Objective To explore the evidence for Traditional Chinese Medicine(TCM)in the treatment of premature ovarian insufficiency(POI)based on evidence map and re-evaluation of systematic reviews.Methods CNKI,WanFang Data,VIP,SinoMed,PubMed,Embase,Cochrane Library and Web of Science database were electronically searched to collect systematic reviews(SR)/Meta-analysis on the treatment of POI with TCM from the inception to March 31,2025.The reporting quality,methodological quality,and evidence quality of the included studies were evaluated using the PRISMA 2020 Statement,AMSTAR 2 Checklist,and GRADE system,respectively.The interventions,number of studies,and evidence grades were comprehensively displayed using evidence map.Results A total of 15 SR/Meta-analysis were included,comprising 9 Chinese articles and 6 English articles.The PRISMA 2020 checklist evaluation revealed that 8 articles had certain deficiencies in reporting,while 7 articles demonstrated relatively complete reporting.Based on the AMSTAR 2 checklist,5 articles were rated as high-level and 10 as very low-level.A total of 10 primary outcome indicators were involved,reported 133 times.When classified using the GRADE system,there were 20 pieces of moderate-quality evidence,58 pieces of low-quality evidence,and 55 pieces of very low-quality evidence.The evidence map showed that TCM alone or in combination with hormone therapy could effectively treat POI,reduce follicle-stimulating hormone and luteinizing hormone levels,increase estradiol levels,and improve clinical manifestations and TCM syndrome manifestations.Conclusion TCM has certain advantages in the treatment of POI,enhancing the overall treatment effect,alleviating clinical symptoms of low estrogen,and regulating sex hormone levels to some extent.However,there are deficiencies in methodological quality and reporting quality,and the level of evidence is not high.Therefore,the findings should be used with caution in clinical practice.

Objective:To explore the efficacy of the features of ultrasound imaging omics at the area peripheral thyroid nodule in predicting cervical lymph node metastasis(LNM)of papillary thyroid carcinoma(PTC),and construct a prediction model based on the features of imaging omics and to verify its performance.Methods:A total of 237 PTC patients who admitted to Shaanxi Provincial Hospital of Chinese Medicine from March 2021 to June 2024 and were confirmed by pathology were retrospectively collected.They were divided into the training set(166 cases)and the validation set(71 cases)as a ratio of 7 to 3.According to the postoperatively pathological results,237 patients were divided into the metastasis group(108 cases)and the non-metastasis group(129 cases).The clinical data and conventional ultrasound characteristic information of all patients were collected,and a feature model of imaging omics was constructed through quantitative extracting and screening the features of ultrasound imaging omics within nodules and peripheral nodules,and utilizing machine learning classifier.Then,the feature score(Rad-Score)of image omics was obtained.The Rad-Score values within and peripheral nodules,and the Rad-Score values peripheral nodules of metastasis group and non-metastasis group were compared.In training set,the independent risk factors of affecting neck LNM were analyzed,and a clinical-ultrasonic model was constructed,which was combined with Rad-Score to construct a joint model based on the features of imaging omics peripheral nodules.The receiver operating characteristic(ROC)curve was used to analyze and compare its predictive efficacy.The nomogram of the joint model was constructed,and then,the calibration and fitting degrees of the nomogram were assessed by calibration curve and Hosmer-Lemeshow test.Result:In training set,6 features of imaging omics within nodules and 11 features of imaging omics peripheral nodules were respectively extracted and screened out through the least absolute shrinkage and selection operator(LASSO)algorithm.In the training set and validation set,the Rad-Scores peripheral the nodules in the metastasis group were respectively(7.43±0.45)points and(7.19±0.51)points,which were significantly higher than(3.25±0.28)points and(3.51±0.32)points peripheral the nodules in the non-metastasis group,and the differences were statistically significant(t=72.708,61.222,P<0.05).The results of factor analysis showed that age,capsule invasion,microcalcification,ultrasound-indicated lymph node positivity and Rad-Score around nodules were independent risk factors of affecting cervical LNM of PTC patients(OR=0.592,2.983,3.593,4.424,2.575,P<0.05).The ROC curve showed that the area under curve(AUC)values of the ROC curve of joint model in training set and validation set were respectively 0.861 and 0.872 in predicting LNM,respectively,which were superior to 0.759 and 0.783 of the clinical-ultrasound model.Conclusion:In both the training set and the validation set,the nomogram of joint model has favorable calibration and fitting in predicting cervical LNM of PTC patients.The construction of clinical model based on the features of ultrasound imaging omics peripheral nodules has a favorable efficacy in predicting the status of cervical lymph node of PTC patients before surgery,which is expected to be an effective tool of individual prediction for LNM.

