ObjectiveTo investigate the application of central auditory testing combined with electroencephalographic features in the early screening of mild cognitive impairment due to Alzheimer's disease. MethodsA convenience sampling method was used to conduct a field survey in the Qixia District of Nanjing City, Jiangsu Province, from July to September, 2025. A total of 40 older adults diagnosed as mild cognitive impairment due to Alzheimer's disease and 23 cognitively normal older adults were recruited. Auditory N-back and dichotic listening paradigms were employed for assessment, while the scores of Montreal Cognitive Assessment Beijing Version (MoCA-BJ) and 32-channel electroencephalogram (EEG) data were simultaneously collected. Binary logistic regression analysis was applied to identify predictive indicators, receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated. ResultsThe total score of dichotic listening was positively correlated with overall cognitive function (r = 0.475, P < 0.01), while right-ear advantage showed negative correlations with overall cognition, visuospatial ability, abstract reasoning, and delayed recall (r < -0.276, P < 0.05). Task performance across all conditions of the N-back task was positively correlated with overall cognitive function (r > 0.249, P < 0.05). Regarding EEG features, δ and θ band power and power peaks were positively correlated with delayed recall (r > 0.258, P < 0.05), whereas (α+θ)/(α+β) and θ/(α+β) were positively correlated with naming ability and visuospatial executive function, respectively (r > 0.261, P < 0.05). The results of the binary logistic regression analysis showed that the total score of binaural dichotic listening, the accuracy of 1-back task, the average power of δ waves, and the ratio of θ/(α+β) were independent influencing factors for mild cognitive impairment due to Alzheimer's disease (P < 0.05). The ROC analysis indicated that the AUC for auditory task performance and EEG features were 0.845 and 0.735 respectively, and when combined, the AUC increased to 0.862. ConclusionThe screening model based on the integration of auditory task performance and EEG features can be used in the early identification of mild cognitive impairment due to Alzheimer's disease.

Objective To explore the quantitative electroencephalography(qEEG)characteristics of the prefrontal cortex in patients with mild cognitive impairment(MCI)during digital screening tasks for MCI screening.Methods A total of 592 MCI patients(MCI group)and 317 normal cognitively elderly individuals(control group)were recruited from 40 communities in Nanjing,Jiangsu Province,from July to August,2024.All participants were as-sessed using Montreal Cognitive Assessment-Beijing Version(MoCA-BJ).Prefrontal EEG data were collected using a portable EEG device,and power spectral analysis was performed via Fast Fourier Transform.An XG-Boost algorithm was employed to construct an MCI identification model based on qEEG power features,and the model's performance was evaluated using receiver operating characteristic(ROC)curve.Results Compared with the control group,prefrontal δ,α,and β band power increased during screening tasks in MCI group(P<0.05);δ power was negatively correlated with MoCA-BJ total scores,and visuospatial/executive func-tion,attention and delayed recall scores(r=-0.269,-0.169,-0.133,-0.171,P<0.001);α power was negative-ly correlated with MoCA-BJ total scores,attention and delayed recall scores(r=-0.113,-0.075,-0.091,P<0.05).The XGBoost model based on δ and α power was excellent in MCI identification,with an area under the curve of 0.91,accuracy of 0.81,precision of 0.89,F1 score of 0.84,recall of 0.80,and specificity of 0.81.Conclusion MCI patients exhibit increased power in the prefrontal δ and α frequency bands during digital screening tasks,which is associated with cognitive decline.An XGBoost model based on qEEG power features can enable early prediction of MCI.

