in each group. Patients in the two groups were respectively given corresponding drugs during dressing change. The frequency and time of dressing change, Verbal Rating Scale (VRS) score of patients during dressing change (at drug administration for 25 minutes) and after dressing change (25 min after dressing change), Ramsay Sedation Score (RSS) during dressing change, satisfaction level for anesthesia of the patients and physicians after dressing change, dosage of remifentanil, and various adverse effects during and after dressing change were recorded. The heart rate, mean arterial blood pressure (MAP), respiratory rate, and pulse oxygen saturation (SpO2) before drug administration and at 10, 15, and 25 minutes after drug administration were also recorded. Data were processed with analysis of variance for repeated measurement,
2.CT radiomics nomogram for predicting Ki-67 expression of thymus epithelial tumors
Zhengping ZHANG ; Xiaojing HOU ; Zijin LIU ; Kede MI ; Zhitao WANG ; Shuping MENG ; Xingcang TIAN ; Li ZHU
Chinese Journal of Medical Imaging Technology 2024;40(11):1693-1697
Objective To observe the value of CT radiomics nomogram for predicting Ki-67 expression of thymus epithelial tumors.Methods Totally 163 patients with thymus epithelial tumor,including 114 patients in training set and 49 patients in validation set were retrospectively enrolled.The patients were further divided into low expression(<50%)and high expression(≥50%)subgroups according to Ki-67 index.Multivariate logistic regression analysis was performed to screen independent predicting factors of Ki-67 expression in thymus epithelial tumors,and clinical-CT model was constructed.The optimal radiomics features were extracted and screened based on chest plain and venous phase enhanced CT images,respectively.Then radiomics modelplain and radiomics modelenhanced were constructed,and Radscoreplain and Radscoreenhanced were calculated,respectively.The nomogram model was constructed based on clinical-CT model,Radscoreplain and Radscoreenhanced.Receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the efficacy of each model for predicting Ki-67 expression of thymus epithelial tumors.Results Patient's gender and enhanced CT value of lesion were both independent predicting factors of Ki-67 expression in thymus epithelial tumors(both P<0.05).The AUC of clinical-CT model,radiomics modelplain,radiomics modelenhanced and nomogram model for predicting Ki-67 expression was 0.736,0.814,0.836 and 0.857 in training set,which was 0.746,0.746,0.750 and 0.799 in validation set,respectively.Conclusion CT radiomics nomogram could be used to predict Ki-6 7 expression of thymus epithelial tumors.