Biological use influences the impact of inflammation on risk of major adverse cardiovascular events in rheumatoid arthritis.

OBJECTIVES: Chronic inflammation promotes cardiovascular risk in rheumatoid arthritis (RA). Biological disease-modifying antirheumatic drugs (bDMARDs) improve disease activity and cardiovascular disease outcomes. We explored whether bDMARDs influence the impact of disease activity and inflammatory markers on long-term cardiovascular risk in RA. METHODS: We studied 4370 participants without cardiovascular disease in a 10-country observational cohort of patients with RA. Endpoints were (1) major adverse cardiovascular events (MACE) encompassing myocardial infarction, stroke and cardiovascular death; and (2) any ischaemic cardiovascular events (iCVE) including MACE plus revascularisation, angina, transient ischaemic attack and peripheral arterial disease. RESULTS: Over 26 534 patient-years, 239 MACE and 362 iCVE occurred. The interaction between 28-joint Disease Activity Score with C-reactive protein (DAS28-CRP) and bDMARD use was significant for MACE (p=0.017), suggesting the effect of DAS28-CRP on MACE risk differed among bDMARD users (n=515) and non-users (n=3855). DAS28-CRP (per unit increase) is associated with MACE risk in bDMARD non-users (HR 1.21 (95% CI 1.07 to 1.37)) but not users (HR 0.69 (95% CI 0.40 to 1.20)). The interaction between CRP (per log unit increase) and bDMARD use was also significant for MACE (p=0.011). CRP associated with MACE risk in bDMARD non-users (HR 1.16 (95% CI 1.04 to 1.30)), but not users (HR 0.65 (95% CI 0.36 to 1.17)). No interaction was observed between bDMARD use and DAS28-CRP (p=0.167) or CRP (p=0.237) for iCVE risk. CONCLUSIONS: RA activity and inflammatory markers associated with risk of MACE in bDMARD non-users but not users suggesting the possibility of biological-specific benefits locally on arterial wall independently of effects on systemic inflammation.

Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping review.

Background: The field of precision medicine endeavors to transform the healthcare industry by advancing individualised strategies for diagnosis, treatment modalities, and predictive assessments. This is achieved by utilizing extensive multidimensional biological datasets encompassing diverse components, such as an individual's genetic makeup, functional attributes, and environmental influences. Artificial intelligence (AI) systems, namely machine learning (ML) and deep learning (DL), have exhibited remarkable efficacy in predicting the potential occurrence of specific cancers and cardiovascular diseases (CVD). Methods: We conducted a comprehensive scoping review guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. Our search strategy involved combining key terms related to CVD and AI using the Boolean operator AND. In August 2023, we conducted an extensive search across reputable scholarly databases including Google Scholar, PubMed, IEEE Xplore, ScienceDirect, Web of Science, and arXiv to gather relevant academic literature on personalised medicine for CVD. Subsequently, in January 2024, we extended our search to include internet search engines such as Google and various CVD websites. These searches were further updated in March 2024. Additionally, we reviewed the reference lists of the final selected research articles to identify any additional relevant literature. Findings: A total of 2307 records were identified during the process of conducting the study, consisting of 564 entries from external sites like arXiv and 1743 records found through database searching. After 430 duplicate articles were eliminated, 1877 items that remained were screened for relevancy. In this stage, 1241 articles remained for additional review after 158 irrelevant articles and 478 articles with insufficient data were removed. 355 articles were eliminated for being inaccessible, 726 for being written in a language other than English, and 281 for not having undergone peer review. Consequently, 121 studies were deemed suitable for inclusion in the qualitative synthesis. At the intersection of CVD, AI, and precision medicine, we found important scientific findings in our scoping review. Intricate pattern extraction from large, complicated genetic datasets is a skill that AI algorithms excel at, allowing for accurate disease diagnosis and CVD risk prediction. Furthermore, these investigations have uncovered unique genetic biomarkers linked to CVD, providing insight into the workings of the disease and possible treatment avenues. The construction of more precise predictive models and personalised treatment plans based on the genetic profiles of individual patients has been made possible by the revolutionary advancement of CVD risk assessment through the integration of AI and genomics. Interpretation: The systematic methodology employed ensured the thorough examination of available literature and the inclusion of relevant studies, contributing to the robustness and reliability of the study's findings. Our analysis stresses a crucial point in terms of the adaptability and versatility of AI solutions. AI algorithms designed in non-CVD domains such as in oncology, often include ideas and tactics that might be modified to address cardiovascular problems. Funding: No funding received.

