Search

Objective: To 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., Methods: Information 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., Results: After 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., Conclusions: In 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., Competing Interests: Declaration of competing interest The authors declare they do not have financial interests, which could create a potential conflict of interest or the appearance of a conflict of interest with regard to the current work., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: To develop an improved score for prediction of severe infection in patients with systemic lupus erythematosus (SLE), namely, the SLE Severe Infection Score-Revised (SLESIS-R) and to validate it in a large multicentre lupus cohort., Methods: We used data from the prospective phase of RELESSER (RELESSER-PROS), the SLE register of the Spanish Society of Rheumatology. A multivariable logistic model was constructed taking into account the variables already forming the SLESIS score, plus all other potential predictors identified in a literature review. Performance was analysed using the C-statistic and the area under the receiver operating characteristic curve (AUROC). Internal validation was carried out using a 100-sample bootstrapping procedure. ORs were transformed into score items, and the AUROC was used to determine performance., Results: A total of 1459 patients who had completed 1 year of follow-up were included in the development cohort (mean age, 49±13 years; 90% women). Twenty-five (1.7%) had experienced ≥1 severe infection. According to the adjusted multivariate model, severe infection could be predicted from four variables: age (years) ≥60, previous SLE-related hospitalisation, previous serious infection and glucocorticoid dose. A score was built from the best model, taking values from 0 to 17. The AUROC was 0.861 (0.777-0.946). The cut-off chosen was ≥6, which exhibited an accuracy of 85.9% and a positive likelihood ratio of 5.48., Conclusions: SLESIS-R is an accurate and feasible instrument for predicting infections in patients with SLE. SLESIS-R could help to make informed decisions on the use of immunosuppressants and the implementation of preventive measures., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: To evaluate the prevalence of self-perceived depression and anxiety in patients with systemic lupus erythematosus (SLE) and to explore associated factors., Methods: Cross-sectional study of unselected patients with SLE (ACR-97 criteria) and controls with chronic inflammatory rheumatic diseases. Both completed the Hospital Anxiety and Depression Scale (HADS). Demographic and clinical characteristics, comorbidity, and treatments were collected, and a multivariate analysis was performed to explore factors associated with depression and anxiety in SLE., Results: The study population comprised 172 patients and 215 controls. Women accounted for 93% of the patients with SLE. Fibromyalgia was recorded in 12.8% and a history of depression in 17%. According to HADS, 37.2% fulfilled the diagnostic criteria for depression and 58.7% those for anxiety; prevalence was similar in the controls (32.6% and 55.1%, respectively). Up to a third of patients with self-perceived depression were not receiving antidepressants. There was no concordance between a previous history of depression and current depression. In the multivariate model, current depression was associated with single marital status (OR 2.69; 95% CI: 1.17-6.42; p = .022), fibromyalgia (7.69; 2.35-30.72; p = .001), smoking (3.12; 1.24-8.07; p = .016), severity of SLE (0.76; 0.6-0.94; p = .016), and organ damage (1.27; 1.01-1.61; p = .042). Current anxiety was only associated with fibromyalgia (3.97; 1.21-17.98; p = .036)., Conclusions: Depression and anxiety are most likely underdiagnosed in SLE. Prevalence appears to be similar to that of other chronic inflammatory rheumatic diseases. Anxiety is associated with fibromyalgia, while depression is also associated with single marital status, smoking, organ damage, and severity of SLE.