Asymmetric dimethylarginine correlates with worsening peripheral microangiopathy in systemic sclerosis.

BACKGROUND: Systemic sclerosis (SSc) is a connective tissue disease characterized primarily by micro-angiopathy and endothelial dysfunction which stimulate a fibrotic process. Asymmetric dimethylarginine (ADMA) is an endogenous nitric oxide (NO) inhibitor and represents a novel biomarker for vascular dysfunction. Nailfold video capillaroscopy (NVC) represents a non-invasive and reliable technique for the evaluation of microvasculopathy in SSc. OBJECTIVES: The aim of this study was to examine the possible association between ADMA and microvascular involvement in patients with SSc. METHODS: This was a cross-sectional study including consecutive SSc patients attending the Scleroderma Outpatient Clinic. ADMA was measured in serum samples using a commercial enzyme immunoassay. Participants underwent NVC with qualitative and semi-quantitative assessment and all NVC parameters were measured in the distal row of each finger. The findings were classified in one of the three qualitative NVC patterns: early, active, and late. RESULTS: Eighty-one (92,6 % women) SSc individuals with mean age 55.44 ± 13.4 years were included in this analysis. Within-groups comparisons revealed a trend between higher ADMA levels and progressive micro-vasculopathy (1,29 [2,1] vs 1,57 [1,95] vs 2,41 [3,87]; for early, active and late patterns respectively, p = 0.039). Furthermore, ADMA concentration was significantly associated with the number of capillaries/mm (r = -0.235; p = 0.035). CONCLUSIONS: Serum ADMA levels were significantly associated with advancing stages of microcirculatory abnormalities suggesting that ADMA may have a role in promoting microvascular endothelial dysfunction in SSc individuals.

Peripheral nailfold capillary microscopic abnormalities in rheumatoid arthritis are associated with arterial stiffness: Results from a cross-sectional study.

Vascular injury eventually resulting in the establishment of cardiovascular disease is a serious complication in rheumatoid arthritis (RA). Nailfold videocapillaroscopy (NVC) is a non-invasive imaging modality that enables the quantitative and qualitative assessment of the peripheral microvasculature. Nevertheless, capillaroscopic patterns remain inadequately defined in RA, especially regarding their clinical significance as potential markers of systemic vascular impairment. Consecutive RA patients underwent NVC using a standardized protocol, to assess the following parameters: capillary density, avascular areas, capillary dimensions, microhemorrhages, subpapillary venous plexus, and presence of ramified, bushy, crossed and tortuous capillaries. Carotid-femoral pulse wave velocity (PWV) and pulse pressure were measured as well-acknowledged markers of large artery stiffening. The vast majority of our cohort (n = 44) presented a combination of non-specific and abnormal capillaroscopic parameters. Capillary ramification was associated with both PWV and pulse pressure, even after adjustment for cardiovascular risk factors and systemic inflammation. Our study highlights the high prevalence of a wide range of capillaroscopic deviations from the normal patterns in RA. Furthermore, it provides for the first time evidence of an association between structural disorders of the microcirculation and markers of macrovascular dysfunction, suggesting that NVC might have a role as an index of generalised vascular impairment in RA.

Number of days required to measure sedentary time and physical activity using accelerometery in rheumatoid arthritis: a reliability study.

