Background: Early identification of patients with a prolonged stay due to acute exacerbation of chronic obstructive pulmonary disease (COPD) may reduce risk of adverse event and treatment costs. This study aimed to identify predictors of prolonged stay after acute exacerbation of COPD based on variables on admission; the study also looked to establish a prediction model for length of stay (LOS).
Methods: We extracted demographic and clinical data from the medical records of 599 patients discharged after an acute exacerbation of COPD between March 2006 and December 2008 at Oslo University Hospital, Aker. We used logistic regression analyses to assess predictors of a length of stay above the 75th percentile and assessed the area under the receiving operating characteristic curve to evaluate the model's performance.
Results: We included 590 patients (54% women) aged 73.2±10.8 years (mean ± standard deviation) in the analyses. Median LOS was 6.0 days (interquartile range [IQR] 3.5-11.0). In multivariate analysis, admission between Thursday and Saturday (odds ratio [OR] 2.24 [95% CI 1.60-3.51], P<0.001), heart failure (OR 2.26, 95% CI 1.34-3.80), diabetes (OR 1.90, 95% CI 1.07-3.37), stroke (OR 1.83, 95% CI 1.04-3.21), high arterial PCO2 (OR 1.26 [95% CI 1.13-1.41], P<0.001), and low serum albumin level (OR 0.92 [95% CI 0.87-0.97], P=0.001) were associated with a LOS >11 days. The statistical model had an area under the receiver operating characteristic curve of 0.73.
Conclusion: Admission between Thursday and Saturday, heart failure, diabetes, stroke, high arterial PCO2, and low serum albumin level were associated with a prolonged LOS. These findings may help physicians to identify patients that will need a prolonged LOS in the early stages of admission. However, the predictive model exhibited suboptimal performance and hence is not ready for clinical use.
Keywords: COPD; exacerbation; length of stay; predicting model; predictors.