Abstract

RationaleAs the prevalence of multimorbidity increases, understanding the impact of isolated comorbidities in people COPD becomes increasingly challenging. A simplified model of common comorbidity patterns may improve outcome prediction and allow targeted therapy. ObjectivesTo assess whether comorbidity phenotypes derived from routinely collected clinical data in people with COPD show differences in risk of hospitalisation and mortality. MethodsTwelve clinical measures related to common comorbidities were collected during annual reviews for people with advanced COPD and k-means cluster analysis performed. Cox proportional hazards with adjustment for covariates was used to determine hospitalisation and mortality risk between clusters. Measurements and main resultsIn 203 participants (age 66 ± 9 years, 60 % male, FEV1%predicted 31 ± 10 %) no comorbidity in isolation was predictive of worse admission or mortality risk. Four clusters were described: cluster A (cardiometabolic and anaemia), cluster B (malnourished and low mood), cluster C (obese, metabolic and mood disturbance) and cluster D (less comorbid). FEV1%predicted did not significantly differ between clusters. Mortality risk was higher in cluster A (HR 3.73 [95%CI 1.09–12.82] p = 0.036) and B (HR 3.91 [95%CI 1.17–13.14] p = 0.027) compared to cluster D. Time to admission was highest in cluster A (HR 2.01 [95%CI 1.11–3.63] p = 0.020). Cluster C was not associated with increased risk of mortality or hospitalisation. ConclusionsDespite presence of advanced COPD, we report striking differences in prognosis for both mortality and hospital admissions for different co-morbidity phenotypes. Objectively assessing the multi-system nature of COPD could lead to improved prognostication and targeted therapy for patients.

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