Cardiovascular Risk Algorithms Research Articles

Evaluation of novel cardiovascular risk calculators in patients with rheumatoid arthritis

Abstract Background Patients with rheumatoid arthritis (RA) have a higher cardiovascular risk (CVR) compared to the general population contributing to a decreased life expectancy. Systematic and periodic assessment of CVR is recommended in all patients with RA. The newly developed PREVENTTM calculator was designed to estimate the absolute risk of cardiovascular disease and provides an estimate of atherosclerotic cardiovascular disease and heart failure. Purpose This study aimed to evaluate the sensitivity and specificity of the new PREVENTTM algorithm to identify CP in RA patients without prior CVD and to compare these results with other CVR algorithms. Methods We performed a cross-sectional study that included patients with RA aged 40 to 79 who fulfilled the 2010 ACR/EULAR Classification Criteria for RA. Patients with previous CVD, pregnancy, or overlap syndrome were excluded. A B-mode carotid ultrasound was performed on all patients. The presence of CP was defined as diffuse carotid intima-media thickness (cIMT) ³1.2 mm or focal thickness ³0.5 mm. The CVR was evaluated using Globorisk, HEARTS, QRISK3, ERS-RA, SCORE2, and PREVENTTM algorithms. The result was multiplied by 1.5 in algorithms where RA is not included as a variable, according to EULAR 2015/2016 recommendations. ROC curve analysis was performed to evaluate the different CVR algorithms' performance to identify CP. Youden index was calculated to select the optimum cutoff point and posteriorly calculate sensitivity, specificity, and predictive values. A p-value of £0.05 was considered statistically significant. Statistical analysis was performed with SPSS version 29.0 (IBM Corp, Armonk, NY, USA). Results A total of 261 patients with RA were included, mostly women (n=244, 93.5%), with a mean age of 56±9.3 years, and a median disease duration of 7.7 (3.0-14.7) years. Dyslipidemia was the most prevalent CVR factor (n=104, 39.8%). The prevalence of CP was 38.0%. According to the ROC curves, the Globorisk, HEARTS, and QRISK3 algorithms showed a higher area under the curve (AUC) than the other algorithms. The HEARTS and QRISK3 algorithms showed the highest positive likelihood ratios, showing rates of 1.87 and 1.84, respectively, to identify RA patients with CP (Figure 1). Conclusion Our study showed that Globorisk, HEARTS, and QRISK3 calculators presented the best diagnostic accuracy to detect CP in patients with RA. The novel CVR calculator PREVENTTM did not show better performance than older calculators in our population. Imaging studies evaluating coronary artery calcium and CP may offer better alternatives in high-risk populations like patients with RA.

Inadequate identification of high cardiovascular risk and carotid plaques in rheumatoid arthritis patients by the 2024 Predicting Risk of Cardiovascular EVENTs and the 2013 Atherosclerotic Cardiovascular Disease algorithms: findings from a Mexican cohort.

The American College of Cardiology/American Heart Association introduced the Predicting Risk of Cardiovascular EVENTs (PREVENT™) algorithm to estimate the 10-year risk of developing cardiovascular disease. We aimed to assess the cardiovascular risk (CVR) reclassification among rheumatoid arthritis (RA) patients using traditional CVR algorithms-the 2024 PREVENT™ and the 2013 Atherosclerotic Cardiovascular Disease (ASCVD)-and the presence of carotid plaque (CP). This was a cross-sectional study nested of a RA patients' cohort. A certified radiologist performed a high-resolution B-mode carotid ultrasound to identify the presence of CP. The CVR evaluation was performed by a cardiologist, blinded to carotid ultrasound results, using the PREVENT™ and the ASCVD algorithms. Cohen's kappa (k) coefficient assessed concordance between high-risk classification by CVR algorithms and CP presence. ROC curve analysis evaluated the algorithms' capacity to identify RA patients with CP. The cutoff point was determined by the Youden-Index, with p < 0.05 as statistically significant. A total of 210 RA patients were included. The reclassification of CVR due to CP was 34.3% for the PREVENT™ algorithm and 30.0% for the ASCVD algorithm. Of these, 44.4% and 71.4%, respectively, were initially classified as low risk. Concordance between CVR algorithms and carotid ultrasound showed slight agreement (k = 0.032 and k = 0.130, respectively). The PREVENT™ algorithm did not identify more than one-third of high-CVR RA patients with indication of starting statin therapy based on carotid ultrasound findings. The PREVENT™ and ASCVD algorithms showed poor performance in identifying RA patients with CP. Key Points • The presence of CP was identified in more than a third of the evaluated RA patients (35.7%), classifying them as high CVR. • CVR reclassification by the presence of CP was observed in 34.3% RA patients with the PREVENTTM algorithm and in 30.0% RA patients with the ASCVD algorithm. • Most of the reclassified patients belonged to the low-risk category, 44.4% with the PREVENTTM algorithm and 71.4% with the ASCVD algorithm. • When evaluating the concordance between the ASCVD algorithm and the carotid ultrasound for high-risk classification, a slight agreement was found (k = 0.130).

