Objective:The level of discipline construction is an important indicator of a hospital′s comprehensive strength and core competitiveness.Establishing a scientific, reasonable, and effective performance evaluation system for the clinical medicine advantageous disciplines is of particular significance for university affiliated hospitals to strengthen discipline construction, improve governance systems, and promote high-quality development of hospitals.Methods:The Delphi method was used to determine the reliability of the indicator system by measuring the positivity coefficient, authority level, coefficient of variation, and coordination coefficient.Using Analytic Hierarchy Process, judgment matrix was established to determine the corresponding weights of elements, and calculate the total weight coefficients of each indicator, as well the consistency of the judgment matrix was checked.Results:The Cronbach′s coefficient of the questionnaire was 0.945, indicating high reliability.The effective recovery rates of the two rounds of expert consultation were 90.0%and 94.7%.Two rounds′ expert authority coefficients were 0.743 and 0.720.And the Kendall harmony coefficient was 0.196~0.731. The differences mentioned above were statistically significant(all P<0.05).Through two rounds consultation, a performance evaluation system for the clinical medicine advantageous disciplines was constructed, including 8 primary indicators and 24 secondary indicators.The weight coefficients of the primary indicators were 0.126, 0.208, 0.091, 0.162, 0.178, 0.118, 0.068, 0.049, and the total weight coefficients of each indicator were calculated, which showed good logical reliability. Conclusions:The performance evaluation system for the clinical medicine advantageous disciplines has strong scientific validity.It can provide evaluation tools for promoting the rational allocation and efficient utilization of hospital resources.

Objective:To explore the clinical symptoms, imaging characteristics, cerebrospinal fluid (CSF) features, as well as the treatment and prognosis of autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy.Methods:Sixty-one patients with anti-GFAP astrocyte antibody (GFAP-IgG) single-positive autoimmune encephalitis who were treated at the Third Affiliated Hospital, Sun Yat-sen University between January 2017 and September 2023 were retrospectively collected. The demographic characteristics (age at onset, sex), clinical symptoms (core symptoms, neurological deficits, psychiatric behavioral abnormalities, and autonomic dysfunction), imaging features [brain/spinal cord/optic nerve magnetic resonance imaging (MRI) lesion distribution and enhancement patterns], and CSF parameters were analyzed. Acute-phase treatments, including methylprednisolone pulse therapy, intravenous immunoglobulin (IVIG), etc, along with the follow-up outcomes [modified Rankin Scale (mRS) score] were recorded.Results:The onset age was 40 (30, 55) years, and 68.9% (42/61) of the patients were male. The most common clinical manifestations were fever (65.6%, 40/61), headache (60.7%, 37/61), and urinary/defecatory abnormalities (45.9%, 28/61). Brain MRI revealed lesions predominantly in the cerebral cortex and subcortical white matter (57.4%, 35/61), periventricular white matter (50.8%, 31/61), and basal ganglia (36.1%, 22/61). Periventricular linear-radiating enhancement was the predominant MRI enhancement pattern (55.7%, 34/61). Spinal MRI showed lesions mainly in the cervical (42.6%, 26/61) and thoracic spinal cord (32.8%, 30/61), with leptomeningeal enhancement (31.1%, 19/61) and scattered punctate/patchy enhancements (21.3%, 13/61). Optic neuropathy was observed in 6 cases (9.8%). CSF analysis demonstrated a pressure of 180 (133, 240) mmH 2O (1 mmH 2O=0.009 8 kPa), white blood cell count of 29 (4, 156)×10?/L, and protein level of 0.72 (0.40, 1.44) g/L. Nineteen patients (31.1%) experienced rapid progression of meningoencephalitis or myelitis within 3 days of admission. All patients received methylprednisolone pulse therapy, with 47.5% (29/61) additionally treated with IVIG. At a follow-up of 12 (3, 28) months, 12 cases (19.7%) relapsed, and 75.4% (46/61) had favorable outcomes (mRS score 0-2). Poor prognosis (mRS score>2) was observed in 4 cases, including 3 with cervical spinal cord involvement and status epilepticus, 1 elderly patient with lung cancer. Conclusions:GFAP astrocytopathy predominantly affects young adults, with a male predominance. Spinal cord involvement is common, manifesting as myelitis and myelopathy. Rapid progression of meningoencephalitis or myelitis may occur early in the disease course. Periventricular linear-radiating enhancement on brain MRI is a key diagnostic clue. Leukocyte and protein levels in the cerebrospinal fluid are generally mildly to moderately elevated. Most patients respond well to corticosteroids and immunotherapy, with favorable outcomes. However, advanced age and cervical spinal cord involvement are associated with poor prognosis.

