1.Research progress on the addictivity and neurotoxicity of ketamine
Zhian ZI ; Tingyi ZHAO ; Gongwu WANG ; Jun CAO
Chinese Journal of Clinical Pharmacology and Therapeutics 2025;30(9):1233-1242
As a new type of rapid antidepres-sant,ketamine has provided a new approach for the treatment and research on the pathological mechanism of major depressive disorder.However,the addictive potential and neurotoxicity of ket-amine have become issues that cannot be ignored in clinical medication.This article briefly introduces the relevant research progress on ketamine addic-tion and neurotoxicity mechanisms at home and abroad,hoping to provide a reference for the ratio-nal development and utilization of ketamine.
2.Analysis on the Equitable Distribution of Medical and Health Resources under the Background of Digital Economy
Zhian LI ; Peiwen BAI ; Xiaoran WANG
Chinese Health Economics 2025;44(5):43-48
Objective:To investigate the impact of the development of the digital economy on the unfair of healthcare resource allocation in China.Methods:The sample data from 23 provinces across the country from 2015 to 2021 were tested using econometric regression.Results:It is found that the development of the digital economy will exacerbate the unfairness of the allocation of medical and health resources in China.Further analysis results show that there are regional differences in the impact of digital economy on the distribution of medical resources,which is mainly manifested in the central and western regions,but weaker in the eastern region,and this impact will weaken with the improvement of the development level of digital economy.At the same time,it also explores the possible influencing mechanisms.It is found that due to the demand-oriented allocation of medical and health resources,the development of digital economy will lead to more unfair allocation of medical resources by affecting economic level,education level and income gap.Conclusion:In the face of the challenges brought by the digital economy to the allocation of medical and health resources,effective measures need to be taken to solve them,thus laying a solid foundation for achieving the goals of comprehensive health coverage and common prosperity.
3.Research progress on the addictivity and neurotoxicity of ketamine
Zhian ZI ; Tingyi ZHAO ; Gongwu WANG ; Jun CAO
Chinese Journal of Clinical Pharmacology and Therapeutics 2025;30(9):1233-1242
As a new type of rapid antidepres-sant,ketamine has provided a new approach for the treatment and research on the pathological mechanism of major depressive disorder.However,the addictive potential and neurotoxicity of ket-amine have become issues that cannot be ignored in clinical medication.This article briefly introduces the relevant research progress on ketamine addic-tion and neurotoxicity mechanisms at home and abroad,hoping to provide a reference for the ratio-nal development and utilization of ketamine.
4.Analysis on the Equitable Distribution of Medical and Health Resources under the Background of Digital Economy
Zhian LI ; Peiwen BAI ; Xiaoran WANG
Chinese Health Economics 2025;44(5):43-48
Objective:To investigate the impact of the development of the digital economy on the unfair of healthcare resource allocation in China.Methods:The sample data from 23 provinces across the country from 2015 to 2021 were tested using econometric regression.Results:It is found that the development of the digital economy will exacerbate the unfairness of the allocation of medical and health resources in China.Further analysis results show that there are regional differences in the impact of digital economy on the distribution of medical resources,which is mainly manifested in the central and western regions,but weaker in the eastern region,and this impact will weaken with the improvement of the development level of digital economy.At the same time,it also explores the possible influencing mechanisms.It is found that due to the demand-oriented allocation of medical and health resources,the development of digital economy will lead to more unfair allocation of medical resources by affecting economic level,education level and income gap.Conclusion:In the face of the challenges brought by the digital economy to the allocation of medical and health resources,effective measures need to be taken to solve them,thus laying a solid foundation for achieving the goals of comprehensive health coverage and common prosperity.
