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.

Chronotropic Response and Risk Factors for Cardiovascular Disease in Patients with Rheumatoid Arthritis: A Cross-Sectional Study.

BACKGROUND: Individuals with rheumatoid arthritis (RA) are at a high risk of cardiovascular diseases (CVD). A reduced chronotropic response (CR), which produces exercise intolerance, is known to be a contributing factor to CVD and mortality. Studies have shown that patients with RA have a reduced CR. However, knowledge of CR-related factors in patients with RA is limited. This study aimed to explore CR-related factors, including CVD risk factors, inflammatory markers, and cardiorespiratory fitness (VO2PEAK). METHODS: A total of 106 RA patients underwent a treadmill test, heart rate monitoring, and various assessments, including serological CVD risk factors, inflammatory markers, and VO2PEAK. RESULTS: A total of 34% of participants demonstrated a reduced CR (≤80%). Body mass index, HOMA, hsCRP, and fibrinogen were inversely related to CR, while HDL, QUICKi, VO2PEAK, and RER exhibited a positive association. HDL and VO2PEAK emerged as independent CR-related factors in regression analysis. CONCLUSIONS: The current findings suggest that reduced CR in RA is associated with several CVD risk factors, inflammatory markers, and cardiorespiratory fitness. Future studies should investigate the effects of controlling these associated variables on CR in patients with RA.

The interrater and test-retest reliability of 3 modalities of quantitative sensory testing in healthy adults and people with chronic low back pain or rheumatoid arthritis.

Introduction: Quantitative Sensory Testing (QST) modalities used to assess central pain mechanisms require different protocols in people with different musculoskeletal conditions. Objectives: We aimed to explore the possible effects of musculoskeletal diagnosis and test site on QST interrater and test-retest reliability. Methods: The study included participants with rheumatoid arthritis (RA, n = 18; QST conducted on lower leg) and low back pain (LBP, n = 25; QST conducted on forearm), plus 45 healthy control participants (n = 20 QST on lower leg and n = 25 QST on forearm). Test-retest reliability was assessed from QST conducted 1 to 3 weeks apart. Quantitative sensory testing modalities used were pressure pain detection threshold (PPT) at a site distant to tissue pathology, temporal summation (TS), and conditioned pain modulation (CPM). Temporal summation was calculated as difference or ratio of single and repeated punctate stimuli and unconditioned thresholds for CPM used single or mean of multiple PPTs. Intraclass correlation coefficients (ICCs) were compared between different subgroups. Results: High to very high reliability was found for all assessments of PPT and TS across anatomical sites (lower leg and forearm) and participants (healthy, RA, and LBP) (ICC ≥ 0.77 for PPT and ICC ≥ 0.76 for TS). Reliability was higher when TS was calculated as a difference rather than a ratio. Conditioned pain modulation showed no to moderate reliability (ICC = 0.01-0.64) that was similar between leg or forearm, and between healthy people and those with RA or LBP. Conclusion: PPT and TS are transferable tools to quantify pain sensitivity at different testing sites in different musculoskeletal diagnoses. Low apparent reliability of CPM protocols might indicate minute-to-minute dynamic pain modulation.

Effects of lifestyle physical activity and sedentary behaviour interventions on disease activity and patient- and clinician- important health outcomes in rheumatoid arthritis: a systematic review with meta-analysis.

BACKGROUND: Lifestyle physical activity (PA) is defined as any type of PA undertaken as part of daily life. It can include engagement in activities of daily living (i.e., household chores, gardening, walking to work), incidental PA, walking and/or reducing sedentary or sitting behaviours (SB). Regular PA is recommended for people with Rheumatoid Arthritis (RA) to reduce disease activity and systemic inflammation, as well as to improve patient- and clinician-important health outcomes. However, there is no summarised evidence of the effectiveness of interventions specifically targeting lifestyle PA and SB in this population. The aims of this systematic review with meta-analysis were to evaluate interventions targeting lifestyle PA and/or SB on 1) disease activity; 2) PA, SB and 3) patient- and clinician-important outcomes in people with RA. METHODS: Eight databases [Medline, Cochrane Library CENTRAL, Web of Science, PsychINFO, Cumulative Index to Nursing & Allied Health Literature, Scopus, Excerpta Medica database and Physiotherapy Evidence Database] were searched from inception-August 2022. Inclusion criteria required interventions to target lifestyle PA and/or SB, conducted in adults with RA, assessing patient- and/or clinician-important outcomes. RESULTS: Of 880 relevant articles, 16 interventions met the inclusion criteria. Meta-analyses showed statistically significant effects of interventions on disease activity (standardised mean difference = -0.12 (95% confidence interval = -0.23 to -0.01, I2 = 6%, z = 2.19, p = .03), moderate-to-vigorous PA, light/leisure PA, steps, functional ability, and fatigue. Whereas, no intervention effects were visualised for total PA, pain, anxiety or quality of life. CONCLUSIONS: Lifestyle PA interventions led to increased PA, reductions in SB and improvements in disease activity and other patient- and/or clinician-important health outcomes in people with RA. Future interventions should be less heterogenous in content, structure, focus and outcome measures used to aid understanding of the most effective intervention components for improving health. More SB interventions are needed to determine their effectiveness at producing clinical benefits.