This paper reviews the published articles of recent years on the application of deep learning methods in automatic localization of acupoint, and summarizes it from 3 key links, i.e. the dataset construction, the neural network model design, and the accuracy evaluation of acupoint localization. The significant progress has been obtained in the field of deep learning for acupoint localization, but the scale of acupoint detection needs to be expanded and the precision, the generalization ability, and the real-time performance of the model be advanced. The future research should focus on the support of standardized datasets, and the integration of 3D modeling and multimodal data fusion, so as to increase the accuracy and strengthen the personalization of acupoint localization.
Deep Learning ; Acupuncture Points ; Humans ; Neural Networks, Computer

Adverse drug reactions (ADRs) significantly impact clinical medication safety. The timely identification and prediction of ADRs rely on the efficient analysis of real-world data, such as electronic health records, social media, and spontaneous reporting databases. In recent years, the rapid advancement of artificial intelligence, particularly large language models, in natural language processing, causal reasoning, and complex data mining has provided new technological means for real-time ADRs monitoring and individualized prediction. This paper summarizes the latest research achievements in AI-driven ADRs monitoring. Focusing on diverse data sources, including structured databases and electronic health records, it elaborates on the advantages andchallenges of AI in ADRs event extraction, relationship identification, causal analysis, and risk prediction. The aim is to provide a theoretical reference for constructing more intelligent and efficient ADRs monitoring systems.

Objective:The level of discipline construction is an important indicator of a hospital′s comprehensive strength and core competitiveness.Establishing a scientific, reasonable, and effective performance evaluation system for the clinical medicine advantageous disciplines is of particular significance for university affiliated hospitals to strengthen discipline construction, improve governance systems, and promote high-quality development of hospitals.Methods:The Delphi method was used to determine the reliability of the indicator system by measuring the positivity coefficient, authority level, coefficient of variation, and coordination coefficient.Using Analytic Hierarchy Process, judgment matrix was established to determine the corresponding weights of elements, and calculate the total weight coefficients of each indicator, as well the consistency of the judgment matrix was checked.Results:The Cronbach′s coefficient of the questionnaire was 0.945, indicating high reliability.The effective recovery rates of the two rounds of expert consultation were 90.0%and 94.7%.Two rounds′ expert authority coefficients were 0.743 and 0.720.And the Kendall harmony coefficient was 0.196~0.731. The differences mentioned above were statistically significant(all P<0.05).Through two rounds consultation, a performance evaluation system for the clinical medicine advantageous disciplines was constructed, including 8 primary indicators and 24 secondary indicators.The weight coefficients of the primary indicators were 0.126, 0.208, 0.091, 0.162, 0.178, 0.118, 0.068, 0.049, and the total weight coefficients of each indicator were calculated, which showed good logical reliability. Conclusions:The performance evaluation system for the clinical medicine advantageous disciplines has strong scientific validity.It can provide evaluation tools for promoting the rational allocation and efficient utilization of hospital resources.