This study aimed to determine the minimum number of days required to reliably estimate free-living sedentary time, light-intensity physical activity (LPA) and moderate-intensity physical activity (MPA) using accelerometer data in people with Rheumatoid Arthritis (RA), according to Disease Activity Score-28-C-reactive protein (DAS-28-CRP). Secondary analysis of two existing RA cohorts with controlled (cohort 1) and active (cohort 2) disease was undertaken. People with RA were classified as being in remission (DAS-28-CRP < 2.4, n = 9), or with low (DAS-28-CRP ≥ 2.4-≤ 3.2, n = 15), moderate (DAS-28-CRP > 3.2-≤ 5.1, n = 41) or high (DAS-28-CRP > 5.1, n = 16) disease activity. Participants wore an ActiGraph accelerometer on their right hip for 7 days during waking hours. Validated RA-specific cut-points were applied to accelerometer data to estimate free-living sedentary time, LPA and MPA (%/day). Single-day intraclass correlation coefficients (ICC) were calculated and used in the Spearman Brown prophecy formula to determine the number of monitoring days required to achieve measurement reliability (ICC ≥ 0.80) for each group. The remission group required ≥ 4 monitoring days to achieve an ICC ≥ 0.80 for sedentary time and LPA, with low, moderate and high disease activity groups requiring ≥ 3 monitoring days to reliably estimate these behaviours. The monitoring days required for MPA were more variable across disease activity groups (remission = ≥ 3 days; low = ≥ 2 days; moderate = ≥ 3 days; high = ≥ 5 days). We conclude at least 4 monitoring days will reliably estimate sedentary time and LPA in RA, across the whole spectrum of disease activity. However, to reliably estimate behaviours across the movement continuum (sedentary time, LPA, MPA), at least 5 monitoring days are required.

Artificial intelligence-based preventive, personalized and precision medicine for cardiovascular disease/stroke risk assessment in rheumatoid arthritis patients: a narrative review.

The challenges associated with diagnosing and treating cardiovascular disease (CVD)/Stroke in Rheumatoid arthritis (RA) arise from the delayed onset of symptoms. Existing clinical risk scores are inadequate in predicting cardiac events, and conventional risk factors alone do not accurately classify many individuals at risk. Several CVD biomarkers consider the multiple pathways involved in the development of atherosclerosis, which is the primary cause of CVD/Stroke in RA. To enhance the accuracy of CVD/Stroke risk assessment in the RA framework, a proposed approach involves combining genomic-based biomarkers (GBBM) derived from plasma and/or serum samples with innovative non-invasive radiomic-based biomarkers (RBBM), such as measurements of synovial fluid, plaque area, and plaque burden. This review presents two hypotheses: (i) RBBM and GBBM biomarkers exhibit a significant correlation and can precisely detect the severity of CVD/Stroke in RA patients. (ii) Artificial Intelligence (AI)-based preventive, precision, and personalized (aiP3) CVD/Stroke risk AtheroEdge™ model (AtheroPoint™, CA, USA) that utilizes deep learning (DL) to accurately classify the risk of CVD/stroke in RA framework. The authors conducted a comprehensive search using the PRISMA technique, identifying 153 studies that assessed the features/biomarkers of RBBM and GBBM for CVD/Stroke. The study demonstrates how DL models can be integrated into the AtheroEdge™-aiP3 framework to determine the risk of CVD/Stroke in RA patients. The findings of this review suggest that the combination of RBBM with GBBM introduces a new dimension to the assessment of CVD/Stroke risk in the RA framework. Synovial fluid levels that are higher than normal lead to an increase in the plaque burden. Additionally, the review provides recommendations for novel, unbiased, and pruned DL algorithms that can predict CVD/Stroke risk within a RA framework that is preventive, precise, and personalized.

Coronary microvascular disease: The "Meeting Point" of Cardiology, Rheumatology and Endocrinology.

