Source: International Congress 2015 – Occupational and environmental cohort investigations and population studies

Abstract

BackgroundSpirometry is often included in workplace-based respiratory surveillance programmes but its performance in the identification of restrictive lung disease is poor, especially when the expected prevalence of this condition is low.Aims and objectivesTo improve the specificity and positive predictive value of current spirometry-based algorithms in the diagnosis of restrictive pulmonary impairment in the workplace, in order to reduce the proportion of false positives findings and so unnecessary referrals for lung volume measurements.MethodsWe re-analysed two studies (n=259 and 265) of hospital patients, respectively used to derive and validate a recommended spirometry-based algorithm (FVC<85%predicted+FEV1/FVC>55%) for the recognition of restrictive pulmonary impairment. We used true lung restrictive cases as gold standard in 2x2contingency tables to estimate sensitivity, specificity, positive and negative predictive values for each diagnostic cut-off. We simulated a working population less than 65 years old and with a disease prevalence ranging 1-10% and compared algorithms using receiver operating characteristic (ROC) curves.ResultsOur best algorithm (FVC<70%predicted+FEV1/FVC³70%) achieved the highest specificity (96%) and positive predictive value (67% and 15% for a disease prevalence of 10% and 1%, respectively) with the lowest proportion of false positives (4%); its high sensitivity (71%) predicted the highest proportion of correctly classified restrictive cases (91%), corresponding to a ROC curve of 0.83.ConclusionsOur proposed spirometry-based algorithm accurately excludes pulmonary restriction and reduces unnecessary lung volume testing in an occupational health setting.


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Sara De Matteis (London, United Kingdom), Sara De Matteis, Amaia Iridoy, Paul Cullinan. A new spirometry-based algorithm to predict occupational pulmonary restrictive impairment. Eur Respir J 2015; 46: Suppl. 59, 1171

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