Decisions about the intensity of treatment for patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are influenced by predictions about survival and quality of life. Evidence suggests that these predictions are poorly calibrated and tend to be pessimistic.Aim
The aim of this study was to develop an outcome prediction model for COPD patients to support treatment decisions.Methods
A prospective multi-centre cohort study in Intensive Care Units (ICU) and Respiratory High Dependency Units (RHDU) in the UK recruited patients aged 45 years and older admitted with an exacerbation of obstructive lung disease. Data were collected on patients’ characteristics prior to ICU admission, and on their survival and quality of life after 180 days. An outcome prediction model was developed using multivariate logistic regression and bootstrapping.Results
Ninety-two ICUs (53% of those in the UK) and three RHDUs took part. A total of 832 patients were recruited. Cumulative 180-day mortality was 37.9%. Using data available at the time of admission to the units, a prognostic model was developed which had an estimated area under the receiver operating characteristic curve (‘c’) of 74.7% after bootstrapping that was more discriminating than the clinicians (P=0.033) and was well calibrated.Discussion
This study has produced an outcome prediction model with slightly better discrimination and much better calibration than the participating clinicians. It has the potential to support risk adjustment and clinical decision making about admission to intensive care.