Objective To analyze the influencing factors of tumor-specific mortality in patients with advanced endometrial carcinoma and construct a risk prediction model.Methods A total of 150 patients with advanced endometrial carcinoma admitted to the Fourth Clinical College of Zhejiang Chinese Medical University,Hangzhou First People's Hospital from January 2020 to January 2023 were selected as subjects.Cox regression was employed to analyze factors influencing mortality in advanced endometrial carcinoma.A Logistic regression model was constructed,with receiver operating characteristic(ROC)curve used to evaluate model discrimination,calibration curve for precision assessment,and decision curve for net benefit evaluation.Results Overall 2-year survival rate of 150 patients was 58.67％.The univariate analysis demonstrated that histological grade,lymph node metastasis,tumor maximum diameter,and preoperative carcinoembryonic antigen 125(CA125)levels were all significant risk factors for mortality in advanced endometrial carcinoma(P＜0.05).Multivariate analysis confirmed these parameters as independent prognostic indicators(P＜0.05).A Logistic regression model established using multivariate Cox regression yielded a C index of 0.873(95％CI:0.792-0.951).ROC curve analysis revealed the model's area under the curve for predicting mortality risk factors in advanced endometrial carcinoma was 0.916(95％CI:0.872-0.960).Conclusion The linear chart prediction model constructed based on histological grading,lymph node metastasis,maximum tumor diameter and preoperative CA125 level in this study can effectively predict the death of advanced endometrial carcinoma.

Objective:To construct a training program for epilepsy specialist nurses, so as to provide a theoretical basis for the training and development of epilepsy specialist nurses.Methods:A preliminary training program for epilepsy specialist nurses was developed based on literature review, semi-structured interview, focus group discussion and clinical practice experience. Delphi method was used to select 20 experts from several regions of China for two rounds of consultation.Results:In the two rounds of expert consultation, the effective recovery rate of the questionnaire was both 100%, the expert authority coefficient was 0.908 and 0.958, and the degree of coordination of expert opinions was 0.180 to 0.229 and 0.138 to 0.189, respectively ( P<0.05). The standardized training program for epilepsy specialist nurses was finally constructed, including 5 first-level indicators (admission conditions, general theory courses, specialty theory courses, specialty nursing practice courses, training modes and effectiveness evaluation), 15 second-level indicators and 61 third-level indicators. Conclusions:The training program constructed for epilepsy specialist nurses is scientific and reasonable, with certain reliability and practicality, which provides a theoretical basis for the training of epilepsy specialist nurses, and promotes the common development of China's epilepsy specialist nurse team.

Objective To explore the evidence for Traditional Chinese Medicine(TCM)in the treatment of premature ovarian insufficiency(POI)based on evidence map and re-evaluation of systematic reviews.Methods CNKI,WanFang Data,VIP,SinoMed,PubMed,Embase,Cochrane Library and Web of Science database were electronically searched to collect systematic reviews(SR)/Meta-analysis on the treatment of POI with TCM from the inception to March 31,2025.The reporting quality,methodological quality,and evidence quality of the included studies were evaluated using the PRISMA 2020 Statement,AMSTAR 2 Checklist,and GRADE system,respectively.The interventions,number of studies,and evidence grades were comprehensively displayed using evidence map.Results A total of 15 SR/Meta-analysis were included,comprising 9 Chinese articles and 6 English articles.The PRISMA 2020 checklist evaluation revealed that 8 articles had certain deficiencies in reporting,while 7 articles demonstrated relatively complete reporting.Based on the AMSTAR 2 checklist,5 articles were rated as high-level and 10 as very low-level.A total of 10 primary outcome indicators were involved,reported 133 times.When classified using the GRADE system,there were 20 pieces of moderate-quality evidence,58 pieces of low-quality evidence,and 55 pieces of very low-quality evidence.The evidence map showed that TCM alone or in combination with hormone therapy could effectively treat POI,reduce follicle-stimulating hormone and luteinizing hormone levels,increase estradiol levels,and improve clinical manifestations and TCM syndrome manifestations.Conclusion TCM has certain advantages in the treatment of POI,enhancing the overall treatment effect,alleviating clinical symptoms of low estrogen,and regulating sex hormone levels to some extent.However,there are deficiencies in methodological quality and reporting quality,and the level of evidence is not high.Therefore,the findings should be used with caution in clinical practice.

