Literature DB >> 33303555

High eosinophil counts predict decline in FEV1: results from the CanCOLD study.

Wan C Tan1, Jean Bourbeau2, Gilbert Nadeau3, Wendy Wang4, Neil Barnes5, Sarah H Landis6, Miranda Kirby4,7, James C Hogg4, Don D Sin4,8.   

Abstract

INTRODUCTION: The aim of this study was to examine the association between blood eosinophil levels and the decline in lung function in individuals aged >40 years from the general population.
METHODS: The study evaluated the eosinophil counts from thawed blood in 1120 participants (mean age 65 years) from the prospective population-based Canadian Cohort of Obstructive Lung Disease (CanCOLD) study. Participants answered interviewer-administered respiratory questionnaires and performed pre-/post-bronchodilator spirometric tests at 18-month intervals; computed tomography (CT) imaging was performed at baseline. Statistical analyses to describe the relationship between eosinophil levels and decline in forced expiratory volume in 1 s (FEV1) were performed using random mixed-effects regression models with adjustments for demographics, smoking, baseline FEV1, ever-asthma and history of exacerbations in the previous 12 months. CT measurements were compared between eosinophil subgroups using ANOVA.
RESULTS: Participants who had a peripheral eosinophil count of ≥300 cells·µL-1 (n=273) had a greater decline in FEV1 compared with those with eosinophil counts of <150 cells·µL-1 (n=430; p=0.003) (reference group) and 150-<300 cells·µL-1 (n=417; p=0.003). The absolute change in FEV1 was -32.99 mL·year-1 for participants with eosinophil counts <150 cells·µL-1; -38.78 mL·year-1 for those with 150-<300 cells·µL-1 and -67.30 mL·year-1 for participants with ≥300 cells·µL-1. In COPD, higher eosinophil count was associated with quantitative CT measurements reflecting both small and large airway abnormalities.
CONCLUSION: A blood eosinophil count of ≥300 cells·µL-1 is an independent risk factor for accelerated lung function decline in older adults and is related to undetected structural airway abnormalities.
Copyright ©ERS 2021.

Entities:  

Year:  2021        PMID: 33303555     DOI: 10.1183/13993003.00838-2020

Source DB:  PubMed          Journal:  Eur Respir J        ISSN: 0903-1936            Impact factor:   16.671


  8 in total

1.  Predictors of High Sputum Eosinophils in Chronic Obstructive Pulmonary Disease.

Authors:  Xiang Wen; Jieqi Peng; Youlan Zheng; Jiaxing Liu; Heshen Tian; Fan Wu; Zihui Wang; Huajing Yang; Zhishan Deng; Shan Xiao; Peiyu Huang; Jianwu Xu; Cuiqiong Dai; Ningning Zhao; Lifei Lu; Jianwei Dai; Bing Li; Pixin Ran; Yumin Zhou
Journal:  Chronic Obstr Pulm Dis       Date:  2022-07-29

2.  The Combined Value of Type2 Inflammatory Markers in Chronic Obstructive Pulmonary Disease.

Authors:  Yunhuan Liu; Guanhua Ma; Yan Mou; Xuanqi Liu; Wenjia Qiu; Yang Zheng; Huili Zhu; Haiyan Ge
Journal:  J Clin Med       Date:  2022-05-16       Impact factor: 4.964

3.  A multipurpose machine learning approach to predict COVID-19 negative prognosis in São Paulo, Brazil.

Authors:  Fernando Timoteo Fernandes; Tiago Almeida de Oliveira; Cristiane Esteves Teixeira; Andre Filipe de Moraes Batista; Gabriel Dalla Costa; Alexandre Dias Porto Chiavegatto Filho
Journal:  Sci Rep       Date:  2021-02-08       Impact factor: 4.379

4.  Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

Authors:  Wan Xu; Nan-Nan Sun; Hai-Nv Gao; Zhi-Yuan Chen; Ya Yang; Bin Ju; Ling-Ling Tang
Journal:  Sci Rep       Date:  2021-02-03       Impact factor: 4.379

Review 5.  Chronic obstructive pulmonary disease risk assessment tools: is one better than the others?

Authors:  Jennifer M Wang; MeiLan K Han; Wassim W Labaki
Journal:  Curr Opin Pulm Med       Date:  2022-03-01       Impact factor: 3.155

6.  Determinants of blood eosinophil levels in the general population and patients with COPD: a population-based, epidemiological study.

Authors:  Marc Miravitlles; Juan José Soler-Cataluña; Joan B Soriano; Francisco García-Río; Pilar de Lucas; Inmaculada Alfageme; Ciro Casanova; José Miguel Rodríguez González-Moro; M Guadalupe Sánchez-Herrero; Julio Ancochea; Borja G Cosío
Journal:  Respir Res       Date:  2022-03-05

7.  Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes.

Authors:  Shiyang Ma; James Dalgleish; Justin Lee; Chen Wang; Linxi Liu; Richard Gill; Joseph D Buxbaum; Wendy K Chung; Hugues Aschard; Edwin K Silverman; Michael H Cho; Zihuai He; Iuliana Ionita-Laza
Journal:  Proc Natl Acad Sci U S A       Date:  2021-11-23       Impact factor: 12.779

8.  Low Eosinophil Phenotype Predicts Noninvasive Mechanical Ventilation Use in Patients with Hospitalized Exacerbations of COPD.

Authors:  Tingting Wei; Xiaocen Wang; Ke Lang; Cuicui Chen; Yansha Song; Jinlong Luo; Zhaolin Gu; Xianglin Hu; Dong Yang
Journal:  J Inflamm Res       Date:  2022-02-24
  8 in total

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