Objective To explore the quantitative electroencephalography(qEEG)characteristics of the prefrontal cortex in patients with mild cognitive impairment(MCI)during digital screening tasks for MCI screening.Methods A total of 592 MCI patients(MCI group)and 317 normal cognitively elderly individuals(control group)were recruited from 40 communities in Nanjing,Jiangsu Province,from July to August,2024.All participants were as-sessed using Montreal Cognitive Assessment-Beijing Version(MoCA-BJ).Prefrontal EEG data were collected using a portable EEG device,and power spectral analysis was performed via Fast Fourier Transform.An XG-Boost algorithm was employed to construct an MCI identification model based on qEEG power features,and the model's performance was evaluated using receiver operating characteristic(ROC)curve.Results Compared with the control group,prefrontal δ,α,and β band power increased during screening tasks in MCI group(P<0.05);δ power was negatively correlated with MoCA-BJ total scores,and visuospatial/executive func-tion,attention and delayed recall scores(r=-0.269,-0.169,-0.133,-0.171,P<0.001);α power was negative-ly correlated with MoCA-BJ total scores,attention and delayed recall scores(r=-0.113,-0.075,-0.091,P<0.05).The XGBoost model based on δ and α power was excellent in MCI identification,with an area under the curve of 0.91,accuracy of 0.81,precision of 0.89,F1 score of 0.84,recall of 0.80,and specificity of 0.81.Conclusion MCI patients exhibit increased power in the prefrontal δ and α frequency bands during digital screening tasks,which is associated with cognitive decline.An XGBoost model based on qEEG power features can enable early prediction of MCI.

Bone metastasis-caused pain （BMP） is a common complication of cancer， and the incidence has been on the rise with the increase in the overall prevalence of cancer， threatening the survival and quality of life of patients. BMP is a kind of special pain with the characteristics of inflammatory pain and neuropathic pain， but is different from the two. Therefore， its pathogenesis is very complicated， and it is of great significance to understand the pathogenesis. The currently available studies mainly focused on osteoclast activation， changes in the bone microenvironment， glial cell activation， spinal cord neuron activation， and miRNA dysregulation. Modern therapies include the three-step analgesics， bisphosphonates， palliative radiotherapy， and interventional therapy for bone metastases， which show definite efficacy in short term. However， the long-term effect is unsatisfactory due to the adverse reactions， addiction， and drug resistance. Studies have shown that traditional Chinese medicine （TCM） has definite curative effect on BMP， which is safe， enhances efficacy， reduces toxicity， and boosts immunity. Moreover， it exerts the effect through multiple components， multiple targets， and multiple pathways. As a result， it has unique advantages in the prevention and treatment of BMP and has become a research focus. This paper summarizes the research on the pathogenesis of BMP， the intervention of TCM （compound Chinese medicine prescriptions， Chinese medicinals， and monomers from Chinese medicinals）， and the mechanisms of TCM， such as inhibiting osteoclast activation， glial cell activation， and spinal cord neuron activation， regulating pain mediators and abnormal expression of microRNA， and anti-tumor， which is expected to further clarify the pathogenesis of BMP and provide ideas and methods for the effective prevention and treatment of BMP with TCM.

Objective:To explore the effect of case-based learning (CBL) guided by ICF (International Classification of Functioning, Disability and Health) in rehabilitation practice teaching.Methods:Fifty-eight rehabilitation undergraduates who had practiced in the Department of Rehabilitation Medicine in The First Affiliated Hospital of Chongqing Medical University from February 2019 to December 2019 were randomized into observation group and control group. The observation group adopted ICF-guided CBL method for practice teaching, while the control group adopted traditional teaching methods. At the end of the internship, all the students were assessed in terms of their theoretical knowledge, case analysis and clinical practice ability. At the same time, questionnaires were used to conduct a satisfaction survey on the teaching method, and the results of the two groups were compared and analyzed by ttest and rank-sum test through SPSS 25.0. Results:The scores of the observation group were higher than those of the control group, with statistical significance ( P<0.05) . In the satisfaction survey, the observation group was superior to the traditional teaching method in terms of self-thinking ability and learning initiative, with statistical significance ( P<0.05). Conclusion:ICF-guided CBL method can strengthen students' independent thinking ability and learning initiative, and improve the students' clinical comprehensive ability of rehabilitation treatment.

