机构：[1]State Key Laboratory of Respiratory Diseases, National Center for Respiratory Medicine, Guangdong Key Laboratory of Vascular Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China[2]Department of Pulmonary Circulation, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China[3]Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China北京朝阳医院[4]Department of Cardiology, Gansu Provincial Hospital, Lanzhou, Gansu, China[5]The First People’s Hospital of Yunnan, Kunming, Yunnan, China[6]Department of Neurology, Guangzhou Women and Children’s Medical Center, Guangzhou, Guangdong, China[7]Department of Pulmonary and Critical Care Medicine, Shenzhen Institute of Respiratory Disease, Shenzhen Institute of Respiratory Disease,Shenzhen People’s Hospital ( The Second Clinical Medical College,Jinan University深圳市康宁医院深圳市人民医院深圳医学信息中心[8]The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, China[9]GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China[10]Department of Pulmonary and Critical Care Medicine, The Affiliated Hospital of Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, China[11]Heart, Lung and Vessels Center, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China四川省人民医院[12]Guangzhou Laboratory, Guangzhou International Bio Island, Guangzhou, Guangdong, China[13]Section of Physiology, Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego, La Jolla, California, USA
BackgroundPatients with pulmonary hypertension (PH) and chronic obstructive pulmonary disease (COPD) have an increased risk of disease exacerbation and decreased survival. We aimed to develop and validate a non-invasive nomogram for predicting COPD associated with severe PH and a prognostic nomogram for patients with COPD and concurrent PH (COPD-PH). MethodsThis study included 535 patients with COPD-PH from six hospitals. A multivariate logistic regression analysis was used to analyse the risk factors for severe PH in patients with COPD and a multivariate Cox regression was used for the prognostic factors of COPD-PH. Performance was assessed using calibration, the area under the receiver operating characteristic curve and decision analysis curves. Kaplan-Meier curves were used for a survival analysis. The nomograms were developed as online network software. ResultsTricuspid regurgitation velocity, right ventricular diameter, N-terminal pro-brain natriuretic peptide (NT-proBNP), the red blood cell count, New York Heart Association functional class and sex were non-invasive independent variables of severe PH in patients with COPD. These variables were used to construct a risk assessment nomogram with good discrimination. NT-proBNP, mean pulmonary arterial pressure, partial pressure of arterial oxygen, the platelet count and albumin were independent prognostic factors for COPD-PH and were used to create a predictive nomogram of overall survival rates. ConclusionsThe proposed nomograms based on a large sample size of patients with COPD-PH could be used as non-invasive clinical tools to enhance the risk assessment of severe PH in patients with COPD and for the prognosis of COPD-PH. Additionally, the online network has the potential to provide artificial intelligence-assisted diagnosis and treatment.
基金：
National Natural Science Foundation of China; National Key R&D Program of China [2022YFE0131500, 2016YFC1304102, 2018YFC1311900]; R&D Program of Guangzhou National Laboratory [GZNL2023A02013]; Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program [2017BT01S155]; Guangdong Department of Science and Technology [2024A1515011208, 2023A1515010443, 2022A1515012052]; Basic Science and Application of Guangzhou Science and Technology Plan [202201010069, 202102020019]; Guangzhou Municipal Science and Technology Bureau Guangzhou Key Research and Development Program [2023B03J1387]; Guangzhou Municipal Science and Technology Bureau Municipal Schools (Institutes) [202201020401]; Independent Project of State Key Laboratory of Respiratory Disease [SKLRD-Z-202101, SKLRD-Z-202313, YKD2021MS003]; Project of Shanghai Pulmonary Hospital Clinical Research [FKLY 20005]; Reform and Development Program of Beijing Institute of Respiratory Medicine [2022-03]; Open Research Funds from The Sixth Affiliated Hospital of Guangzhou Medical University (Qingyuan People's Hospital) [202201-101]; Key Laboratory Development Projects of Department of Science and Technology of Yunnan Province [2017ZDKFKTO02]; Guangzhou Medical University Student Innovation Enhancement Program [01-408-2201096]; [82370063]; [82170069]; [82120108001]; [82241012]; [8224100322]; [82000045]
第一作者机构：[1]State Key Laboratory of Respiratory Diseases, National Center for Respiratory Medicine, Guangdong Key Laboratory of Vascular Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
共同第一作者：
通讯作者：
通讯机构：[1]State Key Laboratory of Respiratory Diseases, National Center for Respiratory Medicine, Guangdong Key Laboratory of Vascular Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China[4]Department of Cardiology, Gansu Provincial Hospital, Lanzhou, Gansu, China[11]Heart, Lung and Vessels Center, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China[12]Guangzhou Laboratory, Guangzhou International Bio Island, Guangzhou, Guangdong, China[13]Section of Physiology, Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego, La Jolla, California, USA[*1]State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 151 Yanjiang Road, Guangzhou, Guangdong, 510120, China.[*2]Heart, Lung and Vessels Center, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610072, China.
推荐引用方式(GB/T 7714)：
Zhou Dansha,Liu Chunli,Wang Lan,et al.Prediction of clinical risk assessment and survival in chronic obstructive pulmonary disease with pulmonary hypertension[J].CLINICAL AND TRANSLATIONAL MEDICINE.2024,14(6):doi:10.1002/ctm2.1702.
APA：
Zhou, Dansha,Liu, Chunli,Wang, Lan,Li, Jifeng,Zhao, Yating...&Chen, Yuqin.(2024).Prediction of clinical risk assessment and survival in chronic obstructive pulmonary disease with pulmonary hypertension.CLINICAL AND TRANSLATIONAL MEDICINE,14,(6)
MLA：
Zhou, Dansha,et al."Prediction of clinical risk assessment and survival in chronic obstructive pulmonary disease with pulmonary hypertension".CLINICAL AND TRANSLATIONAL MEDICINE 14..6(2024)
