Pericardial Abnormalities Predict the Presence of Echocardiographically Defined Pulmonary Arterial Hypertension in Systemic Sclerosis-Related Interstitial Lung Disease

2007 
Objectives To determine the prevalence and significance of pericardial abnormalities in systemic sclerosis (SSc)-related interstitial lung disease (ILD). Methods Retrospective study of 41 subjects with SSc-related ILD who underwent evaluation including thoracic high-resolution CT (HRCT) imaging, transthoracic echocardiography (TTE), and pulmonary function testing. HRCT review evaluated the pericardium for the presence of pericardial effusion (PEf), thickness of the anterior pericardial recess (APR) [abnormal defined as > 10 mm], and pericardial thickening as calculated by total pericardial score (TPS) [abnormal defined as > 8 mm]. Pulmonary arterial hypertension (PAH) was defined as a pulmonary artery pressure > 35 mm Hg estimated by TTE. Results Fifty-nine percent had an abnormal pericardium, 49% had a PEf, 56% had an abnormal APR, and 49% had an abnormal TPS. An abnormal pericardium was more common in men than women. Subjects with and without pericardial abnormalities were otherwise similar with respect to age, SSc classification, autoantibodies, ILD radiographic pattern, and presence of esophageal dilation. Both groups had similar median percentage of predicted total lung capacity, percentage of predicted FVC, percentage of predicted FEV 1 , and percentage of predicted diffusion capacity of the lung for carbon monoxide. Subjects with pericardial abnormalities were more likely to have coexistent PAH (35% vs 75%; p = 0.02) and a higher median right ventricular systolic pressure (31 mm Hg vs 44 mm Hg; p = 0.03). Multiple logistic regression revealed that TPS was the best individual predictor of the presence of TTE-defined PAH. Conclusions In patients with SSc-related ILD, pericardial abnormalities are commonly seen on HRCT, and their presence is strongly associated with echocardiographically defined PAH, with abnormal TPS as the best individual predictor.
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