{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T18:06:13Z","timestamp":1779818773165,"version":"3.53.1"},"reference-count":50,"publisher":"Public Library of Science (PLoS)","issue":"5","license":[{"start":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T00:00:00Z","timestamp":1779753600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Dong-A University Research Fund"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide, ranking eighth in disability-adjusted life years (DALYs). Patients with COPD frequently exhibit multimorbidity\u2014including cardiovascular disease, cerebrovascular disease, diabetes, and lung cancer. Accordingly, the Charlson Comorbidity Index (CCI) is widely used as a standard tool for comorbidity adjustment; however, as a general-purpose index, it may not fully capture disease-specific patterns of multimorbidity, underscoring the urgency for tailored approaches. Therefore, we aimed to construct a comorbidity severity adjustment model to improve the prediction of in-hospital mortality among COPD patients using large-scale registry data from the Korea Disease Control and Prevention Agency.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>This retrospective study used the Korea National Hospital Discharge In-Depth Injury Survey (KNHDIS) from 2011 to 2023, including 13,385 hospitalized COPD patients (ICD-10 code J44). All analyses accounted for the complex sample design with stratification, clustering, and sampling weights. The baseline model used multivariable logistic regression with conventional covariates, whereas the extended model incorporated comorbidity clusters derived from Apriori association rule mining to capture interconnected disease patterns. Odds ratios (OR) and 95% confidence intervals (CI) were calculated to assess determinants of in-hospital mortality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Result<\/jats:title>\n                    <jats:p>In the baseline model, advanced age, emergency admission, larger hospital size, and higher CCI scores were significantly associated with increased mortality. In the extended model with Apriori-derived clusters, additional high-risk profiles were identified: (i) septicemia with pneumonia, (ii) respiratory failure with sequelae of tuberculosis, and (iii) pulmonary heart disease with sequelae of tuberculosis. The predictive performance improved with the inclusion of comorbidity clusters (AUC 0.753 vs. 0.732), indicating that the cluster-augmented model provided superior discrimination compared with the baseline model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These findings indicate that integrating data-driven comorbidity patterns into traditional risk models enhances mortality risk stratification for COPD inpatients and may support both clinical decision-making and the development of evidence-based health policies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0348191","type":"journal-article","created":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T17:38:37Z","timestamp":1779817117000},"page":"e0348191","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Comorbidity severity adjusted model for predicting mortality in hospitalized patients with COPD"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5644-6143","authenticated-orcid":true,"given":"Ji Hyeon","family":"Seo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ji Hye","family":"Lim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,5,26]]},"reference":[{"issue":"2","key":"pone.0348191.ref001","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1097\/00063198-199903000-00003","article-title":"Worldwide epidemiology of chronic obstructive pulmonary disease","volume":"5","author":"JC Chen","year":"1999","journal-title":"Curr Opin Pulm Med"},{"issue":"9524","key":"pone.0348191.ref002","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1016\/S0140-6736(06)68770-9","article-title":"Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data","volume":"367","author":"AD Lopez","year":"2006","journal-title":"Lancet"},{"issue":"1","key":"pone.0348191.ref003","doi-asserted-by":"crossref","first-page":"47","DOI":"10.26719\/emhj.18.014","article-title":"Global prevalence of chronic obstructive pulmonary disease: systematic review and meta-analysis","volume":"25","author":"M Varmaghani","year":"2019","journal-title":"East Mediterr Health J"},{"issue":"2","key":"pone.0348191.ref004","doi-asserted-by":"crossref","first-page":"020415","DOI":"10.7189\/jogh.05.020415","article-title":"Global and regional estimates of COPD prevalence: Systematic review and meta-analysis","volume":"5","author":"D Adeloye","year":"2015","journal-title":"J Glob Health"},{"key":"pone.0348191.ref005","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/S2213-2600(17)30293-X","article-title":"Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990\u20132015: a systematic analysis for the Global Burden of Disease Study 2015","volume":"5","author":"GBD 2015 Chronic Respiratory Disease Collaborators","year":"2017","journal-title":"Lancet Respir Med"},{"issue":"12","key":"pone.0348191.ref006","doi-asserted-by":"crossref","first-page":"1185","DOI":"10.4187\/respcare.03481185","article-title":"Chronic obstructive pulmonary disease: definition and epidemiology","volume":"48","author":"DM Mannino","year":"2003","journal-title":"Respir Care"},{"key":"pone.0348191.ref007","unstructured":"Cho KS. 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