Objective:To explore the current status of clinical teaching staff for the graduate program of master of nursing specialist (abbreviated to nursing masters) in traditional Chinese medicine (TCM) universities and compare it with the role expectations of students, aiming to provide a reference for the subsequent construction and improvement of clinical teaching staff.Methods:Totally 172 nursing masters from Jiangsu, Zhejiang, Henan provinces and Tianjin and 86 clinical teaching staff from the hospitals where they practiced were selected using convenient samping and investigated with the self-made questionnaire from October to December 2018. The differences between clinical teaching staff's resources, abilities and students' expectations were compared. A total of 258 questionnaires were distributed among 86 clinical teachers and 172 nursing masters, and 258 valid questionnaires were recovered, with an effective rate of 100%. SPSS 22.0 software was used for statistical analysis of data.Results:There was a certain gap between the clinical teaching staff and students' expectations, especially in terms of the graduate school and academic qualifications of the clinical teachers. Totally 34.88% (30/86) of the clinical teachers graduated from TCM universities, while 71.51% (123/172) of the students expected to be taught by teachers graduating from TCM universities. Among the clinical teachers, 60.47% (52/86) were undergraduates, and fewer were masters or graduates with higher education. There was a certain difference between the teaching teachers' abilities and students' expectations. There were statistically significant differences in 17 secondary indicators (χ 2 were 12.027-130.149, P<0.05) , except for the professional attitude in clinical nursing abilities, decision-making abilities in clinical management abilities, communication abilities in interpersonal abilities, and collaboration abilities ( P>0.05) . There were statistically significant differences between students' current status and their learning needs for TCM nursing (χ 2 were 14.722-165.339, P<0.01) . TCM nursing skills and practical application of TCM nursing research were the contents that most students wanted to learn, accounting for 83.72% (144/172) and 70.35% (151/172) , respectively. Conclusions:There were differences between the current status of the teaching staff for nursing masters at TCM universities and the expectations of the students. The universities should fully consider the graduates' own expectations and needs based on the training objectives for graduates, actively explore the admission system for clinical teachers, improve the training system for teachers, and standardize the teaching evaluation mechanism based on the status quo of nursing talents in China.

Traditional Chinese medicine (TCM) nursing is an important part in the nursing discipline which plays an important role in prevention, health care and nursing rehabilitation. It is imperative to strengthen the cultivation of health service ability of TCM for nurses. However, the expert consensus on the training standard of core knowledge and practical ability of TCM nursing has not been formed so far. On the basis of establishing a research group, a questionnaire was formed based on literature research, university research, brain storm and expert interviews. A total of 76 TCM nursing experts from universities and hospitals at home and abroad of TCM were investigated with the questionnaire to form an expert consensus. Finally, the training standard of core knowledge and practical ability of TCM nursing was established, including three course modules of basic courses of TCM, basic courses of TCM nursing, and specialized courses of TCM nursing, and 9 courses of basic theory of TCM, diagnosis of TCM, science of Chinese materia medica, pharmacology of TCM, fundamental of TCM nursing, TCM diet therapy, acupuncture and moxibustion and nursing, TCM nursing skill operation, TCM nursing clinical practice so as to provide a reference for the training of nursing talents of TCM at home and abroad.