Objective:To explore the efficacy of the features of ultrasound imaging omics at the area peripheral thyroid nodule in predicting cervical lymph node metastasis(LNM)of papillary thyroid carcinoma(PTC),and construct a prediction model based on the features of imaging omics and to verify its performance.Methods:A total of 237 PTC patients who admitted to Shaanxi Provincial Hospital of Chinese Medicine from March 2021 to June 2024 and were confirmed by pathology were retrospectively collected.They were divided into the training set(166 cases)and the validation set(71 cases)as a ratio of 7 to 3.According to the postoperatively pathological results,237 patients were divided into the metastasis group(108 cases)and the non-metastasis group(129 cases).The clinical data and conventional ultrasound characteristic information of all patients were collected,and a feature model of imaging omics was constructed through quantitative extracting and screening the features of ultrasound imaging omics within nodules and peripheral nodules,and utilizing machine learning classifier.Then,the feature score(Rad-Score)of image omics was obtained.The Rad-Score values within and peripheral nodules,and the Rad-Score values peripheral nodules of metastasis group and non-metastasis group were compared.In training set,the independent risk factors of affecting neck LNM were analyzed,and a clinical-ultrasonic model was constructed,which was combined with Rad-Score to construct a joint model based on the features of imaging omics peripheral nodules.The receiver operating characteristic(ROC)curve was used to analyze and compare its predictive efficacy.The nomogram of the joint model was constructed,and then,the calibration and fitting degrees of the nomogram were assessed by calibration curve and Hosmer-Lemeshow test.Result:In training set,6 features of imaging omics within nodules and 11 features of imaging omics peripheral nodules were respectively extracted and screened out through the least absolute shrinkage and selection operator(LASSO)algorithm.In the training set and validation set,the Rad-Scores peripheral the nodules in the metastasis group were respectively(7.43±0.45)points and(7.19±0.51)points,which were significantly higher than(3.25±0.28)points and(3.51±0.32)points peripheral the nodules in the non-metastasis group,and the differences were statistically significant(t=72.708,61.222,P<0.05).The results of factor analysis showed that age,capsule invasion,microcalcification,ultrasound-indicated lymph node positivity and Rad-Score around nodules were independent risk factors of affecting cervical LNM of PTC patients(OR=0.592,2.983,3.593,4.424,2.575,P<0.05).The ROC curve showed that the area under curve(AUC)values of the ROC curve of joint model in training set and validation set were respectively 0.861 and 0.872 in predicting LNM,respectively,which were superior to 0.759 and 0.783 of the clinical-ultrasound model.Conclusion:In both the training set and the validation set,the nomogram of joint model has favorable calibration and fitting in predicting cervical LNM of PTC patients.The construction of clinical model based on the features of ultrasound imaging omics peripheral nodules has a favorable efficacy in predicting the status of cervical lymph node of PTC patients before surgery,which is expected to be an effective tool of individual prediction for LNM.

Objective:To construct a training program for epilepsy specialist nurses, so as to provide a theoretical basis for the training and development of epilepsy specialist nurses.Methods:A preliminary training program for epilepsy specialist nurses was developed based on literature review, semi-structured interview, focus group discussion and clinical practice experience. Delphi method was used to select 20 experts from several regions of China for two rounds of consultation.Results:In the two rounds of expert consultation, the effective recovery rate of the questionnaire was both 100%, the expert authority coefficient was 0.908 and 0.958, and the degree of coordination of expert opinions was 0.180 to 0.229 and 0.138 to 0.189, respectively ( P<0.05). The standardized training program for epilepsy specialist nurses was finally constructed, including 5 first-level indicators (admission conditions, general theory courses, specialty theory courses, specialty nursing practice courses, training modes and effectiveness evaluation), 15 second-level indicators and 61 third-level indicators. Conclusions:The training program constructed for epilepsy specialist nurses is scientific and reasonable, with certain reliability and practicality, which provides a theoretical basis for the training of epilepsy specialist nurses, and promotes the common development of China's epilepsy specialist nurse team.

Objective To analyze the influencing factors of tumor-specific mortality in patients with advanced endometrial carcinoma and construct a risk prediction model.Methods A total of 150 patients with advanced endometrial carcinoma admitted to the Fourth Clinical College of Zhejiang Chinese Medical University,Hangzhou First People's Hospital from January 2020 to January 2023 were selected as subjects.Cox regression was employed to analyze factors influencing mortality in advanced endometrial carcinoma.A Logistic regression model was constructed,with receiver operating characteristic(ROC)curve used to evaluate model discrimination,calibration curve for precision assessment,and decision curve for net benefit evaluation.Results Overall 2-year survival rate of 150 patients was 58.67％.The univariate analysis demonstrated that histological grade,lymph node metastasis,tumor maximum diameter,and preoperative carcinoembryonic antigen 125(CA125)levels were all significant risk factors for mortality in advanced endometrial carcinoma(P＜0.05).Multivariate analysis confirmed these parameters as independent prognostic indicators(P＜0.05).A Logistic regression model established using multivariate Cox regression yielded a C index of 0.873(95％CI:0.792-0.951).ROC curve analysis revealed the model's area under the curve for predicting mortality risk factors in advanced endometrial carcinoma was 0.916(95％CI:0.872-0.960).Conclusion The linear chart prediction model constructed based on histological grading,lymph node metastasis,maximum tumor diameter and preoperative CA125 level in this study can effectively predict the death of advanced endometrial carcinoma.

