Relevant literature on TCM diagnostic and treatment equipment from January 1994 to May 2023 was collected with three Chinese databases,namely,China National Knowledge Infrastructure,Wanfang and Wipu.CiteSpace software was used for the analyses of the trend of annual publication volume,co-occurrence of publication institutions,co-occurrence of keywords,cluster and burst and the generation of corresponding knowledge graphs.It's pointed out TCM diagnostic and treatment equipment had problems in low publication volume and collaboration between research institutions,hotspots of Chinese medicine diagnosis and treatment,diagnosis and treatment equipment,diagnosis device,Chinese medicine diagnosis,diagnosis and treatment technology and traditional Chinese medicine,and research frontiers of artificial intelligence,medical alliance,curriculum design and innovation and entrepreneurship.References were provided for relevant research in China.[Chinese Medical Equipment Journal,2024,45(3):76-80]

Objective:To investigate the influence of changes in the cognitive load of anesthesia residents on the teaching effectiveness of high-fidelity scenario simulation.Methods:Eighty-seven anesthesia residents in a grade-A tertiary hospital from February to November 2022 were divided into groups A, B, and C according to the random number method. Three cases were selected from the anesthesia crisis resource teaching case library for high-fidelity simulation training for the three groups, respectively, using the crossover design to control the order of the cases. Each round of training consisted of pre-training instruction, simulation teaching, and post-training summarization and analysis. After three rounds of simulation teaching, cognitive load, anxiety status, test scores, and non-technical skills were evaluated for all the study participants. SPSS 20.0 was used to perform analysis of variance with repeated measures and Pearson's correlation analysis.Results:All the three groups showed significantly higher cognitive load and anxiety scores during the first-round simulation training than during the second-round and third-round simulation trianing. The test scores were significantly lower in the first round [(87.07±5.66), (88.38±5.41), (89.07±6.17)] than in the second round [(95.69±2.29), (96.10±2.08), (96.07±2.60)] and the third round [(96.34±1.45), (96.38±1.50), (96.17±1.73); all P<0.05]. The non-technical skill scores were also significantly lower in the first round [(37.24±7.58), (38.69±7.27), (39.24±8.74)] than in the second round [(46.17±5.55), (47.07±5.59), (47.59±6.74)] and the third round [(47.17±5.21), (48.48±5.38), (48.24±6.83); all P<0.05]. For simulations with the same cases, the trainees showed significantly higher cognitive load and anxiety scores and significantly lower test scores and non-technical skill scores in the first round than in the second and third rounds ( P<0.05). Conclusions:Anesthesia residents have higher levels of cognitive load and anxiety in the first scenario simulation training, which can reduce learning outcomes, and repeated simulation training can reduce trainees' cognitive load and anxiety.

Objective:In the context of the aging trend of China's population,it aims to analyze the trend of elderly disabled population growth in various regions and calculate the potential payment pressure of long-term care insurance for the disabled population,thereby providing policy implications for China's long-term care insurance system.Methods:A model for estimating the amount of expenditure on long-term care insurance fund was constructed,using the population age structure of each province in China from 2025 to 2060 obtained from the random forest model,and combining multi-source data such as the disability rate of the elderly population and the care cost of disabled elderly people to predict the number of elderly disabled people and the payment amount of long-term care insurance in each province in the future.Results:The aging trend in China will continue to intensify and exhibit a significant structural feature.The peak of the aging ratio in northeastern regions such as Inner Mongolia,Heilongjiang,Jilin,and Liaoning will come earliest,while the number of elderly people with disabilities in provinces with large populations such as Shandong,Sichuan,and Henan are relatively larger.Guangdong will have the largest number of disabled elderly people by 2055.Conclusion:It is suggested that the long-term care insurance system should be steadily advanced,with national-level support for the construction of the system in Northeast China and populous provinces.

Objective:In the context of the aging trend of China's population,it aims to analyze the trend of elderly disabled population growth in various regions and calculate the potential payment pressure of long-term care insurance for the disabled population,thereby providing policy implications for China's long-term care insurance system.Methods:A model for estimating the amount of expenditure on long-term care insurance fund was constructed,using the population age structure of each province in China from 2025 to 2060 obtained from the random forest model,and combining multi-source data such as the disability rate of the elderly population and the care cost of disabled elderly people to predict the number of elderly disabled people and the payment amount of long-term care insurance in each province in the future.Results:The aging trend in China will continue to intensify and exhibit a significant structural feature.The peak of the aging ratio in northeastern regions such as Inner Mongolia,Heilongjiang,Jilin,and Liaoning will come earliest,while the number of elderly people with disabilities in provinces with large populations such as Shandong,Sichuan,and Henan are relatively larger.Guangdong will have the largest number of disabled elderly people by 2055.Conclusion:It is suggested that the long-term care insurance system should be steadily advanced,with national-level support for the construction of the system in Northeast China and populous provinces.