Combined use of QRISK3 and SCORE2 increases identification of ankylosing spondylitis patients at high cardiovascular risk: Results from the CARMA Project cohort after 7.5 years of follow-up

ObjectiveTo establish the predictive value of the QRESEARCH risk estimator version 3 (QRISK3) algorithm in identifying Spanish patients with ankylosing spondylitis (AS) at high risk of cardiovascular (CV) events and CV mortality. We also sought to determine whether to combine QRISK3 with another CV risk algorithm: the traditional SCORE, the modified SCORE (mSCORE) EULAR 2015/2016 or the SCORE2 may increase the identification of AS patients with high-risk CV disease. MethodsInformation of 684 patients with AS from the Spanish prospective CARdiovascular in ReuMAtology (CARMA) project who at the time of the initial visit had no history of CV events and were followed in rheumatology outpatient clinics of tertiary centers for 7.5 years was reviewed. The risk chart algorithms were retrospectively tested using baseline data. ResultsAfter 4,907 years of follow-up, 33 AS patients had experienced CV events. Linearized rate=6.73 per 1000 person-years (95 % CI: 4.63, 9.44). The four CV risk scales were strongly correlated. QRISK3 correctly discriminated between people with lower and higher CV risk, although the percentage of accumulated events over 7.5 years was clearly lower than expected according to the risk established by QRISK3. Also, mSCORE EULAR 2015/2016 showed the same discrimination ability as SCORE, although the percentage of predicted events was clearly higher than the percentage of actual events. SCORE2 also had a strong discrimination capacity according to CV risk. Combining QRISK3 with any other scale improved the model. This was especially true for the combination of QRISK3 and SCORE2 which achieved the lowest AIC (406.70) and BIC (415.66), so this combination would be the best predictive model. ConclusionsIn patients from the Spanish CARMA project, the four algorithms tested accurately discriminated those AS patients with higher CV risk and those with lower CV risk. Moreover, a model that includes QRISK3 and SCORE2 combined the best discrimination ability of QRISK3 with the best calibration of SCORE2.

Red Cell Distribution Width Association with Subclinical Cardiovascular Disease in Patients with Rheumatoid Arthritis.