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.

Cardiovascular disease/stroke risk stratification in deep learning framework: a review.

The global mortality rate is known to be the highest due to cardiovascular disease (CVD). Thus, preventive, and early CVD risk identification in a non-invasive manner is vital as healthcare cost is increasing day by day. Conventional methods for risk prediction of CVD lack robustness due to the non-linear relationship between risk factors and cardiovascular events in multi-ethnic cohorts. Few recently proposed machine learning-based risk stratification reviews without deep learning (DL) integration. The proposed study focuses on CVD risk stratification by the use of techniques mainly solo deep learning (SDL) and hybrid deep learning (HDL). Using a PRISMA model, 286 DL-based CVD studies were selected and analyzed. The databases included were Science Direct, IEEE Xplore, PubMed, and Google Scholar. This review is focused on different SDL and HDL architectures, their characteristics, applications, scientific and clinical validation, along with plaque tissue characterization for CVD/stroke risk stratification. Since signal processing methods are also crucial, the study further briefly presented Electrocardiogram (ECG)-based solutions. Finally, the study presented the risk due to bias in AI systems. The risk of bias tools used were (I) ranking method (RBS), (II) region-based map (RBM), (III) radial bias area (RBA), (IV) prediction model risk of bias assessment tool (PROBAST), and (V) risk of bias in non-randomized studies-of interventions (ROBINS-I). The surrogate carotid ultrasound image was mostly used in the UNet-based DL framework for arterial wall segmentation. Ground truth (GT) selection is vital for reducing the risk of bias (RoB) for CVD risk stratification. It was observed that the convolutional neural network (CNN) algorithms were widely used since the feature extraction process was automated. The ensemble-based DL techniques for risk stratification in CVD are likely to supersede the SDL and HDL paradigms. Due to the reliability, high accuracy, and faster execution on dedicated hardware, these DL methods for CVD risk assessment are powerful and promising. The risk of bias in DL methods can be best reduced by considering multicentre data collection and clinical evaluation.

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.

New-onset systemic vasculitis following SARS-CoV-2 infection and vaccination: the trigger, phenotype, and outcome.

The global health crisis caused by the COVID-19 pandemic overwhelmed the capacity of healthcare systems to cope with the rapidly spreading infection and its associated complications. Among these complications, autoimmune phenomena such as systemic vasculitis emerged as a significant challenge. Both the SARS-CoV-2 virus and the vaccines developed to combat it appeared to induce clinical manifestations resembling various types of systemic vasculitis, affecting large, medium, and small vessels. These virus- or vaccine-induced vasculitides exhibited a distinct natural history and course from de novo vasculitis, as they were more responsive to steroid therapy and some mild cases even resolved spontaneously. Notably, there have been no confirmed cases of SARS-CoV-2 infection or vaccination triggering variable vessel vasculitis like Behcet's disease or Kawasaki disease. IgA vasculitis, which is predominantly a pediatric condition, was more prevalent in adults after COVID-19 infection and they had a favorable outcome with glucocorticoid treatment. The impact of immunosuppression, especially B-cell-depleting agents, on the immunogenicity of the vaccine was evident, but there was no significant increase in the incidence of SARS-CoV-2 infection in these patients compared to the general population. Considering their relatively benign course, these post-COVID or post-vaccine vasculitides seem to be amenable to 0.8 to 1 mg/kg prednisolone or equivalent, which could be gradually tapered. The need for immunosuppression and the duration of steroid therapy should be determined on an individual basis. While the world still reels from the perils of a deadly pandemic, the aftermath continues to haunt. Our narrative review aims to explore the effects of COVID and the vaccine on systemic vasculitis, as well as the effect of disease and immunosuppression on the immunogenicity of the COVID vaccine.

