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      The Laboratory-Based Intermountain Validated Exacerbation (LIVE) Score Identifies Chronic Obstructive Pulmonary Disease Patients at High Mortality Risk

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          Abstract

          Background: Identifying COPD patients at high risk for mortality or healthcare utilization remains a challenge. A robust system for identifying high-risk COPD patients using Electronic Health Record (EHR) data would empower targeting interventions aimed at ensuring guideline compliance and multimorbidity management. The purpose of this study was to empirically derive, validate, and characterize subgroups of COPD patients based on routinely collected clinical data widely available within the EHR.

          Methods: Cluster analysis was used in 5,006 patients with COPD at Intermountain to identify clusters based on a large collection of clinical variables. Recursive Partitioning (RP) was then used to determine a preferred tree that assigned patients to clusters based on a parsimonious variable subset. The mortality, COPD exacerbations, and comorbidity profile of the identified groups were examined. The findings were validated in an independent Intermountain cohort and in external cohorts from the United States Veterans Affairs (VA) and University of Chicago Medicine systems.

          Measurements and Main Results: The RP algorithm identified five LIVE Scores based on laboratory values: albumin, creatinine, chloride, potassium, and hemoglobin. The groups were characterized by increasing risk of mortality. The lowest risk, LIVE Score 5 had 8% 4-year mortality vs. 56% in the highest risk LIVE Score 1 ( p < 0.001). These findings were validated in the VA cohort ( n = 83,134), an expanded Intermountain cohort ( n = 48,871) and in the University of Chicago system ( n = 3,236). Higher mortality groups also had higher COPD exacerbation rates and comorbidity rates.

          Conclusions: In large clinical datasets across different organizations, the LIVE Score utilizes existing laboratory data for COPD patients, and may be used to stratify risk for mortality and COPD exacerbations.

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          Most cited references26

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          Susceptibility to exacerbation in chronic obstructive pulmonary disease.

          Although we know that exacerbations are key events in chronic obstructive pulmonary disease (COPD), our understanding of their frequency, determinants, and effects is incomplete. In a large observational cohort, we tested the hypothesis that there is a frequent-exacerbation phenotype of COPD that is independent of disease severity. We analyzed the frequency and associations of exacerbation in 2138 patients enrolled in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study. Exacerbations were defined as events that led a care provider to prescribe antibiotics or corticosteroids (or both) or that led to hospitalization (severe exacerbations). Exacerbation frequency was observed over a period of 3 years. Exacerbations became more frequent (and more severe) as the severity of COPD increased; exacerbation rates in the first year of follow-up were 0.85 per person for patients with stage 2 COPD (with stage defined in accordance with Global Initiative for Chronic Obstructive Lung Disease [GOLD] stages), 1.34 for patients with stage 3, and 2.00 for patients with stage 4. Overall, 22% of patients with stage 2 disease, 33% with stage 3, and 47% with stage 4 had frequent exacerbations (two or more in the first year of follow-up). The single best predictor of exacerbations, across all GOLD stages, was a history of exacerbations. The frequent-exacerbation phenotype appeared to be relatively stable over a period of 3 years and could be predicted on the basis of the patient's recall of previous treated events. In addition to its association with more severe disease and prior exacerbations, the phenotype was independently associated with a history of gastroesophageal reflux or heartburn, poorer quality of life, and elevated white-cell count. Although exacerbations become more frequent and more severe as COPD progresses, the rate at which they occur appears to reflect an independent susceptibility phenotype. This has implications for the targeting of exacerbation-prevention strategies across the spectrum of disease severity. (Funded by GlaxoSmithKline; ClinicalTrials.gov number, NCT00292552.)
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            An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.

            Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and bioinformatics within the past few years. High-dimensional problems are common not only in genetics, but also in some areas of psychological research, where only a few subjects can be measured because of time or cost constraints, yet a large amount of data is generated for each subject. Random forests have been shown to achieve a high prediction accuracy in such applications and to provide descriptive variable importance measures reflecting the impact of each variable in both main effects and interactions. The aim of this work is to introduce the principles of the standard recursive partitioning methods as well as recent methodological improvements, to illustrate their usage for low and high-dimensional data exploration, but also to point out limitations of the methods and potential pitfalls in their practical application. Application of the methods is illustrated with freely available implementations in the R system for statistical computing. (c) 2009 APA, all rights reserved.
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              Prevalence and outcomes of diabetes, hypertension and cardiovascular disease in COPD.

