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Symptom Network and Subgroup Analysis in Patients with Exacerbation of Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study
Published 2025-01-01“…Chunchun Yu,1 Mengying Xu,1 Xinyue Pang,2 Yuting Zhang,3 Xinmei Cao,2 Yixin Xu,1 Shuai Huang,1 Hongjun Zhao,4 Chengshui Chen1,3,4 1Key Laboratory of Interventional Pulmonology of Zhejiang Province, Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of China; 2Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of China; 3Cixi Biomedical Research Institute, Wenzhou Medical University, Wenzhou, Zhejiang, 315302, People’s Republic of China; 4Zhejiang Province Engineering Research Center for Endoscope Instruments and Technology Development, Department of Pulmonary and Critical Care Medicine, Quzhou People’s Hospital, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, 324000, People’s Republic of ChinaCorrespondence: Hongjun Zhao; Chengshui Chen, Zhejiang Province Engineering Research Center for Endoscope Instruments and Technology Development, Department of Pulmonary and Critical Care Medicine, Quzhou People’s Hospital, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, 324000, People’s Republic of China, Email zhaohongjun@wmu.edu.cn; chenchengshui@wmu.edu.cnPurpose: This study aims to construct a contemporaneous symptom network of inpatients with Exacerbation of Chronic Obstructive Pulmonary Disease (ECOPD) based on the symptom cluster, identify core and bridge symptoms, and patient subgroups with different symptom clusters based on individual differences in the intensity of patient symptom experiences.Patients and Methods: This study used convenience sampling to collect demographic, symptom, auxiliary examination, and prognosis information of 208 inpatients with ECOPD from April 2022 to October 2023. …”
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Metabolomic Analysis of the Chemical Composition of Chongjue Luohan Tea
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Artificial intelligence for quantifying immune infiltrates interacting with stroma in colorectal cancer
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Fault tolerant GPS-AOA-SINS integrated navigation algorithm based on federated Kalman filter
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Pluripotency-State-Dependent Role of Dax1 in Embryonic Stem Cells Self-Renewal
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On-chip integrated plasmon-induced high-performance self-powered Pt/GaN ultraviolet photodetector
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A Predictive Model for Pulmonary Aspergillosis in ICU Patients: A Multicenter Retrospective Cohort Study
Published 2025-01-01“…Yujing Li,1,2,* Xindie Ren,3,* Qianqian Wang,4,* Songying Shen,2,* Yihao Li,1,2 Xinling Qian,2 Yufei Tang,2 Jinguang Jia,2 Hao Zhang,2 Junjie Ding,2 Yinsen Song,1 Sisen Zhang,1 Shengfeng Wang,5 Yinghe Xu,6 Yongpo Jiang,6 Xuwei He,7 Muhua Dai,8 Lin Zhong,9 Yonghui Xiong,10 Yujie Pan,11 Mingqiang Wang,12 Huanzhang Shao,12 Hongliu Cai,3 Lingtong Huang,3 Hongyu Wang1,2 1Department of Critical Care Medicine, The Fifth Clinical Medical College of Henan University of Chinese Medicine, Zhengzhou, Henan Province, People’s Republic of China; 2Department of Critical Care Medicine, People’s Hospital of Henan University of Chinese Medicine/People’s Hospital of Zhengzhou, Zhengzhou, Henan Province, People’s Republic of China; 3Department of Critical Care Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, People’s Republic of China; 4Department of Critical Care Medicine, The First Hospital of Jiaxing, Jiaxing, Zhejiang Province, People’s Republic of China; 5Department of Critical Care Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, People’s Republic of China; 6Department of Critical Care Medicine, Taizhou Hospital of Zhejiang Province affiliated with Wenzhou Medical University, Taizhou, Zhejiang Province, People’s Republic of China; 7Department of Critical Care Medicine, Lishui People’s Hospital, Lishui, Zhejiang Province, People’s Republic of China; 8Department of Critical Care Medicine, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang Province, People’s Republic of China; 9Department of Critical Care Medicine, The First People’s Hospital of Pinghu, Pinghu, Zhejiang Province, People’s Republic of China; 10Department of Critical Care Medicine, Lanxi Hospital of Traditional Chinese Medicine, Lanxi, Zhejiang Province, People’s Republic of China; 11Department of Critical Care Medicine, Wenzhou Central Hospital, Wenzhou, Zhejiang Province, People’s Republic of China; 12Department of Critical Care Medicine, Henan Key Laboratory for Critical Care Medicine, Zhengzhou Key Laboratory for Critical Care Medicine, Henan Provincial People’s Hospital; Zhengzhou University People’s Hospital, Henan University People’s Hospital, Zhengzhou, Henan Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lingtong Huang, Department of Critical Care Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China, Email lingtonghuang@zju.edu.cn Hongyu Wang, Department of Critical Care Medicine, People’s Hospital of Henan University of Chinese Medicine/People’s Hospital of Zhengzhou, Zhengzhou, Henan Province, People’s Republic of China, Email hongyu260@163.comBackground: Several predictive models for invasive pulmonary aspergillosis (IPA) based on clinical characteristics have been reported. …”
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