Ensemble Deep Learning Derived from Transfer Learning for Classification of COVID-19 Patients on Hybrid Deep-Learning-Based Lung Segmentation: A Data Augmentation and Balancing Framework.

BACKGROUND AND MOTIVATION: Lung computed tomography (CT) techniques are high-resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease control classification. Most artificial intelligence (AI) systems do not undergo generalization and are typically overfitted. Such trained AI systems are not practical for clinical settings and therefore do not give accurate results when executed on unseen data sets. We hypothesize that ensemble deep learning (EDL) is superior to deep transfer learning (TL) in both non-augmented and augmented frameworks. METHODOLOGY: The system consists of a cascade of quality control, ResNet-UNet-based hybrid deep learning for lung segmentation, and seven models using TL-based classification followed by five types of EDL's. To prove our hypothesis, five different kinds of data combinations (DC) were designed using a combination of two multicenter cohorts-Croatia (80 COVID) and Italy (72 COVID and 30 controls)-leading to 12,000 CT slices. As part of generalization, the system was tested on unseen data and statistically tested for reliability/stability. RESULTS: Using the K5 (80:20) cross-validation protocol on the balanced and augmented dataset, the five DC datasets improved TL mean accuracy by 3.32%, 6.56%, 12.96%, 47.1%, and 2.78%, respectively. The five EDL systems showed improvements in accuracy of 2.12%, 5.78%, 6.72%, 32.05%, and 2.40%, thus validating our hypothesis. All statistical tests proved positive for reliability and stability. CONCLUSION: EDL showed superior performance to TL systems for both (a) unbalanced and unaugmented and (b) balanced and augmented datasets for both (i) seen and (ii) unseen paradigms, validating both our hypotheses.

Cardiovascular risk in vasculitis.

The present review summarizes the burden, risk factors, biomarkers of and therapeutic consideration for cardiovascular disease in systemic vasculitis. Ischemic heart disease (IHD) and stroke are intrinsic features of Kawasaki disease, Takayasu arteritis, Giant Cell Arteritis (GCA), and Behcet's disease. The risk of IHD and stroke is increased in anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) and cryoglobulinemic vasculitis. Behcet's disease could present with venous thromboembolism. The risk of venous thromboembolism is increased in AAV, polyarteritis nodosa, and GCA. The risk of cardiovascular events is greatest at or immediately after the diagnosis of AAV or GCA, therefore, controlling vasculitis disease activity is of utmost importance. Traditional as well as disease-related risk factors drive the heightened cardiovascular risk in vasculitis. Aspirin or statins reduce the risk of IHD or stroke in GCA or the risk of IHD in Kawasaki Disease. Venous thromboembolism in Behcet's disease should be treated with immunosuppressive therapy rather than with anticoagulation.

Combined Effects of Diet and Physical Activity on Inflammatory Joint Disease: A Systematic Review and Meta-Analysis.

Research evidence suggests that, individually, diet and physical activity are effective interventions for reducing levels of inflammation in inflammatory joint diseases (IJD), however little is known about their combined use. This systematic review and meta-analysis aimed to examine the effects and/or associations of combined diet and physical activity interventions in IJD, specifically rheumatoid arthritis (RA) and the spondyloarthropathies (SpA) (PROSPERO registration number: CRD42022370993). Ten out of 11 eligible studies examined RA patients. We found that a combination of diet/nutrition and physical activity/exercise improved Health Assessment Questionnaire score (standardized mean difference = -1.36, confidence interval (CI) = (-2.43)-(-0.30), I2 = 90%, Z = 2.5, p = 0.01), while surprisingly they increased erythrocyte sedimentation rate (mean difference = 0.20, CI = 0.09-0.31, I2 = 0%, Z = 3.45, p < 0.01). No effects were found on C-reactive protein or weight (p > 0.05) of RA patients. We did not find studies in other IJDs that provided sufficient data for a meta-analysis. The narrative data synthesis provided limited evidence to address our research question. No firm conclusions can be made as to whether the combination of diet/nutrition and physical activity/exercise affects inflammatory load in IJDs. The results of this study can only be used as a means of highlighting the low-quality evidence in this field of investigation and the need for further and better-quality research.

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.

Do Interleukin-1 and Interleukin-6 Antagonists Hold Any Place in the Treatment of Atherosclerotic Cardiovascular Disease and Related Co-Morbidities? An Overview of Available Clinical Evidence.

