Roy T M Sprooten1, Gernot G U Rohde2, Glenn Lawyer3, Wouter T Leijte1, Emiel F M Wouters1,4, Frits M E Franssen1,4. 1. Department of Respiratory Medicine, Maastricht University Medical Center, Maastricht, The Netherlands. 2. Pneumologie/Allergologie, Medizinische Klinik 1, Klinikum der Johann Wolfgang Goethe-Universität, Frankfurt, Germany. 3. Machine Learning Solutions, Luxembourg, Luxembourg. 4. Ciro+, Centre of Expertise for Chronic Organ Failure, Horn, The Netherlands.
Abstract
BACKGROUND AND OBJECTIVE: Exacerbations of chronic obstructive pulmonary disease (ECOPD) are associated with increased in-hospital and short-term mortality. Developing an easy-to-use model to predict adverse outcomes will be useful in daily clinical practice and will facilitate management decisions. We aimed to assess mortality rates and potential predictors for short-term mortality after severe ECOPD. Classification and Regression Tree (CART) model was used to identify predictors of adverse outcome. METHODS: A retrospective observational cohort study, including all patients admitted to Maastricht University Medical Center with ECOPD between June 2011 and December 2014 was performed. The last admission was taken into account, and its demographic, clinical and biochemical data were recorded. RESULTS: A total of 364 hospitalized patients were enrolled. Mean (SD) age was 70.5 (10.2) years, 54.4% were male and mean FEV1 45.2% (17.7) of predicted. The in-hospital and 90-day mortality were, respectively, 8.5 and 16.2%. Independent risk factors for 90-day mortality were: PaC02 (odds ratio (OR): 1.31; 95% confidence interval (CI): 1.00-0.35), age (OR: 1.09; CI: 0.06-0.11), body mass index (BMI) < 18.5 kg/m2 (OR: 2.72; 95% CI: 0.53-1.47) and previous admission for ECOPD in last 2 years (OR: 1.29; 95% CI: -0.14, -0.65). The CART model selected PaCO2 ≥ 9.1 kPa, age > 80 years, BMI < 18.5 kg/m2 and previous admission for ECOPD as the most discriminatory factors. CONCLUSION: According CART analysis, high PaCO2 and age, low BMI and previous admission for ECOPD in last 2 years were the strongest predictors of 90-day mortality in patients with severe ECOPD. In absence of any of these factors, no patients died, suggesting that this model indeed enables risk stratification.
BACKGROUND AND OBJECTIVE: Exacerbations of chronic obstructive pulmonary disease (ECOPD) are associated with increased in-hospital and short-term mortality. Developing an easy-to-use model to predict adverse outcomes will be useful in daily clinical practice and will facilitate management decisions. We aimed to assess mortality rates and potential predictors for short-term mortality after severe ECOPD. Classification and Regression Tree (CART) model was used to identify predictors of adverse outcome. METHODS: A retrospective observational cohort study, including all patients admitted to Maastricht University Medical Center with ECOPD between June 2011 and December 2014 was performed. The last admission was taken into account, and its demographic, clinical and biochemical data were recorded. RESULTS: A total of 364 hospitalized patients were enrolled. Mean (SD) age was 70.5 (10.2) years, 54.4% were male and mean FEV1 45.2% (17.7) of predicted. The in-hospital and 90-day mortality were, respectively, 8.5 and 16.2%. Independent risk factors for 90-day mortality were: PaC02 (odds ratio (OR): 1.31; 95% confidence interval (CI): 1.00-0.35), age (OR: 1.09; CI: 0.06-0.11), body mass index (BMI) < 18.5 kg/m2 (OR: 2.72; 95% CI: 0.53-1.47) and previous admission for ECOPD in last 2 years (OR: 1.29; 95% CI: -0.14, -0.65). The CART model selected PaCO2 ≥ 9.1 kPa, age > 80 years, BMI < 18.5 kg/m2 and previous admission for ECOPD as the most discriminatory factors. CONCLUSION: According CART analysis, high PaCO2 and age, low BMI and previous admission for ECOPD in last 2 years were the strongest predictors of 90-day mortality in patients with severe ECOPD. In absence of any of these factors, no patientsdied, suggesting that this model indeed enables risk stratification.