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Influenza and pneumococcal vaccination coverage and associated factors in patients hospitalized with acute exacerbations of COPD in China: Findings from real-world data

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中华医学杂志(英文版) 2024年第10期137卷 1179-1189页

作者： He Ruoxi Ren Xiaoxia Huang Ke Lei Jieping Niu Hongtao Li Wei Dong Fen Li Baicun Wang Ye Yang Ting Wang Chen School of Population medicine and Public Health Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China Department of respiratory medicine National Key Clinical Specialty Branch of National Clinical Research Center for Respiratory Disease Xiangya Hospital Central South University Changsha Hunan China Department of Pulmonary and Critical Care medicine Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China institute of respiratory medicine Chinese Academy of Medical Sciences Beijing China National Center for respiratory medicine Beijing China National Clinical Research Center for respiratory Diseases Beijing China Department of Clinical Research and Data Management Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China

Background: Influenza and pneumococcal vaccination are a priority in patients with chronic obstructive pulmonary disease (COPD). However, limited information is available on vaccination coverage among patients with acute exacerbations of COPD (AECOPD) in China. This study aimed to determine the rates and associated factors of influenza and pneumococcal vaccination in patients hospitalized with AECOPD.Methods: Baseline data from a national, multicenter, hospital-based study that included adult inpatients with AECOPD between 2017 and 2021 were analyzed. The outcomes of interest were the influenza vaccination in the past year and the pneumococcal vaccination in the past 5 years. To ensure national representativeness, rates were weighted according to the distribution of hospital levels and types enrolled in this study. Multivariable Poisson regression based on mixed-effects models were used to determine the associated factors. The independent variables included the region and hospital features where the participants were located, sociodemographic characteristics (age, sex, rural/urban residence, education, etc.), and clinical indicators (COPD disease history, lung function parameters, comorbidities, etc.). The treatment profiles of the vaccinated and unvaccinated participants were compared.Results: Of 6949 eligible participants, the weighted rates of influenza/pneumococcal, influenza, and pneumococcal vaccination were 2.72% (95% confidence interval [CI]: 2.34%-3.10%), 2.09% (95% CI: 1.76%-2.43%), and 1.25% (95% CI: 0.99%-1.51%), respectively. In multivariable models, age ≥60 years (60-69 years, odds ratio [OR]: 1.90, 95% CI: 1.11-3.25; ≥80 years, OR: 2.00, 95% CI: 1.06-3.78), geographical regions (Northern China relative to Eastern China, OR: 5.09, 95% CI: 1.96-13.21), urban residence (OR: 1.69, 95% CI: 1.07-2.66), a higher education level (junior high school, OR: 1.77, 95% CI: 1.21-2.58; senior high school or above, OR: 2.61, 95% CI: 1.69-4.03), former smoking (OR: 1.79, 95% CI: 1.15-2.79), and regular inhaled medic

关键词： Chronic obstructive pulmonary disease Influenza Pneumococcal Vaccine AECOPD

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A machine learning model for diagnosing acute pulmonary embolism and comparison with Wells score,revised Geneva score,and Years algorithm

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Chinese Medical Journal 2024年第6期137卷 676-682页

作者： Linfeng Xi Han Kang Mei Deng Wenqing Xu Feiya Xu Qian Gao Wanmu Xie Rongguo Zhang Min Liu Zhenguo Zhai Chen Wang Capital Medical University Beijing 100069China National Center for respiratory medicine State Key Laboratory of Respiratory Health and MultimorbidityNational Clinical Research Center for Respiratory DiseasesInstitute of Respiratory MedicineChinese Academy of Medical SciencesDepartment of Pulmonary and Critical Care MedicineCenter of Respiratory MedicineChina-Japan Friendship HospitalBeijing 100029China institute of Advanced Research Infervision Medical Technology Co.Ltd.Beijing 100025China Department of Radiology China-Japan Friendship HospitalBeijing 100029China Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730China Department of Radiology Peking University China-Japan Friendship School of Clinical MedicineBeijing 100191China

Background:Acute pulmonary embolism(APE)is a fatal cardiovascular disease,yet missed diagnosis and misdiagnosis often occur due to non-specific symptoms and signs.A simple,objective technique will help clinicians make a quick and precise diagnosis.In population studies,machine learning(ML)plays a critical role in characterizing cardiovascular risks,predicting outcomes,and identifying biomarkers.This work sought to develop an ML model for helping APE diagnosis and compare it against current clinical probability assessment models.Methods:This is a single-center retrospective study.Patients with suspected APE were continuously enrolled and randomly divided into two groups including training and testing sets.A total of 8 ML models,including random forest(RF),Naïve Bayes,decision tree,K-nearest neighbors,logistic regression,multi-layer perceptron,support vector machine,and gradient boosting decision tree were developed based on the training set to diagnose APE.Thereafter,the model with the best diagnostic performance was selected and evaluated against the current clinical assessment strategies,including the Wells score,revised Geneva score,and Years algorithm.Eventually,the ML model was internally validated to assess the diagnostic performance using receiver operating characteristic(ROC)analysis.Results:The ML models were constructed using eight clinical features,including D-dimer,cardiac troponin T(cTNT),arterial oxygen saturation,heart rate,chest pain,lower limb pain,hemoptysis,and chronic heart failure.Among eight ML models,the RF model achieved the best performance with the highest area under the curve(AUC)(AUC=0.774).Compared to the current clinical assessment strategies,the RF model outperformed the Wells score(P=0.030)and was not inferior to any other clinical probability assessment strategy.The AUC of the RF model for diagnosing APE onset in internal validation set was 0.726.Conclusions:Based on RF algorithm,a novel prediction model was finally constructed for APE diagnosis.When compared to the current clinica

