Abstract
Background: Exercise impairment is common in subjects with asbestosis. Arterial oxygen desaturation during exercise is an important contributor to exercise limitation. The International Labour Office (ILO) classification of plain chest radiographs correlates with resting pulmonary function, but its value in predicting abnormal ventilatory responses to exercise, including desaturation, has not been explored.
Aims: To determine in subjects with asbestosis (1) if radiographic profusion scores and the extent of small irregular shadows on plain chest radiographs correlate with resting lung function and abnormal ventilatory responses to exercise; and (2) if radiographic scores add value to resting lung function tests in predicting abnormal ventilatory responses to exercise.
Methods: Thirty eight male subjects with asbestosis were included. Plain chest radiographs were read according to the ILO classification independently by three observers. All subjects underwent assessment of lung function and an incremental exercise test.
Results: Profusion scores and number of affected zones correlated significantly with the percentage predicted values of single breath diffusing capacity (DLCO), forced vital capacity (FVC), and total lung capacity (TLC). Arterial oxygen desaturation occurred in 29% of the subjects. The severity of desaturation correlated significantly with profusion and the number of affected zones. The combined use of number of affected zones, FEV1/FVC ratio and DLCO predicted desaturation during exercise with an explained variance of 41%. VO2max was significantly related only to DLCO but was not predicted by the ILO score.
Conclusion: Arterial oxygen desaturation correlated with the profusion and extent of parenchymal abnormality on chest radiographs. The addition of morphological indices to physiological measurements is valuable for predicting oxygen desaturation during exercise but not for VO2max. Refinement of the radiographic scoring system and the addition of more sophisticated imaging techniques may further improve the predictive power.
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