Objective To analyze the cognitive function and sleep quality of the elderly in Shanghai community, and explore the related influencing factors. Methods A stratified cluster random sampling method was used to select 8 community health centers in Shanghai for a questionnaire survey, including 3 677 elderly individuals who completed the “Comprehensive Health Status Survey of Elderly Residents in Shanghai” from September 2023 to November 2023. Basic information of the elderly was collected, including age, gender, education level, smoking, drinking, mahjong playing behavior, and exercise habits. The Pittsburgh sleep quality index (PSQI) was used to assess the sleep quality of the elderly, subjective cognitive decline (SCD) self-assessment questionnaire and Mini-Mental State Examination (MMSE) were used to evaluate cognitive function, while the Hamilton Anxiety Scale (HAMA) and patient health questionnaire-9 (PHQ-9) were used to assess anxiety and depression levels, and the mini nutritional assessment (MNA) was used to evaluate nutritional status. According to the MMSE scores, the elderly were divided into three groups: no cognitive impairment (MMSE ≥ 27), mild cognitive impairment (MMSE 21-26), and moderate to severe cognitive impairment (MMSE ≤ 20). The general data, lifestyle habits, and scale scores of the three groups were compared. Ordered logistic regression was used to analyze the influencing factors of sleep quality. Results There were statistically significant differences in age, gender, waist circumference, body mass index (BMI), education level, pet ownership, smoking, drinking, mahjong playing behavior, exercise habits, and scale scores among the three groups (P＜0.05). Logistic regression analysis showed that age, waist circumference, gender, drinking habits, mahjong playing behavior, and chronic comorbidities are influencing factors for the PSQI grading in the elderly (P＜0.05). The MMSE score (OR＝1.037, P＝0.001), SCD score (OR＝1.123, P＜0.001), HAMA score (OR＝1.183, P＜0.001), PHQ-9 score (OR＝1.249, P＜0.001) are positive influencing factors for PSQI grading, while the MNA score is a negative influencing factor (OR＝0.960, P＝0.037). Conclusions Advanced age, female gender, low education level, no pet ownership, no mahjong playing behavior, no exercise habits, and poor sleep quality are risk factors for cognitive impairment in the elderly. Advanced age, female gender, no mahjong playing behavior and poor nutritional status are influencing factors for poor sleep quality in the elderly, and severe comorbidities, anxiety, depression, and subjective decline in cognitive function all affect sleep quality.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

With the continuous development of surgery,the amount of Da Vinci robot surgery has increased year by year,and Da Vinci robot has been widely used in the field of surgery.However,due to its structural characteristics,robot surgical instruments are difficult to clean after contamination,which poses a great challenge to the cleaning technology of nurses in central sterile supply department(CSSD).At present,there are still some problems in the cleaning quality management of Da Vinci robotic surgical instruments,such as inadequate pre-treatment,non-standard manual cleaning process,and inconsistent cleaning quality evaluation methods,which bring great hidden dangers to patients'medical safety.Therefore,scientific and effective cleaning quality control is very important to prevent nosocomial infection and ensure the life safety of patients.This paper reviews the cleaning process and quality control on Da Vinci robotic surgical instruments by consulting,screening,sorting and summarizing domestic and foreign relevant literature of the cleaning and management,and combining with the actual clinical work of the disinfection supply center,and aims to provide theoretical references for the formulation of guidelines and clinical practice for the personnel of CSSD.

ObjectiveTo explore the recognition of oral breath odor map of chronic atrophic gastritis （CAG） patients with dampness-heat syndrome by electronic nose technique. MethodsPatients with chronic gastritis were recruited， including 60 cases in CAG group of dampness-heat syndrome， 50 cases in CAG group of non-dampness-heat syndrome， 60 cases in chronic non-atrophic gastritis （CNAG） group of dampness-heat syndrome， 50 cases in CNAG group of non-dampness-heat syndrome， and 30 cases of healthy volunteers were selected to set up the health control group. Ten cases in the CAG dampness-heat group and 50 cases in the CAG non-dampness-heat group were selected to form the CAG group， and 10 cases in CNAG dampness-heat group and 50 cases in CNAG non-dampness-heat group were selected to form the CNAG group. In addition to the health control group， the remaining patients were tested for Helicobacter pylori （Hp）； the electronic nose （GISXM-MQWA01） was used to collect the oral breath odor of all the participants to draw the mapping， and amplitudes and slopes of each curve （including curves A， B， C， D， E， F， G， H， I， J） of the oral odor mapping of health control group， CAG group， CNAG group， CAG dampness-heat group， CAG non-dampness-heat group， and CNAG dampness-heat group was compared. The modified transformer model was used to classify the odor mapping characteristics， and the confusion matrix method was used to evaluate the classification model， with metrics including accuracy and area under ROC curve （AUC）. ResultsThe Hp positivity rate in CAG dampness-heat group was 80.00% （48/60）， CAG non-dampness-heat group was 62.00% （31/50）， CNAG dampness-heat group was 46.67% （28/60）， and CNAG non-dampness-heat group was 42.00% （21/50）； the difference in Hp positivity rate between CAG dampness-heat group and CAG non-dampness-heat group was statistically significant （P＜0.05）. The amplitudes of response curves A， B， C， D， F， G， and I， and slopes of A and F in the odor mapping of the CAG group were lower than those in health control group， while the amplitude and slope of curve E were higher than those in the health control group and CNAG group （P＜0.05 or P＜0.01）； The amplitude of the response curves A， B， C， D， F， G， and I， and slopes of A， D， and F in the CNAG group were lower than those in the health control group （P＜0.05 or P＜0.01）. The amplitude of response curve D and slope of response curve J in the odor mapping of the CAG dampness-heat group were higher than those in CNAG dampness-heat group， the amplitude of curve F was lower than that in CAG non-dampness-heat group， and the amplitude of curve H and slopes of curve A， H， and J were higher than those in CAG non-dampness-heat group （P＜0.05）. The recognition accuracy of CAG group and health control group reached 77.78%， AUC = 0.88； the recognition accuracy of CAG group and CNAG group was 69.44%， AUC = 0.61； the recognition accuracy of CAG dampness-heat group and CAG non-dampness-heat group reached 75.8%， AUC=0.70. ConclusionElectronic nose technology can make a more accurate identification of the oral breath odor in CAG patients with dampness-heat syndrome， with a decrease in the amplitude of the curve F and an increase in the amplitude of the curve H and in the slopes of the curves A， H， and J may as the characteristics of their odor mapping.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.