BACKGROUND: Exertional chest pain/dyspnea or chest pain at rest are the main symptoms of coronary artery disease (CAD), which are traditionally attributed to insufficiency of the epicardial coronary arteries. However, 2/3 of women and 1/3 of men with angina and 10% of patients with acute myocardial infarction have no evidence of epicardial coronary artery stenosis in X-ray coronary angiography. In these cases, coronary microvascular disease (CMD) is the main causative factor. AIMS: To present the pathophysiology of CMD in Cardiology, Rheumatology and Endocrinology. MATERIALS-METHODS: The pathophysiology of CMD in Cardiology, Rheumatology and Endocrinology was evaluated. It includes impaired microvascular vasodilatation, which leads to inability of the organism to deal with myocardial oxygen needs and, hence, development of ischemic pain. CMD, observed in inflammatory autoimmune rheumatic and endocrine/metabolic disorders, brings together Cardiology, Rheumatology and Endocrinology. Causative factors include persistent systemic inflammation and endocrine/metabolic abnormalities influencing directly the coronary microvasculature. In the past, the evaluation of microcirculation was feasible only with the use of invasive techniques, such as coronary flow reserve assessment. Currently, the application of advanced imaging modalities, such as cardiovascular magnetic resonance (CMR), can evaluate CMD non-invasively and without ionizing radiation. RESULTS: CMD may present with a variety of symptoms with 1/3 to 2/3 of them expressed as typical chest pain in effort, more commonly found in women during menopause than in men. Atypical presentation includes chest pain at rest or exertional dyspnea,but post exercise symptoms are not uncommon. The treatment with nitrates is less effective in CMD, because their vasodilator action in coronary micro-circulation is less pronounced than in the epicardial coronary arteries. DISCUSSION: Although both classic and new medications have been used in the treatment of CMD, there are still many questions regarding both the pathophysiology and the treatment of this disorder. The potential effects of anti-rheumatic and endocrine medications on the evolution of CMD need further evaluation. CONCLUSION: CMD is a multifactorial disease leading to myocardial ischemia/fibrosis alone or in combination with epicardial coronary artery disease. Endothelial dysfunction/vasospasm, systemic inflammation, and/or neuroendocrine activation may act as causative factors and bring Cardiology, Rheumatology and Endocrinology together. Currently, the application of advanced imaging modalities, and specifically CMR, allows reliable assessment of the extent and severity of CMD. These measurements should not be limited to "pure cardiac patients", as it is known that CMD affects the majority of patients with autoimmune rheumatic and endocrine/metabolic disorders.

The second decade of anti-TNF-a therapy in clinical practice: new lessons and future directions in the COVID-19 era.

Since the late 1990s, tumor necrosis factor alpha (TNF-α) inhibitors (anti-TNFs) have revolutionized the therapy of immune-mediated inflammatory diseases (IMIDs) affecting the gut, joints, skin and eyes. Although the therapeutic armamentarium in IMIDs is being constantly expanded, anti-TNFs remain the cornerstone of their treatment. During the second decade of their application in clinical practice, a large body of additional knowledge has accumulated regarding various aspects of anti-TNF-α therapy, whereas new indications have been added. Recent experimental studies have shown that anti-TNFs exert their beneficial effects not only by restoring aberrant TNF-mediated immune mechanisms, but also by de-activating pathogenic fibroblast-like mesenchymal cells. Real-world data on millions of patients further confirmed the remarkable efficacy of anti-TNFs. It is now clear that anti-TNFs alter the physical course of inflammatory arthritis and inflammatory bowel disease, leading to inhibition of local and systemic bone loss and to a decline in the number of surgeries for disease-related complications, while anti-TNFs improve morbidity and mortality, acting beneficially also on cardiovascular comorbidities. On the other hand, no new safety signals emerged, whereas anti-TNF-α safety in pregnancy and amid the COVID-19 pandemic was confirmed. The use of biosimilars was associated with cost reductions making anti-TNFs more widely available. Moreover, the current implementation of the "treat-to-target" approach and treatment de-escalation strategies of IMIDs were based on anti-TNFs. An intensive search to discover biomarkers to optimize response to anti-TNF-α treatment is currently ongoing. Finally, selective targeting of TNF-α receptors, new forms of anti-TNFs and combinations with other agents, are being tested in clinical trials and will probably expand the spectrum of TNF-α inhibition as a therapeutic strategy for IMIDs.

Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek cohort of 542 individuals with rheumatoid arthritis, or diabetes mellitus, and/or arterial hypertension, using conventional or office-based, laboratory-based blood biomarkers and carotid/femoral ultrasound image-based phenotypes. Two kinds of data (CVD risk factors and presence of CVD-defined as stroke, or myocardial infarction, or coronary artery syndrome, or peripheral artery disease, or coronary heart disease) as ground truth, were collected at two-time points: (i) at visit 1 and (ii) at visit 2 after 3 years. The CVD risk factors were divided into three clusters (conventional or office-based, laboratory-based blood biomarkers, carotid ultrasound image-based phenotypes) to study their effect on the ML classifiers. Three kinds of ML classifiers (Random Forest, Support Vector Machine, and Linear Discriminant Analysis) were applied in a two-fold cross-validation framework using the data augmented by synthetic minority over-sampling technique (SMOTE) strategy. The performance of the ML classifiers was recorded. In this cohort with overall 46 CVD risk factors (covariates) implemented in an online cardiovascular framework, that requires calculation time less than 1 s per patient, a mean accuracy and area-under-the-curve (AUC) of 98.40% and 0.98 (p < 0.0001) for CVD presence detection at visit 1, and 98.39% and 0.98 (p < 0.0001) at visit 2, respectively. The performance of the cardiovascular framework was significantly better than the classical CVD risk score. The ML paradigm proved to be powerful for CVD prediction in individuals at medium to high cardiovascular risk.

Global Health Strategies in the Face of the COVID-19 Pandemic and Other Unprecedented Threats.

Global health is evolving as a discipline aiming at exploring needs and offering equitable health services for all people. Over the past four decades, several global initiatives have been introduced to improve the accessibility of primary health care (PHC) and solve most health issues at this level. Historically, the 1978 Alma-Ata and 2018 Astana Declarations were perhaps the most important documents for a comprehensive approach to PHC services across the world. With the introduction of the United Nations Sustainable Development Goals in 2015, developments in all spheres of human life and multi-sectoral cooperation became the essential action targets that could contribute to improved health, well-being, and safety of all people. Other global initiatives such as the Riyadh Declaration on Digital Health and São Paulo Declaration on Planetary Health called to urgent action to employ advanced digital technologies, improve health data processing, and invest more in research management. All these initiatives are put to the test in the face of the coronavirus disease 2019 (COVID-19) pandemic and other unprecedented threats to humanity.

Knowledge and Perceptions of Reactive Arthritis Diagnosis and Management Among Healthcare Workers During the COVID-19 Pandemic: Online Survey.

BACKGROUND: Reactive arthritis (ReA) is an often neglected disease that received some attention during the coronavirus disease 2019 (COVID-19) pandemic. There is some evidence that infection with severe acute respiratory syndrome coronavirus 2 can lead to "reactive" arthritis. However, this does not follow the classical definition of ReA that limits the organisms leading to this condition. Also, there is no recommendation by any international society on the management of ReA during the current pandemic. Thus, a survey was conducted to gather information about how modern clinicians across the world approach ReA. METHODS: An e-survey was carried out based on convenient sampling via social media platforms. Twenty questions were validated on the pathogenesis, clinical presentation, and management of ReA. These also included information on post-COVID-19 arthritis. Duplicate entries were prevented and standard guidelines were followed for reporting internet-based surveys. RESULTS: There were 193 respondents from 24 countries. Around one-fifth knew the classical definition of ReA. Nearly half considered the triad of conjunctivitis, urethritis and asymmetric oligoarthritis a "must" for diagnosis of ReA. Other common manifestations reported include enthesitis, dermatitis, dactylitis, uveitis, and oral or genital ulcers. Three-fourths opined that no test was specific for ReA. Drugs for ReA were non-steroidal anti-inflammatory drugs, intra-articular injections, and conventional disease-modifying agents with less than 10% supporting biological use. CONCLUSION: The survey brought out the gap in existing concepts of ReA. The current definition needs to be updated. There is an unmet need for consensus recommendations for the management of ReA, including the use of biologicals.

Pain and fatigue are longitudinally and bi-directionally associated with more sedentary time and less standing time in rheumatoid arthritis.

