Chronic obstructive pulmonary disease(COPD)is a complex condition marked by considerable interindividual heterogeneity.Comorbidities exacerbate this variability,worsening disease severity and reducing health-related q...Chronic obstructive pulmonary disease(COPD)is a complex condition marked by considerable interindividual heterogeneity.Comorbidities exacerbate this variability,worsening disease severity and reducing health-related quality of life(HRQoL).Despite the high prevalence of COPD in China,COPD patient clusters remain poorly characterized.This study aimed to identify and validate clusters of Chinese patients with COPD,characterized primarily by comorbidity profiles,using cluster analysis.This cross-sectional,multicenter cohort study used data from the Chinese Enjoying Breathing Program(2020–2023).HRQoL was measured using the EuroQol five dimension(EQ-5D).Dimension reduction was performed via multiple correspondence analysis on 31 variables,including indicators of 27 comorbidities and four sociodemographic or health-related characteristics.Unsupervised machine learning algorithms,K-means++,and hierarchical clustering identified distinct clusters.Robustness was assessed using random forest classification.Logistic regression evaluated the association between cluster membership and EQ-5D outcomes.Among 11145 patients,59.4%had comorbidities.Four clusters emerged:young male smokers,biomass-exposed females,respiratory comorbidity,and elderly multimorbid.The last two clusters had notably lower HRQoL.Cluster analysis identified four clinically meaningful COPD patient clusters based on comorbidities and risk profiles,each with distinct HRQoL outcomes.These findings support targeted public health interventions and integrated care strategies for COPD management.展开更多
Most studies of coronavirus disease 2019(COVID-19)progression have focused on the transfer of patients within secondary or tertiary care hospitals from regular wards to intensive care units.Little is known about the r...Most studies of coronavirus disease 2019(COVID-19)progression have focused on the transfer of patients within secondary or tertiary care hospitals from regular wards to intensive care units.Little is known about the risk factors predicting the progression to severe COVID-19 among patients in community iso-lation,who are either asymptomatic or suffer from only mild to moderate symptoms.Using a multivari-able competing risk survival analysis,we identify several important predictors of progression to severe COVID-19—rather than to recovery—among patients in the largest community isolation center in Wuhan,China from 6 February 2020(when the center opened)to 9 March 2020(when it closed).All patients in community isolation in Wuhan were either asymptomatic or suffered from mild to moderate COVID-19 symptoms.We performed competing risk survival analysis on time-to-event data from a cohort study of all COVID-19 patients(n=1753)in the isolation center.The potential predictors we inves-tigated were the routine patient data collected upon admission to the isolation center:age,sex,respira-tory symptoms,gastrointestinal symptoms,general symptoms,and computed tomography(CT)scan signs.The main outcomes were time to severe COVID-19 or recovery.The factors predicting progression to severe COVID-19 were:male sex(hazard ratio(HR)=1.29,95%confidence interval(CI)1.04–1.58,p=0.018),young and old age,dyspnea(HR=1.58,95%CI 1.24–2.01,p<0.001),and CT signs of ground-glass opacity(HR=1.39,95%CI 1.04–1.86,p=0.024)and infiltrating shadows(HR=1.84,95%CI 1.22–2.78,p=0.004).The risk of progression was found to be lower among patients with nausea or vomiting(HR=0.53,95%CI 0.30–0.96,p=0.036)and headaches(HR=0.54,95%CI 0.29–0.99,p=0.046).Our results suggest that several factors that can be easily measured even in resource-poor set-tings(dyspnea,sex,and age)can be used to identify mild COVID-19 patients who are at increased risk of disease progression.Looking for CT signs of ground-glass opacity and infiltrating shadows may be an affordable option to support triage decisions in resource-rich settings.Common and unspecific symptoms(headaches,nausea,and vomiting)are likely to have led to the identification and subsequent community isolation of COVID-19 patients who were relatively unlikely to deteriorate.Future public health and clinical guidelines should build on this evidence to improve the screening,triage,and monitoring of COVID-19 patients who are asymtomatic or suffer from mild to moderate symptoms.展开更多