关键词： Acute pulmonary embolism Machine learning Wells score Revised Geneva score Years algorithm

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EGFR-mutant non-small cell lung cancer patients harboring CDK4 amplification show favorable response to afatinib: Two case reports

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中华医学杂志(英文版) 2024年第12期137卷 2024 May 21页

作者： Zhan Shuting Cheng Bo Liu Xiwen Li Jianfu Bai Ge Cai Qi Wang Huiting Xiang Yang Li Chunyan He Jianxing Liang Wenhua Department of Thoracic Surgery and Oncology The First Affiliated Hospital of Guangzhou Medical University &amp Guangzhou institute of respiratory Health State Key Laboratory of Respiratory Disease &amp National Clinical Research Center for respiratory Disease Guangzhou Guangdong China National Center for respiratory medicine State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory Diseases Guangzhou Institute of Respiratory Health &amp The First Affiliated Hospital of Guangzhou Medical University Guangzhou Guangdong China Southern Medical University Guangzhou Guangdong China Department of respiratory and Critical Care medicine The Tenth Affiliated Hospital of Southern Medical University Dongguan Guangdong China.

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PD-L1-driven efficient enrichment and elimination of circulating cancer cells by magnetic MoSe_(2) nanosheet

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Nano Research 2024年第5期17卷 4350-4358页

作者： Hongjie Huang Binhua Zou Shanlin Zhu Xingchen Zhang Jiale Huang Jinlin Wang Xiaoling Li Tianfeng Chen The Sixth Affiliated Hospital Jinan UniversityDongguan 523566China Department of Chemistry Institute of Food Safety and NutritionJinan UniversityGuangzhou 510632China Department of Rehabilitation medicine Nanfang HospitalSouthern Medical UniversityGuangzhou 510515China Pulmonary and Critical Care medicine Guangzhou Institute of Respiratory HealthNational Clinical Research Center for Respiratory DiseaseNational Center for Respiratory MedicineState Key Laboratory of Respiratory DiseasesThe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510120China

Circulating tumor cells(CTCs)are important biomarkers in the development and progression of lung cancer because they can reach other organs through the blood circulation and form distant metastases,exacerbating lung cancer progression.The presence of CTCs is also the main reason for the failure of nanomedicine-based lung cancer treatments.Therefore,magnetic MoSe_(2) nanosheets loaded with programmed death-ligand 1(PD-L1),named PD-L1-MFP NS,were employed here to precisely capture lung cancer CTCs in the blood circulation through the tumor-targeting effect of PD-L1 killing CTCs with highly effective photothermal therapy(PTT).In addition,by increasing the expression of cytomegalovirus UL16-binding protein(ULBP)ligands on tumor cells,the PD-L1-MFP NS further activated natural killer(NK)cells and triggered NK cell-induced cancer immunotherapy,thereby enhancing the overall tumor-killing effect.In summary,this material designed to capture CTCs provides a substantial advancement for personalized PTT-triggered immunotherapy and has great clinical translational potential.

关键词： circulating tumor cells selenide photothermal therapy(PTT) natural killer(NK)cell immunotherapy

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Formulation of international standards of Chinese medicine technology:clinical practice guide of Chinese medicine for cough

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Journal of Traditional Chinese medicine 2024年第2期44卷 396-402页

作者： FANG Hanyu HONG Zheng LI Deming ZHANG Hongchun SHI Yihang LI Xiaojuan SUN Zengtao CHEN Wei ZHANG Chuchu ZU Yaqi Beijing University of Chinese medicine Beijing 100029China Department of Traditional Chinese medicine for Pulmonary Diseases Center of Respiratory MedicineChina-Japan Friendship HospitalBeijing 100029 National Center for respiratory medicine Beijing 100029China Department of Traditional Chinese medicine for Pulmonary Diseases Center of Respiratory MedicineChina-Japan Friendship HospitalBeijing 100029China Tianjin University of Traditional Chinese medicine Tianjin 301617China Second Teaching Hospital of Tianjin University of Traditional Chinese medicine Tianjin 300250China Center for Evidence-based medicine Beijing University of Chinese MedicineBeijing 100029China institute of Information on Traditional Chinese medicine China Academy of Chinese Medical SciencesBeijing 100700China

OBJECTIVE:To formulate the first clinical practice guideline for the treatment of cough using Chinese medicine based on the grading of recommendations assessment,development,and evaluation(GRADE)systematic approach,including clinical evidence,evaluation of ancient literature,and expert consensus.METHODS:In the process of development,the regulation of"evidence-based,consensus-assisted,and empirical"was followed,and a comprehensive systematic approach of recommendation assessment,GRADE,evidence-based evaluation,expert consensus,and the Delphi method was used.In the process of guideline development,evidence-based evaluation of ancient literature was included for the first time,and clinical evidence was fully integrated with clinical expert consensus.RESULTS:The clinical practice guidelines for the treatment of cough with Chinese herbal medicine were developed after a comprehensive consideration of evidence-based evaluation and expert opinions.The guideline recommendations focused on recommending herbal compound decoctions and Chinese patent medicines for cough in different conditions.Based on the GRADE systematic approach,we conducted an evidence-based evaluation of the recommended Chinese patent medicines one by one;meanwhile,the expert consensus method was used to unify the recommendations of both.CONCLUSION:Based on clinical evidence,ancient literature evaluation,and expert consensus,a clinical practice guideline for Traditional Chinese medicine(TCM)in the treatment of cough was developed,providing the first current clinical practice guideline for domestic and foreign TCM and Western medicine practitioners,especially respiratory professionals at home and abroad.

关键词： medicine Chinese Traditional clinical practice cough practice guide international standard

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