The diagnosis of hypersensitivity pneumonitis (HP) is difficult and often relies on histopathology. Our objective was to identify diagnostic criteria and to develop a clinical prediction rule for this disease. Consecutive patients presenting a condition for which HP was considered in the differential diagnosis underwent a program of simple standardized diagnostic procedures. High-resolution computed tomography scan and bronchoalveolar lavage (BAL) defined the presence or absence of HP. Patients underwent surgical lung biopsy when the computed tomography scan, BAL, and other diagnostic procedures failed to yield a diagnosis. A cohort of 400 patients (116 with HP, 284 control subjects) provided data for the rule derivation. Six significant predictors of HP were identified: (1) exposure to a known offending antigen, (2) positive precipitating antibodies to the offending antigen, (3) recurrent episodes of symptoms, (4) inspiratory crackles on physical examination, (5) symptoms occurring 4 to 8 hours after exposure, (6) and weight loss. The area under the receiver operating characteristic curve was 0.93 (95% confidence interval: 0.90-0.95). The rule retained its accuracy when validated in a separate cohort of 261 patients. The diagnosis of HP can often be made or rejected with confidence, especially in areas of high or low prevalence, respectively, without BAL or biopsy.
Hypersensitivity pneumonitis (HP) develops after inhalation of many different environmental antigens, causing variable clinical symptoms that often make diagnosis uncertain. The prevalence of HP is higher than recognized, especially its chronic form. Mechanisms of disease are still incompletely known. Strategies to improve detection and diagnosis are needed, and treatment options, principally avoidance, are limited. A workshop recommended: a population-based study to more accurately document the incidence and prevalence of HP; better classification of disease stages, including natural history; evaluation of diagnostic tests and biomarkers used to detect disease; better correlation of computerized tomography lung imaging and pathologic changes; more study of inflammatory and immune mechanisms; and improvement of animal models that are more relevant for human disease.
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