Background:Understanding willingness to undergo pulmonary function tests(PFTs)and the factors associated with poor uptake of PFTs is crucial for improving early detection and treatment of chronic obstructive pulmonary...Background:Understanding willingness to undergo pulmonary function tests(PFTs)and the factors associated with poor uptake of PFTs is crucial for improving early detection and treatment of chronic obstructive pulmonary disease(COPD).This study aimed to understand willingness to undergo PFTs among high-risk populations and identify any barriers that may contribute to low uptake of PFTs.Methods:We collected data from participants in the"Happy Breathing Program"in China.Participants who did not follow physicians’recommendations to undergo PFTs were invited to complete a survey regarding their willingness to undergo PFTs and their reasons for not undergoing PFTs.We estimated the proportion of participants who were willing to undergo PFTs and examined the various reasons for participants to not undergo PFTs.We conducted univariable and multivariable logistic regressions to analyze the impact of individual-level factors on willingness to undergo PFTs.Results:A total of 8475 participants who had completed the survey on willingness to undergo PFTs were included in this study.Out of these participants,7660(90.4%)were willing to undergo PFTs.Among those who were willing to undergo PFTs but actually did not,the main reasons for not doing so were geographical inaccessibility(n=3304,43.1%)and a lack of trust in primary healthcare institutions(n=2809,36.7%).Among the 815 participants who were unwilling to undergo PFTs,over half(n=447,54.8%)believed that they did not have health problems and would only consider PFTs when they felt unwell.In the multivariable regression,individuals who were≤54 years old,residing in rural townships,with a secondary educational level,with medical reimbursement,still working,with occupational exposure to dust,and aware of the abbreviation"COPD"were more willing to undergo PFTs.Conclusions:Willingness to undergo PFTs was high among high-risk populations.Policymakers may consider implementing strategies such as providing financial incentives,promoting education,and establishing community-based programs to enhance the utilization of PFTs.展开更多
基金supported by the Ministry of Science and Tech-nology of the People’s Republic of China(2023ZD0506000)the CAMS Innovation Fund for Medical Sciences(ClFMS,2023-I2M-2-001)the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences(2022-ZHCH330-01).The statements made and views expressed are solely the responsibility of the authors.
文摘Chronic obstructive pulmonary disease(COPD)is a complex condition marked by considerable interindividual heterogeneity.Comorbidities exacerbate this variability,worsening disease severity and reducing health-related quality of life(HRQoL).Despite the high prevalence of COPD in China,COPD patient clusters remain poorly characterized.This study aimed to identify and validate clusters of Chinese patients with COPD,characterized primarily by comorbidity profiles,using cluster analysis.This cross-sectional,multicenter cohort study used data from the Chinese Enjoying Breathing Program(2020–2023).HRQoL was measured using the EuroQol five dimension(EQ-5D).Dimension reduction was performed via multiple correspondence analysis on 31 variables,including indicators of 27 comorbidities and four sociodemographic or health-related characteristics.Unsupervised machine learning algorithms,K-means++,and hierarchical clustering identified distinct clusters.Robustness was assessed using random forest classification.Logistic regression evaluated the association between cluster membership and EQ-5D outcomes.Among 11145 patients,59.4%had comorbidities.Four clusters emerged:young male smokers,biomass-exposed females,respiratory comorbidity,and elderly multimorbid.The last two clusters had notably lower HRQoL.Cluster analysis identified four clinically meaningful COPD patient clusters based on comorbidities and risk profiles,each with distinct HRQoL outcomes.These findings support targeted public health interventions and integrated care strategies for COPD management.
