Background:It has been described an increased prevalence of cardiovascular diseases (CVD) in rheumatoid arthritis (RA) patients. When compared with the general population, CVD mortality is 50% higher in RA (1). It is reported a 35.3% prevalence of CVD in Latin-American population with RA (2). Cardio-rheuma (CR) clinics were designed to enhance detection, prevention and treatment of CVD in patients with rheumatic conditions. Our clinic located in the University Hospital in Monterrey Mexico, is the first and only established in Latin-America since 2014.Objectives:To describe the characteristics of patients with RA attending to a Latin-American CR clinic and compare the findings by carotid ultrasound (US) and echocardiography to controls.Methods:Cross-sectional, observational, comparative study. RA patients aged 40 to 75 years that fulfilled the 2010 EULAR criteria and matched controls were included. Patients with prior atherosclerotic CVD and overlap syndromes were excluded. Clinical history, blood samples, physical exam, carotid US and echocardiography were performed. Carotid plaque (CP) was defined as a focal narrowing ≥0.5 mm of the surrounding lumen or a carotid intima media thickness (cIMT) ≥1.2 mm, and increased cIMT was defined as ≥0.9 mm. Transthoracic echocardiogram was performed and reviewed by 2 board-certified cardiologists. Differences were solved by consensus. Categorical variables are expressed as total number (%), and numerical variables as median (q25-q75). Chi square and Mann-Whitney U-test were used to compare groups and considered significant if p<0.05.Results:A total of 336 RA patients and 144 controls were included (Table 1). Table 2 summarizes echocardiographic and carotid US findings; ejection fraction was higher in controls than RA patients, prevalence of bilateral CP and increased cIMT was significantly higher in RA patients.Table 1 Patient characteristics Variable RA (n=336) Controls (n=144) p Age (years), median (q25-q75)55.5 (48-61)53 (48-58)0.017Women, n (%)311 (92.6)134 (93.1)NSDisease duration (years), median (q25-q75)7.8 (3.2-15)--BMI (kg/m2), median (q25-q75)27.6 (25.1-31.2)27.8 (24.9-31.5)NSDiabetes Mellitus, n (%)47 (14)14 (9.7)NSDyslipidemia, n (%)93 (27.7)31 (21.5)NSHypertension, n (%)93 (27.7)31 (21.5)NSDAS28-CRP, median (q25-q75)3.2 (2.1-4.3)--Past or current smoker, n (%)65 (19.3)36 (25)NSNonsteroidal anti-inflammatory drugs, n (%)90 (26.8)--Prednisone, n (%)195 (58)--Methotrexate, n (%)283 (84.2)--Leflunomide, n (%)69 (20.5)--Chloroquine, n (%)54 (16.1)--Sulfasalazine, n (%)59 (17.6)--Hydroxychloroquine, n (%)34 (10.1)--Biologic DMARDs, n (%)21 (6.3)--Table 2 Echocardiographic and carotid US findings Echocardiography RA (n=60) Controls (n=28) p Ejection fraction, median (q25-q75)60 (56.2-65.0)63 (60-69) 0.008 Abnormal LV geometry, n (%)21 (35)7 (25)NSAbnormal LA geometry, n (%)6 (10)3 (10.7)NS Carotid US, n (%) RA (n=128) Controls (n=110) CP38 (29.7)25 (22.7) NS Increased cIMT64 (50)32 (29.1) 0.001 Unilateral CP18 (14.1)17 (15.5) NS Bilateral CP20 (15.6)8 (7.3)...

