Open AccessPredicting Hospitalization Due to COPD Exacerbations in Swedish Primary Care Patients Using Machine Learning – Based on the ARCTIC Study
Author(s) -
Björn Ställberg,
Karin Lisspers,
Kjell Larsson,
Christer Janson,
Mario Müller,
Mateusz Łuczko,
Bine Kjøller Bjerregaard,
Gerald Bacher,
Björn Holzhauer,
Pankaj Goyal,
Gunnar Johansson
Publication year - 2021
Publication title -
international journal of chronic obstructive pulmonary disease/international journal of copd
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 67
eISSN - 1178-2005
pISSN - 1176-9106
DOI - 10.2147/copd.s293099
Subject(s) - medicine , copd , exacerbation , comorbidity , receiver operating characteristic , emergency medicine , medical diagnosis , medical record , intensive care medicine , physical therapy , pathology
Chronic obstructive pulmonary disease (COPD) exacerbations can negatively impact disease severity, progression, mortality and lead to hospitalizations. We aimed to develop a model that predicts a patient's risk of hospitalization due to severe exacerbations (defined as COPD-related hospitalizations) of COPD, using Swedish patient level data.