5.Comparison of the validity of different self-rated tools for identifying (Hypo-) manic episodes mixed features: based on Date from the Second Phase of the National Bipolar Mania Clinical Pathway Survey
Zuowei WANG ; Yuncheng ZHU ; Chuangxin WU ; Guiyun XU ; Miao PAN ; Zhiyu CHEN ; Xiaohong LI ; Wenfei LI ; Zhian JIAO ; Mingli LI ; Yong ZHANG ; Jingxu CHEN ; Xiuzhe CHEN ; Na LI ; Jing SUN ; Jian ZHANG ; Shaohua HU ; Haishan WU ; Zhaoyu GAN ; Yan QIN ; Yumei WANG ; Yantao MA ; Xiaoping WANG ; Yiru FANG
Chinese Journal of Psychiatry 2024;57(7):426-432
Objective:A nationwide multi-center and large sample survey was conducted to compare the validity of the Mini International Neuropsychiatric Interview (Hypo-) Manic Episode with Mixed Features-DSM-5 Module (MINI-M) questionnaire and the Clinically Useful Depression Outcome Scale Supplemented with Questions for the DSM-5 Mixed Features Specifier (CUDOS-M) depression subscale in identifying mixed features in patients experiencing (hypo-) manic episodes.Methods:Using a convenience sampling method, 366 patients with bipolar disorder experiencing acute (hypo-) manic episodes who met the inclusion and exclusion criteria were recruited. The diagnosis of "with mixed features" was based on the DSM-5 criteria for mixed features. The predictive validity of the MINI-M questionnaire and the CUDOS-M depression subscale to screen mixed features was analyzed using the receiver operating characteristic (ROC) curve. Additionally, the difference in area under the ROC curve (AUC) between the two instruments was compared.Results:The AUC for the MINI-M questionnaire and the CUDOS-M depression subscale in screening mixed features were 0.79 (95 %CI=0.75-0.84) and 0.81 (95 %CI=0.77-0.86), respectively. There was no statistically significant difference in AUC between the two measurements ( Z=-1.19, P>0.05). Among patients with acute (hypo-) manic episodes, 45.9% (168/366) presented with mixed features according to the DSM-5 criteria, while the corresponding figures were 43.7% (160/366) using the MINI-M questionnaire (total score≥3) and 42.1% (154/366) using the CUDOS-M depression subscale (total score≥20). Screening results were comparable among the three measures. Conclusion:Mixed features are common among patients experiencing acute (hypo-) manic episodes. The MINI-M questionnaire and the CUDOS-M depression subscale demonstrate equivalent validity in identifying mixed features.
6.Comparison of the validity of different self-rated tools for identifying (Hypo-) manic episodes mixed features: based on Date from the Second Phase of the National Bipolar Mania Clinical Pathway Survey
Zuowei WANG ; Yuncheng ZHU ; Chuangxin WU ; Guiyun XU ; Miao PAN ; Zhiyu CHEN ; Xiaohong LI ; Wenfei LI ; Zhian JIAO ; Mingli LI ; Yong ZHANG ; Jingxu CHEN ; Xiuzhe CHEN ; Na LI ; Jing SUN ; Jian ZHANG ; Shaohua HU ; Haishan WU ; Zhaoyu GAN ; Yan QIN ; Yumei WANG ; Yantao MA ; Xiaoping WANG ; Yiru FANG
Chinese Journal of Psychiatry 2024;57(7):426-432
Objective:A nationwide multi-center and large sample survey was conducted to compare the validity of the Mini International Neuropsychiatric Interview (Hypo-) Manic Episode with Mixed Features-DSM-5 Module (MINI-M) questionnaire and the Clinically Useful Depression Outcome Scale Supplemented with Questions for the DSM-5 Mixed Features Specifier (CUDOS-M) depression subscale in identifying mixed features in patients experiencing (hypo-) manic episodes.Methods:Using a convenience sampling method, 366 patients with bipolar disorder experiencing acute (hypo-) manic episodes who met the inclusion and exclusion criteria were recruited. The diagnosis of "with mixed features" was based on the DSM-5 criteria for mixed features. The predictive validity of the MINI-M questionnaire and the CUDOS-M depression subscale to screen mixed features was analyzed using the receiver operating characteristic (ROC) curve. Additionally, the difference in area under the ROC curve (AUC) between the two instruments was compared.Results:The AUC for the MINI-M questionnaire and the CUDOS-M depression subscale in screening mixed features were 0.79 (95 %CI=0.75-0.84) and 0.81 (95 %CI=0.77-0.86), respectively. There was no statistically significant difference in AUC between the two measurements ( Z=-1.19, P>0.05). Among patients with acute (hypo-) manic episodes, 45.9% (168/366) presented with mixed features according to the DSM-5 criteria, while the corresponding figures were 43.7% (160/366) using the MINI-M questionnaire (total score≥3) and 42.1% (154/366) using the CUDOS-M depression subscale (total score≥20). Screening results were comparable among the three measures. Conclusion:Mixed features are common among patients experiencing acute (hypo-) manic episodes. The MINI-M questionnaire and the CUDOS-M depression subscale demonstrate equivalent validity in identifying mixed features.