基金supported by the Alexander von Humboldt Foundation in Germany and the Bill & Melinda Gates Foundation (Project INV-006261)supported by the National Center for Advancing Translational Sciences of the National Institutes of Health (KL2TR003143)+4 种基金supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor awardfunded by the German Federal Ministry of Education and Research, the European Union’s Research and Innovation Programme Horizon 2020the European & Developing Countries Clinical Trials Partnership (EDCTP)supported by the Sino-German Center for Research Promotion (Project C-0048), which is funded by the German Research Foundation (DFG)the National Natural Science Foundation of China (NSFC)
文摘Most studies of coronavirus disease 2019(COVID-19)progression have focused on the transfer of patients within secondary or tertiary care hospitals from regular wards to intensive care units.Little is known about the risk factors predicting the progression to severe COVID-19 among patients in community iso-lation,who are either asymptomatic or suffer from only mild to moderate symptoms.Using a multivari-able competing risk survival analysis,we identify several important predictors of progression to severe COVID-19—rather than to recovery—among patients in the largest community isolation center in Wuhan,China from 6 February 2020(when the center opened)to 9 March 2020(when it closed).All patients in community isolation in Wuhan were either asymptomatic or suffered from mild to moderate COVID-19 symptoms.We performed competing risk survival analysis on time-to-event data from a cohort study of all COVID-19 patients(n=1753)in the isolation center.The potential predictors we inves-tigated were the routine patient data collected upon admission to the isolation center:age,sex,respira-tory symptoms,gastrointestinal symptoms,general symptoms,and computed tomography(CT)scan signs.The main outcomes were time to severe COVID-19 or recovery.The factors predicting progression to severe COVID-19 were:male sex(hazard ratio(HR)=1.29,95%confidence interval(CI)1.04–1.58,p=0.018),young and old age,dyspnea(HR=1.58,95%CI 1.24–2.01,p<0.001),and CT signs of ground-glass opacity(HR=1.39,95%CI 1.04–1.86,p=0.024)and infiltrating shadows(HR=1.84,95%CI 1.22–2.78,p=0.004).The risk of progression was found to be lower among patients with nausea or vomiting(HR=0.53,95%CI 0.30–0.96,p=0.036)and headaches(HR=0.54,95%CI 0.29–0.99,p=0.046).Our results suggest that several factors that can be easily measured even in resource-poor set-tings(dyspnea,sex,and age)can be used to identify mild COVID-19 patients who are at increased risk of disease progression.Looking for CT signs of ground-glass opacity and infiltrating shadows may be an affordable option to support triage decisions in resource-rich settings.Common and unspecific symptoms(headaches,nausea,and vomiting)are likely to have led to the identification and subsequent community isolation of COVID-19 patients who were relatively unlikely to deteriorate.Future public health and clinical guidelines should build on this evidence to improve the screening,triage,and monitoring of COVID-19 patients who are asymtomatic or suffer from mild to moderate symptoms.
基金funding from the Strategic Research and Consulting Project of the Chinese Academy of Engineering(No.2022-XBZD-14)funding from the CAMS Innovation Fund for Medical Sciences(CIFMS)(No.2021-I2M-1-049).
文摘Background:Understanding willingness to undergo pulmonary function tests(PFTs)and the factors associated with poor uptake of PFTs is crucial for improving early detection and treatment of chronic obstructive pulmonary disease(COPD).This study aimed to understand willingness to undergo PFTs among high-risk populations and identify any barriers that may contribute to low uptake of PFTs.Methods:We collected data from participants in the"Happy Breathing Program"in China.Participants who did not follow physicians’recommendations to undergo PFTs were invited to complete a survey regarding their willingness to undergo PFTs and their reasons for not undergoing PFTs.We estimated the proportion of participants who were willing to undergo PFTs and examined the various reasons for participants to not undergo PFTs.We conducted univariable and multivariable logistic regressions to analyze the impact of individual-level factors on willingness to undergo PFTs.Results:A total of 8475 participants who had completed the survey on willingness to undergo PFTs were included in this study.Out of these participants,7660(90.4%)were willing to undergo PFTs.Among those who were willing to undergo PFTs but actually did not,the main reasons for not doing so were geographical inaccessibility(n=3304,43.1%)and a lack of trust in primary healthcare institutions(n=2809,36.7%).Among the 815 participants who were unwilling to undergo PFTs,over half(n=447,54.8%)believed that they did not have health problems and would only consider PFTs when they felt unwell.In the multivariable regression,individuals who were≤54 years old,residing in rural townships,with a secondary educational level,with medical reimbursement,still working,with occupational exposure to dust,and aware of the abbreviation"COPD"were more willing to undergo PFTs.Conclusions:Willingness to undergo PFTs was high among high-risk populations.Policymakers may consider implementing strategies such as providing financial incentives,promoting education,and establishing community-based programs to enhance the utilization of PFTs.