Objective:In the context of the aging trend of China's population,it aims to analyze the trend of elderly disabled population growth in various regions and calculate the potential payment pressure of long-term care insurance for the disabled population,thereby providing policy implications for China's long-term care insurance system.Methods:A model for estimating the amount of expenditure on long-term care insurance fund was constructed,using the population age structure of each province in China from 2025 to 2060 obtained from the random forest model,and combining multi-source data such as the disability rate of the elderly population and the care cost of disabled elderly people to predict the number of elderly disabled people and the payment amount of long-term care insurance in each province in the future.Results:The aging trend in China will continue to intensify and exhibit a significant structural feature.The peak of the aging ratio in northeastern regions such as Inner Mongolia,Heilongjiang,Jilin,and Liaoning will come earliest,while the number of elderly people with disabilities in provinces with large populations such as Shandong,Sichuan,and Henan are relatively larger.Guangdong will have the largest number of disabled elderly people by 2055.Conclusion:It is suggested that the long-term care insurance system should be steadily advanced,with national-level support for the construction of the system in Northeast China and populous provinces.

Objective:In the context of the aging trend of China's population,it aims to analyze the trend of elderly disabled population growth in various regions and calculate the potential payment pressure of long-term care insurance for the disabled population,thereby providing policy implications for China's long-term care insurance system.Methods:A model for estimating the amount of expenditure on long-term care insurance fund was constructed,using the population age structure of each province in China from 2025 to 2060 obtained from the random forest model,and combining multi-source data such as the disability rate of the elderly population and the care cost of disabled elderly people to predict the number of elderly disabled people and the payment amount of long-term care insurance in each province in the future.Results:The aging trend in China will continue to intensify and exhibit a significant structural feature.The peak of the aging ratio in northeastern regions such as Inner Mongolia,Heilongjiang,Jilin,and Liaoning will come earliest,while the number of elderly people with disabilities in provinces with large populations such as Shandong,Sichuan,and Henan are relatively larger.Guangdong will have the largest number of disabled elderly people by 2055.Conclusion:It is suggested that the long-term care insurance system should be steadily advanced,with national-level support for the construction of the system in Northeast China and populous provinces.

Objective:In the context of the aging trend of China's population,it aims to analyze the trend of elderly disabled population growth in various regions and calculate the potential payment pressure of long-term care insurance for the disabled population,thereby providing policy implications for China's long-term care insurance system.Methods:A model for estimating the amount of expenditure on long-term care insurance fund was constructed,using the population age structure of each province in China from 2025 to 2060 obtained from the random forest model,and combining multi-source data such as the disability rate of the elderly population and the care cost of disabled elderly people to predict the number of elderly disabled people and the payment amount of long-term care insurance in each province in the future.Results:The aging trend in China will continue to intensify and exhibit a significant structural feature.The peak of the aging ratio in northeastern regions such as Inner Mongolia,Heilongjiang,Jilin,and Liaoning will come earliest,while the number of elderly people with disabilities in provinces with large populations such as Shandong,Sichuan,and Henan are relatively larger.Guangdong will have the largest number of disabled elderly people by 2055.Conclusion:It is suggested that the long-term care insurance system should be steadily advanced,with national-level support for the construction of the system in Northeast China and populous provinces.

Objective:In the context of the aging trend of China's population,it aims to analyze the trend of elderly disabled population growth in various regions and calculate the potential payment pressure of long-term care insurance for the disabled population,thereby providing policy implications for China's long-term care insurance system.Methods:A model for estimating the amount of expenditure on long-term care insurance fund was constructed,using the population age structure of each province in China from 2025 to 2060 obtained from the random forest model,and combining multi-source data such as the disability rate of the elderly population and the care cost of disabled elderly people to predict the number of elderly disabled people and the payment amount of long-term care insurance in each province in the future.Results:The aging trend in China will continue to intensify and exhibit a significant structural feature.The peak of the aging ratio in northeastern regions such as Inner Mongolia,Heilongjiang,Jilin,and Liaoning will come earliest,while the number of elderly people with disabilities in provinces with large populations such as Shandong,Sichuan,and Henan are relatively larger.Guangdong will have the largest number of disabled elderly people by 2055.Conclusion:It is suggested that the long-term care insurance system should be steadily advanced,with national-level support for the construction of the system in Northeast China and populous provinces.

Objective:In the context of the aging trend of China's population,it aims to analyze the trend of elderly disabled population growth in various regions and calculate the potential payment pressure of long-term care insurance for the disabled population,thereby providing policy implications for China's long-term care insurance system.Methods:A model for estimating the amount of expenditure on long-term care insurance fund was constructed,using the population age structure of each province in China from 2025 to 2060 obtained from the random forest model,and combining multi-source data such as the disability rate of the elderly population and the care cost of disabled elderly people to predict the number of elderly disabled people and the payment amount of long-term care insurance in each province in the future.Results:The aging trend in China will continue to intensify and exhibit a significant structural feature.The peak of the aging ratio in northeastern regions such as Inner Mongolia,Heilongjiang,Jilin,and Liaoning will come earliest,while the number of elderly people with disabilities in provinces with large populations such as Shandong,Sichuan,and Henan are relatively larger.Guangdong will have the largest number of disabled elderly people by 2055.Conclusion:It is suggested that the long-term care insurance system should be steadily advanced,with national-level support for the construction of the system in Northeast China and populous provinces.