7.Study on platelet components production in 19 provincial blood centers in China before and during the COVID-19 epidemic
Yuan ZHANG ; Yang CHEN ; Lin WANG ; Zhian ZHANG ; Ying LI ; Jincai ZHANG ; Mengzhuo LUO ; Huiling MENG ; Juan ZHOU ; Xia DU ; Changchun LU ; Ying XIE ; Li DENG ; Huijuan AN ; Sheling LIANG ; Yang ZHANG ; Yan LAN ; Yuan ZHOU ; Yan QIU
Chinese Journal of Blood Transfusion 2023;36(10):898-902
【Objective】 To study the changes of platelet components(PC), apheresis platelets (AP) and pooled platelet concentrates (PPC) production of 19 provincial blood centers before and during the COVID-19 epidemic. 【Methods】 The data related to the collection of AP and the preparation of PPC from 2016 to 2021 of 19 provincial blood centers was collected. The production of PC, AP and PPC during the four years before the epidemic (i.e. 2016-2019) and during the COVID-19 epidemic (i.e. 2020 and 2021) were calculated respectively, and the change of production was analyzed. 【Results】 The total production of PC in 19 blood centers steadily increased from 2016 to 2019, with a decrease of 4.16% in 2020 and an increase of 15.60% in 2021, exceeding the output before the COVID-19 epidemic. In 2020, the production of PC of 42.11% (8/19) blood centers decreased compared with 2019, while 94.74% (18/19) in 2021 increased compared with 2020. The changes of AP output was basically consistent with the trend of PC. The total production of PPC in 2017 and 2018 both doubled compared to the previous year, while decreased by 67.98% in 2019, increased by 30.38% in 2020 and decreased by 27.08% in 2021. 【Conclusion】 The total production of PC kept increasing steadily between 2016 and 2019, but decreased in 2020 under the COVID-19 epidemic, with some blood centers being significantly affected. In 2021, with the strong support from government and various measures by blood centers, the total production of PC increased.
8.Analysis of clinical phenotypes of bipolar disorder with mixed states diagnosed using ICD-10 and DSM-5
Yang LI ; Jia ZHOU ; Zuowei WANG ; Yuncheng ZHU ; Guiyun XU ; Miao PAN ; Zhiyu CHEN ; Wenfei LI ; Zhian JIAO ; Mingli LI ; Yong ZHANG ; Jingxu CHEN ; Xiuzhe CHEN ; Na LI ; Jing SUN ; Jian ZHANG ; Shaohua HU ; Haishan WU ; Zhaoyu GAN ; Yan QIN ; Yumei WANG ; Yantao MA ; Xiaoping WANG ; Xiaohong LI ; Yiru FANG
Chinese Journal of Psychiatry 2023;56(4):267-275
Objective:This study investigates the difference in the detection rate and symptomatology between ICD-10 and DSM-5 diagnostic criteria for bipolar disorder with mixed states.Methods:Based on the Phase Ⅰ (2012) and Phase Ⅱ (2021) databases of National Bipolar Mania Pathway Survey (BIPAS), patients with bipolar disorder were included. General demographic data, clinical characteristics, symptomatic phenotypes, and mixed characteristics were retrieved. The detection rates and symptomatic performances of patients with or without mixed states in Phase Ⅰ and Ⅱ were compared using the chi-square test.Results:For patients with mixed states, the detection rate during Phase Ⅱ (2021) using DSM-5 (18.79%, 199/1 059) criteria was significantly higher than that during Phase Ⅰ (2012) using ICD-10 (6.78%, 199/2 934; χ 2=125.05, P<0.001). Whether using ICD-10 or DSM-5 criteria, patients with mixed states had a significantly higher frequency of multiple symptomatic manifestations. Conclusion:The DSM-5 diagnostic criteria generate a high detection rate for bipolar disorder with mixed states. The clinical phenotypes of bipolar disorder with mixed states vary significantly using different diagnostic tools.
