W. Stringer, J. Porszasz, S. Bhatt, M. McCormack, B. Make, R. Casaburi
{"title":"慢性阻塞性肺病遗传流行病学研究的生理学见解。","authors":"W. Stringer, J. Porszasz, S. Bhatt, M. McCormack, B. Make, R. Casaburi","doi":"10.15326/jcopdf.6.3.2019.0128","DOIUrl":null,"url":null,"abstract":"COPD Genetic Epidemiology Study (COPDGene®) manuscripts have provided important insights into chronic obstructive pulmonary disease (COPD) pathophysiology and outcomes, including a better understanding of COPD phenotypes relating computed tomography (CT) anatomic data to spirometric and patient-reported outcomes. Spirometry significantly underdiagnoses smoking-induced lung disease, and there is a marked improvement in sensitivity and specificity with CT scanning. This review also highlights the COPDGene® exploration of specific spirometry phenotypes (e.g.,PRISm), contributors to spirometric decline, composite physiologic measures, asthma-COPD overlap (ACO) syndrome, consequences of bronchodilator responsiveness, newer methods to assess small airway dysfunction, and spirometric correlates of comorbid diseases such as obesity and diabetes.","PeriodicalId":10249,"journal":{"name":"Chronic obstructive pulmonary diseases","volume":"152 1","pages":"256-266"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Physiologic Insights from the COPD Genetic Epidemiology Study.\",\"authors\":\"W. Stringer, J. Porszasz, S. Bhatt, M. McCormack, B. Make, R. Casaburi\",\"doi\":\"10.15326/jcopdf.6.3.2019.0128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"COPD Genetic Epidemiology Study (COPDGene®) manuscripts have provided important insights into chronic obstructive pulmonary disease (COPD) pathophysiology and outcomes, including a better understanding of COPD phenotypes relating computed tomography (CT) anatomic data to spirometric and patient-reported outcomes. Spirometry significantly underdiagnoses smoking-induced lung disease, and there is a marked improvement in sensitivity and specificity with CT scanning. This review also highlights the COPDGene® exploration of specific spirometry phenotypes (e.g.,PRISm), contributors to spirometric decline, composite physiologic measures, asthma-COPD overlap (ACO) syndrome, consequences of bronchodilator responsiveness, newer methods to assess small airway dysfunction, and spirometric correlates of comorbid diseases such as obesity and diabetes.\",\"PeriodicalId\":10249,\"journal\":{\"name\":\"Chronic obstructive pulmonary diseases\",\"volume\":\"152 1\",\"pages\":\"256-266\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chronic obstructive pulmonary diseases\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15326/jcopdf.6.3.2019.0128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chronic obstructive pulmonary diseases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15326/jcopdf.6.3.2019.0128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Physiologic Insights from the COPD Genetic Epidemiology Study.
COPD Genetic Epidemiology Study (COPDGene®) manuscripts have provided important insights into chronic obstructive pulmonary disease (COPD) pathophysiology and outcomes, including a better understanding of COPD phenotypes relating computed tomography (CT) anatomic data to spirometric and patient-reported outcomes. Spirometry significantly underdiagnoses smoking-induced lung disease, and there is a marked improvement in sensitivity and specificity with CT scanning. This review also highlights the COPDGene® exploration of specific spirometry phenotypes (e.g.,PRISm), contributors to spirometric decline, composite physiologic measures, asthma-COPD overlap (ACO) syndrome, consequences of bronchodilator responsiveness, newer methods to assess small airway dysfunction, and spirometric correlates of comorbid diseases such as obesity and diabetes.