ObjectiveTo develop a community-family management model for older adults with mild cognitive impairment (MCI) and to formulate detailed application specifications, and to fully leverage the initiative of communities and families under limited resource conditions, for achieving community-based early detection and early intervention for older adults with MCI. MethodsA systematic literature review was conducted to identify pertinent publications. Corpus-based research methodologies were employed to extract, refine, integrate and synthesize management elements, thereby establishing the specific content and service processes for each stage of the management model. Utilizing the 5W2H analytical framework, essential elements such as management stakeholders, target populations, content and methods for each stage were delineated. The model and its application guidelines were finalized through expert consultation and demonstration. ResultsAn expert evaluation of the management model yielded mean scores of 4.84, 4.32 and 4.84 for acceptability, feasibility and systematicity, respectively. By integrating the identified core elements with expert ratings and feedback, the final iteration of the community-family management model for older adults with MCI was formulated. This model comprised of five stages: screening and identification, comprehensive assessment, intervention planning, monitoring and referral pathways to ensure implementation, and enhanced support for communities, family members and caregivers. Additionally, it included 18 specific application guidelines. ConclusionThe proposed management model may theoretically help delay cognitive decline, improve cognitive function and potentially promote reversal from MCI to normal cognition. It may also enhance the awareness and coping capacity of older adults and their families, strengthen community healthcare professionals' ability to early identify and manage MCI.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.

Objective:To analyze postictal electroencephalographic(EEG) characteristics of patients with status epilepticus (SE) based on the score of grand total electroencephalography (GTE), and explore the relationship between electroencephalographic characteristics of SE and clinical prognosis.Methods:A total of 110 SE patients were enrolled in the Department of Neurology, the Affiliated Hospital of Yangzhou University from September 1, 2021 to September 1, 2023. EEG and GTE scores were performed in all patients after seizures (0-2 days after the cessation of SE). After one year of discharge, the medication and seizure status of patients were followed up by phone or outpatient visits. The seizure outcomes were recorded according to the international league against epilepsy (ILAE) seizure outcome classification, with favorable outcomes defined as good prognosis group ( n=54) and unfavorable outcomes defined as poor prognosis group ( n=56). SPSS 27.0 software was used for statistical analysis. Binary Logistic regression analysis was employed to screen impact variables of prognosis. The receiver operating characteristic(ROC) curve was plotted to determine the optimal cut-off point for predicting prognosis in epilepsy. Results:There were statistically significant differences in the total GTE score(2(1, 4), 8(5, 10); Z=-6.837, P<0.001), diffuse slow activity(0(0, 1), 2(0, 2); Z=-6.495, P<0.001), reactivity of the rhythmic background activity(0(0, 0), 0(0, 1); Z=-2.705, P=0.007), paroxysmal activity(0(0, 0), 1.5(0, 3.0); Z=-4.420, P<0.001), focal disturbances(0(0, 0), 0(0, 0); Z=-2.130, P=0.033), and sharp wave activity(0(0, 2), 2(2, 3); Z=-5.714, P<0.001)between the good prognosis group and poor prognosis group. The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity and total GTE score (all P<0.05). The differences in EEG results between SE patients with clear and unknown causes were statistically significant in terms of paroxysmal activity and focal disturbances(both P<0.05). The results of binary Logistic regression analysis showed that independent factors associated with the prognosis of SE included medication adherence ( B=-0.496, OR=0.609, 95% CI=0.395-0.940, P=0.025), diffuse slow activity( B=1.580, OR=4.854, 95% CI=1.586-14.855, P=0.006), sharp wave activity( B=0.824, OR=2.280, 95% CI=1.210-4.297, P=0.011), and total GTE score ( B=0.561, OR=1.753, 95% CI=1.360-2.259, P<0.001). In evaluating the prognosis of SE, the GTE score had a certain sensitivity (74.6%) and specificity (85.1%), with a optimal cut-off point of 6. Conclusions:The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity. The appearance of diffuse slow activity and sharp wave activity in the electroencephalogram of SE patients indicates poor prognosis, and the total GTE score≥6 may be a strong predictor of poor prognosis. However, good medication adherence is a protective factor for epilepsy recurrence.