Red cell distribution width (RDW) is a measure of the variation in mean corpuscular volume that reflects the degree of anisocytosis on the peripheral blood smear. RDW value variation has been implicated in several disorders including chronic inflammatory processes and cardiovascular (CV) diseases. In the present work, our objective was to study the relationship that RDW has with the characteristics of the disease in patients with rheumatoid arthritis (RA), focusing on CV risk factors and subclinical atherosclerosis. A cross-sectional study was conducted that included 430 patients with RA and 208 controls matched by sex and age. Complete blood count, including RDW, was assessed. Multivariable analysis was performed to analyze the relationship of RDW with RA disease characteristics, subclinical carotid atherosclerosis, and traditional CV factors, including a comprehensive profile of lipid molecules and insulin resistance and beta cell function indices. After multivariable adjustment, the RDW was significantly higher in RA patients compared with controls (beta coefficient 1.0 [95% confidence interval 0.2 to 1.8] %, p = 0.020). Furthermore, although the erythrocyte sedimentation rate showed a positive and significant relationship with RDW, this association was not found with C-reactive protein and interleukin-6. A positive and independent relationship was observed between DAS28-ESR disease activity score and RDW. However, no association was found between the RDW and other disease activity scores that do not include erythrocyte sedimentation rate in their formula. The SCORE2 CV risk algorithm was positively and significantly associated with higher RDW values. Likewise, a negative relationship was found between RDW with total cholesterol and low-density lipoprotein cholesterol, and a positive relationship was found between RDW and insulin resistance indices. In conclusion, RDW values are higher in RA patients compared to matched controls. Although the relationship of RDW with disease activity was not consistent, RDW shows associations with subclinical CV disease risk factors, including dyslipidemia and insulin resistance, and with the SCORE2 CV disease-risk prediction algorithm.

Cardiovascular mortality risk beyond 10 years in men and women; long-term follow-up from the EPIC-Norfolk prospective population study

Abstract Introduction Current primary prevention strategies in cardiovascular (CV) disease focus on initiating preventive interventions in people at high 10-year risk of CV mortality. However, initiating such strategies should be beneficial not only in the first 10 years, but throughout life. Established risk algorithms estimate the risk of 10-year CV mortality, but limited evidence is available about the relationship between 10-year and longer-term CV mortality. Purpose To compare cumulative incidence of CV mortality in a population cohort at 10- and 20-years follow-up, stratified by sex. Methods We analysed CV mortality at 10-years and 20-years follow-up using Kaplan-Meier estimates among men and women aged 39–70 years without baseline CV disease or diabetes mellitus in the large, prospective population-based EPIC-Norfolk cohort. CV mortality included death with as underlying or contributing cause ischaemic heart disease, heart failure, cerebrovascular disease or peripheral artery disease. Results We analysed data from 20,453 participants (56% women), with a mean age of 56±8 years, and median (IQR) follow-up of 22 (21–23) years. At baseline, there were no clinically relevant differences in CV risk factors between men and women. Overall cumulative CV mortality rate was 1.9% (384 deaths) in the first 10 years, and 7.3% (995 deaths) at 20 years follow-up (ratio 3.8). Among men, 10-year CV mortality was 2.9% (249 deaths), and 9.6% (785 deaths) at 20 years follow-up (ratio 3.3). Among women, CV mortality was 1.2% (135 deaths) at 10 year and 5.5% (594 deaths) at 20 years follow-up (ratio 4.6). Conclusion We observed an incremental increase in CV mortality beyond the 10-year scope of current established CV risk algorithms. At 20 years follow-up, CV mortality rates were 3–5 times higher compared with the first decade, indicating that 20-year CV mortality risk for both men and women cannot simply be estimated based on extrapolation of 10-year risk. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): EPIC-Norfolk is supported by programme grants from the Medical Research Council UK (MRC G0401527, MRC G0701863, MRC G1000143) and Cancer Research UK (CRUK 8257).

Persistence of C-reactive protein increased levels and high disease activity are predictors of cardiovascular disease in patients with axial spondyloarthritis

An accurate prediction of cardiovascular (CV) risk in patients with Axial Spondyloarthritis (axSpA) is a strong unmet need, as CV risk algorithms poorly perform in these subjects. The aim of this study was to establish whether the persistence of high C-reactive protein (CRP) and high disease activity may be considered predictive factors of CVD in axSpA. 295 patients without personal history of CVD, were consecutively enrolled in this study. To evaluate the relationship between CV events occurrence (fatal and non-fatal) and the persistence of increased CRP levels, ASDAS (Ankylosing Spondylitis Disease Activity Score) > 2.1, and BASDAI (Bath Ankylosing Spondylitis Disease Activity) > 4 during the follow-up, univariable and multivariable Cox Proportional Hazard Models have been performed. During follow-up (we analyzed 10-years retrospective data), 23 patients had a CV event. Multivariable Cox Proportional Hazard Models showed a strong association between CV event and the persistency of increased CRP levels (namely, percentage of visits in which CRP levels were increased) (HR = 1.03; 95%CI 1.015–1.045; p < 0.001), of ASDAS > 2.1 (HR = 1.014, 95%CI 1.000–1.028, p = 0.047), and of BASDAI > 4 (HR 1.019, 95%CI 1.006–1.033, p = 0.006) during follow-up, after adjustment for age, sex, and diabetes. This study suggests that persistence of increased CRP levels and high disease activity may be considered biomarkers to identify those axSpA patients at higher risk of CVD. Innovative axSpA-specific CV risk score, including these variables, have to be developed.