9.Analysis of clinical phenotypes of bipolar disorder with mixed states diagnosed using ICD-10 and DSM-5
Yang LI ; Jia ZHOU ; Zuowei WANG ; Yuncheng ZHU ; Guiyun XU ; Miao PAN ; Zhiyu CHEN ; Wenfei LI ; Zhian JIAO ; Mingli LI ; Yong ZHANG ; Jingxu CHEN ; Xiuzhe CHEN ; Na LI ; Jing SUN ; Jian ZHANG ; Shaohua HU ; Haishan WU ; Zhaoyu GAN ; Yan QIN ; Yumei WANG ; Yantao MA ; Xiaoping WANG ; Xiaohong LI ; Yiru FANG
Chinese Journal of Psychiatry 2023;56(4):267-275
Objective:This study investigates the difference in the detection rate and symptomatology between ICD-10 and DSM-5 diagnostic criteria for bipolar disorder with mixed states.Methods:Based on the Phase Ⅰ (2012) and Phase Ⅱ (2021) databases of National Bipolar Mania Pathway Survey (BIPAS), patients with bipolar disorder were included. General demographic data, clinical characteristics, symptomatic phenotypes, and mixed characteristics were retrieved. The detection rates and symptomatic performances of patients with or without mixed states in Phase Ⅰ and Ⅱ were compared using the chi-square test.Results:For patients with mixed states, the detection rate during Phase Ⅱ (2021) using DSM-5 (18.79%, 199/1 059) criteria was significantly higher than that during Phase Ⅰ (2012) using ICD-10 (6.78%, 199/2 934; χ 2=125.05, P<0.001). Whether using ICD-10 or DSM-5 criteria, patients with mixed states had a significantly higher frequency of multiple symptomatic manifestations. Conclusion:The DSM-5 diagnostic criteria generate a high detection rate for bipolar disorder with mixed states. The clinical phenotypes of bipolar disorder with mixed states vary significantly using different diagnostic tools.
10.Evaluation and study on the effect of nucleic acid testing in blood screening on the residual risk of transfusion transmitted HBV infection
Min HUANG ; Lin BAI ; Changchun LU ; Shanshan ZHU ; Yujun LI ; Zhian ZHANG ; Haili MA ; Rong YOU ; Yanli QIN ; Bing JU ; Wei HAN ; Fang WANG ; Xue CHEN ; Xiaohua YUAN ; Xingli REN ; Lei ZHAO ; Linghao ZHANG ; Xing YI ; Yan QIU
Chinese Journal of Experimental and Clinical Virology 2022;36(4):429-435
Objective:To preliminarily estimate and study the effect of nucleic acid testing in blood screening on the residual risk (RR) of transfusion transmitted HBV infection (TTI HBV).Methods:Using the NAT yield/WP ratio model and adopting the relevant data of information management system of practice comparison working party in the Mainland of China, this paper analyzed the trend of the RR of TTI HBV among 18 blood centers from 2015 to 2019 in China, and compared the impact of two kinds of blood screening strategies which were ELISA+ ID-NAT/MP-NAT (individual-donation nucleic acid testing or mini-pool nucleic acid testing) and ELISA + MP-NAT on RR in 2019.Results:The overall trends of the 5-year RR of HBV among 18 blood centers showed by trend chi square test were NAT single positive rate trend χ2= 39.42( P<0.01) and residual risk trend χ2= 279.792( P<0.01); The influence on RR from the differences of ELISA+ ID-NAT/MP-NAT and ELISA+ MP-NAT was statistically significant, and chi square test showed that χ2= 7.4( P<0.01). Conclusions:Since the implementation of nucleic acid testing in the blood screening in China from 2015, the residual risk of transfusion transmitted HBV infection has decreased year by year. The observed two blood screening strategies which dominated in China may lead to discrepancy in the residual risk of TTI.

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