Background:Rheumatoid arthritis (RA) is an inflammatory disease with an increased mortality compared to the general population. The measurement of carotid intima media thickness (CIMT) is used as an independent marker of subclinical atherosclerosis.Objectives:To determine the prevalence of carotid plaque (CP) in a cohort of Mexican RA subjects and diagnostic performance of cardiovascular risk (CVR) calculators for the prediction of augmented CIMT and CP.Methods:A cross-sectional study of subjects aged from 40-75 years that fulfilled the 2010 ACR/EULAR RA criteria. Exclusion criteria: previous CV disease and overlap syndromes. CVR was calculated by 6 scales: ACC/AHA 2013, Framingham-lipids (FRS-lipids), Framingham-Body Mass Index (FRS-BMI), Reynolds Risk Score (RRS), QRISK2 and SCORE. Carotid ultrasound (US) was performed by a board-certified radiologist and reviewed by other two. We defined an augmented CIMT as ≥0.9 mm and CP as CIMT ≥1.2 mm. We categorized subjects in 3 groups: 1) normal carotid US, 2) augmented CIMT, and 3) CP. We used Kruskal-Wallis test to compare the groups.Results:130 patients were included, 124 (95.4%) were females with median age of 57 years old and disease duration of 9.7 years. Almost 50% of the subjects with CP were in the low-risk strata of every CVR calculator. The presence of CP was higher in subjects categorized as moderate/high risk using ACC/AHA 2013 CVR score (p=0.013), moderate/high risk strata of QRISK2 (p=0.004), and high-risk strata of ACC/AHA 2013 CVR score (p=0.02). Of these 3, the highest sensitivity was obtained by the moderate risk stratum of QRISK2 with 51%; the highest specificity was obtained by the high-risk stratum of the ACC/AHA 2013 CVR score with 84%.Table 1Comparison groups CP presence N=39 CIMT ≥0.9mm N= 29 Normal CIMT N= 62 p Age years59 (55-66)60 (53-70)51 (44-58) 0.00 BMI kg/m2 27.3 (25.3-29.9)27.8 (24.7-31.3)29.9 (26.6-34.5) 0.022 ACC/AHA 20134.6 (2.3-10.2)5.6 (2.2-11.8)1.7 (0.7-3.5) 0.00 FRS-LIPIDS7.1 (5.3-10.3)9.25 (6.1-13.4)3.8 (2.1-6.1) 0.00 FRS-BMI10.4 (7.7-15.4)12.2 (8.7-21.6)4.8 (2.7-9.3) 0.00 SCORE1 (0.5-2)1 (0-2)0 (0-1) 0.00 QRISK210.5 (5.2-16.7)11.6 (5.6-17.1)3.1 (1.9-6.3) 0.00 RRS2 (1.3-4)3 (1-5.7)1 (1-2) 0.00 Variables reported as median, (q25 - q75)Table 2.Diagnostic test performance CVR score moderate and high risk CP (n=39) No CP (n=91) p HR (95% CI) Sens (%) Spec (%) PPV (%) NPV (%) ACC/AHA 2013, n (%)19 (48.7)24 (26.4) 0.01 2.6 (1.2-5.7) 0.480.730.440.77FRS-Lipids, n (%)11 (28.2)17 (18.7)0.221.71 (0.7-4)0.280.810.390.72FRS-BMI, n (%)20 (51.3)31 (34.1)0.062.03 (0.9-4.3)0.510.650.390.75QRISK2, n (%)20 (51.3)23 (25.3) 0.00 3.1 (1.4-6.8) 0.510.740.460.78RRS, n (%)2 (5.1)2 (2.2)0.372.4 (0.3-17.7)0.050.970.500.70Conclusion:Increased CIMT or CP might be unidentified if the risk is exclusively determined by CVR calculators. Patients with a CIMT ≥0.9 mm had an average score that placed them in the low risk strata, leading to an underestimation of their real CVR. Calculators can be helpful to estimate the CVR, however, they don’t seem...