OBJECTIVES: The aims of this study were to examine the longitudinal and bi-directional associations of pain and fatigue with sedentary, standing and stepping time in RA. METHODS: People living with RA undertook identical assessments at baseline (T1, n = 104) and 6-month follow-up (T2, n = 54). Participants completed physical measures (e.g. height, weight, BMI) and routine clinical assessments to characterize RA disease activity (DAS-28). Participants also completed questionnaires to assess physical function (HAQ), pain (McGill Pain Questionnaire) and fatigue (Multidimensional Assessment of Fatigue Scale). Participants' free-living sedentary, standing and stepping time (min/day) were assessed over 7 days using the activPAL3µ™. For the statistical analysis, hierarchical regression analysis was employed to inform the construction of path models, which were subsequently used to examine bi-directional associations of pain and fatigue with sedentary, standing and stepping time. Specifically, where significant associations were observed in longitudinal regression analysis, the bi-directionality of these associations was further investigated via path analysis. For regression analysis, bootstrapping was applied to regression models to account for non-normally distributed data, with significance confirmed using 95% CIs. Where variables were normally distributed, parametric, non-bootstrapped statistics were also examined (significance confirmed via ß coefficients, with P < 0.05) to ensure all plausible bi-directional associations were examined in path analysis. RESULTS: Longitudinal bootstrapped regression analysis indicated that from T1 to T2, change in pain, but not fatigue, was positively associated with change in sedentary time. In addition, change in pain and fatigue were negatively related to change in standing time. Longitudinal non-bootstrapped regression analysis demonstrated a significant positive association between change in fatigue with change in sedentary time. Path analysis supported the hypothesized bi-directionality of associations between change in pain and fatigue with change in sedentary time (pain, ß = 0.38; fatigue, ß = 0.44) and standing time (pain, ß = -0.39; fatigue, ß = -0.50). CONCLUSION: Findings suggest pain and fatigue are longitudinally and bi-directionally associated with sedentary and standing time in RA.

Incidence, risk factors and validation of the RABBIT score for serious infections in a cohort of 1557 patients with rheumatoid arthritis.

OBJECTIVES: Predicting serious infections (SI) in patients with rheumatoid arthritis (RA) is crucial for the implementation of appropriate preventive measures. Here we aimed to identify risk factors for SI and to validate the RA Observation of Biologic Therapy (RABBIT) risk score in real-life settings. METHODS: A multi-centre, prospective, RA cohort study in Greece. Demographics, disease characteristics, treatments and comorbidities were documented at first evaluation and one year later. The incidence of SI was recorded and compared with the expected SI rate using the RABBIT risk score. RESULTS: A total of 1557 RA patients were included. During follow-up, 38 SI were recorded [incidence rate ratio (IRR): 2.3/100 patient-years]. Patients who developed SI had longer disease duration, higher HAQ at first evaluation and were more likely to have a history of previous SI, chronic lung disease, cardiovascular disease and chronic kidney disease. By multivariate analysis, longer disease duration (IRR: 1.05; 95% CI: 1.005, 1.1), history of previous SI (IRR: 4.15; 95% CI: 1.7, 10.1), diabetes (IRR: 2.55; 95% CI: 1.06, 6.14), chronic lung disease (IRR: 3.14; 95% CI: 1.35, 7.27) and daily prednisolone dose ≥10 mg (IRR: 4.77; 95% CI: 1.47, 15.5) were independent risk factors for SI. Using the RABBIT risk score in 1359 patients, the expected SI incidence rate was 1.71/100 patient-years, not different from the observed (1.91/100 patient-years; P = 0.97). CONCLUSION: In this large real-life, prospective study of RA patients, the incidence of SI was 2.3/100 patient-years. Longer disease duration, history of previous SI, comorbidities and high glucocorticoid dose were independently associated with SI. The RABBIT score accurately predicted SI in our cohort.