High inflammatory burden predicts cardiovascular events in patients with axial spondyloarthritis: a long-term follow-up study.

Background:Axial spondyloarthritis (axSpA) patients are at higher risk of cardiovascular (CV) disease (CVD) than the general population, partly due to consequences of inflammation or its treatment. But relationship between inflammation in axSpA and cardiovascular events (CVE) is unknown.Objectives:To examine whether inflammatory burden over time can predict CVE independent of baseline CV risk factors in axSpA patients.Design:A cohort analysis was performed in patients who had been recruited since January 2001. The primary outcome was a first CVE occurring between January 2001 and December 2020.Methods:Three CVD risk scores were computed at baseline. The performance of the original and modified (*1.5 multiplication factor) CV risk algorithms were assessed. Time-varying Cox proportional hazard models and Kaplan–Meier survival analysis were used to assess whether inflammatory burden (Bath ankylosing spondylitis disease activity index [BASDAI] and inflammatory markers), nonsteroidal anti-inflammatory drugs (NSAIDs) and disease modifying antirheumatic drugs (DMARDs) can predict the development of first CVE.Results:463 patients (35 [26–45] years, male: 360 [77.8%]) were recruited. After a median follow-up of 12 (7–19) years, 61 patients (13.2%) experienced a first CVE. Traditional/modified CV risk scores underestimated CV risk. Erythrocyte sedimentation rate (ESR) ⩾ 20 mm/h was associated with a significantly higher risk of CVE during follow-up (HR: 2.07, 95%CI [1.10, 3.98], p = 0.008). Active disease as indicated by a rising BASDAI also showed positive trend towards a higher risk of developing CVE over time. After adjusting for CV risk scores in the multivariable models, high ESR level (ESR ⩾ 20 mm/h) over time remained significantly associated with a higher risk of developing CV events.Conclusion:Increased inflammatory burden as reflected by elevated ESR levels (ESR ⩾ 20) was associated with increased risk of CVE, while the use of NSAIDs and DMARDs were not.

SCORE2 versus SCORE in patients with systemic lupus erythematosus.

Introduction:Systemic lupus erythematosus (SLE) has been associated with an increased risk of cardiovascular (CV) disease. Recently, the Systematic Coronary Risk Assessment (SCORE), a well-known CV risk algorithm, has been updated to a new predictive model (SCORE2). This new algorithm improves the identification of individuals at high risk of developing CV disease across Europe. Since carotid atherosclerosis is a predictor of future CV events and CV death, our objective was to compare the predictive capacity of SCORE2 versus SCORE for the presence of subclinical carotid atherosclerosis in patients with SLE.Methods:Two hundred and thirty-five individuals over 40 years of age diagnosed with SLE were consecutively recruited in this cross-sectional study. SCORE and SCORE2 were calculated. The relationship of SCORE and SCORE2 with each other, and with the presence of subclinical carotid atherosclerosis (both carotid plaque and carotid intima media thickness -cIMT-), was studied.Results:SCORE2 and SCORE did not correlate with each other (Spearman’s Rho = 0.125, p = 0.065). Although SCORE did not correlate with cIMT (Spearman’s Rho = -0.022, p = 0.75), the correlation of SCORE2 with cIMT was statistically significant (Spearman’s Rho = 0.367, p < 0.001). Similarly, SCORE did not show significant discrimination for the presence of carotid plaque [AUC = 0.521 (95% CI = 0.443–0.600)], while SCORE2 did [AUC = 0.720 (95% CI = 0.656–0.785)]. The difference between AUCs was found to be statistically significant (p < 0.001), thus showing that the prediction capacity of SCORE2 was significantly higher than that of SCORE.Conclusion:In SLE patients, the ability of SCORE2 to predict the presence of subclinical atherosclerosis is higher than that of SCORE. According to our results, SCORE2, rather than SCORE, should be used in the CV risk stratification of patients with SLE. Prospective studies are needed to confirm these findings.

