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BackgroundMany activity indices have been developed for Systemic Lupus Erythematosus. However, they present important limitations due to the multi-organ compromise.The SLEDAI score and its different versions are widely used in daily practice and in clinical research.Diogo Jesus et al (2018) developed the SLE-DAS (Systemic Lupus Erythematosus Disease Activity Score), that include 17 items, 4 of them continuous. SLE-DAS assesses disease activity in the 28 previous days using an online calculator, with clinical characteristics non-evaluated by SLEDAI. It showed greater precision to measure disease activity, greater sensitivity to detect clinically significant changes and better performance to predict accumulated damage than SLEDAI. It has not yet been validated in Argentina.ObjectivesTo determine the validity of the SLE-DAS score in a population of patients with SLE from Argentina.MethodsA multicenter observational study was conducted. Outpatients and hospitalized patients with SLE from 9 Argentinian centers were included between July to August 2021. Socio-demographic and disease variables were studied and SLE activity was measured by physician’s global assessment (PGA), SLEDAI 2K and SLE-DAS. The disease activity categories used for SLE-DAS were: remission ≤2.08; mild activity >2.08 to 7.10, moderate and severe activity >7.10. For SLEDAI 2K, remission was considered 0, mild activity 1 to 5, moderate 6 to 10, high 11 to 19, very high >20 points.To determine construct validity and criterion validity, SLEDAI 2K and PGA were used as the gold standard and correlation between scores was analyzed with the Pearson and Spearman correlation coefficient. Sensitivity and specificity of the points that define each of the activity levels were established by ROC curves to determine the discriminative capacity of SLE-DAS.ResultsA multicenter observational study was conducted. Outpatients and hospitalized patients with SLE from 9 Argentinian centers were included between July to August 2021. Socio-demographic and disease variables were studied and SLE activity was measured by physician’s global assessment (PGA), SLEDAI 2K and SLE-DAS. The disease activity categories used for SLE-DAS were: remission ≤2.08; mild activity >2.08 to 7.10, moderate and severe activity >7.10. For SLEDAI 2K, remission was considered 0, mild activity 1 to 5, moderate 6 to 10, high 11 to 19, very high >20 points.To determine construct validity and criterion validity, SLEDAI 2K and PGA were used as the gold standard and correlation between scores was analyzed with the Pearson and Spearman correlation coefficient. Sensitivity and specificity of the points that define each of the activity levels were established by ROC curves to determine the discriminative capacity of SLE-DAS.ConclusionIn this population of lupus patients from Argentina, the SLE-DAS allowed to discriminate between remission and disease activity, being a useful and practical tool.Disclosure of InterestsNone declared

BackgroundAdvances in rheumatology and new therapeutic options have certainly impacted patient survival, changing the age range, from youth to seniors. The differences between the age groups could influence the evolution of the disease and the adverse events (AEs) related to the treatments. There are few real-world data on the safety and efficacy of treatments in different age groups.ObjectivesTo evaluate the frequency of AEs and the survival of treatments according to the age in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) or ankylosing spondylitis (AS).MethodsRetrospective, observational, multicenter study of real-life data of patients included in the BIOBADASAR 3.0 registry; exposed and not exposed to original biological treatments (b-DMARDs), biosimilars, targeted synthetic drugs (ts-DMARDs). The unexposed group received treatment with conventional disease-modifying drugs (cDMARDs). A Kaplan-Meier and Log Rank Test analysis was performed to study AEs-free survival and treatment in different age groups (young people 65). Factors related to treatment survival were evaluated using Cox regression models.Results5,297 patients were included, 80.3% female, mean age 43.7 years (SD 15.6) and median disease progression 14.3 [IQR 11.5]. RA 4658 (87.9%); APs 490 (9.25%) and EA 149 (2.8%). The main reason for treatment discontinuation was ineffectiveness, in 624 patients in the exposed group and in 53 (2.5%) patients in control group, followed by the presence of AEs in 352 (11.2%) and 83 (3.9%), respectively (p=0.001).A mean Charlson Score of 0.268 (SD 0.6) in the exposed group and 0.306 (SD 0.7) in the control group (p=0.095). Median EAs-free survival in the exposed group was 12.5 years [IQR 16.6] while in controls was 28 years [IQR 11], p0.017). The exposed group presented a median treatment survival in years of 11.25 years [IQR: 10] in young people; 12.5 years [IQR: 4.7] in young adults, 7.5 years [IQR: 12.1] in mature adults and 4.5 years [IQR: 1.14] in old adults (p>0.0001). Considering only the first line of treatment, a median survival of 11.5 years [IQR: 10] was evidenced in the age group 65 years old (p>0.004). (Figure 1). Considering the second line of treatment, the differences between the groups were not statistically significant (p=0.57). In the multivariate