Different types of physical activity are positively associated with indicators of mental health and psychological wellbeing in rheumatoid arthritis during COVID-19.

Nationwide lockdowns during SARS-CoV-2 (COVID-19) can compromise mental health and psychological wellbeing and limit opportunities for physical activity (PA), particularly in clinical populations, such as people with rheumatoid arthritis (RA), who are considered at risk for COVID-19 complications. This study aimed to investigate associations between PA and sedentary time (ST) with indicators of mental health and wellbeing in RA during COVID-19 lockdown, and examine the moderation effects of self-isolating. 345 RA patients completed an online questionnaire measuring PA (NIH-AARP Diet and Health Study Questionnaire), ST (International Physical Activity Questionnaire-Short Form), pain (McGill Pain Questionnaire and Visual Analogue Scale), fatigue (Multidimensional Fatigue Inventory), depressive and anxious symptoms (Hospital Anxiety and Depression Scale), and vitality (Subjective Vitality Scale) during the United Kingdom COVID-19 lockdown. Associations between PA and ST with mental health and wellbeing were examined using hierarchical multiple linear regressions. Light PA (LPA) was significantly negatively associated with mental fatigue (ß = - .11), depressive symptoms (ß = - .14), and positively with vitality (ß = .13). Walking was negatively related to physical fatigue (ß = - .11) and depressive symptoms (ß = - .12) and positively with vitality (ß = .15). Exercise was negatively associated with physical (ß = - .19) and general (ß = - .12) fatigue and depressive symptoms (ß = - .09). ST was positively associated with physical fatigue (ß = .19). Moderation analyses showed that LPA was related to lower mental fatigue and better vitality in people not self-isolating, and walking with lower physical fatigue in people self-isolating. These findings show the importance of encouraging PA for people with RA during a lockdown period for mental health and wellbeing.

Article-Level Metrics.

In the era of digitization and Open Access, article-level metrics are increasingly employed to distinguish influential research works and adjust research management strategies. Tagging individual articles with digital object identifiers allows exposing them to numerous channels of scholarly communication and quantifying related activities. The aim of this article was to overview currently available article-level metrics and highlight their advantages and limitations. Article views and downloads, citations, and social media metrics are increasingly employed by publishers to move away from the dominance and inappropriate use of journal metrics. Quantitative article metrics are complementary to one another and often require qualitative expert evaluations. Expert evaluations may help to avoid manipulations with indiscriminate social media activities that artificially boost altmetrics. Values of article metrics should be interpreted in view of confounders such as patterns of citation and social media activities across countries and academic disciplines.

Formulating Hypotheses for Different Study Designs.

Generating a testable working hypothesis is the first step towards conducting original research. Such research may prove or disprove the proposed hypothesis. Case reports, case series, online surveys and other observational studies, clinical trials, and narrative reviews help to generate hypotheses. Observational and interventional studies help to test hypotheses. A good hypothesis is usually based on previous evidence-based reports. Hypotheses without evidence-based justification and a priori ideas are not received favourably by the scientific community. Original research to test a hypothesis should be carefully planned to ensure appropriate methodology and adequate statistical power. While hypotheses can challenge conventional thinking and may be controversial, they should not be destructive. A hypothesis should be tested by ethically sound experiments with meaningful ethical and clinical implications. The coronavirus disease 2019 pandemic has brought into sharp focus numerous hypotheses, some of which were proven (e.g. effectiveness of corticosteroids in those with hypoxia) while others were disproven (e.g. ineffectiveness of hydroxychloroquine and ivermectin).

A Review on Joint Carotid Intima-Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework.