Background:There has been seen a low adherence to treatment in patients with rheumatic diseases, which can have important consequences in disease prognosis. Although literature in Latin-American population is scarce, a previous study evaluating medication adherence in this population reported a 16.4% prevalence of adherence in Rheumatoid Arthritis (RA) and 45.9% in Systemic Lupus Erythematosus (SLE) patients (1). It has been demonstrated better outcomes in patients with rheumatic conditions who have good adherence to treatment therapies (2).Objectives:To describe the adherence to synthetic Disease-Modifying Antirheumatic Drugs (DMARDs) in patients with rheumatic diseases from a Mexican outpatient rheumatology clinic.Methods:This study was conducted in the outpatient rheumatology clinic of University Hospital in Monterrey, México, cross-sectional, descriptive, self-report adherence study. Consecutive patients with RA, SLE, Inflammatory Myopathies, Psoriatic arthritis (PsA), Systemic Sclerosis (SSc) were approached during their normal routine rheumatology appointments, in the March 2018 to December 2018 period. They were asked how many days of the last month they forgot or took their DMARDs. We classified the adherence rate in 4 categories based on the days of the last month it took the indicated medication; good: 75%-100% (> 21 days), regular 50-74% (21-15 days), bad 25-49% (14-8 days) and null: <25% (< 7 days). When adherence was not good we interrogated about the cause. Data was obtained from REPAIR ® (internal electronic patient record) and analyzed with the statistical package SPSS version 24.Table 1 Adherence for Rheumatic Disease Group n (DMARDs) Good n (%) Regular n (%) Bad n (%) Null n (%) Rheumatoid Arthritis1,6861442(85.5)105(6.2)47(2.8)92(5.5)Systemic Lupus Erythematosus440393(89.3)16(3.6)12(2.7)19(4.3)Inflammatory Myopathies9183(92.1)2(2.2)0(0)6(6.6)Psoriatic arthritis8476(90.5)1(1.2)3(3.6)4(4.8)Systemic Sclerosis9180(87.9)6(6.6)1(1.1)4(4.4)N2,392Table 2 Reasons for Bad or Null adherence Rheumatoid Arthritis % Systemic Lupus Erythematosus % Inflammatory Myopathies % Psoriatic arthritis % Systemic Sclerosis % Economic30.133.337.53720Own decision27.933.312.52540Side effects11.511.112.512.50Lack of availability1513.312.512.540forgetfulness of dose11.94.42512.50Other3.54.4000Conclusion:Adherence in this group of patients was good, for the definition used in our study.The method used (self-report) is very sensitive to detect non-adherence, but it overestimate good adherence, therefore the potential bias of results must be considered and confirmed whit objective measurement.The main reason for poor or no adherence was the economic, with the exception of the Ssc group it was their own decision and the patients with SLE that had the same percentage for economic and self-decision.References[1] - Resende Prudente L, Souza Diniz J, Matteucci Ferreira TXA, Marçal Lima D, Antônio Silva N, Saraiva G, et al. Medication adherence in patients in treatment for rheumatoid arthritis and systemic lupus erythematosus...

Background:Several immune-inflammatory diseases are associated with an increased prevalence of cardiovascular diseases. Risk reduction through improved control of traditional cardiovascular risk (CVR) factors and the adoption of healthy lifestyle behaviors are critically important to reduce the CVR, although the general population must be aware of their CVR to make healthy sound decisions. Individuals who perceive an increased risk are more likely to adopt behaviors to reduce it, such as smoking cessation, exercise, weight loss, and medication compliance.Objectives:The aim of this study is to assess the awareness of the CVR in patients with/without rheumatic diseases (RD).Methods:Observational, cross-sectional study was design. Subjects with RD attending an outpatient clinic were consecutively recruited (RA, SLE, PsA OA, Sjögren syndrome, fibromyalgia, scleroderma, osteoporosis and osteopenia). A complete clinical history was made and a self-applied questionnaire (Precaution Adoption Process Model) was used to assess the awareness of the CVR in patients with RD. Comparisons were made to controls without RD. Frequencies (%), media and median values (q25-q75) were used for descriptive analysis and Chi Square test for comparisons.Figure 1Results:250 patients were included with 76 controls and 174 cases. Demographic characteristics shown in table 1. The majority of the patients located themselves in stage 1 of their CVR perception 31.6% in cases vs. 30.3% in controls (p>0.05), other results are shown in figure 2. In the case group, 69.5% have not made any changes to reduce their CVR and the same was seen in controls. Most of the individuals are unaware of their higher CVR even though they have traditional CVR factors. Only 30.5% of the group of RD have received information from a health care provider about their CVR.Abstract AB1255 Table 1Demographic Characteristics Rheumatic Diseases (n =167 ) Controls (n= 60) p Age, n (%)58 (47-60)51.5 (34-65) 0.001 Female, n (%)156 (89.7)51 (67.1) 0.000 Family history CVD, n (%)79 (45.4)29 (38.2)NSHypertension, n (%)43 (24.7)16 (21.1)NST2DM, n (%)16 (9.2)13 (17.1)NSDyslipidemia, n (%)52 (29.9)26 (34.2)NSMyocardial infarction, n (%)3 (1.7)2 (2.6)NSStroke, n (%)5 (2.3)0NSKidney disease, n (%)6 (3.4)4 (6.6)NSActive smoking, n (%)12 (6.9)8 (10.5)NSInactive lifestyle, n (%)92 (52.9)36 (47.4)NSAbstract AB1255 Table 2Source of Information of Cardiovascular Risk Rheumatic diseases (n= 167) Controls (n= 60) p None, n (%)62 (35.6)24 (31.6)NSHealth care provider, n (%)53 (30.5)19 (25)Television, n (%)18 (10.3)8 (10.5)Magazine, n (%)4 (2.3)2 (2.6)Internet, n (%)14 (8)14 (18.4)Books, n (%)01 (1.3)More than 1, n (%)11 (7.7)5 (5.3)No answer, n (%)12 (6.8)3 (3.9)Conclusion:Even though patients with RD have and increased CVR, most of the individuals perceived it the same as the control group. The majority of the individuals (69.5%) haven’t made any changes to reduce their CVR and many of them didn’t have any source of information about their CVR, and according to EULAR recommendations the r...

