Prevalence of chronic kidney disease among Chinese adults with diabetes: a nationwide population-based cross-sectional studyResearch in context by Weiping Jia, Rong Yu, Limin Wang, Dalong Zhu, Lixin Guo, Jianping Weng, Hong Li, Mei Zhang, Xiaoqi Ye, Zhiguang Zhou, Dajin Zou, Qiuhe Ji, Xiaohui Guo, Yinan Zhang, Dong Lang, Jiarui Wu, Jing Wu, Xuhong Hou, Xiaohui Guo, Kai Wu, Liming Chen, Demin Liu, Guangyao Song, Linyi Shu, Jing Yang, Yan Wang, Dongmei Li, Qiansha Guo, Ling Li, Na Wu, Yadong Sun, Huifang Cheng, Hongyu Kuang, Huijuan Zhang, Weiping Jia, Xuhong Hou, Dalong Zhu, Jian Zhu, Hong Li, Fenping Zheng, Qiu Zhang, Honglin Hu, Gang Chen, Xingquan Yang, Xiaoyang Lai, Jianping Liu, Li Chen, Ming Dong, Zhigang Zhao, Jian Liu, Guangda Xiang, Junxia Zhang, Zhiguang Zhou, Jian Peng, Jianping Weng, Longyi Zeng, Yuzhen Liang, Guoqiao Li, Kaining Chen, Leweihua Lin, Qifu Li, Qingfeng Cheng, Xingwu Ran, Dawei Chen, Hong Li, Xin Nian, Lihui Yang, Shuyou Meng, Jing Xu, Junhong Long, Jing Liu, Qi Zhang, Qingxiang Dai, Xiaomin Xie, Guirong Bai, Jun Li, Tao Li, Zhong Dong, Tao Zhang, Sijia Liu, Yong Yang, Kun Geng, Wenlong Zheng, Zhihong Li, Hui Wang, Zuojun Wu, Miao Wang, Jixin Sun, Jianwei Zhou, Jun An, Huaqing Shen, Yanfang Li, Zeping Ren, Xiuli Xue, Shaohui Jia, Yongping Zheng, Jiaoxia Li, Yonggang Qian, Ping Ma, Yan Su, Liang Cao, Xuyi Yang, Guowei Pan, Guangzhi Pan, Ling Jin, Quanfu Yu, Yunfei Liu, Yingli Zhu, Zhifang Cheng, Jun Yang, Chundi Jia, Qing Wang, Shichun Yan, Jingyang Huang, Yumei Chi, Li Zhang, Ruifa Pang, Yan Shi, Yan Lu, Yiling Wu, Jie Yu, Chunxiang Wu, Jinyi Zhou, Yunxia Wu, Ning Zhang, Jing Sun, Xiumei Tian, Jieming Zhong, Jingying Chen, Kaixu Xie, Lingjuan Fu, Xiaohua Wang, Yeji Chen, Ling Zeng, Zhenqian Cao, Maomin Yang, Biao Hu, Wenling Zhong, Qingyan Liu, Zhiding Huang, Qingbin Lai, Yuyu Zhang, Liping Zhu, Yujing Zhao, Wuming Tao, Yonghai Tu, Lin Zhou, Xiaolei Guo, Benzheng Chai, Liping Ding, Yuewei Zou, Dongzhi Li, Li Hua, Shixian Feng, Jianli Guo, Wanguang Liu, Qingxiang Li, Yunzhi Zheng, Minli Xu, Lan Zhang, Chunbo Li, Yingchao Wan, Chi Hu, Shengping Xu, Biyun Chen, Huilin Liu, Xiaojia Bian, Wenwei Chen, Honghua Li, Yanjun Xu, Fan Weng, Hong Wu, Weijin Zhang, Liankai Zhu, Jun Meng, Jin Yang, Yongsong Zeng, Gaoke Zhai, Lingfeng Qin, Yi Lu, Zhenwang Fu, Shukuan Wu, Caigang Li, Na Wang, Lianfen Chen, Xianbin Ding, Qi Zhou, Yiling Xie, Rui Chen, Dongsheng Yang, Ying Deng, Youping Hu, Bo Huang, Ping Wang, Peng Cai, Changyan Peng, Xiaofang Chen, Ling Li, Liang Xiao, Chenglin Wang, Chaogang Tan, Daobin Chen, Min Chen, Mingfang Qin, Zhaomin Lei, Jianzhi Qiu, Wei Yu, Yunfei Li, Guoxia Bai, Ying Wang, Lin Qiu, Ning Wang, Xudong Zhao, Ani Yan, Jianfei Liu, Tingcai Wang, Kaihua Hao, Zaihong Zhang, Zhanqi Xian, Tenghuan Ma, Zhihua Xu, Yi Yang, Hongli Wang, Rong Li, Zhonggang Zhao, Caixia Fan, Purhati, Hongjun Xu, Liping Gao