Cardiovascular diseases (CVDs) are the top ten leading causes of death worldwide. Atherosclerosis disease in the arteries is the main cause of the CVD, leading to myocardial infarction and stroke. The two primary image-based phenotypes used for monitoring the atherosclerosis burden is carotid intima-media thickness (cIMT) and plaque area (PA). Earlier segmentation and measurement methods were based on ad hoc conventional and semi-automated digital imaging solutions, which are unreliable, tedious, slow, and not robust. This study reviews the modern and automated methods such as artificial intelligence (AI)-based. Machine learning (ML) and deep learning (DL) can provide automated techniques in the detection and measurement of cIMT and PA from carotid vascular images. Both ML and DL techniques are examples of supervised learning, i.e., learn from "ground truth" images and transformation of test images that are not part of the training. This review summarizes (1) the evolution and impact of the fast-changing AI technology on cIMT/PA measurement, (2) the mathematical representations of ML/DL methods, and (3) segmentation approaches for cIMT/PA regions in carotid scans based for (a) region-of-interest detection and (b) lumen-intima and media-adventitia interface detection using ML/DL frameworks. AI-based methods for cIMT/PA segmentation have emerged for CVD/stroke risk monitoring and may expand to the recommended parameters for atherosclerosis assessment by carotid ultrasound.

Smoking cessation is associated with lower disease activity and predicts cardiovascular risk reduction in rheumatoid arthritis patients.

OBJECTIVES: Smoking is a major risk factor for the development of both cardiovascular disease (CVD) and RA and may cause attenuated responses to anti-rheumatic treatments. Our aim was to compare disease activity, CVD risk factors and CVD event rates across smoking status in RA patients. METHODS: Disease characteristics, CVD risk factors and relevant medications were recorded in RA patients without prior CVD from 10 countries (Norway, UK, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico). Information on CVD events was collected. Adjusted analysis of variance, logistic regression and Cox models were applied to compare RA disease activity (DAS28), CVD risk factors and event rates across categories of smoking status. RESULTS: Of the 3311 RA patients (1012 former, 887 current and 1412 never smokers), 235 experienced CVD events during a median follow-up of 3.5 years (interquartile range 2.5-6.1). At enrolment, current smokers were more likely to have moderate or high disease activity compared with former and never smokers (P < 0.001 for both). There was a gradient of worsening CVD risk factor profiles (lipoproteins and blood pressure) from never to former to current smokers. Furthermore, former and never smokers had significantly lower CVD event rates compared with current smokers [hazard ratio 0.70 (95% CI 0.51, 0.95), P = 0.02 and 0.48 (0.34, 0.69), P < 0.001, respectively]. The CVD event rates for former and never smokers were comparable. CONCLUSION: Smoking cessation in patients with RA was associated with lower disease activity and improved lipid profiles and was a predictor of reduced rates of CVD events.

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence.

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors.

Replication of Newly Identified Genetic Associations Between Abdominal Aortic Aneurysm and SMYD2, LINC00540, PCIF1/MMP9/ZNF335, and ERG.

OBJECTIVE: A recently published genome wide association study of abdominal aortic aneurysms (AAA), based on pooled case control data of European ancestry, identified four new loci for AAA: SMYD2 (top single nucleotide polymorphism [SNP] rs1795061), LINC00540 (rs9316871), PCIF1/MMP9/ZNF335 (rs3827066), and ERG (rs2836411). Of the four, rs1795061 and rs2836411 showed significant heterogeneity across studies and the p value for rs9316871 did not reach the genome wide significance threshold until discovery and replication data were pooled together in that study. The objective of this study was to replicate these newly identified genetic associations for AAA in a US based prospective cohort study, the Atherosclerosis Risk in Communities (ARIC) Study, and a Greece based case control study. METHODS: ARIC identified 408 clinically diagnosed AAAs among 8 962 individuals of European ancestry during a median of 22 years of follow up. The Greek case control study included 341 AAAs of European ancestry recruited in a tertiary referral centre and 292 geographically and ethnically matched controls recruited from the same institution. A Cox proportional hazards model was used to analyse the ARIC data and logistic regression to analyse the Greek data. RESULTS: In ARIC, rs9316871 and rs3827066 were significantly associated with AAA risk (HR [p] was 0.77 [.004] and 1.22 [.03], respectively), rs2836411 was associated at borderline significance (1.13 [.08]), whereas rs1795061 was not associated (p = .55). In the Greek case control study, rs1795061 and rs2836411 were significantly associated with AAA (OR [p] was 1.66 [< .001] and 1.29 [.04], respectively), whereas rs9316871 was not (p = .81). Genotyping of rs3827066 did not succeed. In the meta-analysis of the two studies, the association for rs9316871and rs2836411 was statistically significant and consistent between the two studies: p = .02 and .007, respectively. CONCLUSIONS: Associations between rs9316871and rs2836411 and AAA risk were replicated in the meta-analysis of the two independent cohorts, providing further support for the importance of these loci in the aetiology of AAA.