Objective To define the traditional Chinese medicine (TCM) nursing core knowledge and practical ability which nurses should be equipped with when carrying out TCM service so as to provide a reference for the training of nursing talents of TCM at home and abroad. MethodsOn the basis of establishing a research group, a questionnaire was formed based on literature research, university research, brain storm and expert interviews. A total of 76 TCM nursing experts from universities and hospitals at home and abroad of TCM were investigated with the questionnaire to form an expert consensus. ResultsA total of 76 questionnaires were issued in this survey, of which 64 were valid.This study formed the core knowledge and practical ability training standard including three course modules of basic courses of TCM, basic courses of TCM nursing and specialized courses of TCM nursing, and 9 courses of basic theory of TCM, diagnosis of TCM, science of Chinese materia medica, pharmacology of TCM, fundamental of TCM nursing, TCM diet therapy, acupuncture and moxibustion and nursing, TCM nursing skill operation, TCM nursing clinical practice. ConclusionsThe standard could provide a basis for the standardized teaching of TCM nursing, establishment of training module, formulation of training plan and evaluation of talent training quality.

OBJECTIVE： To establish antibiotics use rationality evaluation model in type Ⅰ incision surgery patients， and to provide reference for prescription review of clinical pharmacists. METHODS： Totally 432 inpatients underwent type Ⅰ surgical incision in a hospital from Jan. 1st- Dec. 31st， 2017 were selected as the research objects. The information of diagnosis and treatment including age， nosocomial infection， the number of kinds of antibiotics used were extracted. Based on the results of clinical pharmacists’ comments on the antibiotics use rationality in patients’ prevention and treatment， non-conditional Logistic regression and support vector machine （SVM） in machine learning method were used to convert clinical pharmacists’ comments into objective index that can be recognized by the machine learning model， using categories of antibiotics （preventive or therapeutic use） as dependent variables and the patient’s diagnosis and treatment information as independent variables. Classification and identification model was established for antibiotics use rationality in type Ⅰ incision surgery patients. Using sensitivity， specificity and Youden index as indexes， established mode was validated on the other 61 samples of type Ⅰ incision surgery patients. The rationality of antibiotics prescriptions in type Ⅰ incision surgery patients before （by manual review， Jan.-Dec. 2017） and after （Jan.-Oct. 2018） using the model were collected， and the effects of the model were evaluated. RESULTS： The sensitivity， specificity and Youden index of non-conditional Logistic regression model were 65.63％， 75.00％ and 40.63％， respectively. Main parameters of the model established by SVM included gamma 0.01， cost 10， sensitivity 92.19％， specificity 87.50％， Youden index 79.69％. The model established by SVM was better than non-conditional Logistic regression. SVM was used to validate established mode， and sensitivity， specificity and Youden index were 100％， 88.57％ and 88.57％， respectively. Compared with before using the model， the evaluation ratio increased from 69.44％ to 100％， the rate of prophylactic use of antibiotics decreased from 23.84％ to 16.43％， the rate of rational drug type selection increased from 37.86％ to 54.39％， and treatment course shortened from 5.01 days to 3.26 days after using the model. CONCLUSIONS： Established antibiotics use rationality evaluation model in typeⅠincision surgery patients by SVM in machine learning method fully covers all the patients， promotes rational use of antibiotics in typeⅠincision surgery patients， and provides a new idea for pharmacist prescription comment.

Objective To construct a grading nursing care system at public hospitals based on the severity of illness and activities of daily living ( ADL). Methods Multi-center stratified random sampling was used to investigate the general adult patients hospitalized in 12 wards of six tertiary-level hospitals in the eastern, central and western parts of China from January to December of 2016. The Barthel index and simple clinical score ( SCS) were used to evaluate their ADL and severity of illness, while a customized direct nursing hour scale was applied to record the direct nursing time needed by patients in 24 hours. Nursing grades were defined according to different conditions and ADL and to the difference of patient needs of 24 h direct nursing hours. Results 7 200 patients were investigated in total, and 7 073 effective questionnaires were collected (98. 24% ). Seven new grades of nursing care were defined based on patients′ severity of illness, ADL and different 24 h direct nursing time. These grades match the existing four grading nursing care levels to become refined sub-levels. Conclusions Patients can be graded according to their conditions, ADL and the 24 h direct nursing time needed. Such a new method is more objective, specific and quantitative than before, conducive to upgrading fine management level of nursing.