Background:Subjects with rheumatic diseases have an increased risk of cardiovascular morbimortality. Hypertension (HTN) is a key modifiable risk factor for cardiovascular events (1). A recently published and validated prediction model (Predicting Out-of-Office Blood Pressure, PROOF-BP) has been proposed as a tool to improve diagnosis of HTN, and detection of out-of-office HTN in subjects with a previous diagnosis, with a c-statistic (AUC) of 0.86 in non-rheumatic subjects (2). This model has not been explored in rheumatic patients.Objectives:To evaluate the diagnostic performance of the PROOF-BP algorithm for the prediction of HTN in subjects with/without rheumatic diseases.Methods:A cross-sectional, observational trial was designed. Subjects were recruited at a rheumatology outpatient clinic in northeastern Mexico. Subjects with/without rheumatologic conditions were recruited. Complete clinical history with somatometry of each subject was registered. BP was measured by a physician 3 times to each participant using current recommendations, with an OMRON HEM-7121 BP monitor. Calculations using the PROOF-BP online site were done, and risk categories were assigned to each subject using their predicted out-of-office BP: low (<130/80 mmHg), medium (130/80-145/90 mmHg) and high risk (>145/90 mmHg). Subjects in the medium and high risk strata were then asked to return for further evaluation and additional BP measurement, to define each diagnosis of HTN. We used frequencies (%) and median (q25-q75) for descriptive analysis. Diagnostic accuracy of each category was determined using 2 x 2 tables.Results:A total of 217 subjects were included. Baseline characteristics are shown in Table 1. The most frequent rheumatic disease was RA (n=78, 35.9%). Using PROOF-BP, 84 (38.7%) subjects were stratified as medium or high risk. Of these, only 36 (42.8%) returned for evaluation. A final diagnosis of HTN was attained in 14 (38.8%) of those who returned. Diagnostic performances of the low and high risk categories are shown in Table 2. In 21 (67.7%) cases of the medium risk category the diagnosis of HTN was finally discarded, and in the remaining 10 (32.2%) diagnosis of HTN was finally ascertained. The high risk category had a specificity of 95% and a PPV of 80% for the diagnosis of HTN.Abstract USAGE Table 1Clinical characteristics.Number of patients, n (%)N= 217Female188 (86.6)Hypertension51 (23.5)T2DM24 (11.1)Dyslipidemia68 (31.3)Active smoking13 (6.0)No rheumatic disease65 (30.0)RA78 (35.9)SLE6 (2.8)Sjögren syndrome5 (2.3)OA29 (13.4)Other34 (15.6)PROOF-BP class:Low risk133 (61.3)Medium risk71 (33.6)High risk11 (5.1)New diagnosis of hypertension14 (38.9)Abstract USAGE Table 2Diagnostic performances.Sensitivity(%)Specificity(%)PPV(%)NVP(%)Low risk1005558100High risk29958068PPV: Positive predictive value; NPV: Negative predictive value.Conclusion:In a cohort of Mexican-mestizo subjects with rheumatic diseases, 38.7% were classified as medium or high-risk for HTN. Only 42.8% of patients that required further evaluation followed medical ...