Objective:To analyze postictal electroencephalographic(EEG) characteristics of patients with status epilepticus (SE) based on the score of grand total electroencephalography (GTE), and explore the relationship between electroencephalographic characteristics of SE and clinical prognosis.Methods:A total of 110 SE patients were enrolled in the Department of Neurology, the Affiliated Hospital of Yangzhou University from September 1, 2021 to September 1, 2023. EEG and GTE scores were performed in all patients after seizures (0-2 days after the cessation of SE). After one year of discharge, the medication and seizure status of patients were followed up by phone or outpatient visits. The seizure outcomes were recorded according to the international league against epilepsy (ILAE) seizure outcome classification, with favorable outcomes defined as good prognosis group ( n=54) and unfavorable outcomes defined as poor prognosis group ( n=56). SPSS 27.0 software was used for statistical analysis. Binary Logistic regression analysis was employed to screen impact variables of prognosis. The receiver operating characteristic(ROC) curve was plotted to determine the optimal cut-off point for predicting prognosis in epilepsy. Results:There were statistically significant differences in the total GTE score(2(1, 4), 8(5, 10); Z=-6.837, P<0.001), diffuse slow activity(0(0, 1), 2(0, 2); Z=-6.495, P<0.001), reactivity of the rhythmic background activity(0(0, 0), 0(0, 1); Z=-2.705, P=0.007), paroxysmal activity(0(0, 0), 1.5(0, 3.0); Z=-4.420, P<0.001), focal disturbances(0(0, 0), 0(0, 0); Z=-2.130, P=0.033), and sharp wave activity(0(0, 2), 2(2, 3); Z=-5.714, P<0.001)between the good prognosis group and poor prognosis group. The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity and total GTE score (all P<0.05). The differences in EEG results between SE patients with clear and unknown causes were statistically significant in terms of paroxysmal activity and focal disturbances(both P<0.05). The results of binary Logistic regression analysis showed that independent factors associated with the prognosis of SE included medication adherence ( B=-0.496, OR=0.609, 95% CI=0.395-0.940, P=0.025), diffuse slow activity( B=1.580, OR=4.854, 95% CI=1.586-14.855, P=0.006), sharp wave activity( B=0.824, OR=2.280, 95% CI=1.210-4.297, P=0.011), and total GTE score ( B=0.561, OR=1.753, 95% CI=1.360-2.259, P<0.001). In evaluating the prognosis of SE, the GTE score had a certain sensitivity (74.6%) and specificity (85.1%), with a optimal cut-off point of 6. Conclusions:The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity. The appearance of diffuse slow activity and sharp wave activity in the electroencephalogram of SE patients indicates poor prognosis, and the total GTE score≥6 may be a strong predictor of poor prognosis. However, good medication adherence is a protective factor for epilepsy recurrence.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.

