These results support a potential role for the TUG test to be incorporated into community COPD assessment to stratify patients functionally, particularly where time and space are limited. Future studies are required to assess impact of interventions on TUG test and determine the predictive ability to identify future falls.

With the increased cardiovascular (CV) morbidity and mortality in subjects with chronic obstructive pulmonary disease (COPD), there is a priority to identify those patients at increased risk of cardiovascular disease. Stable patients with COPD (n = 185) and controls with a smoking history (n = 106) underwent aortic pulse wave velocity (PWV), blood pressure (BP) and skin autofluorescence (AF) at clinical stability. Blood was sent for fasting lipids, soluble receptor for advanced glycation end products (sRAGE) and CV risk prediction scores were calculated. More patients (18%) had a self-reported history of CV disease than controls (8%), p = 0.02, whilst diabetes was similar (14% and 10%), p = 0.44. Mean (SD) skin AF was greater in patients: 3.1 (0.5) AU than controls 2.8 (0.6) AU, p < 0.001. Aortic PWV was greater in patients: 10.2 (2.3) m/s than controls: 9.6 (2.0) m/s, p = 0.02 despite similar BP. The CV risk prediction scores did not differentiate between patients and controls nor were the individual components of the scores different. The sRAGE levels were not statistically different. We present different indicators of CV risk alongside each other in well-defined subjects with and without COPD. Two non-invasive biomarkers associated with future CV burden: skin AF and aortic PWV are both significantly greater in patients with COPD compared to the controls. The traditional CV prediction scores used in the general population were not statistically different. We provide new data to suggest that alternative approaches for optimal CV risk detection should be employed in COPD management.

Introduction In many chronic diseases vitamin D has been proposed as an adjunctive anti-inflammatory therapy. Vitamin D upregulates MKP1, thereby downregulating p38 phosphorylation and the NFKB inflammatory cascade (Zhang et al, J Immunol. 2012;188(5):2127-35). Steroids exert anti-inflammatory effects via this cascade, and exhibit synergy with vitamin D for some effects (Yu et al, Journal of the National Cancer Institute. 1998;90(2):134-41). Patients with COPD have chronic pulmonary inflammation, with upregulation of NFKB, yet do not exhibit a good response to steroids. Vitamin D therapy has been trialled in COPD patients, albeit with disappointing results (Lehouck et al, Annals of internal medicine. 2012;156(2):105-14). We hypothesised that COPD patients' inflammatory response would differ from health, and that vitamin D would exhibit synergy with steroids in vitro to improve this. Methods PBMCs isolated from 10 COPD patients and 10 healthy control subjects were incubated with LPS, vitamin D, dexamethasone, a p38 MAPK inhibitor or combinations of these agents. Supernatants were harvested for TNF and IL6 measurements (ELISA). Results LPS caused a marked rise in IL6 in both healthy controls (p = 0.044) and COPD patients (p = 0.008). IL6 reduction with vitamin D was only seen in health. IL6 reduction with addition of dexamethasone was not statistically significant (p = 0.636) in COPD. Combinations of agents failed to produce any additional benefit in both health and COPD.The response to vitamin D was heterogeneous; half of healthy subjects showed an anti-inflammatory response but in COPD only 12.5% of patients exhibited this. The difference in response rate was not significant (p = 0.120, Fishers exact test), though this may be due to low power. Similarly reduced response rate to dexamethasone was seen in COPD. Conclusion Vitamin D does not enhance the anti-inflammatory effect of steroids. The anti-inflammatory effects of vitamin D are no different between COPD and health; variability of response may be one reason for lack of effect of vitamin D in clinical trials to date in COPD patients. 2 Several CV risk calculators for the general population exist but it is unclear whether they are applicable for COPD. Hypothesis Standard CV risk calculators do not identify the increased risk in patients with COPD. Methods Subjects with a smoking history >10 pack years, with and without COPD, were assessed at clinical stability, COPD n = 191 and controls n = 106. Post-bronchodilator spirometry and blood pressure were performed, blood taken for lipids and self-reported medical and smoking history recorded. In those without documented established CV disease or diabetes (COPD n = 135 and controls n = 88), 10 year CV risk was calculated using ACC/AHA 3 and NHLBI[4] calculators. Results Both groups were well matched for gender and mean arterial blood pressure (MAP), with the COPD group slightly older, Table 1. Mean CV risk scores were similar between patients with COPD and controls, Table 1, ACC/AHA p = 0.16 and NHLBI p = 0.59. Wh...