{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T15:51:00Z","timestamp":1788277860145,"version":"build-2803163510"},"reference-count":25,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"National key R&D plan","award":["2020YFC2003700"],"award-info":[{"award-number":["2020YFC2003700"]}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["20DZ2261200"],"award-info":[{"award-number":["20DZ2261200"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["20Z11901000"],"award-info":[{"award-number":["20Z11901000"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["20XD1401200"],"award-info":[{"award-number":["20XD1401200"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81800008"],"award-info":[{"award-number":["81800008"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81770075"],"award-info":[{"award-number":["81770075"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82041003"],"award-info":[{"award-number":["82041003"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Municipal Key Clinical Specialty","award":["shslczdzk02201"],"award-info":[{"award-number":["shslczdzk02201"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Chron Respir Dis"],"published-print":{"date-parts":[[2022,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Active targeted case-finding is a cost-effective way to identify individuals with high-risk for early diagnosis and interventions of chronic obstructive pulmonary disease (COPD). A precise and practical COPD screening instrument is needed in health care settings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We created four statistical learning models to predict the risk of COPD using a multi-center randomized cross-sectional survey database ( n = 5281). The minimal set of predictors and the best statistical learning model in identifying individuals with airway obstruction were selected to construct a new case-finding questionnaire. We validated its performance in a prospective cohort ( n = 958) and compared it with three previously reported case-finding instruments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A set of seven predictors was selected from 643 variables, including age, morning productive cough, wheeze, years of smoking cessation, gender, job, and pack-year of smoking. In four statistical learning models, generalized additive model model had the highest area under curve (AUC) value both on the developing cross-sectional data set (AUC = 0.813) and the prospective validation data set (AUC = 0.880). Our questionnaire outperforms the other three tools on the cross-sectional validation data set.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We developed a COPD case-finding questionnaire, which is an efficient and cost-effective tool for identifying high-risk population of COPD.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/14799731221116585","type":"journal-article","created":{"date-parts":[[2022,8,9]],"date-time":"2022-08-09T13:32:01Z","timestamp":1660051921000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Developing and validating a chronic obstructive pulmonary disease quick screening questionnaire using statistical learning models"],"prefix":"10.1177","volume":"19","author":[{"given":"Xiaoyue","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China"},{"name":"Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"He","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Fudan University Shanghai Cancer Center, Shanghai, China"},{"name":"Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Xu","sequence":"additional","affiliation":[{"name":"AI Center, Ping An Technology (Shenzhen) Co. Ltd, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cuicui","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China"},{"name":"Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jieqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, China"},{"name":"Department of Pharmacy, Zhongshan Hospital, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Na","family":"Li","sequence":"additional","affiliation":[{"name":"AI Center, Ping An Technology (Shenzhen) Co. Ltd, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianxian","family":"Chen","sequence":"additional","affiliation":[{"name":"AI Center, Ping An Technology (Shenzhen) Co. Ltd, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weipeng","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China"},{"name":"Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China"},{"name":"Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linlin","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China"},{"name":"Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanlin","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China"},{"name":"Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Xiao","sequence":"additional","affiliation":[{"name":"AI Center, Ping An Technology (Shenzhen) Co. 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