regression model for patients with RA, the factors with the greatest impact on treatment survival were female sex (HR 1.3, 95% CI 1.2-1.4), old age (HR 1.01, 95% CI 1.008-1.01), treatment with steroids (HR 1.19, 95% CI1.1-1.2) and longer disease duration (HR 1.01, 95% CI1.01 – 1.02).ConclusionIn the present study we were able to demonstrate a greater occurrence of AEs in old adults and mature adults compared to young people and young adults. Conversely, survival for b-DMARDs and ts-DMARDs were greater in youth and young adults. In patients with RA, female sex, corticosteroid therapy, old aged and longer disease duration were associated with treatment discontinuation.References[1]Souto A, et al. Rate of discontinuation and drug survival of biologic therapies in rheumatoid arthritis: a systematic review and meta-analysis of drug registries and health care databases. Rheumatology (Oxford). 2016;55(3):523–34.[2]Ray D, et al. Immune senescence, epigenetics and autoimmunity. Clin Immunol. 2018 Nov;196:59-63. doi: 10.1016/j.clim.2018.04.002. Epub 2018 Apr 11.[3]Vela P, et al. Influence of age on the occurrence of adverse events in rheumatic patients at the onset of biological treatment: data from the BIOBADASER III register. Arthritis Res Ther. 2020 Jun 15;22(1):143. doi: 10.1186/s13075-020-02231-x.Disclosure of InterestsNone declared

BackgroundInterstitial Lung Disease (ILD) is a frequent complication in patients with autoimmune diseases. Rheumatoid arthritis (RA) does not escape this statement. Different protocols have been proposed for the ultrasound evaluation of this affectation showing very good correlation with high-resolution computed tomography.ObjectivesTo determine the sensitivity and specificity of an ultrasound evaluation protocol as a screening method for interstitial lung disease in rheumatoid arthritis.MethodsConsecutive patients diagnosed with RA, with and without ILD, will be included. High-resolution chest CT (HRCT) will be performed in all patients. The lung evaluation protocol by ultrasonography (US); evaluates 50 intercostal spaces (ICS) and will be performed by a rheumatologist and imaging specialist trained in the procedure. The presence of B lines and pleural alterations in the EICs explored will be evaluated. A semiquantitative scale will be used to assess each EIC: 0 = normal, ( 50 B lines). CT scan was considered the “gold standard” for the diagnosis of ILD and they were evaluated by experienced pulmonologists who were blind to the patient.Results79 patients were included. Female sex 77% with a mean age of 55 (SD 11.4). The comorbidities observed were: hypertension 27%, dyslipidemia 15%, diabetes mellitus 10%, hypothyroidism 30%, smokers 14%, former smokers 18% and osteoporosis in 14% of patients. The patients had a median duration of the disease in years of 7.5 [IQR 9.2]. Erosive disease was seen in 20 (20%) and rheumatoid nodules in 9.1% of patients. 91% of the patients were under treatment with corticosteroids. Rheumatoid factor was observed in 87% of the patients and Anti-CCP in 71% of the patients, of which 70% had high titers. DILD was observed by HRCT in 21 (27%) patients. The tomographic patterns observed were UIP 7 (33%), probable UIP 2 (10%), cellular NSIP 6 (29%), fibrosing NSIP 3 (14%). An indeterminate pattern was observed in 3 patients. The extent of pulmonary involvement was extensive in 48% of patients and limited in 52%. A sensitivity of 63% (CI95% 44-78) and a specificity of 92% (CI95% 81-97) were observed for the ultrasound evaluation protocol with a PPV of 81% (CI95% 61-92) and NPV of 83 % (95% CI 71-90) and an LR+ 8.1 (95% CI 4.6-14.3) and LR- 0.4 (95% CI 0.3-0.48). AUC: 0.81 (pConclusionWe observed a moderate sensitivity and specificity of the method to assess interstitial lung involvement in RA with an acceptable AUC for a screening method. These findings are similar to what was found in other cohorts. We observe a high NPV. This means that in patients with a negative study result, the possibility of ILD would be removed. Studies in larger cohorts and comparison with other factors associated with ILD are necessary to improve our understanding of the method and give it the place it deserves.References[1]Spagnolo P. et al. The Lung in Rheumatoid Arthritis ARTHRITIS & RHEUMATOLOGY Vol. 70, No. 10, 2018, pp 1544–1554[2]Barskova T. et al. Lung ultrasound for the screening of interstitial lung disease in very early systemic sclerosis. Ann Rheum Dis 2013;72:390–395.[3]GUTIERREZ M, SALAFFI F, CAROTTI M et al.: Utility of a simplified ultrasound assessment to assess interstitial pulmonary fibrosis in connective tissue disorders – preliminary results. Arthritis Res Ther 2011; 13: R134.[4]Cazenave T. et al. EVALUACIÓN DE PARÉNQUIMA PULMONAR Y LINEA PLEURAL POR ULTRASONOGRAFÍA: GRADO DE ACUERDO ENTRE OBSERVADORES ARGENTINOS. 53° Congreso de Reumatología.Salta. 2020.Disclosure of InterestsNone declared

