These findings suggest that the standard 48-week treatment is insufficient and that an extended course of treatment may be necessary. Relapse is a poorly understood clinical outcome in the treatment of chronic HCV patients. Retreatment can give a chance to some patients specially who have early virologic response and negative HCV RNA at the end of the first therapy.

Objective To identify the different clinical phenotypes of antiphospholipid syndrome (APS) by using cluster analysis and describe cumulative damage of disease clusters. Methods This retrospective study includes patients with APS (±systemic lupus erythematosus (SLE)). Two-step cluster analysis was applied by considering clinical data. Damage was calculated for all patients by applying damage index for APS (DIAPS). Results A total of 237 patients (198 females; median age of 43 years; median follow-up of 9.5 years) were classified into four clusters. Cluster 1 ( n = 74) consisted of older patients with arterial-predominant thrombosis, livedo reticularis, and increased cardiovascular risk; cluster 2 ( n = 70) of SLE+APS patients with thrombocytopenia and heart valve disease; cluster 3 ( n = 59) of patients with venous-predominant thrombosis, less extra-criteria manifestations; and cluster 4 ( n = 34) of patients with only pregnancy morbidity with lower frequency of extra-criteria features and cardiovascular risk. Patients with SLE+APS ( n = 123) had the highest mean DIAPS. Regarding clusters, 1 and 2 had high cumulative damage. While cumulative survival rates of clusters did not differ, cluster 2 and 3 had lower survival rates at further years. There was no correlation between DIAPS and mortality. Conclusion SLE+APS patients with extra-criteria manifestations and older APS patients with arterial thrombosis and increased cardiovascular risk have higher cumulative damage. Effective treatment of SLE disease activity and control of cardiovascular risk may help to reduce cumulative damage in these patients.

Background and Aims Although hematuria is the cardinal symptom of IgA nephropathy (IgAN), its effects on the outcome have not been studied extensively. We, therefore, aimed to analyze the association between microhematuria and clinicopathological features as well as outcome parameters in adult patients with IgAN. Method 129 adults with IgAN, diagnosed by kidney biopsy, and followed up for a median duration of 54.5 (IQR: 24.25-92.75) months, were included in this retrospective study. Urinary sediment analyses during the bouts of macrohematuria were not taken into consideration. For the purpose of this analysis, microhematuria was described as ≥5 red blood cells per high-power field (RBCs/hpf) and classified as mild (5-9 RBCs/hpf), moderate (10-19 RBCs/hpf), or severe (≥20 RBCs/hpf). Study outcome (event) was defined as at least a 50% reduction in baseline eGFR or development of stage 5 chronic kidney disease (eGFR <15 ml/min/1.73 m2). eGFRs of the patients were calculated by using CKD-EPI formula. Results Demographic, clinical, laboratory and histopathological features of patients at the time of diagnosis are summarized in the table. Usage of ACEi/ARBs [75/81 (92.5%) vs 45/48 (93.75%), p=0.803], fish oil [30/81 (37%) vs 19/48 (39.5%), p=0.773], azathioprine [16/81 (19.7%) vs 10/48 (20.8%), p=0.882] and mycophenolic acid derivatives [14/81 (17.2%) vs 11/48 (22.9%), p=0.434] were comparable among the patients with and without microhematuria. Corticosteroids were more frequently used in patients with microhematuria [41/81 (50.6%) vs 17/48 (35.4%)], although this difference was not statistically significant (p=0.093). Overall 30 patients (23.2%) reached the study outcome, and there were no differences between patients with (19, 23.4%) and without (11, 22.9%) microhematuria (p=0.944). Kaplan-Meier analysis revealed that event free survival rates were similar across study groups: 77.1% for patients without microhematuria; while 80% for mild, 77.3% for moderate, and 72.7% for severe microhematuria (p=0.436) (Figure). Microhematuria did not predict the study outcome when multivariable Cox regression analyses were performed [HR: 1.847 (95% CI: 0.696-4.904), p=0.218]. Throughout the follow-up, microhematuria disappeared (dropped below 5 RBCs/hpf) in 43 patients (53%), 8 of whom (18.6%) reached the study outcome as compared to 11 patients (28.9%) with persistent microhematuria (p=0.273). Disappearance of microhematuria was not a predictor of study outcome, as well [HR: 0.386 (95% CI: 0.068-2.180), p=0.281]. Conclusion Microhematuria is not associated with renal outcomes of adult patients with IgAN.