Objective:To explore the clinical symptoms, imaging characteristics, cerebrospinal fluid (CSF) features, as well as the treatment and prognosis of autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy.Methods:Sixty-one patients with anti-GFAP astrocyte antibody (GFAP-IgG) single-positive autoimmune encephalitis who were treated at the Third Affiliated Hospital, Sun Yat-sen University between January 2017 and September 2023 were retrospectively collected. The demographic characteristics (age at onset, sex), clinical symptoms (core symptoms, neurological deficits, psychiatric behavioral abnormalities, and autonomic dysfunction), imaging features [brain/spinal cord/optic nerve magnetic resonance imaging (MRI) lesion distribution and enhancement patterns], and CSF parameters were analyzed. Acute-phase treatments, including methylprednisolone pulse therapy, intravenous immunoglobulin (IVIG), etc, along with the follow-up outcomes [modified Rankin Scale (mRS) score] were recorded.Results:The onset age was 40 (30, 55) years, and 68.9% (42/61) of the patients were male. The most common clinical manifestations were fever (65.6%, 40/61), headache (60.7%, 37/61), and urinary/defecatory abnormalities (45.9%, 28/61). Brain MRI revealed lesions predominantly in the cerebral cortex and subcortical white matter (57.4%, 35/61), periventricular white matter (50.8%, 31/61), and basal ganglia (36.1%, 22/61). Periventricular linear-radiating enhancement was the predominant MRI enhancement pattern (55.7%, 34/61). Spinal MRI showed lesions mainly in the cervical (42.6%, 26/61) and thoracic spinal cord (32.8%, 30/61), with leptomeningeal enhancement (31.1%, 19/61) and scattered punctate/patchy enhancements (21.3%, 13/61). Optic neuropathy was observed in 6 cases (9.8%). CSF analysis demonstrated a pressure of 180 (133, 240) mmH 2O (1 mmH 2O=0.009 8 kPa), white blood cell count of 29 (4, 156)×10?/L, and protein level of 0.72 (0.40, 1.44) g/L. Nineteen patients (31.1%) experienced rapid progression of meningoencephalitis or myelitis within 3 days of admission. All patients received methylprednisolone pulse therapy, with 47.5% (29/61) additionally treated with IVIG. At a follow-up of 12 (3, 28) months, 12 cases (19.7%) relapsed, and 75.4% (46/61) had favorable outcomes (mRS score 0-2). Poor prognosis (mRS score>2) was observed in 4 cases, including 3 with cervical spinal cord involvement and status epilepticus, 1 elderly patient with lung cancer. Conclusions:GFAP astrocytopathy predominantly affects young adults, with a male predominance. Spinal cord involvement is common, manifesting as myelitis and myelopathy. Rapid progression of meningoencephalitis or myelitis may occur early in the disease course. Periventricular linear-radiating enhancement on brain MRI is a key diagnostic clue. Leukocyte and protein levels in the cerebrospinal fluid are generally mildly to moderately elevated. Most patients respond well to corticosteroids and immunotherapy, with favorable outcomes. However, advanced age and cervical spinal cord involvement are associated with poor prognosis.

Objective To understand the epidemiological characteristics of scrub typhus disease and to provide a scientific basis for the prevention and control of scrub typhus disease. Methods Descriptive epidemiological methods were used to analyze the population and regional distribution of scrub typhus. Seasonal characteristics were analyzed using concentration method and circular distribution method, and incidence trend was analyzed using joinpoint regression model. Results The annual incidence rate of scrub typhus was 0.95/100 000 from 2010 to 2022. The incidence rate of male was 0.77/100 000, lower than that of female 1.12/100 000 (χ²=18.89, P<0.05). The incidence rate of the 60-74 years old group was 3.38/100,000, and the total number of cases in the age group 45-74 years was 416 (74.95%). Occupational distribution was mainly among farmers, with 448 cases (80.72%). The top three regions with the highest number of reported cases (in order: Donghai County, Ganyu District, and Guannan County) reported a total of 416 cases, accounting for 74.95%. Concentration ratio was M=0.9408, and the incidence of scrub typhus disease was strictly seasonal. Circular distribution results showed a^-=-62.3728, S=20.8960. The circular distribution results indicated that the peak day was October 19th, and the peak period was between October 7 to December 19. The average annual percentage change (AAPC) of the incidence rate from 2010 to 2022 was 13.70%, 95% CI (-8.62%~41.48%), and the incidence rate showed an upward trend (t=1.15, P=0.249). Conclusion The incidence of scrub typhus disease is strictly seasonal, and the incidence rate over the years shows an upward trend. It is necessary to strengthen monitoring and take various intervention measures to reduce the risk of scrub typhus disease.