              Chronic obstructive pulmonary disease (COPD) is associated with important chronic comorbid diseases, including cardiovascular disease, diabetes and hypertension. The present study analysed data from 20,296 subjects aged > or =45 yrs at baseline in the Atherosclerosis Risk in Communities Study (ARIC) and the Cardiovascular Health Study (CHS). The sample was stratified based on baseline lung function data, according to modified Global Initiative for Obstructive Lung Disease (GOLD) criteria. Comorbid disease at baseline and death and hospitalisations over a 5-yr follow-up were then searched for. Lung function impairment was found to be associated with more comorbid disease. In logistic regression models adjusting for age, sex, race, smoking, body mass index and education, subjects with GOLD stage 3 or 4 COPD had a higher prevalence of diabetes (odds ratio (OR) 1.5, 95% confidence interval (CI) 1.1-1.9), hypertension (OR 1.6, 95% CI 1.3-1.9) and cardiovascular disease (OR 2.4, 95% CI 1.9-3.0). Comorbid disease was associated with a higher risk of hospitalisation and mortality that was worse in people with impaired lung function. Lung function impairment is associated with a higher risk of comorbid disease, which contributes to a higher risk of adverse outcomes of mortality and hospitalisations.
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                Author and article information

                Contributors
                Journal
                Front Med (Lausanne)
                Front Med (Lausanne)
                Front. Med.
                Frontiers in Medicine
                Frontiers Media S.A.
                2296-858X
                11 June 2018
                2018
                : 5
                : 173
                Affiliations
                [1] 1Division of Pulmonary and Critical Care Medicine, Department of Medicine, Intermountain Medical Center , Murray, UT, United States
                [2] 2Division of Respiratory, Critical Care, and Sleep Medicine, Department of Medicine, University of Utah School of Medicine , Salt Lake City, UT, United States
                [3] 3Office of Research, Intermountain Healthcare , Salt Lake City, UT, United States
                [4] 4Homer Warner Center for Informatics Research , Murray, UT, United States
                [5] 5Intermountain Medical Center, Intermountain Heart Institute , Murray, UT, United States
                [6] 6Department of Biomedical Informatics, University of Utah , Salt Lake City, UT, United States
                [7] 7Section of General Internal Medicine, Department of Medicine, University of Chicago Medicine , Chicago, IL, United States
                [8] 8Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Chicago Medicine , Chicago, IL, United States
                [9] 9Kaiser Permanente Center for Health Research—Northwest , Portland, OR, United States
                [10] 10Division of Pulmonary and Critical Care Medicine, Oregon Health & Science University , Portland, OR, United States
                [11] 11Division of Pulmonary and Critical Care Medicine, San Francisco Veterans Affairs Medical Center , San Francisco, CA, United States
                [12] 12Division of Pulmonary and Critical Care Medicine, University of California, San Francisco , San Francisco, CA, United States
                Author notes

                Edited by: Mehdi Mirsaeidi, University of Miami, United States

                Reviewed by: Esmaeil Mortaz, National Research Institute Tuberculosis and Lung Diseases, Iran; Naresh Kumar, University of Miami, United States

                *Correspondence: Denitza P. Blagev denitza.blagev@ 123456imail.org

                This article was submitted to Pulmonary Medicine, a section of the journal Frontiers in Medicine

                Article
                10.3389/fmed.2018.00173
                6004514
                631c1041-5f2f-4965-8cab-c1dec36fec74
                Copyright © 2018 Blagev, Collingridge, Rea, Horne, Press, Churpek, Carey, Mularski, Zeng and Arjomandi.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 04 December 2017
                : 17 May 2018
                Page count
                Figures: 5, Tables: 2, Equations: 0, References: 45, Pages: 10, Words: 7057
                Funding
                Funded by: Intermountain Research and Medical Foundation 10.13039/100008173
                Award ID: #755
                Categories
                Medicine
                Original Research

                copd,cluster analysis,comorbidity,risk stratification,informatics,live score

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