Objective:To explore the effects of small-group collaborative stratified teaching in critical care medicine training for professional postgraduate students.Methods:We randomly assigned 71 professional postgraduate students who entered the Intensive Care Unit of The Affiliated Hospital of Qingdao University for standardized training between June 2020 and November 2020 into experimental group and control group. An entrance examination was taken after one week of unified training. Then the experimental group adopted small-group collaborative stratified teaching, while the control group adopted traditional teaching for training. After two months of training, the Mini-Clinical Evaluation Exercise (Mini-CEX) assessment, post competency assessment, exit examination, and teaching satisfaction evaluation were conducted. SPSS 25.0 was used for the t test and chi-square test. Results:In the Mini-CEX assessment, the experimental group had significantly higher scores in history-taking skills [(7.42±0.60) vs. (7.00±0.55)], physical examination [(7.47±0.56) vs. (6.94±0.24)], communication skills [(7.56±0.50）vs.(7.24±0.49)], clinical dialectical thinking [(7.53±0.56) vs. (7.03±0.39)], clinical judgement [(7.50±0.51) vs.(6.90±0.42)], organization/efficiency [(7.58±0.50) vs. (7.15±0.44)], and overall clinical competence [(7.64±0.49) vs. (7.17±0.39); all P<0.05] than the control group. In the post competency assessment, the experimental group had significantly better performance in clinical basic competence [(89.15±9.12) vs. (86.24±10.23)], medical knowledge application [(48.37±5.87) vs. (46.98±3.68)], teamwork [(48.10±3.55) vs. (45.96±4.83)], information and management [(68.52±7.61) vs. (66.38±5.54)], and academic research [(22.18±0.95) vs. (20.87±1.22); all P<0.05] than the control group. The experimental group was also significantly superior to the control group in terms of the exit examination score and teaching satisfaction (both P<0.05). Conclusions:Small-group collaborative stratified teaching can improve the quality of critical care medicine training for professional postgraduate students, and strengthen their clinical comprehensive abilities and post competencies.

Objective To investigate the influential factors for the outcome of the first 131I therapy in patients with PTC after total thyroidectomy.Methods One hundred and fifty-nine patients (45 males,114 females,average age (43.4± 12.2) years) with PTC after total thyroidectomy who underwent 131I therapy from July 2014 to December 2015 were retrospectively analyzed.Curative efficacy was evaluated 6 months after 131I therapy.Therapeutic outcome was evaluated according to TSH stimulated Tg (sTg) level,Dx-WBS and evidences of other imaging modalities.Twelve possible factors affecting therapeutic outcome of 131I therapy,including patients' age,gender,time interval between thyroidectomy and 131I therapy,primary tumors size and extrathyroidal extension,number and range of primary tumor lesions,lymph node metastases in surgery,status of thyroid remnant in 99TcmO4-imaging,pre-treatment laboratory measurements (TSH,sTg and TgAb),131I therapeutic dose,results of Rx-WBS and SPECT after 131I therapy,were analyzed with univariate and multivariate logistic regression.ROC curve and diagnostic critical point were analyzed to evaluate the predictive value of influential factors for the outcome of 131I therapy.Results The cure rate of the first 131I therapy was 64.2％ (102/159).Univariate logistic regression analysis showed that age,gender,lymph node metastases,sTg and 131I therapeutic dose (all P＜0.01) were the influential factors for the outcome of 131I therapy.Multivariate logistic regression analysis showed that lymph node metastases (regression coefficient:1.118) and sTg (regression coefficient:0.314) were influential factors (both P＜0.05).The regression equation was:Logit P =-4.155+ 1.118×lymph node metastases+0.314×sTg (x2 =93.7,P＜0.001).Taking sTg as a predictive factor for the outcome of 131I therapy,the AUC of ROC curve was 0.926 (95％ CI:0.888-0.963).The cut-off value of sTg was 2.97 μg/L with a sensitivity of 94.7％ (54/57) and a specificity of 76.5％ (78/102).Conclusions PTC patients with low sTg levels and few lymph node metastases after total thyroidectomy are more likely to be cured in the first 131I therapy.