PROGNOSTIC ALGORITHM FOR DISEASE FLOW IN PULMONARY AND THORACIC LYMPH NODES SARCOIDOSIS

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Abstract

Background: Sarcoidosis is a systemic granulomatosis commonly affecting respiratory system. Variable and often unpredictable flow of the disease provides rationale for the development of prognostic algorithm. Aim: To detect predictive parameters in pulmonary and thoracic lymph nodes sarcoidosis; to develop prognostic algorithm. Materials and methods: The results of examination of 113 patients (85 women and 28 men, 19–77 years old) with morphologically verified sarcoidosis has been assessed. Clinical manifestations, functional, radiographic (including CT numerical scores) and morphological features of the disease were analyzed against 3-year outcomes in prednisolon/hydroxychloroquine-treated or treatment-naive patients. Results: Radiographic stage, CT-pattern scores, several parameters of pulmonary function tests (DLCO, RV, FEV1, FVC) and dyspnoe had the greatest prognostic significance for disease flow. Prognostic accuracy was 87.8% and increased to 94.5% after one-year dynamics of symptoms was taken into account. Therapy with systemic glucocorticosteroids did not influence outcomes in sarcoidosis with asymptomatic enlargement of thoracic lymph nodes. Conclusion: We have developed an algorithm for prognosis assessment in pulmonary sarcoidosis. Taking into account the results of patients follow-up significantly improves the accuracy of the prognosis.

About the authors

S. A. Terpigorev

Moscow Regional Research and Clinical Institute (MONIKI); 61/2 Shchepkina ul.,
Moscow, 129110, Russian Federation

Author for correspondence.
Email: smith42@yandex.ru
MD, PhD, Chief of the Department for Occupational Diseases and Medical and Labour Expert Commission Russian Federation

V. A. Ilchenko

Moscow Regional Research and Clinical Institute (MONIKI); 61/2 Shchepkina ul.,
Moscow, 129110, Russian Federation

Email: fake@neicon.ru
MD, PhD, Assistant Professor, Internal Diseases Department, Postgraduate Medical School Russian Federation

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Copyright (c) 2016 Terpigorev S.A., Ilchenko V.A.

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