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Deep Learning for Obstructive Sleep Apnea Detection and Severity Assessment: A Multimodal Signals Fusion Multiscale Transformer Model by Zhang Y, Zhou L, Zhu S, Zhou Y, Wang Z, Ma L, Yuan Y, Xie Y, Niu X, Su Y, Liu H, Hei X, Shi Z, Ren X, Shi Y

“…Yitong Zhang,1 Liang Zhou,2 Simin Zhu,1 Yanuo Zhou,1 Zitong Wang,1 Lina Ma,1 Yuqi Yuan,1 Yushan Xie,1 Xiaoxin Niu,1 Yonglong Su,1 Haiqin Liu,1 Xinhong Hei,2 Zhenghao Shi,2 Xiaoyong Ren,1 Yewen Shi1 1Department of Otorhinolaryngology Head and Neck Surgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, People’s Republic of China; 2School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, Shaanxi Province, People’s Republic of ChinaCorrespondence: Xiaoyong Ren; Yewen Shi, Department of Otorhinolaryngology Head and Neck Surgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Address: NO. 157 Xi Wu Road, Xi’an, Shaanxi Province, Email cor_renxiaoyong@126.com; shiyewen59@outlook.comPurpose: To develop a deep learning (DL) model for obstructive sleep apnea (OSA) detection and severity assessment and provide a new approach for convenient, economical, and accurate disease detection.Methods: Considering medical reliability and acquisition simplicity, we used electrocardiogram (ECG) and oxygen saturation (SpO2) signals to develop a multimodal signal fusion multiscale Transformer model for OSA detection and severity assessment. …”
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Nursing of a patient with post-stroke constipation of Qi-deficiency type treated by Baliao acupoints moxibustion and acupuncture combined with oral administration of Yiqi Runchang... by LI Juan (李娟), FENG Ruiping (冯瑞萍), LI Ling (黎玲)

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Clinicopathological Features and Increased Expression of Toll-Like Receptor 4 of Gastric Cardia Cancer in a High-Risk Chinese Population by Guangcan Chen, Muming Xu, Jingyao Chen, Liangli Hong, Wenting Lin, Shukun Zhao, Guohong Zhang, Guo Dan, Shuhui Liu

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Impact of Antimicrobial Stewardship and Infection Prevention and Control Programmes on Antibiotic Usage and A. baumannii resistance: A 2016–2023 Multicentre Prospective Study by Liu L, Liu B, Li L, Li Y, Zhou X, Li Q

“…Lei Liu,1,2,* Bin Liu,1,2,* Liang Li,1,2 Yu Li,3 Xiangdong Zhou,1,2 Qi Li1,2 1Department of Respiratory Medicine, The First Affiliated Hospital, Hainan Medical University, Haikou, Hainan, People’s Republic of China; 2Hainan Province Clinical Medical Center of Respiratory Disease, Haikou, Hainan, People’s Republic of China; 3Department of Respiratory Medicine, The Fourth Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qi Li, Email lqlq198210@sina.comObjective: This study assesses the efficacy of antimicrobial stewardship (AMS) and infection prevention and control programmes (IPCP) in guiding the use of antibiotics and the control of A. baumannii (AB) resistance at multiple medical centres.Methods: We evaluated the effectiveness of the policy on antibiotic consumption and AB resistance by determining the relationship between the defined daily doses (DDD) for antibiotics – or alcohol-based hand gel (ABHG) consumption – and the incidence of carbapenem-resistant AB (CR-AB), multidrug-resistant AB (MDR-AB) and extensively drug-resistant AB (XDR-AB) at two medical centers from 2016– 2023.Results: In total, 4057 AB isolates were collected; 64.95% of the AB isolates were CR, 59.48% were MDR and 1.41% were XDR. …”
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