Background:SARS-CoV-2 infection can present with a broad clinical spectrum, from asymptomatic to lethal. Different risk factors have been recognized. Socio-economic status and educational level may affect access to the healthcare system and therefore COVID-19 infection outcome.Objectives:The aim of this study was to assess the association between socio-demographic status and educational level and SARS-CoV-2 outcomes, such as hospitalization, ICU admission, need for mechanical ventilation and death, in Argentinean patients with rheumatic diseases from the SAR-COVID Registry.Methods:We performed a cross-sectional study of consecutive adult patients with rheumatic diseases and SARS-CoV-2 infection included in the multicentric Argentinean SAR-COVID Registry. The following variables were included: gender, ethnicity, age, health insurance, educational level (under or over 12 years of education), socio-economic level according to Graffar Scale in high, medium-high, medium, medium-low, low; underlying rheumatic disease, its duration and treatment at the time of infection.SARS-CoV-2 infection outcomes were: hospitalization, admission to ICU, mechanical ventilation requirement and death.Statistical analysis was performed using Chi2, Fisher, T-test, ANOVA.Results:Five hundred and twenty-five patients were included, 422 (80.4%) were female, with a mean age of 51.3 years (SD 15.2). Most of them were caucasians (48%) or mestizos (43%) and 96.8% lived in an urban environment. Almost half of the patients (47%) were categorized as middle-class, 24% middle-high or high class, 21% middle-low or low. 48.4% of the patients were employed. Regarding educational level, 54% had more than 12 years of education.The most prevalent rheumatic disease was Rheumatoid Arthritis (40.4%), followed by Systemic Lupus Erythematosus (14.9%), Sjögren (5.5%) and Psoriatic Arthritis (5.5%). Treatments used at the time of SARS-CoV-2 infection were corticosteroids (19%), cs-DMARDs (49%), and b- and ts-DMARDs (16%).Overall hospitalization frequency was 35%, median hospital stay was 10 days (IQR 10 days), 11.6% were admitted to the ICU, 10% required mechanical ventilation and the global mortality was 8%.Notably, patients with less than 12 years of education required mechanical ventilation more frequently than the more educated ones (11.9% vs. 5.6%, p=0.026) and showed a higher mortality due to COVID-19 (9% vs. 2.8%, p=0.0004).Patients categorized as upper social classes (middle-high and high) were admitted to the hospital on a more frequent basis (74.4% of cases), when compared with middle class (64.4%) and middle-low and low class (58%) (p=0.77). Median duration of hospitalization for the aforementioned groups was 12.5 (IQR 17.3), 10 (IQR 9) and 10.5 (IQR 9.3) days respectively (p=0.60).Patients with health insurance were found to be hospitalized more frequently in comparison to those without insurance (42.4% vs. 33.7%, p=0.14), but showed similar admission rates to the ICU (11.8% vs. 12.8%; p=0.78), need for mechanical ventilation (10.7% vs. 8.7%; p=0.70) and mortality (7.1% vs. 6.5%; p=0.99).Caucasian patients had fewer hospital admissions when compared against other ethnicities (mestizos mostly) (26.1% vs. 43.4%; pConclusion:Patients with lower educational level needed twice the frequency of mechanical ventilation, and showed thrice the mortality than those with more than 12 years of education.Albeit patients in upper social stratus and those with health insurance were admitted to the hospital in a more frequent manner, no statistically significant differences were found regarding the need for ICU, mechanical ventilation or mortality.Caucasians were hospitalized less frequently than mestizos, but had no significant differences in the other measured outcomes.Disclosure of Interests:Laura Sorrentino Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Jonathan Rebak Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Federico Maldonado Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Vanessa Viviana Castro Coello Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Alejandro Brigante Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Adriana Hamaui Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Diana Dubinsky Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Roberto Baez Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Cecilia Pisoni Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Carla Gobbi Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Leandro Carlevaris Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Romina Tanten Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Adriana Karina Cogo Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Maria DeLaVega Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Rodolfo Perez Alamino Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Maria Alicia Lazaro Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Mariana Pera Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Susana Isabel Pineda Vidal Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Maria Elena Calvo Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Debora Guaglianone Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Carla G Alonso Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Mara Guinsburg Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Cinthya Retamozo Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Carolina Aeschlimann Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Rosana Quintana Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Karen Roberts Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Carolina Ayelen Isnardi Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Guillermo Pons Estel Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.

