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COPD Hospitalization Risk Increased with Distinct Patterns of Multiple Systems Comorbidities Unveiled by Network Modeling.
Lee, Young Ji; Boyd, Andrew D; Li, Jianrong John; Gardeux, Vincent; Kenost, Colleen; Saner, Don; Li, Haiquan; Abraham, Ivo; Krishnan, Jerry A; Lussier, Yves A.
Afiliação
  • Lee YJ; Department of Medicine, University of Illinois at Chicago, Chicago, IL.
  • Boyd AD; Institute for Translational Health Informatics, University of Illinois at Chicago, Chicago, IL ; Departments of Biomedical and Health Information Sciences, University of Illinois at Chicago, Chicago, IL ; University of Illinois Hospital and Health Science System, University of Illinois at Chicago, C
  • Li JJ; Department of Medicine, The University of Arizona, Tucson, AZ, USA.
  • Gardeux V; Department of Medicine, The University of Arizona, Tucson, AZ, USA.
  • Kenost C; Department of Medicine, The University of Arizona, Tucson, AZ, USA ; Biomedical Informatics Service Group, Arizona Health Science Center, The University of Arizona, Tucson, AZ, USA.
  • Saner D; Cancer Center, The University of Arizona, Tucson, AZ, USA ; Biomedical Informatics Service Group, Arizona Health Science Center, The University of Arizona, Tucson, AZ, USA.
  • Li H; Department of Medicine, The University of Arizona, Tucson, AZ, USA.
  • Abraham I; Department of Pharmacy Practice and Science, The University of Arizona, Tucson, AZ, USA.
  • Krishnan JA; Department of Medicine, University of Illinois at Chicago, Chicago, IL ; University of Illinois Hospital and Health Science System, University of Illinois at Chicago, Chicago, IL.
  • Lussier YA; Department of Medicine, The University of Arizona, Tucson, AZ, USA ; Cancer Center, The University of Arizona, Tucson, AZ, USA ; Biomedical Informatics Service Group, Arizona Health Science Center, The University of Arizona, Tucson, AZ, USA ; Interdisciplinary Program in Statistics, The University o
AMIA Annu Symp Proc ; 2014: 855-64, 2014.
Article em En | MEDLINE | ID: mdl-25954392
Earlier studies on hospitalization risk are largely based on regression models. To our knowledge, network modeling of multiple comorbidities is novel and inherently enables multidimensional scoring and unbiased feature reduction. Network modeling was conducted using an independent validation design starting from 38,695 patients, 1,446,581 visits, and 430 distinct clinical facilities/hospitals. Odds ratios (OR) were calculated for every pair of comorbidity using patient counts and compared their tendency with hospitalization rates and ED visits. Network topology analyses were performed, defining significant comorbidity associations as having OR≥5 & False-Discovery-Rate≤10(-7). Four COPD-associated comorbidity sub-networks emerged, incorporating multiple clinical systems: (i) metabolic syndrome, (ii) substance abuse and mental disorder, (iii) pregnancy-associated conditions, and (iv) fall-related injury. The latter two have not been reported yet. Features prioritized from the network are predictive of hospitalizations in an independent set (p<0.004). Therefore, we suggest that network topology is a scalable and generalizable method predictive of hospitalization.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Comorbidade / Doença Pulmonar Obstrutiva Crônica / Hospitalização Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Pregnancy Idioma: En Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Comorbidade / Doença Pulmonar Obstrutiva Crônica / Hospitalização Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Pregnancy Idioma: En Ano de publicação: 2014 Tipo de documento: Article