Risk of Major Adverse Cardiovascular Events and Venous Thromboembolism with JAK Inhibitors versus TNF Inhibitors in Rheumatoid Arthritis Patients: A Systematic Review and Meta-Analysis.

Objective: The aim of this study was to compare the risk of major cardiovascular events (MACE) and venous thromboembolic events (VTE) between tumour necrosis factor (TNF) and Janus kinase (JAK) inhibitors in patients with rheumatoid arthritis (RA). Methods: We researched PubMed, Scopus, Cochrane Library, and clinicaltrials.gov until December of 2023 for randomised controlled trials (RCTs) and observational studies. The outcomes studied were MACE (stroke, heart attack, myocardial infarction, sudden cardiac death) and VTE (deep vein thrombosis, pulmonary embolism). We pooled data using random effects model. Risk for the reported outcomes was expressed as odds ratio (OR) with a 95% confidential interval (CI). We performed a subgroup analysis based on study design. Results: We identified 23 studies, 20 of which compared the odds for MACE and 14 the odds for VTE between JAK and TNF inhibitors in RA patients. Ten studies were RCTs and the rest were observational. Regarding MACE risk we pooled data from a total of 215,278 patients (52,243 were treated with JAK inhibitors, while the rest 163,035 were under TNF inhibitors). Compared with TNF inhibitors, the OR for JAK inhibitors in regards with MACE risk was 0.87 (0.64-1.17, p<0.01). Regarding VTE, a total of 176,951 patients were analysed (41,375 JAK inhibitors users and 135,576 TNF inhibitors users). The OR for VTE for JAK inhibitors compared with TNF inhibitors was 1.28 (0.89-1.84, p<0.01). Conclusion: According to our results, there is no statistically significant difference for MACE or VTE in RA patients who receive either JAK or TNF inhibitors.

Non-Invasive Assessment of Micro- and Macrovascular Function after Initiation of JAK Inhibitors in Patients with Rheumatoid Arthritis.

BACKGROUND: Janus kinase (JAK) inhibitors constitute a novel class of oral biologic disease-modifying antirheumatic drugs for patients with rheumatoid arthritis (RA). However, their use has been associated with increased risk of major cardiovascular events. We investigated whether treatment with JAK inhibitors exerts significant alterations in the micro- and microvasculature in RA patients. METHODS: Thirteen patients with RA initiating treatment with JAK inhibitors were prospectively studied. Eventually, data from 11 patients who completed the study were analyzed. Procedures were performed at baseline and 3 months after treatment. Nailfold videocapillaroscopy was applied to detect alterations of the dermal capillary network. Participants underwent 24 h ambulatory blood pressure monitoring (Mobil-O-Graph device) for the assessment of blood pressure (both brachial and aortic) and markers of large artery stiffening [pulse wave velocity (PWV), augmentation index] throughout the whole 24 h and the respective day- and nighttime periods. Carotid intima-media thickness was assessed with ultrasound. RESULTS: Three-month treatment with JAK inhibitors was not associated with any differences in brachial and aortic blood pressure, arterial stiffness, and carotid atherosclerosis, with the only exception of nighttime PWV, which was significantly elevated at follow-up. However, three-month treatment with JAK inhibitors induced significant microvascular alterations and increased the total number of capillaroscopic abnormalities. CONCLUSIONS: Three-month treatment with JAK inhibitors may exert significant effects on microcirculation as assessed with nailfold videocapillaroscopy, whereas macrovascular structure and function appears largely unaffected. Further research toward this direction may add substantial information to the available literature regarding cardiovascular aspects of JAK inhibitors in RA.

Cardiovascular Magnetic Resonance for the Evaluation of Arrhythmogenic Substrates in Patients with Systemic Autoimmunity: An Update.

Patients with systemic autoimmunity due to autoimmune rheumatic diseases (ARDs) or sarcoidosis frequently present with systemic manifestations including cardiac involvement. Cardiac rhythm disturbances and specifically ventricular arrhythmias (VAs) may affect the prognosis of these patients. Cardiovascular magnetic resonance imaging (CMR) is a non-invasive imaging modality that can provide valuable diagnostic and prognostic information in patients with ARDs or systemic autoimmunity in general. In this narrative review, we briefly present the underlying pathophysiologic mechanisms contributing to arrhythmogenicity in patients with systemic autoimmunity. Furthermore, we discuss recent advances underlying the role and value of CMR for use in the detection and risk stratification of arrhythmogenic substrates in patients with systemic autoimmunity and VAs.