Background Pannikulitis (PN) is a heterogeneous group of inflammatory diseases associated with damage of subcutaneous fat and internal organs. The difficulties of PN diagnosis are due to variety of clinical and pathological forms and lack of specific markers of the disease.
Objectives The objective was to develop an algorithm for diagnosis of Pn.
Methods 361 patients with PN were included. There were 51 males and 310 females aged 15-79 years referred to clinic with suspected diagnosis of “erythema nodosum” (EN) in 2008-2012. Physical examination, laboratory investigation (determination of amylase, lipase, α1-antitrypsin, creatine kinase and CRP levels, anti-DNA-antibodies, antibodies to hepatitis B/C, Yersinia and ASL-O etc.) and instrumental assessment (chest CT scan and ultrasonography of lower extremities and subcutaneous nodules), intradermal tuberculin test and pathomorphological study of skin biopsy specimen from the node area were performed.
Results Septal Pn was established in 189 (53,1%) cases. 182 from these patients had EN, 7 - Behcet's disease. Septal Pn was characterized by painful (pain of VAS 59±27,6 mm), isolated from each other, clearly marked from surrounding skin nodules which had diameter till 5 cm and regressed without ulcers and scars. Lobular Pn was diagnosed in 167 patients, including sarcoidosis (Darier-Roussy sarcoid) (68), Weber-Christian disease (32), lipodermatosclerosis (44), infectious Pn (11), oncogematopathology (5), erythema induratum Bazin's (3), fastitial Pn, pancreatic Pn, lupus Pn, dermatomyositis, - 1 case each. Tipical signs of lobular panniculitis were multiple “sauser-formed” moderately painful (pain of VAS 46±19,3 mm) hardenings with development of subcutaneous fat atrophy on lower (95,2%) and upper (42%) extremities, less often on breast, abdomen and face (17,4%). On the whole in 68% of patients appearance of nodules was accompanied by fever, polyarthralgias, myalgias, elevation of ESR and CRP. Diagnosis of Pn was excluded in 5 patients. At pathomorphological research Pn's diagnosis was verified in all cases.
Conclusions The proposed algorithm represents the first stage of the Pn diagnosis development. Further research is needed to assess its sensitivity and specificity
Disclosure of Interest None declared