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.

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.

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.

Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review.

BACKGROUND: Artificial Intelligence (AI), in particular, machine learning (ML) has shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) risk prediction. Bias in ML systems is of great interest due to its over-performance and poor clinical delivery. The main objective is to understand the nature of risk-of-bias (RoB) in ML and non-ML studies for CVD risk prediction. METHODS: PRISMA model was used to shortlisting 117 studies, which were analyzed to understand the RoB in ML and non-ML using 46 and 32 attributes, respectively. The mean score for each study was computed and then ranked into three ML and non-ML bias categories, namely low-bias (LB), moderate-bias (MB), and high-bias (HB), derived using two cutoffs. Further, bias computation was validated using the analytical slope method. RESULTS: Five types of the gold standard were identified in the ML design for CAD/CVD risk prediction. The low-moderate and moderate-high bias cutoffs for 24 ML studies (5, 10, and 9 studies for each LB, MB, and HB) and 14 non-ML (3, 4, and 7 studies for each LB, MB, and HB) were in the range of 1.5 to 1.95. BiasML< Biasnon-ML by ∼43%. A set of recommendations were proposed for lowering RoB. CONCLUSION: ML showed a lower bias compared to non-ML. For a robust ML-based CAD/CVD prediction design, it is vital to have (i) stronger outcomes like death or CAC score or coronary artery stenosis; (ii) ensuring scientific/clinical validation; (iii) adaptation of multiethnic groups while practicing unseen AI; (iv) amalgamation of conventional, laboratory, image-based and medication-based biomarkers.

Patterns and factors associated with pneumococcal vaccination in a prospective cohort of 1,697 patients with rheumatoid arthritis.

Introduction: Patients with rheumatoid arthritis (RA) are at increased risk for serious infections. Pneumococcal vaccination is among the most important preventive measures, however, vaccine uptake is suboptimal. We explored the rate and factors associated with pneumococcal vaccination in a contemporary RA cohort. Materials and methods: Multi-center, prospective, RA cohort study in Greece. Patient and disease characteristics and influenza and pneumococcal vaccinations were documented at baseline and 3 years later. Results: One thousand six hundred and ninety-seven patients were included and 34.5% had already received at least one pneumococcal vaccine at baseline. Among 1,111 non-vaccinated patients, 40.1% received pneumococcal vaccination during follow-up, increasing the vaccine coverage to 60.8%. By multivariate analysis, positive predictors for pneumococcal vaccination included prescription of influenza vaccine (OR = 33.35, 95% CI: 18.58-59.85), history of cancer (OR = 2.35, 95% CI: 1.09-5.06), bDMARD use (OR = 1.85, 95% CI: 1.29-2.65), seropositivity (OR = 1.47, 95% CI: 1.05-2.05), and high disease activity (DAS28-ESR, OR = 1.33, 95% CI: 1.17-1.51). Male sex (OR = 0.65, 95% CI: 0.43-0.99) was a negative predictor for pneumococcal vaccination during follow-up. Discussion: Despite increasing rates of pneumococcal vaccine coverage, 40% of RA patients remain unvaccinated. Severe disease, bDMARD use, comorbidities, and more importantly flu vaccination were the most significant factors associated with pneumococcal vaccination, emphasizing the currently unmet need for cultivating a "vaccination culture" in RA patients.

Six artificial intelligence paradigms for tissue characterisation and classification of non-COVID-19 pneumonia against COVID-19 pneumonia in computed tomography lungs.

BACKGROUND: COVID-19 pandemic has currently no vaccines. Thus, the only feasible solution for prevention relies on the detection of COVID-19-positive cases through quick and accurate testing. Since artificial intelligence (AI) offers the powerful mechanism to automatically extract the tissue features and characterise the disease, we therefore hypothesise that AI-based strategies can provide quick detection and classification, especially for radiological computed tomography (CT) lung scans. METHODOLOGY: Six models, two traditional machine learning (ML)-based (k-NN and RF), two transfer learning (TL)-based (VGG19 and InceptionV3), and the last two were our custom-designed deep learning (DL) models (CNN and iCNN), were developed for classification between COVID pneumonia (CoP) and non-COVID pneumonia (NCoP). K10 cross-validation (90% training: 10% testing) protocol on an Italian cohort of 100 CoP and 30 NCoP patients was used for performance evaluation and bispectrum analysis for CT lung characterisation. RESULTS: Using K10 protocol, our results showed the accuracy in the order of DL > TL > ML, ranging the six accuracies for k-NN, RF, VGG19, IV3, CNN, iCNN as 74.58 ± 2.44%, 96.84 ± 2.6, 94.84 ± 2.85%, 99.53 ± 0.75%, 99.53 ± 1.05%, and 99.69 ± 0.66%, respectively. The corresponding AUCs were 0.74, 0.94, 0.96, 0.99, 0.99, and 0.99 (p-values < 0.0001), respectively. Our Bispectrum-based characterisation system suggested CoP can be separated against NCoP using AI models. COVID risk severity stratification also showed a high correlation of 0.7270 (p < 0.0001) with clinical scores such as ground-glass opacities (GGO), further validating our AI models. CONCLUSIONS: We prove our hypothesis by demonstrating that all the six AI models successfully classified CoP against NCoP due to the strong presence of contrasting features such as ground-glass opacities (GGO), consolidations, and pleural effusion in CoP patients. Further, our online system takes < 2 s for inference.

