Objective: to compare the frequency of comorbid diseases in axial psoriatic arthritis (axSpA) and in other variants (OV) of axial spondyloarthritis (axSpA).Material and methods. We studied 60 patients, 30 with axPsA (15 men and 15 women, mean age – 49.1±10.4 years, disease duration – 12.6±6.9 years) and 30 with OV axSpA (16 men and 14 women, mean age – 42.9±9.7 years, disease duration – 16.30±8.3 years). All patients underwent a standard rheumatological examination. The diagnosis of comorbid diseases was confirmed using ICD-10 codes. The Cumulative Illness Rating Scale (CIRS), Charlson comorbidity index (CCI) and the weighted version of Functional Comorbidity Index (w-FCI) were used to assess comorbidity.Results and discussion. Comparative analysis of the two groups revealed that axPsA patients were older than OV axSpA patients (p <0.05). Occurrence of back pain before the age of 40 was observed in 60% of axPsA cases, compared to 86.7% in OV axSpA (p<0.05). The limitation of spinal and hip mobility was less severe in axPSA than in OV axSpA. The median side flexion was 12.3 [10; 15] and 9.5 [8; 11] cm, the Schober test was 4.2 [3; 5] and 3.0 [2; 4] cm and intermalleolar distance was 95.9 [86; 102] and 83.0 [75; 100] cm, respectively (p<0.05). Patients with axPsA were more likely to have peripheral arthritis compared to patients with OV axSpA: 27 (90%) and 11 (36.7%) cases, respectively (p<0.05) and higher laboratory indices of activity: median ESR, 31.9 [10; 38] and 20.4 [5; 14] mm/h, and CRP, 20.5 [2.8; 20.7] and 13.6 [0.9; 12.0] mg/L, respectively (p<0.05). In the axPsA and OV axSpA groups, circulatory system diseases were found in 50 and 50% of patients, metabolic disorders in 76.6 and 76.6%, and gastrointestinal diseases in 46.7 and 70 %. Obesity was more common in axPsA than in OV axSpA – in 40 and 16.7% of patients, respectively (p<0.05).Conclusion. A high frequency of comorbidities, mainly cardiovascular and metabolic diseases, was found in both groups. These data should be considered in the choice of therapy and optimization of existing treatment algorithms.
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