Cardiovascular risk reclassification according to six cardiovascular risk algorithms and carotid ultrasound in psoriatic arthritis patients.

The objective was to compare the prevalence of subclinical atherosclerosis and cardiovascular risk (CVR) reclassification using six CVR algorithms and a carotid ultrasound in psoriatic arthritis (PsA) patients and controls. The method was cross-sectional study. A total of 81 patients aged 40-75 years, who fulfilled the 2006 CASPAR criteria and 81 controls matched by age, gender, and comorbidities were recruited. CVR was evaluated according to six CVR algorithms, including Framingham Risk Score (FRS)-lipids, FRS-body mass index (BMI), Atherosclerotic Cardiovascular Disease (ASCVD) Algorithm, Systematic Coronary Risk Evaluation (SCORE), QRISK3, and Reynolds Risk Score (RRS). A carotid ultrasound was performed to identify the presence of carotid plaque (CP) defined as a carotid intima media thickness ≥ 1.2 mm or a focal narrowing of the surrounding lumen ≥ 0.5mm. Patients with presence of CP, classified in the low-moderate risk by the CVR algorithms, were reclassified to a higher risk category. CP was more prevalent in PsA patients (44.4% vs 24.7%, p = 0.008), as was subclinical atherosclerosis (51.9% vs 33.3%, p = 0.017). When comparing the CVR reclassification to a higher risk category, a difference was found in the six CVR algorithms. The reclassification was more prevalent in PsA patients: 30.8% vs 12.3%, p = 0.004 with FRS-lipids; 28.4% vs 9.9%, p = 0.003 with FRS-BMI; 40.7% vs 19.8%, p = 0.003 with SCORE; 30.9% vs 16.0%, p = 0.026 with ASCVD algorithm; 37.0% vs 19.8%, p = 0.015 with RRS; and 33.3% vs 16.0%, p = 0.011 with QRISK3. The CVR algorithms underestimate the actual CVR of PsA patients. A carotid ultrasound should be considered as part of the CVR evaluation of PsA patients. KEY POINTS: • Subclinical atherosclerosis was more prevalent in psoriatic arthritis patients than controls. • Cardiovascular risk reclassification, through a carotid ultrasound, according to traditional cardiovascular risk algorithms was more common in psoriatic arthritis patients. • The cardiovascular risk algorithm that showed the lowest reclassification rate in psoriatic arthritis patients was the FRS-BMI. • All cardiovascular risk algorithms underestimate the actual risk of psoriatic arthritis patients, preventing the initiation of an adequate cardiovascular treatment.

Younger age and female gender are determinants of underestimated cardiovascular risk in rheumatoid arthritis patients: a prospective cohort study

BackgroundRheumatoid arthritis (RA) patients have an increased cardiovascular (CV) risk. Here, we aimed to investigate whether gender and age are contributing to the misclassification of CV risk in RA patients.MethodsProspectively collected data on cardiovascular risk factors and incident events from the Nijmegen inception cohort were analyzed, with up to 10 years follow-up. Original as well as the EULAR-modified (M)_SCORE algorithms were used to calculate CV risk. Patients were stratified in deciles according to predicted risk; the Hosmer-Lemeshow test was used to check concordance between observed and predicted risk, in subgroups of gender and age.ResultsThere were 863 RA patients included with 128 incident CV events. When using SCORE in the whole group, there was evidence of a discrepancy between the predicted and observed CV risk (H-L test p < 0.003), mainly present in the female subgroup (H-L test p < 0.001). Interestingly, 36% of females who developed an event belonged to the low CV risk group, whereas this was just 10% in RA males. When analyzing the subgroups based on age, a discrepancy was present only in the youngest patients (H-L test p < 0.001 in patients < 55 years) consisting of an underestimation of CV risk (5.3% predicted vs. 8.0% observed). Similar results were obtained when the M_SCORE was applied.ConclusionCV risk is especially underestimated in female and younger RA patients. This suggests that modifying the weight for the female gender and/or younger age in currently used CV risk algorithms might improve their predictive value in RA, contributing to better CV risk management.

