Introduction COPD is a heterogeneous disease with multiple extra-pulmonary manifestations, including cachexia and skeletal muscle wasting. These co-morbidities relate to early mortality but are poorly characterised by measures including weight and BMI. Much of the CT-based body composition literature has focussed on abdominal scans. Using conventional chest CT, we aimed to assess the use of CT-derived measures of thoracic muscle and fat in COPD and report their relationship with traditional measures of body composition and markers of disease severity. Methods AERIS was a two-year study involving patients aged 40–85 with moderate-to-very-severe COPD. At enrollment subjects had pulmonary-function-testing, body composition measurements (BMI and bioelectrical impedance at 50 Hz [R50])and chest CT. 3D-Slicer software was used for semi-automated measurements of cross-sectional areas (CSA) of thoracic muscle (pectoralis [PM], erector spinae [ESM] and chest-wall [CWM]) and fat (TF) on the CT scans, with pre-defined attenuation values used to detect muscle (−29 to +150 HU) and fat (−190 to −30HU) boundaries. PM/TF and ESM were identified on an axial slice at the level of the aortic arch and the 12th thoracic vertebra, respectively. CWM were identified on a coronal slice at the point at which the inferior margin of the trachea was level with the lung apices. Results 120 subjects had CT-derived body composition data. PM was significantly correlated (p<0.05) with ESM (r=0.49), CWM (r=0.53) and TF (r=0.24). BMI had significant associations with PM (r=0.24), ESM (r=0.34), CWM (r=0.21) and TF (r=0.73), and bioelectrical impedance significantly correlated with PM (r=−0.55), ESM (r=−0.50) and CWM (r=−0.49), but not with TF. GOLD groups 2, 3 and 4 displayed significant variance in median CSA of pectoralis muscle (1459.8, 1230.9 and 1228.3 mm2, p<0.033), thoracic fat (2396.1, 2443.3 and 1550.6 mm2, p<0.049) and BMI (27.7, 26.6 and 25.4kg/m2, p<0.023). On multiple regression (table 1), PM, TF and BMI were associated with FEV1% and emphysema, and PM and BMI were associated with six-minute-walk-distance. Conclusions CT-derived measurements of pectoralis muscle and thoracic fat showed significant associations with traditional measures of body composition and markers of disease severity. Further studies are therefore warranted to establish the value of these markers in clinical decision making.

Introduction The importance of eosinophilic inflammation in COPD is in its ability to predict an enhanced response to treatment, such as corticosteroids. However, little is know about the persistence of higher eosinophils, or its associations with infectious aetiology during clinical stability and exacerbation. We investigated the natural history of eosinophilic inflammation over time and studied eosinophil-associated acute exacerbations of COPD and the impact of seasonality in a cohort of COPD patients. Methods 127 subjects with moderate to very severe COPD were enrolled into the AERIS cohort (NCT01360398) and were reviewed monthly for scheduled visits and during exacerbations. Blood sampling was performed quarterly and at exacerbations. Higher blood eosinophils (BE) were defined as ≥2%. Based on frequency of higher BE over the study, subjects were divided into predominantly (PE), intermittent (IE) and rarely eosinophilic (RE) groups. Results Blood eosinophil levels ≥2% were prevalent at baseline (68.3%) and at exacerbations (51.1%). Over the study 57.6% of subjects had predominantly, 16.16% intermittently and 26.26% rarely ≥2% blood eosinophils. Higher BE at enrolment was strongly associated with a predominantly high BE profile for the year (AUC 0.841 p < 0.001) and with greater odds of ≥2% eosinophils at exacerbation (OR 9.60 p < 0.001). The odds of ≥2% BE at exacerbation were higher in the PE group compared to the rarely group (OR 12.00, p < 0.001). A larger proportion of exacerbations were eosinophilic in the Summer than Winter (OR 2.57, p = 0.001). The odds of bacterial presence at exacerbation was higher in Winter than Summer among those in the PE group (OR 4.74, CI: 1.43; 15.71, p = 0.011), but not among those in the RE group (OR 1.15, CI: 0.29; 4.56, p = 0.838). Conclusion Our data suggests that it is possible to stratify COPD patients by stable state blood eosinophil levels. This measure is easily accessible and provides important insights into the longitudinal inflammatory phenotype of COPD. Persistent higher blood eosinophil levels were associated with risk of bacterial infection at exacerbation, and seasonality of exacerbation. Intervention studies are required to establish clear treatment algorithms utilising this measure to stratify therapy.