Objective:To investigate the association between cognitive impairment and manifestation of interictal electroencephalogram (EEG) in epilepsy patients, and the early assessment significance of the Grand Total Electroencephalography (GTE) score.Methods:A totall of 100 patients with primary epilepsy admitted to the Department of Neurology of the Affiliated Hospital of Yangzhou University were continuously collected from January 2019 to January 2024, and they were classified according to the latest version of the epilepsy classification by the International League Against Epilepsy in 2017. General information of all research subjects was recorded, including age, gender, educational level, etc. The disease details of epilepsy patients were recorded, including seizure duration, severity, seizure precursors, post seizure status, and use of anti-seizure medications (ASM). The survey scales and questionnaires used included the interictal GTE, Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale, Hamilton Depression Scale, National Hospital Seizure Severity Scale (NHS3), Status Epilepticus Severity Score (STESS). All research subjects were classified into normal cognitive (NC) group, mild cognitive impairment (MCI) group, and dementia group according to MoCA score. Comparisons among multiple groups and pairwise comparisons were conducted. The correlation between 2 variables was analyzed using Spearman rank correlation analysis, and multiple linear regression analysis was employed to screen variables that have an impact on cognitive impairment. The receiver operating characteristic curve was plotted to determine the optimal cut-off point for predicting cognitive impairment in epilepsy.Results:According to the MoCA score, there were 32 (32%) patients in the NC group, 49 (49%) patients in the MCI group, and 19 (19%) patients in the dementia group. There were statistically significant differences in age [(26.31±10.01) years, (43.96±16.19) years, (57.68±16.83) years,respectively; F=29.440, P<0.001], education ( χ2=28.894, P<0.001), ASM ( χ2=11.258, P<0.017), STESS score [2.00(1.75, 2.25), 2.00(2.00, 3.00), 3.50(2.75, 4.25),respectively; H=12.646, P=0.002], STESS score>2 ( χ2=10.075, P=0.006), frequency of rhythmic background activity ( H=17.429, P<0.001), diffuse slow activity ( H=42.033, P<0.001), reactivity of the rhythmic background activity ( H=15.206, P<0.001), paroxysmal activity ( H=25.279, P<0.001), sharp wave activity ( H=15.492, P<0.001) and total GTE score [1 (1, 3), 6 (2, 8), 8 (7, 11),respectively; H=47.871, P<0.001] among the 3 groups. A significant negative correlation was observed between cognitive level (MoCA scores) and total GTE score ( ρ=-0.766, P<0.001), frequency of rhythmic background activity ( ρ=-0.520, P<0.001), diffuse slow activity ( ρ=-0.734, P<0.001), reactivity of the rhythmic background activity ( ρ=-0.438, P<0.001), paroxysmal activity ( ρ=-0.566, P<0.001), and sharp wave activity ( ρ=-0.407, P<0.001). The results of multiple linear regression analysis indicated that total GTE score ( t=-5.566, P<0.001), diffuse slow activity ( t=-2.548, P=0.014), reactivity of the rhythmic background activity ( t=-3.891, P<0.001), paroxysmal activity ( t=-3.139, P=0.003), age ( t=-5.493, P<0.001), education ( t=3.379, P=0.001), and STESS ( t=-2.183, P=0.033) were independent risk factors for cognitive impairment. In evaluating the cognitive impairment of epilepsy patients, the GTE score had a certain sensitivity (75.0%) and specificity (93.8%), with an optimal critical point value of 5. Conclusions:The interictal EEG of patients with poorer cognitive function is mainly characterized by an increase in slow waves and a decrease in overall background. The increase in slow waves, poor background responsiveness, paroxysmal activity and a high total GTE score may be important factors in predicting the outcome of cognitive impairment in epilepsy.