Cardiovascular disease (CVD) constitutes a real pandemic of the 21st century. According to data from the Centers for Disease Control and Prevention, one person dies every 34 min due to some form of CVD in the United States. Apart from the extremely high morbidity and mortality accompanying CVD, the economic burden seems to be unbearable even for developed countries in the Western World. The role of inflammation in the development and progression of CVD appears to be crucial, while, various inflammatory pathways, such as the Nod-like receptor protein 3 (NLRP3) inflammasome-interleukin (IL)-1/IL-6 pathway of the innate immunity, have attracted scientific interest during the last decade, as a potential treatment target in primary and/or secondary prevention of CVD. Whereas there is a significant amount of evidence, stemming mainly from observational studies, concerning the cardiovascular safety of IL-1 and IL-6 antagonists in patients with rheumatic diseases, evidence from relevant randomized controlled trials (RCTs) is rather scarce and conflicting, especially for patients without underlying rheumatic disease. In this review, we summarize and critically present the currently available evidence, both from RCTs and observational studies, concerning the place that IL-1 and IL-6 antagonists may hold in the treatment of CVD.

Understanding and managing cardiac involvement in systemic sclerosis.

INTRODUCTION: Cardiac involvement is common in systemic sclerosis occurring in up to 80% of patients. Primary myocardial dysfunction results from impairment of coronary microvascular circulation, myocardial inflammation and fibrosis with the prevalence of atherosclerosis remaining contradictory. AREAS COVERED: This review presents the various aspects of cardiac involvement in SSc from a pathophysiological, clinical, diagnostic and therapeutic standpoint. Imaging modalities with emerging role in the understanding of mechanisms and prompt diagnosis of myocardial fibrosis namely cardiac magnetic resonance are also discussed. EXPERT OPINION: Cardiac involvement in SSc - and particularly primary myocardial disease - remains a challenge as clinical symptoms manifest in advanced stages of heart failure and convey poor prognosis. Over the last years the introduction of sophisticated imaging methods of myocardial function has resulted in a better understanding of the underlying pathophysiological processes of myocardial damage such as microvasculopathy, inflammation, diffuse or focal fibrosis. Such developments could contribute to the identification of patients at higher risk for subclinical heart involvement for whom diligent surveillance and prompt initiation of therapy with cardioprotective and/or immunosuppressive drugs coupled with invasive interventions namely radiofrequency ablation, implantable cardioverter-defibrillator when indicated, may improve long-term outcomes.

The behavioural epidemiology of sedentary behaviour in inflammatory arthritis: where are we, and where do we need to go?

In the last decade, studies into sedentary behaviour in inflammatory arthritis have raised important questions regarding its role in this condition. Specifically, evidence is needed on whether sedentary behaviour might exacerbate adverse inflammatory arthritis outcomes, and whether reducing sedentary behaviour might offer an effective avenue for self-management in this population. Research exploring these important research questions is still very much in its infancy and lacks the direction and scientific rigour required to inform effective intervention design, delivery and evaluation. Behavioural epidemiology refers to research that aims explicitly to understand and influence health behaviour patterns to prevent disease and improve health. To this end, the Behavioural Epidemiology Framework specifies a focused approach to health behaviour research, which leads to the development of evidence-based interventions directed at specific populations. In this review, we introduce the Behavioural Epidemiology Framework in the context of research into sedentary behaviour in inflammatory arthritis and ask: where are we, and where do we need to go?

Physicians' perceptions about antineutrophil cytoplasmic antibody-associated vasculitis: an online survey report in the time of the COVID-19 pandemic.

Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAV) are characterized by necrotizing inflammation of small and medium-size vessels that often manifest with devastating multi-organ effects. They present with a myriad of systemic features and require potent immunosuppression. Since they are uncommonly encountered in clinical practice, it is necessary to understand physicians' knowledge and perceptions about this group of diseases. An online questionnaire was designed featuring 28 questions based on relevant global practice guidelines, recommendations, and previous online surveys on AAV. The questionnaire was validated by a core group of specialists with an interest in AAV. It was shared via social networking sites and entries were restricted to physicians. Only completed entries were analyzed with descriptive statistics. A total of 113 respondents from 21 different countries responded of whom the commonest were rheumatologists, internists, and general practitioners. Forty-five (40%) ran clinics dedicated to AAV patients as a part of their practice. They commented on organs involved in AAV; vasculitis secondary to infections, drugs or other rheumatic diseases; various tests useful for AAV diagnosis; and drug choices for induction and maintenance. They mentioned their experience regarding COVID-19 in AAV patients as well as vasculitic manifestations of COVID-19. Various methods to mitigate cardiovascular risks in AAV were mentioned. Finally, the respondents indicated how medical education needed to be strengthened to increase awareness and knowledge regarding AAV. This survey helped to inform about various perceptions regarding AAV across countries, including current practices and recent evolution of management. It also provided information on treatment of the COVID-19 in AAV patients. This survey showed that there is still a lack in understanding the prevalent definitions and there is gap between guidelines and current practice. Key Points • Perception about ANCA-associated vasculitis differ across countries. • The number of cases encountered across 21 different countries are limited implying a need for multi-national cooperation to study this disease further. • The COVID-19 pandemic has changed the approach towards ANCA-associated vasculitis by the various clinicians.