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Introduction COPD is a heterogeneous condition consisting of a number of different clinico-pathological subgroups (phenotypes), leading to particular challenges in managing the condition. Recognising these phenotypes may assist in directing the choice of treatment options. CT is being investigated as a tool for identifying key morphological features seen in COPD. Computer analysis of CT scans allows quantification of emphysema, bronchial wall thickening and gas trapping and offers the opportunity to study the heterogeneity of COPD. This study aims to use quantitative digital software to analyse CT scans from a cohort of COPD patients to define clinically important phenotypes. Methods Acute Exacerbation and Respiratory Infections in COPD (AERIS) is a longitudinal epidemiological study where patients with moderate to very severe COPD were followed monthly for 2 years. At enrolment subjects had pulmonary function testing and high resolution spiral CT was performed in inspiration and expiration. A sub-cohort of 36 patients is included in this analysis. CT scans were reported by a thoracic radiologist using a validated scoring system for emphysema and gas trapping. Image analysis was performed using Apollo software. Emphysema was defined as the percent of lungs with low attenuation values below -950 Hounsfield Units (%LAA) on inspiratory scan. Airway wall thickness was standardised by using the square root of the wall area for a theoretical airway with an internal perimeter of 10 mm (AWT-Pi10). Gas trapping was calculated using the relative volume change of low attenuation areas from -856 to -950 between the inspiratory and expiratory scans (RVC856–950). Results Correlation between the reported CT scores (emphysema and gas trapping) and corresponding quantitative measures (%LAA and RVC856–950) were strong: r = 0.79 and r = 0.5, respectively (p < 0.05). CT scores and quantitative measures for emphysema and gas trapping were significantly correlated with pulmonary function and BODE index (Table 1). Conclusion In this study we have shown that quantitative chest CT measures correlate with a number of traditional physiological and prognostic markers in COPD. These measures have the potential to be clinically useful imaging biomarkers for the disease and further work will help validate this by investigating the longitudinal changes of the AERIS cohort.

Introduction Acute exacerbations of COPD have a major impact on patients’ health related quality of life (HRQoL), and the utilisation of health care resources. Current guidelines recommend oral corticosteroids and/or antibiotics for the treatment of acute exacerbations of COPD based on patients’ symptoms. With increasing bacterial resistance to antibiotics and the rising costs of COPD treatment, further research into diagnostic tools to aid the management of COPD in its stable and exacerbating states is required. Sputum colour (SC) is an accessible marker of underlying bronchial inflammation. We investigated the contribution of objective measures of SC as a component of the clinical assessment of exacerbations and relationships with symptom severity. Methods Data from 36 patients with moderate to very severe COPD was assessed in this prospective observational cohort study (AERIS). There were 122 exacerbations in total over a year. Sputum and blood sampling were performed at enrolment, routine follow up and exacerbation visits. A five-point sputum colour chart was developed to objectively report the SC. Sputum samples from all visits were graded against this chart by the trained laboratory staff. Data from mild, moderate and severe exacerbations were included in the analysis. Results We found a correlation between SC at exacerbations and disease severity (FEV1%) at exacerbations. SC was also related to sputum neutrophilia at exacerbations. SC was significantly associated with systemic markers such as blood neutrophilia, CRP and fibrinogen. Interestingly, we observed no statistically significant correlation between SC and Procalcitonin levels. We also found no statistically significant relationship between SC and symptom scores (CAT and EXACT-PRO) at exacerbations. However, we found a significant association between CAT and EXACT-PRO scores (rho 0.46; p < 0.01). Conclusion We observed that visual colour score of sputum at exacerbations is related to underlying airway and systemic inflammation but not to symptom scores. The use of a SC combined with other clinical and laboratory biomarkers, as part of a multicomponent diagnostic tool, may further improve its clinical utility to better guide effective exacerbation treatment. Further analysis of the full AERIS cohort will explore this.