Cardiovascular Risk Prediction in Ankylosing Spondylitis: From Traditional Scores to Machine Learning Assessment.

IntroductionThe performance of seven cardiovascular (CV) risk algorithms is evaluated in a multicentric cohort of ankylosing spondylitis (AS) patients. Performance and calibration of traditional CV predictors have been compared with the novel paradigm of machine learning (ML).MethodsA retrospective analysis of prospectively collected data from an AS cohort has been performed. The primary outcome was the first CV event. The discriminatory ability of the algorithms was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), which is like the concordance-statistic (c-statistic). Three ML techniques were considered to calculate the CV risk: support vector machine (SVM), random forest (RF), and k-nearest neighbor (KNN).ResultsOf 133 AS patients enrolled, 18 had a CV event. c-statistic scores of 0.71, 0.61, 0.66, 0.68, 0.66, 0.72, and 0.67 were found, respectively, for SCORE, CUORE, FRS, QRISK2, QRISK3, RRS, and ASSIGN. AUC values for the ML algorithms were: 0.70 for SVM, 0.73 for RF, and 0.64 for KNN. Feature analysis showed that C-reactive protein (CRP) has the highest importance, while SBP and hypertension treatment have lower importance.ConclusionsAll of the evaluated CV risk algorithms exhibit a poor discriminative ability, except for RRS and SCORE, which showed a fair performance. For the first time, we demonstrated that AS patients do not show the traditional ones used by CV scores and that the most important variable is CRP. The present study contributes to a deeper understanding of CV risk in AS, allowing the development of innovative CV risk patient-specific models.

Cardiovascular risk estimation with 5 different algorithms before and after 5 years of bDMARD treatment in rheumatoid arthritis.

Assessing cardiovascular (CV) risk represents a challenge for clinicians because more variables can impact CV risk. The aim of this study was to evaluate the change of CV risk after 5years of biological treatment in rheumatoid arthritis (RA) patients and impact of prolonged low disease activity on 5 different CV risk algorithms. We estimated the CV risk, at baseline and at 5-year follow-up (FU), with the Systematic COronary Risk Evaluation(SCORE) charts, the algorithm 'Progetto Cuore', the QRISK3-2018 score, the Reynold Risk Score(RRS) and the Expanded Risk Score in RA(ERS-RA). Clinical disease activity index(CDAI) was used to define RA activity. Wilcoxon signed-rank test was used to compare CV risk scores. In 110 patients with a 5-year FU on biological disease-modifying anti-rheumatic drug treatment, we observed an increase in the 10-year CV risk estimated by SCORE charts [from mean (SD) 0.9% (1.4) to 1.1% (1.5), P<.001], 'Progetto Cuore' [from mean (SD) 5.5% (7.2) to 6.2% (6.8), P<.001], QRISK3-2018 [from mean (SD) 9.3% (10.1) to 11.9% (10.8), P<.001) and RRS [from mean (SD) 5.6% (6.4) to 6.2% (7.5), P<.05], mainly due to age raise. ERS-RA highlighted a significant decrease of estimated CV risk in patients with persistent CDAI≤10[from mean (SD) 9.6% (11.2) to 7.3% (6.4), P<.05], despite age increase and its impact on the CV risk score. Algorithms commonly used to estimate 10-year CV risk in RA perform differently. Scores that include specific inflammatory RA-related variables seem to decrease with amelioration of disease activity. Further investigations are warranted to explore the predictive value of their changing over time.

