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      Prediction models for the development of COPD: a systematic review

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          Abstract

          Early identification of people at risk of developing COPD is crucial for implementing preventive strategies. We aimed to systematically review and assess the performance of all published models that predicted development of COPD. A search was conducted to identify studies that developed a prediction model for COPD development. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was followed when extracting data and appraising the selected studies. Of the 4,481 records identified, 30 articles were selected for full-text review, and only four of these were eligible to be included in the review. The only consistent predictor across all four models was a measure of smoking. Sex and age were used in most models; however, other factors varied widely. Two of the models had good ability to discriminate between people who were correctly or incorrectly classified as at risk of developing COPD. Overall none of the models were particularly useful in accurately predicting future risk of COPD, nor were they good at ruling out future risk of COPD. Further studies are needed to develop new prediction models and robustly validate them in external cohorts.

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          Most cited references 25

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          Chronic obstructive pulmonary disease in non-smokers.

          Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. Tobacco smoking is established as a major risk factor, but emerging evidence suggests that other risk factors are important, especially in developing countries. An estimated 25-45% of patients with COPD have never smoked; the burden of non-smoking COPD is therefore much higher than previously believed. About 3 billion people, half the worldwide population, are exposed to smoke from biomass fuel compared with 1.01 billion people who smoke tobacco, which suggests that exposure to biomass smoke might be the biggest risk factor for COPD globally. We review the evidence for the association of COPD with biomass fuel, occupational exposure to dusts and gases, history of pulmonary tuberculosis, chronic asthma, respiratory-tract infections during childhood, outdoor air pollution, and poor socioeconomic status.
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            Patterns of Growth and Decline in Lung Function in Persistent Childhood Asthma.

            Tracking longitudinal measurements of growth and decline in lung function in patients with persistent childhood asthma may reveal links between asthma and subsequent chronic airflow obstruction.
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              Predictors of mortality in hospitalized adults with acute exacerbation of chronic obstructive pulmonary disease.

              There is a need to identify clinically meaningful predictors of mortality following hospitalized COPD exacerbation. The aim of this study was to systematically review the literature to identify clinically important factors that predict mortality after hospitalization for acute exacerbation of chronic obstructive pulmonary disease (COPD). Eligible studies considered adults admitted to hospital with COPD exacerbation. Two authors independently abstracted data. Odds ratios were then calculated by comparing the prevalence of each predictor in survivors versus nonsurvivors. For continuous variables, mean differences were pooled by the inverse of their variance, using a random effects model. There were 37 studies included (189,772 study subjects) with risk of death ranging from 3.6% for studies considering short-term mortality, 31.0% for long-term mortality (up to 2 yr after hospitalization), and 29.0% for studies that considered solely intensive care unit (ICU)-admitted study subjects. Twelve prognostic factors (age, male sex, low body mass index, cardiac failure, chronic renal failure, confusion, long-term oxygen therapy, lower limb edema, Global Initiative for Chronic Lung Disease criteria stage 4, cor pulmonale, acidemia, and elevated plasma troponin level) were significantly associated with increased short-term mortality. Nine prognostic factors (age, low body mass index, cardiac failure, diabetes mellitus, ischemic heart disease, malignancy, FEV1, long-term oxygen therapy, and PaO2 on admission) were significantly associated with long-term mortality. Three factors (age, low Glasgow Coma Scale score, and pH) were significantly associated with increased risk of mortality in ICU-admitted study subjects. Different factors correlate with mortality from COPD exacerbation in the short term, long term, and after ICU admission. These parameters may be useful to develop tools for prediction of outcome in clinical practice.
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                Author and article information

                Journal
                Int J Chron Obstruct Pulmon Dis
                Int J Chron Obstruct Pulmon Dis
                International Journal of COPD
                International Journal of Chronic Obstructive Pulmonary Disease
                Dove Medical Press
                1176-9106
                1178-2005
                2018
                14 June 2018
                : 13
                : 1927-1935
                Affiliations
                [1 ]Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
                [2 ]Murdoch Children’s Research Institute, Melbourne, VIC, Australia
                [3 ]National Institute of Fundamental Studies, Kandy, Sri Lanka
                [4 ]Department of Respiratory and Sleep Medicine, Institute for Breathing and Sleep, Austin Health, University of Melbourne, Melbourne, VIC, Australia
                [5 ]Department of Community Medicine, University of Sri Jayewardenepura, Nugegoda, Sri Lanka
                [6 ]Telethon Kids Institute, Perth, WA, Australia
                [7 ]School of Physiotherapy and Exercise Science, Curtin University, Perth, WA, Australia
                [8 ]Centre of Child Health Research, University of Western Australia, Perth, WA, Australia
                [9 ]Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
                [10 ]Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia
                [11 ]MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
                [12 ]Population Health and Occupational Diseases, National Heart and Lung Institute, Imperial College London, London, UK
                [13 ]School of Public Health & Preventive Medicine, Monash University, Melbourne, VIC, Australia
                Author notes
                Correspondence: Shyamali C Dharmage, Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, 207 Bouverie Street, Carlton, VIC 3010, Australia, Tel +61 3 8344 0737, Email s.dharmage@ 123456unimelb.edu.au
                [*]

                These authors contributed equally to this work

                Article
                copd-13-1927
                10.2147/COPD.S155675
                6005295
                © 2018 Matheson et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

                Respiratory medicine

                predictors and risk prediction models, copd, early detection

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