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Prognostic marker for severe acute exacerbation of chronic obstructive pulmonary disease: analysis of diffusing capacity of the lung for carbon monoxide (D-LCO) and forced expiratory volume in one second (FEV1)

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dc.contributor.authorChoi, Juwhan-
dc.contributor.authorSim, Jae Kyeom-
dc.contributor.authorOh, Jee Youn-
dc.contributor.authorLee, Young Seok-
dc.contributor.authorHur, Gyu Young-
dc.contributor.authorLee, Sung Yong-
dc.contributor.authorShim, Jae Jeong-
dc.contributor.authorRhee, Chin Kook-
dc.contributor.authorMin, Kyung Hoon-
dc.date.accessioned2021-11-19T23:40:40Z-
dc.date.available2021-11-19T23:40:40Z-
dc.date.created2021-08-30-
dc.date.issued2021-05-06-
dc.identifier.issn1471-2466-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/128050-
dc.description.abstractBackground It is important to assess the prognosis of patients with chronic obstructive pulmonary disease (COPD) and acute exacerbation of COPD (AECOPD). Recently, it was suggested that diffusing capacity of the lung for carbon monoxide (D-LCO) should be added to multidimensional tools for assessing COPD. This study aimed to compare the D-LCO and forced expiratory volume in one second (FEV1) to identify better prognostic factors for admitted patients with AECOPD. Methods We retrospectively analyzed 342 patients with AECOPD receiving inpatient treatment. We classified 342 severe AECOPD patients by severity of D-LCO and FEV1 (<= vs. > 50% predicted). We tested the association of FEV1 and D-LCO with the following outcomes: in-hospital mortality, need for mechanical ventilation, need for intensive care unit (ICU) care. We analyzed the prognostic factors by multivariate analysis using logistic regression. In addition, we conducted a correlation analysis and receiver operating characteristic (ROC) curve analysis. Results In multivariate analyses, D-LCO was associated with mortality (odds ratio = 4.408; 95% CI 1.070-18.167; P = 0.040) and need for mechanical ventilation (odds ratio = 2.855; 95% CI 1.216-6.704; P = 0.016) and ICU care (odds ratios = 2.685; 95% CI 1.290-5.590; P = 0.008). However, there was no statistically significant difference in mortality rate when using FEV1 classification (P = 0.075). In multivariate linear regression analyses, D-LCO (B = - 0.542 +/- 0.121, P < 0.001) and FEV1 (B = - 0.106 +/- 0.106, P = 0.006) were negatively associated with length of hospital stay. In addition, D-LCO showed better predictive ability than FEV1 in ROC curve analysis. The area under the curve (AUC) of D-LCO was greater than 0.68 for all prognostic factors, and in contrast, the AUC of FEV1 was less than 0.68. Conclusion D-LCO was likely to be as good as or better prognostic marker than FEV1 in severe AECOPD.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherBMC-
dc.subjectGEORGES RESPIRATORY QUESTIONNAIRE-
dc.subjectRISK-
dc.subjectCOPD-
dc.subjectSYMPTOMS-
dc.subjectINDEX-
dc.titlePrognostic marker for severe acute exacerbation of chronic obstructive pulmonary disease: analysis of diffusing capacity of the lung for carbon monoxide (D-LCO) and forced expiratory volume in one second (FEV1)-
dc.typeArticle-
dc.contributor.affiliatedAuthorOh, Jee Youn-
dc.contributor.affiliatedAuthorShim, Jae Jeong-
dc.contributor.affiliatedAuthorMin, Kyung Hoon-
dc.identifier.doi10.1186/s12890-021-01519-1-
dc.identifier.scopusid2-s2.0-85105218870-
dc.identifier.wosid000656231600001-
dc.identifier.bibliographicCitationBMC PULMONARY MEDICINE, v.21, no.1-
dc.relation.isPartOfBMC PULMONARY MEDICINE-
dc.citation.titleBMC PULMONARY MEDICINE-
dc.citation.volume21-
dc.citation.number1-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaRespiratory System-
dc.relation.journalWebOfScienceCategoryRespiratory System-
dc.subject.keywordPlusGEORGES RESPIRATORY QUESTIONNAIRE-
dc.subject.keywordPlusRISK-
dc.subject.keywordPlusCOPD-
dc.subject.keywordPlusSYMPTOMS-
dc.subject.keywordPlusINDEX-
dc.subject.keywordAuthorCOPD-
dc.subject.keywordAuthorD-LCO-
dc.subject.keywordAuthorFEV1-
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