Objective:To investigate the association between cognitive impairment and manifestation of interictal electroencephalogram (EEG) in epilepsy patients, and the early assessment significance of the Grand Total Electroencephalography (GTE) score.Methods:A totall of 100 patients with primary epilepsy admitted to the Department of Neurology of the Affiliated Hospital of Yangzhou University were continuously collected from January 2019 to January 2024, and they were classified according to the latest version of the epilepsy classification by the International League Against Epilepsy in 2017. General information of all research subjects was recorded, including age, gender, educational level, etc. The disease details of epilepsy patients were recorded, including seizure duration, severity, seizure precursors, post seizure status, and use of anti-seizure medications (ASM). The survey scales and questionnaires used included the interictal GTE, Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale, Hamilton Depression Scale, National Hospital Seizure Severity Scale (NHS3), Status Epilepticus Severity Score (STESS). All research subjects were classified into normal cognitive (NC) group, mild cognitive impairment (MCI) group, and dementia group according to MoCA score. Comparisons among multiple groups and pairwise comparisons were conducted. The correlation between 2 variables was analyzed using Spearman rank correlation analysis, and multiple linear regression analysis was employed to screen variables that have an impact on cognitive impairment. The receiver operating characteristic curve was plotted to determine the optimal cut-off point for predicting cognitive impairment in epilepsy.Results:According to the MoCA score, there were 32 (32%) patients in the NC group, 49 (49%) patients in the MCI group, and 19 (19%) patients in the dementia group. There were statistically significant differences in age [(26.31±10.01) years, (43.96±16.19) years, (57.68±16.83) years,respectively; F=29.440, P<0.001], education ( χ2=28.894, P<0.001), ASM ( χ2=11.258, P<0.017), STESS score [2.00(1.75, 2.25), 2.00(2.00, 3.00), 3.50(2.75, 4.25),respectively; H=12.646, P=0.002], STESS score>2 ( χ2=10.075, P=0.006), frequency of rhythmic background activity ( H=17.429, P<0.001), diffuse slow activity ( H=42.033, P<0.001), reactivity of the rhythmic background activity ( H=15.206, P<0.001), paroxysmal activity ( H=25.279, P<0.001), sharp wave activity ( H=15.492, P<0.001) and total GTE score [1 (1, 3), 6 (2, 8), 8 (7, 11),respectively; H=47.871, P<0.001] among the 3 groups. A significant negative correlation was observed between cognitive level (MoCA scores) and total GTE score ( ρ=-0.766, P<0.001), frequency of rhythmic background activity ( ρ=-0.520, P<0.001), diffuse slow activity ( ρ=-0.734, P<0.001), reactivity of the rhythmic background activity ( ρ=-0.438, P<0.001), paroxysmal activity ( ρ=-0.566, P<0.001), and sharp wave activity ( ρ=-0.407, P<0.001). The results of multiple linear regression analysis indicated that total GTE score ( t=-5.566, P<0.001), diffuse slow activity ( t=-2.548, P=0.014), reactivity of the rhythmic background activity ( t=-3.891, P<0.001), paroxysmal activity ( t=-3.139, P=0.003), age ( t=-5.493, P<0.001), education ( t=3.379, P=0.001), and STESS ( t=-2.183, P=0.033) were independent risk factors for cognitive impairment. In evaluating the cognitive impairment of epilepsy patients, the GTE score had a certain sensitivity (75.0%) and specificity (93.8%), with an optimal critical point value of 5. Conclusions:The interictal EEG of patients with poorer cognitive function is mainly characterized by an increase in slow waves and a decrease in overall background. The increase in slow waves, poor background responsiveness, paroxysmal activity and a high total GTE score may be important factors in predicting the outcome of cognitive impairment in epilepsy.

Chinese materia medica and its compound formulas have the characteristics of multi-component,multi-target,and multi pathway effects,and have unique advantages in preventing and treating complex diseases.Network pharmacology explains disease patterns and drug mechanisms from the perspective of complex biological networks,and explores the pharmacological substance basis and target of Chinese medicine.This article summarized the application of network pharmacology from the aspects of biological basis of TCM syndrome,the substance basis and pharmacological mechanism of TCM,compatibility theory of TCM compound formulas,etc.,with the purpose to provide a reference for the research and application of network pharmacology in TCM.

Primary sclerosing cholangitis(PSC)is a cholestatic disease characterized by chronic progressive bile duct inflammation and has a low incidence rate and poor prognosis in China.There is still no drug therapy that can change the course of PSC,and liver transplantation is the only effective treatment for PSC,with a 5-year survival rate of 85%after transplantation.Drug therapy for PSC is facing great challenges based on the current status of PSC.At present,drugs for the treatment of PSC are in the stage of clinical trials and have shown certain application prospect,among which ursodeoxycholic acid is the most widely studied and commonly used drug.In addition,there are many emerging drugs in the pipeline.This article summarizes the latest advances in drug therapy for PSC.

Objective To quantitatively analyze and evaluate the content of rehabilitation policy for people with disabilities in China. Methods This study focused on ten national policies of disability rehabilitation issued from 2021 to 2023.It employed text mining techniques to process policy texts and constructed a policy modeling consistency index model for dis-ability rehabilitation policies in China.The relevant policies were evaluated and analyzed quantitatively. Results The disability rehabilitation policies in China were relatively comprehensive in terms of policy transparency,op-erational mechanisms and policy nature.However,there was still a need for optimization in terms of policy per-spectives,target groups,incentive mechanisms,and other aspects. Conclusion The overall quality of disability rehabilitation policy texts at the national level in China is relatively good.There is a need to further enhance the predictability of policy objectives,clarify the responsibilities and division of labor among various departments,and improve policy incentive mechanisms in future policy formulation,which will further refine China's disability rehabilitation policy system and contribute to high-quality develop-ment of the disability cause.