OBJECTIVE: To evaluate the performance of a newly developed intelligent acupuncture robot that simulates human manual acupuncture techniques through an animal experiment using miniature pigs. METHODS: Two 3-month-old Bama miniature pigs were selected. One pig was used for the manual needling techniques of the practitioner, and the other pig was used for the intelligent acupuncture robot. The acupoints selected were "Qiangfeng" "Bojian" "Xiaokua" "Huiyang" (BL 35) and "Baihui" (GV 20), with a straight insertion depth of 25-35 mm. The manipulation techniques, including lifting-thrusting and twisting at a frequency of 90 times/min, were applied for 1 min, with 30 s each for lifting-thrusting (10 mm amplitude) and twisting (180° angle). The practitioner's needling techniques were captured using an optical motion capture system, and the collected data were input into the intelligent acupuncture robot for replication on the second miniature pig. A complete needling session of five acupoints was considered one round, and three rounds were performed per session, every other day, for a total of five sessions, completing 15 rounds. The Fréchet distance method was used to compare the robot's replicated needling data with the practitioner's data, and curve fitting analysis was conducted to evaluate the robot's performance and precision. RESULTS: The intelligent acupuncture robot achieved a total completion rate of 96.00% for 75 needling operations, with a non-completion rate of 4.00%. The robot's replication of the practitioner's needling techniques showed a good fit, with many characteristic points overlapping. The average Fréchet distance was 18.67. The Fréchet distance for the lifting-thrusting and twisting techniques at Baihui (GV 20) and "Huiyang" (BL 35) acupoints was smaller than that at "Xiaokua" and "Qiangfeng" points (P<0.01). The accuracy of the lifting-thrusting technique at "Xiaokua" and "Qiangfeng" acupoints was lower than the twisting technique (P<0.01). CONCLUSION The intelligent acupuncture robot is able to replicate the pre-recorded manual needling parameters with a high degree of accuracy.
Animals ; Swine ; Swine, Miniature ; Acupuncture Therapy/methods* ; Robotics/instrumentation* ; Humans ; Acupuncture Points ; Female ; Male

Objective This study aimed to develop an experimental animal platform for evaluating the feasibility and safety of intelligent acupuncture robots and to lay the foundation for further research.Methods Six 2-month-old Guangxi Bama miniature pigs were used as experimental subjects for acupuncture verification after anesthesia.First,manual acupuncture verification was carried out.Six acupoints were selected for each experimental animal and the needles were left for 20 min after the lifting,inserting,and twisting manipulation.Before and after controls were included.The experiment was carried out for 28 days,and each experiment was conducted once every 2 days for a total of 10 times.After verification of manual acupuncture,a point 10 mm from each of the six selected acupoints was selected,with a total of 12 points,and acupuncture operations were carried out on the experimental animals using the intelligent acupuncture module of the acupuncture robot at different frequencies and angles,to further verify the stability and feasibility of the animal platform.Results Routine safety-related blood indicators and blood biochemistry indicators after the procedure were normal and stable compared with those before the procedure.The average heart rate of the animals was 124 beats/min,the average blood pressure was 87/36 mmHg,and the average body temperature of was 36℃at a room temperature of 25℃,with no significant change in body temperature during and after the experiment.On the basis of this experimental platform,acupuncture manipulation using the intelligent acupuncture module of the acupuncture robot was completed successfully,with no abnormalities related to acupuncture such as bending,breaking,or stagnation of needles during the experimental process,and the experimental animals showed no obvious abnormalities.Conclusions This study established a stable experimental animal platform for evaluating the feasibility and safety of acupuncture carried out by intelligent acupuncture robots,based on the existing experimental method of miniature pigs.These result lay a foundation for further research related to the use of intelligent acupuncture robots.

Objective To evaluate the quality of infectious disease surveillance data and provide scientific basis for improving data quality and health decision-making. Methods The comprehensive index of infectious disease monitoring system evaluation and the integrity, accuracy and reliability of infectious disease report data were used to evaluate the quality of infectious disease monitoring data in multiple dimensions. Results In 2021, The comprehensive evaluation index of infectious disease surveillance system was 98.40%. In terms of data integrity, 1 105 data were missing, and the incomplete rate was 1.46%; In terms of data accuracy, 1978 cases were not accurately, rate of accuracy was 26.72%; In terms of data reliability, the card reporting rate of tertiary medical institutions accounted for 67.05%, the diagnosis rate of confirmed cases was 27.74%, and the correction rate of report card was 28.48%. Conclusion The accuracy and reliability of infectious disease data are insufficient, and new methods for infectious disease monitoring data quality are expanded to make up for the lack of data quality evaluation of the current national epidemic system.