Am. J. Respir. Crit. Care Med., Vol 153, No. 2, 02 1996, 736-741.
A computer program using BALF-analysis results as a diagnostic tool in interstitial lung diseases
M Drent, MA van Nierop, FA Gerritsen, EF Wouters and PG Mulder
Department of Pulmonology, University Hospital Maastricht, The Netherlands.
Recently, we showed that it is possible to distinguish between three common
interstitial lung diseases (ILD) with similarities in clinical presentation
by using a number of selected variables derived from bronchoalveolar lavage
fluid (BALF) analysis. The aim of this study was to develop a more general
discriminant model, based on polychotomous logistic regression analysis.
The 277 patients involved in the study belonged to diagnostic groups with
sarcoidosis (n = 193), extrinsic allergic alveolitis (EAA; n = 39), and
idiopathic pulmonary fibrosis (IPF; n = 45). The diagnosis had been
established independently of the BALF-analysis results. The variables used
to discriminate among these patient groups were the yield of recovered
BALF, total cell count, and percentages of alveolar macrophages,
lymphocytes, neutrophils, and eosinophils. In order to test the predictive
power of the logistic model, we used 128 patients having sarcoidosis (n =
91), EAA (n = 5), or IPF (n = 32) from another hospital. In this test set
the agreement of predicted with actual diagnostic-group membership was the
same as in the learning set in which the logistic model was fitted: 94.5%
of the cases were correctly classified. A validated computer program based
on the polychotomous logistic regression model can be used to predict the
diagnosis for an arbitrary patient with information provided by BALF
analysis, and is thought to be of diagnostic value in patients suspected of
having ILD.
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Copyright © 1996 American Thoracic Society
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