Cardiovascular risk in patients with severe mental illness in Italy.

Patients with severe mental illness (SMI), such as schizophrenia or bipolar disorders, are more frequently affected by metabolic syndrome and cardiovascular (CV) diseases than the general population, with a significant reduction in life expectancy. Beyond metabolic syndrome, quantifying the risk of CV morbidity in the long-term may help clinicians to put in place preventive strategies. In this study, we assessed 10-year CV risk in patients with SMI and healthy individuals using an algorithm validated on the Italian general population. Patients aged 35-69years diagnosed with SMI were consecutively recruited from psychiatric acute care units. Single CV risk factors were assessed, and 10-year CV risk calculated by means of the CUORE Project 10-year CV risk algorithm, based on the combination of the following risk factors: age, systolic blood pressure, total and high-density lipoprotein cholesterol, diabetes, smoking habit, and hypertensive treatment. Patients' data were compared with those from the general population. The 10-year CV risk was log-transformed, and multivariable linear regression was used to estimate mean ratios, adjusting for age, and education. Three hundred patients and 3,052 controls were included in the analysis. Among men, the 10-year CV risk score was very similar between patients with SMI and the general population (mean ratio [MR]: 1.02; 95%CI 0.77-1.37), whereas a 39% increase in 10-year CV risk was observed in women with SMI compared to the general population (MR: 1.39; 95%CI 1.16-1.66). In our study, women with SMI were consistently more at risk than the general population counterpart, even at younger age.

Performance and calibration of the algorithm ASSIGN in predicting cardiovascular disease in Italian patients with psoriatic arthritis.

The increased cardiovascular (CV) risk is one of the major challenges in the management of patients with psoriatic arthritis (PsA). Recently, EULAR suggested to adapt the already available CV risk algorithms with a 1.5 multiplication factor in all the patients with rheumatoid arthritis (RA), but it is still uncertain if this adaptation could also be applied to patients with PsA. This study aims to evaluate the performance and calibration of the CV risk algorithm ASSIGN and its adaptations for RA (ASSIGN-RA) and according to EULAR recommendations in a cohort of patients with PsA (ASSIGN*1.5). Prospectively, collected data from two Italian cohorts has been analyzed. The discriminatory ability for CV risk prediction was assessed using the areas under the ROC curves. Calibration between predicted and observed events was assessed by Hosmer-Lemeshow (HL) test and calibration plots. For each algorithm, sensitivity and specificity were calculated for low- to high-risk cut-off (20%). One hundred fifty-five patients were enrolled with an observation of 1550patient/years. Area under the ROC were 0.8179 (95% CI 0.72014 to 0.91558) for ASSIGN, 0.8160 (95% CI 0.71661 to 0.91529) for ASSIGN-RA, and 0.8179 (95% CI 0.72014 to 0.91558) for ASSIGN*1.5. HL tests did not demonstrate poor model fit for none of the algorithms. Discriminative ability and calibration were not improved by adaptation of the algorithms according to EULAR recommendations. Up to 20% of CV events occurred in patients at "low risk". No difference in performance has been observed between ASSIGN, Progetto CUORE, and QRISK2. ASSIGN could represent a useful tool in predicting CV risk in patients with PsA. Adaptation for RA or according to EULAR recommendations did not show any further improvement in performance and calibration.

SAT0381 On the Hunt for Cardiovascular Risk Factors and Disease in Patients with Psoriatic Arthritis – Results from the Norwegian Hunt Study

BackgroundControversies exist regarding increased risk of cardiovascular (CV) disease in patients with psoriatic arthritis (PsA).ObjectivesTo compare the presence of CV risk factors and disease in patients with PsA and the...