BACKGROUND AND AIMS Galectin-9, interferon-inducible protein-10 (IP-10) and sialoadhesin (SIGLEC-1) are considered as potential biomarkers reflecting disease activity in patients with systemic lupus erythematosus (SLE). In this study, we aimed to investigate the association of serum and urine galectin-9, IP-10 and SIGLEC-1 with disease activity in patients with SLE. Also, we compared the results with ANCA-associated vasculitis (AAV) to test the specificity of the biomarkers. METHOD A total of 63 patients with active SLE (31 renal and 32 extrarenal) were included in the study. A total of 30 patients with inactive SLE (15 renal and 15 extrarenal), 17 with renal active AAV and 32 healthy volunteers were selected as control groups. Serum (s) and urine (u) levels of galectin-9, IP-10 and SIGLEC-1 were tested using ELISA. Urine levels of biomarkers were normalized by urine creatinine. RESULTS Of 142 participants, 109 (76.7%) were female and median age was 36 (28.75–48) years. Groups were comparable with regard to sex and age distribution except for AAV. In AAV group, seven patients (41.1%) were female and median age was 60 (48–65.5) years. Proliferative lupus nephritis (LN) (class III/III + V and IV/IV + V) were found in 22 patients with active renal SLE (70.9%), while 6 patients (19.3%) had pure class V and 3 (9.7%) had class II LN. Levels of sIP-10, uIP-10, sGalectin-9 and uSIGLEC-1 were significantly higher in the active SLE group compared to the inactive SLE group (sIP-10; P = 0.046, uIP-10; P < 0.001, sGalectin-9; P = 0.031 and uSIGLEC-1; P = 0.006); however, no differences were detected in the comparison of uGalectin-9 and sSIGLEC-1 between these two groups (uGalectin-9; P = 0.180 and sSIGLEC-1; P = 0.699). sIP-10 (P < 0.001), uIP-10 (P = 0.029) and uGalectin-9 (P < 0.001) were significantly higher in patients with active SLE compared to AAV (Table 1). Serum and urine galectin-9, IP-10 and SIGLEC-1 did not differ between patients with active renal and extrarenal SLE. Levels of sIP-10, uIP-10 and uSIGLEC-1 were correlated with SLE Disease Activity Index (SLEDAI). ROC analyses confirmed that sIP-10, uIP-10, sGalectin-9 and uSIGLEC-1 discriminated disease activity in SLE (Figure 1). Serum and urine levels of all biomarkers were retested in 41 of 63 patients (65%) with active SLE after a median treatment of 8 (5–22.5) months. At the time of the second tests, there was a significant decrease in disease activity as measured by SLEDAI [2 (0–4)] compared to the time of the first tests [10 (6–15.5)]. Comparison of sGalectin-9 levels between the sample at the time of active disease and remission showed a very significant decline (P < 0.001). uGalectin-9, sIP-10 and uSIGLEC-1 also decreased after treatment; however, the difference was not statistically significant. CONCLUSION sIP-10, uIP-10, sGalectin-9 and uSIGLEC-1 are associated with disease activity in SLE. None is able to discriminate active renal from active extrarenal disease. sIP-10 and uIP-10 are specific for active SLE compared to renal active AAV. sGalectin-9 may be a valuable biomarker to monitor response after treatment for active disease. Funded by Scientific Research Projects Coordination Unit of Istanbul University. Project number: TSA-2019–34 218.

BackgroundCD163 is a glycosylated membrane protein expressed in monocytes and macrophages that phagocytize the hemoglobin/haptoglobin complex. As a result of proinflammatory stimuli, CD163 is shedded from the cell membrane and becomes soluble CD163. Therefore, it has been shown that serum (s) and urine (u) levels of soluble CD163 increase in acute or chronic inflammatory diseases. sCD163 and uCD163 are considered as potential biomarkers reflecting disease activity in patients with systemic lupus erythematosus (SLE).ObjectivesWe aimed to investigate the association of serum and urine soluble CD163 levels and renal CD163 expression with disease activity in patients with lupus nephritis (LN).MethodsSerum and urine levels of CD163 of 45 SLE patients (active renal 20, active non-renal 15, inactive 10) and 20 healthy volunteers were tested by ELISA. Control samples were taken from 12 active renal patients after six months of treatment and 30 renal biopsy specimens were examined for CD163 expression.ResultsOf 45 participants, 37 (82.2%) were female, with a median disease duration of 113 (1-436) months and a mean age of 38,9±13 (18-68) years. Both the frequency of uCD163 positivity and its levels were significantly higher in the active LN group compared to the inactive LN (p=0,007 and 0.02 respectively) and active non-renal SLE (p=0,001 and 0.023 respectively) groups (Table 1). sCD163 and uCD163 levels of 12 patients with active LN were significantly reduced after treatment (p=0,04 and p=0,006) (Figure 1). CD163+ macrophage expression in kidney biopsies of patients with active LN correlated with sCD163 (r= 0.597 and p=0.01) and uCD163 (r=0.507 and p=0.045) levels.ConclusionuCD163 is a promising biomarker that can differentiate active LN from inactive LN and active extrarenal SLE changing in line with treatment response. Correlation of both s and uCD163 with CD163+ macrophage expression in biopsies suggests that it may be used as an activity parameter in patients with lupus nephritis histopathologically. Further studies are awaited to confirm these results (This study was funded by Istanbul University with the project number TTU-2021-38289)Table 1.Serum and urine levels of CD163 across study groupsBiomarkerActive LN (n=20)Inactive LN (n=10)PExtrarenal active SLE (n=15)PHealthy control (n=20)PSerum CD163 % binding (mean+SD)26,7±17,622,8±18,80,5422,06±9,60,317,03±15,60,4Serum CD163 positivity n (%)%75%500,2%730,9%400,05Urine CD163 % binding (mean+SD)3,9±2,42,6±0,040,022,5±0,10,0232,6±0,50,03Urine CD163 positivity n (%)%90%400,007%330,001%12<0,001LN lupus nephritis, SLE systemic lupus erythematosus, SD standard deviationREFERENCES:NIL.Acknowledgements:NIL.Disclosure of InterestsNone Declared.