Is There a Brain/Heart Interaction in Rheumatoid Arthritis and Seronegative Spondyloartropathies? A Combined Brain/Heart Magnetic Resonance Imaging Reveals the Answer.

PURPOSE OF REVIEW: To present the interaction between brain/heart and emphasize the role of combined brain/heart magnetic resonance imaging (MRI) in patients with rheumatoid arthritis (RA) and other seronegative spondyloarthropathies (SNA). RECENT FINDINGS: Both traditional cardiovascular disease (CVD) risk factors and intrinsic RA/SNA features contribute to the increased CVD-related morbidity/mortality. CVD in RA usually occurs a decade earlier than age- and sex-matched controls, and RA patients are twice more likely to develop myocardial infarction irrespective of age, history of prior CVD, and traditional CVD risk factors. RA also increases risk of non-ischemic heart failure (HF), valvular disease, and myo-pericarditis. CVD in SNA affects more commonly patients with long-standing disease. Ascending aortitis, aortic/mitral insufficiency, conduction defects, and diastolic dysfunction are the commonest findings in ankylosing spondylitis (AS). CVD is also the leading cause of death in psoriatic arthritis (PsA), due to myopericarditis, diastolic dysfunction, and valvular disease. Brain damage, due to either ischemic or hemorrhagic stroke and silent vascular damage, such as white matter hyperenhancement (WMH), is increased in both RA/SNA and may lead to cognitive dysfunction, depression, and brain atrophy. Magnetic resonance imaging (MRI) is ideal for serial brain/heart evaluation of patients with systemic diseases. RA/SNA patients are at high risk for brain/heart damage at early age, irrespectively of classic risk factors. Until more data will be obtained, a combined brain/heart MRI evaluation can be proposed in RA/SNA with new onset of arrhythmia and/or HF, cognitive dysfunction and/or depression.

Systemic autoimmune diseases, anti-rheumatic therapies, COVID-19 infection risk and patient outcomes.

As of June 10th 2020 about 7.2 million individuals have tested positive for, and more than 410,000 have died due to COVID-19. In this review we outline the pathophysiology that underpins the potential use of anti-rheumatic therapies for severe COVID-19 infection and summarize the current evidence regarding the risk and outcome of COVID-19 in patients with systemic autoimmune diseases. Thus far there is no convincing evidence that any disease-modifying anti-rheumatic drug (conventional synthetic, biologic or targeted synthetic) including hydroxychloroquine, may protect against severe COVID-19 infection; answers about their possible usefulness in the management of the cytokine storm associated with severe COVID-9 infection will only arise from ongoing randomized controlled trials. Evidence on COVID-19 risk and outcome in patients with systemic autoimmune diseases is extremely limited; thus, any conclusions would be unsafe and should be seen with great caution. At present, the risk and severity (hospitalization, intensive care unit admission and death) of COVID-19 infection in people with autoimmune diseases do not appear particularly dissimilar to the general population, with the possible exception of hospitalization in patients exposed to high glucocorticoid doses. At this stage it is impossible to draw any conclusions for differences in COVID-19 risk and outcome between different autoimmune diseases and between the various immunomodulatory therapies used for them. More research in the field is obviously required, including as a minimum careful and systematic epidemiology and appropriately controlled clinical trials.