Thin-section CT abnormalities and pulmonary gas exchange impairment in workers exposed to asbestos

• Autor(a) principal: Sette, Andrea
• Data de Publicação: 2004
• Outros Autores: Neder, Jose Alberto [UNIFESP], Nery, Luiz Eduardo [UNIFESP], Kavakama, Jorge, Rodrigues, Reinaldo T., Terra-Filho, Mario, Guimaraes, Sandra, Bagatin, Ericson, Muller, Nestor
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNIFESP
• Texto Completo: http://repositorio.unifesp.br/handle/11600/27809; http://dx.doi.org/10.1148/radiol.2321030392
• topic: asbestos; computed tomography (CT), thinsection; lung, function; pneumoconiosis

PURPOSE: To evaluate the relationship between abnormalities at thin-section computed tomography (CT) and indexes of pulmonary gas exchange impairment at rest and during moderate exercise in workers exposed to asbestos.MATERIALS and METHODS: Eighty-two workers with long-term exposure to asbestos and abnormal thin-section CT findings underwent respiratory physiologic measurements at rest (lung diffusing capacity, DLCO) and during exercise (oxygen uptake-corrected alveolar-arterial pressure difference for oxygen, DeltaP[A-a]O-2/VO2). CT results were compared with physiologic measurements of impairment in gas exchange (DLCO < 70% predicted value and/or DeltaP[A-a]O-2/VO2 > 20 mm Hg (.) L (.) min(-1)). the CT findings were divided into five categories by using a previously described method. Odds ratios and 95% Cls for gas exchange defects were calculated for patients grouped according to CT findings. Logistic regression analysis was performed with gas exchange as the dependent response and CT abnormalities as independent variables.RESULTS: A significant association was found between extent of disease at CT and impairment of gas exchange (P <.01). Probability of functional impairment was increased with multifocal (class 11) and diffuse (class 111) CT abnormalities, particularly when several lesion types were found concomitantly. Logistic regression analysis demonstrated significant association of parenchymal bands (odds ratio, 6.20; 95% Cl: 1.99, 19.22) and subpleural nodules (odds ratio, 3.83; 95% Cl: 1.23,11.89) with functional impairment. Presence and number of pleural plaques did not improve model accuracy for gas exchange impairment prediction (P > .05).CONCLUSION: Thin-section CT grading of interstitial lung disease is useful in assessing the likelihood of pulmonary gas exchange impairment at rest (DLCO) and during exercise (DeltaP[A-a]O-2/VO2) in workers with long-term asbestos exposure.