Risk Factors of Poor Outcomes after Admission for a COPD Exacerbation: Multivariate Logistic Predictive Models.

The aim of this study was to identify a multivariate model to predict poor outcomes after admission for exacerbation of chronic obstructive pulmonary disease (COPD).  We performed a multicenter, observational, prospective study. Patients admitted to hospital for COPD were followed up for 3 months. Relevant clinical variables at admission were selected. For each variable, the best cut-offs for the risk of poor outcome were identified using receiver operating characteristic (ROC) curves. Finally, a stepwise logistic regression model was performed. A total of 106 patients with a mean age of 71.1 (9.8) years were included. The mean maximum expiratory volume in the first second (FEV1)(%) was 45.2%, and the mean COPD assessment test (CAT) score at admission was 24.8 (7.1). At 3 months, 39 (36.8%) patients demonstrated poor outcomes: death (2.8%), readmission (20.8%) or new exacerbation (13.2%). Variables included in the logistic model were: previous hospital admission, FEV1 < 45%, Charlson ≥ 3, hemoglobin (Hb)<13 g/L, PCO2 ≥ 46 mmHg, fibrinogen ≥ 554 g/L, C-reactive protein (CRP)≥45 mg/L, leukocyte count < 9810 × 109/L, purulent sputum, long-term oxygen therapy (LTOT) and CAT ≥ 31 at admission. The final model showed that Hb < 13 g/L (OR = 2.46, 95%CI 1.09-6.36), CRP ≥ 45 mg/L (OR = 2.91, 95%CI: 1.11-7.49) and LTOT (3.07, 95%CI: 1.07-8.82) increased the probability of poor outcome up to 82.4%. Adding a CAT ≥ 31 at admission increased the probability to 91.6% (AUC = 0.75; p = 0.001). Up to 36.8% of COPD patients had a poor outcome within 3 months after hospital discharge, with low hemoglobin and high CRP levels being the risk factors for poor outcome. A high CAT at admission increased the predictive value of the model.