The Identification of Prediabetes Condition with ARIC Algorithm Predicts Long-Term CV Events in Patients with Erectile Dysfunction

The Atherosclerosis Risk in Communities (ARIC) algorithm is one of the most efficient instruments for the prediction of incident type 2 diabetes. Recently, it has been shown to predict another relevant cardiovascular (CV) risk factor, such as chronic kidney disease. To verify whether, in patients with erectile dysfunction (ED), the use of ARIC diabetes risk score might improve the efficacy in predicting major CV events of other CV risk algorithms specifically developed for the assessment of CV risk. A consecutive series of 2,437 men (mean age 52.5 ± 12.9 years) attending our outpatient clinic for sexual dysfunction was retrospectively studied. A subset of this sample (N = 1,687) was enrolled in a longitudinal study (mean follow-up of 4.3 ± 2.6 years). The assessment of metabolic risk was evaluated with the ARIC algorithm. The assessment of CV risk was evaluated using the Progetto Cuore risk engine. In the cross-sectional study, ARIC score was inversely related with testosterone levels, sexual functioning, and penile blood flow. When longitudinal sample was analyzed, higher baseline ARIC score significantly predicted major adverse cardiovascular event (MACE) even when subjects with diabetes mellitus at baseline were excluded from the analysis (hazard ratio = 1.522 [1.086-2.135]; P = 0.015 for trend). In addition, among subjects classified as "low risk" (CV risk <20% at 10 years corresponding to <9% at 4.3 years) by Progetto Cuore, a receiving operating curve (ROC) analysis for ARIC (vs. MACE) allowed the identification of a threshold of 0.22, which had a positive predictive value for 4.3-year MACE of 9%. Applying the ARIC score (with a threshold of 0.22) to Progetto Cuore "low-risk" subjects, we could classify as "at high risk" 89.8% of subjects with incident MACE vs. 79.6% with Progetto Cuore only. In patients with ED, identifying prediabetes, even with algorithms, predicts long-term CV events.

248 Underestimation of Cardiovascular Risk in Patients With Elevated Cardiometabolic Risk in the Canadian Primary Care Setting

Primary care offers a unique opportunity for early identification and preventive management of patients at elevated cardiometabolic risk (CMR). We evaluated the risk assessment patterns employed by primary care physicians in patients at elevated CMR. Between April 2011 and March 2012, data from 88 individual physicians from British Columbia, Ontario and Québec, and from multiple physicians from 6 Family Health Teams (FHTs) in Ontario and Québec were collected on the current health profile and management of patients >40 years old with no clinical evidence of cardiovascular (CV) disease and diagnosed with at least one of the following - dyslipidemia, type 2 diabetes mellitus (T2DM) or hypertension as per the current Canadian Clinical Practice Guidelines (CPGs). Key patient characteristics from the 1864 patient charts are shown in the Table. Incidences of dyslipidemia, T2DM and hypertension were higher in individuals with a BMI ≥25 kg/m2 (84.7%) relative to those with a BMI <25 kg/m2. Waist circumference (WC) data, available from solo-physician practice assessments only, revealed that patients with WCs greater than their ethnic-specific cut-offs (41.8%) relative to patients with WCs below the thresholds also demonstrated higher occurrences of dyslipidemia, T2DM and hypertension. Approximately half (54.5%) of the patients managed by physicians in solo-physician practices had the metabolic syndrome based on the Harmonized Definition for the metabolic syndrome. CV risk was estimated in clinic in 52.2% of the 781 patients without T2DM with 98.8% of the physicians indicating that they used the Framingham Risk Score (FRS) and 0.5% the Reynolds Risk Score. Our own FRS analysis based on the complete data sets from 690 patients without T2DM implied that 57.0%, 30.7% and 12.3% of these individuals were actually at high, moderate and low CV risk respectively before invoking the 1.5- to 2-fold multiplier to determine absolute CMR. Notably, this suggests that 44.8% of the patients without T2DM who had their CV risk estimated in clinic were misclassified by their physicians into a lower risk category.Tabled 1 Current Canadian CPGs emphasize the importance of early identification of CMR in order to facilitate preventative measures against CMR factors. In this practice assessment program, CV risk using traditional CV risk algorithms was often underestimated. While the underlying reasons are unknown, this misclassification may have led to an inappropriate selection of therapeutic strategies contributing to a care gap.