Prediction of clinical risk assessment and survival in chronic obstructive pulmonary disease with pulmonary hypertension

Author:

Zhou Dansha1,Liu Chunli1,Wang Lan2,Li JiFeng3,Zhao Yating4,Deng Zheng5,Hou Chi16,Fu Yingyun7,Jiang Qian1,Lai Ning1,Zhang Rui2,Feng Weici1,Gao Chuhui1,Li Xiang1,Jiang Mei1,Fu Xin8,Chen Jiyuan1,Hong Wei18,Xu Lei9,He Wenjun1,Liu Jinming2,Yang YuanHua3,Lu Wenju1,Zhong Nanshan1,Cao Yunshan410ORCID,Wang Jian11112ORCID,Chen Yuqin112ORCID

Affiliation:

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

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;The First Affiliated Hospital, Southern University of Science and Technology) Shenzhen Guangdong China

8. GMU‐GIBH Joint School of Life Sciences Guangzhou Medical University Guangzhou Guangdong China

9. Department of Pulmonary and Critical Care Medicine The Affiliated Hospital of Inner Mongolia Medical University, Inner Mongolia Autonomous Region Hohhot China

10. Heart, Lung and Vessels Center, Sichuan Provincial People's Hospital University of Electronic Science and Technology of China Chengdu Sichuan China

11. Guangzhou Laboratory Guangzhou International Bio Island Guangzhou Guangdong China

12. Section of Physiology, Division of Pulmonary, Critical Care and Sleep Medicine University of California, San Diego La Jolla California USA

Abstract

AbstractBackgroundPatients 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.Highlights A multicentre study with a large sample of chronic obstructive pulmonary disease (COPD) patients diagnosed with PH through right heart catheterisation. A non‐invasive online clinical tool for assessing severe pulmonary hypertension (PH) in COPD. The first risk assessment tool was established for Chinese patients with COPD–PH.

Funder

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Natural Science Foundation of Guangdong Province

Guangzhou Municipal Science and Technology Bureau

State Key Laboratory of Respiratory Disease

Inner Mongolia Medical University

Shanghai Pulmonary Hospital

Yunnan Provincial Science and Technology Department

Guangzhou Medical University

Publisher

Wiley

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