Background:In the last time, many papers about SARS-CoV-2 have been published in the world. However, data from latinamerican patients is still scarce. In order to assess the impact of SARS-CoV-2 infection in patients with rheumatic diseases in our country and contribute to the global knowledge about the effect of immunosuppressive therapies in this group, the Argentine Society of Rheumatology has developed the National Registry of Patients with Rheumatic Diseases and COVID-19 (SAR-COVID).Objectives:The aim of this study was to evaluate clinical characteristics and outcomes of SARS-CoV-2 infection in patients with rheumatic diseases, treated or not with immunomodulators and/or immunosuppressants.Methods:SAR-COVID is a national, multicenter, prospective and observational registry, in which patients, ≥18 years of age, with a diagnosis of a rheumatic disease who had SARS-CoV-2 infection (PCR or positive serology) are consecutively included between August 13, 2020 and January 17, 2021. Sociodemographic data, comorbidities, underlying rheumatic disease and treatment, clinical characteristics, complications, laboratory and treatment of the SARS-CoV-2 infection were recorded. Hospitalization, mechanical ventilation requirements and death were assessed to evaluate COVID-19 outcome. Statistical analysis: Descriptive analysis. Chi2 or Fischer test and T test or Mann-Whitney U test or ANOVA, as appropriate. Multiple logistic regression.Results:A total of 525 patients were included, 80.4% were female, with a median age of 52 years (IQR 40-62). Comorbidities were reported in half of them (53.3%). The most frequent rheumatological diseases were rheumatoid arthritis (40.4%) and systemic lupus erythematosus (14.9%). At the time of the infection, most of them were in remission or in minimal/low disease activity (68.2%) and 72.9% were receiving immunosuppressive or immunomodulatory treatment.Symptoms were present in 96% of the patients, the most frequent being fever (56.2%), cough (46.7%) and headache (39.2%). During infection, 35.1% received some pharmacological treatment, dexamethasone (20%) the most frequently used. One third (35.1%) of the patients were hospitalized, 11.6% were admitted to the ICU, 10.1% needed mechanical ventilation and 6.9% died due to COVID-19. Complications were reported in 12.4%, being acute respiratory distress syndrome the most prevalent (8.8%).Patients over 65 years of age were more frequently hospitalized, admitted to the ICU, needed mechanical ventilation and died due to COVID-19 (50% vs 31.4%, 22% vs 9%, 16.3% vs 5.2%, 14% vs 5%, respectively; pConclusion:In this cohort of patients with a wide distribution of rheumatic diseases, we have found clinical characteristics similar to those reported by other international cohorts. Compared with national data, the mortality reported in these patients is higher. However, it should be noted that these are early data collected during isolation and that there may be an underreporting of asymptomatic patients or with mild symptoms who do not attend the rheumatologist.Older patients, those with comorbidities, with vasculitis and with higher disease activity showed poor COVID-19 outcomes.Disclosure of Interests:Carolina Ayelen Isnardi Speakers bureau: Janssen, BMS, Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Rosana Quintana Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Karen Roberts Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Vanessa Viviana Castro Coello Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Alvaro Andres Reyes Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Yohana Tissera Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Micaela Cosatti Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Romina Rojas Tessel Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Julia Scafati Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Tatiana Barbich Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., María Soledad Gálvez Elkin Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Gustavo Fabian Rodriguez Gil Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Sebastian Moyano Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Marina Laura Werner Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Jonathan Rebak Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Julieta Morbiducci Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Victoria Martire Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., María Sol Castaño Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Carolina Dieguez Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Gisela Constanza Subils Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data., Guillermo Pons-Estel Grant/research support from: Unrestricted grants: Pfizer, Abbvie, Elea Phoenix. None of them have access to patient data.