Cardiac inflammation and fibrosis patterns in systemic sclerosis, evaluated by magnetic resonance imaging: An update.

Systemic sclerosis (SSc) presents high morbidity/mortality, due to internal organ fibrosis, including the heart. Cardiac magnetic resonance (CMR) can perform myocardial function and tissue characterization in the same examination. The Lake Louise criteria (LLC) can identify recent myocardial inflammation using CMR. Abnormal values include: (a) myocardial over skeletal muscle ratio in STIRT2-W images >2, (b) early gadolinium enhancement values >4, (c) epicardial/intramyocardial late gadolinium enhancement (LGE). The diagnosis of myocarditis using LLC is considered if 2/3 criteria are positive. Parametric imaging including T2, native T1 mapping and extracellular volume fraction (ECV) has been recently used to diagnose inflammatory cardiomyopathy. According to expert recommendations, myocarditis should be considered if at least 2 indices, one T2 and one T1 parameter are positive, whereas native T1 mapping and ECV assess diffuse fibrosis or oedema, even in the absence of LGE. Moreover, transmural/subendocardial fibrosis following the distribution of coronary arteries and diffuse subendocardial fibrosis not related with epicardial coronary arteries are indicative of epicardial and micro-vascular coronary artery disease, respectively. To conclude, CMR can identify acute/active myocardial inflammation and myocardial infarction using classic and parametric indices in parallel with ventricular function evaluation.

Atherosclerotic Cardiovascular Risk Stratification in the Rheumatic Diseases:: An Integrative, Multiparametric Approach.

Cardiovascular disease (CVD) risk is increased in most inflammatory rheumatic diseases (IRDs), reiterating the role of inflammation in the initiation and progression of atherosclerosis. An inverse association of CVD risk with body weight and lipid levels has been described in IRDs. Coronary artery calcium scores, plaque burden and characteristics, and carotid plaques on ultrasound optimize CVD risk estimate in IRDs. Biomarkers of cardiac injury, autoantibodies, lipid biomarkers, and cytokines also improve risk assessment in IRDs. Machine learning and deep learning algorithms for phenotype and image analysis hold promise to improve CVD risk stratification in IRDs.

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.

Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment.

Motivation: The price of medical treatment continues to rise due to (i) an increasing population; (ii) an aging human growth; (iii) disease prevalence; (iv) a rise in the frequency of patients that utilize health care services; and (v) increase in the price. Objective: Artificial Intelligence (AI) is already well-known for its superiority in various healthcare applications, including the segmentation of lesions in images, speech recognition, smartphone personal assistants, navigation, ride-sharing apps, and many more. Our study is based on two hypotheses: (i) AI offers more economic solutions compared to conventional methods; (ii) AI treatment offers stronger economics compared to AI diagnosis. This novel study aims to evaluate AI technology in the context of healthcare costs, namely in the areas of diagnosis and treatment, and then compare it to the traditional or non-AI-based approaches. Methodology: PRISMA was used to select the best 200 studies for AI in healthcare with a primary focus on cost reduction, especially towards diagnosis and treatment. We defined the diagnosis and treatment architectures, investigated their characteristics, and categorized the roles that AI plays in the diagnostic and therapeutic paradigms. We experimented with various combinations of different assumptions by integrating AI and then comparing it against conventional costs. Lastly, we dwell on three powerful future concepts of AI, namely, pruning, bias, explainability, and regulatory approvals of AI systems. Conclusions: The model shows tremendous cost savings using AI tools in diagnosis and treatment. The economics of AI can be improved by incorporating pruning, reduction in AI bias, explainability, and regulatory approvals.