Cancer risk in systemic sclerosis: identifying risk and managing high-risk patients.

Introduction: Systemic sclerosis (SSc) is associated with a heightened cancer risk compared to the general population. Several pathways including immune system upregulation, cumulative inflammation, environmental factors, and genetic predisposition contribute to the development of both cancer and autoimmunity. Areas covered: This paper provides an overview of studies investigating the relationship between SSc and various types of cancer with a special focus on the identification of patients at higher risk for malignancy development. The demographic, serological, clinical, and disease-related characteristics of SSc individuals who are diagnosed with cancer over the course of their disease are discussed to provide a practical guidance for relevant screening strategies. Expert opinion: Several studies have identified subgroups of SSc patients at higher cancer risk based on the immunological profile (anti-RNAPol III positivity), diffuse disease type, and older age at SSc onset. Additionally, a close temporal association between SSc and cancer onset in certain antibody subsets raises the question as to whether more aggressive screening strategies should be considered. Currently, there are no published studies investigating the cost-effectiveness, efficacy, and safety of a targeted cancer-detection program. Screening procedures should at least follow recommendations for the general population with a special focus on patients at higher risk and specific cancer types.

3-D optimized classification and characterization artificial intelligence paradigm for cardiovascular/stroke risk stratification using carotid ultrasound-based delineated plaque: Atheromatic™ 2.0.

BACKGROUND AND PURPOSE: Atherosclerotic plaque tissue rupture is one of the leading causes of strokes. Early carotid plaque monitoring can help reduce cardiovascular morbidity and mortality. Manual ultrasound plaque classification and characterization methods are time-consuming and can be imprecise due to significant variations in tissue characteristics. We report a novel artificial intelligence (AI)-based plaque tissue classification and characterization system. METHODS: We hypothesize that symptomatic plaque is hypoechoic due to its large lipid core and minimal collagen, as well as its heterogeneous makeup. Meanwhile, asymptomatic plaque is hyperechoic due to its small lipid core, abundant collagen, and the fact that it is often calcified. We designed a computer-aided diagnosis (CADx) system consisting of three kinds of deep learning (DL) classification paradigms: Deep Convolutional Neural Network (DCNN), Visual Geometric Group-16 (VGG16), and transfer learning, (tCNN). DCNN was 3-D optimized by varying the number of CNN layers and data augmentation frameworks. The DL systems were benchmarked against four types of machine learning (ML) classification systems, and the CADx system was characterized using two novel strategies consisting of DL mean feature strength (MFS) and a bispectrum model using higher-order spectra. RESULTS: After balancing symptomatic and asymptomatic plaque classes, a five-fold augmentation process was applied, yielding 1000 carotid scans in each class. Then, using a K10 protocol (trained to test the ratio of 90%-10%), tCNN and DCNN yielded accuracy (area under the curve (AUC)) pairs of 83.33%, 0.833 (p < 0.0001) and 95.66%, 0.956 (p < 0.0001), respectively. DCNN was superior to ML by 7.01%. As part of the characterization process, the MFS of the symptomatic plaque was found to be higher compared to the asymptomatic plaque by 17.5% (p < 0.0001). A similar pattern was seen in the bispectrum, which was higher for symptomatic plaque by 5.4% (p < 0.0001). It took <2 s to perform the online CADx process on a supercomputer. CONCLUSIONS: The performance order of the three AI systems was DCNN > tCNN > ML. Bispectrum-based on higher-order spectra proved a powerful paradigm for plaque tissue characterization. Overall, the AI-based systems offer a powerful solution for plaque tissue classification and characterization.

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.

Current understanding and future perspectives of brain-heart-kidney axis in psoriatic arthritis.

Psoriatic arthritis (PsA) patients are at a higher risk of systemic inflammatory sequelae, leading to microalbuminuria, cardiovascular (CVD) and neuropsychiatric (NPD) disease. Our aim is to present the existing literature about the relationship between CVD, kidney and NPD in PsA. The literature evaluation of PsA revealed that chronic T-cell activation and increased levels of circulating immune complexes can cause glomerular injury leading to microalbuminuria, which predicts CVD and all-cause mortality in both diabetic and non-diabetic patients. Furthermore, it is a marker of preclinical brain damage and identifies patients at higher risk of NPD/CVD events. Among the currently used imaging modalities in PsA, magnetic resonance imaging (MRI) maintains a crucial role, because it is ideal for concurrent evaluation of brain/heart involvement and serial follow up assessment. There is increasing evidence regarding the relationship between kidneys, heart and brain in PsA. Although currently there are no official recommendations about a combined brain/heart MRI in PsA, it could be considered in PsA with microalbuminuria, arrhythmia, HF, cognitive dysfunction and/or depression.

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.

Integration of estimated glomerular filtration rate biomarker in image-based cardiovascular disease/stroke risk calculator: a south Asian-Indian diabetes cohort with moderate chronic kidney disease.

BACKGROUND: Recently, a 10-year image-based integrated calculator (called AtheroEdge Composite Risk Score-AECRS1.0) was developed which combines conventional cardiovascular risk factors (CCVRF) with image phenotypes derived from carotid ultrasound (CUS). Such calculators did not include chronic kidney disease (CKD)-based biomarker called estimated glomerular filtration rate (eGFR). The novelty of this study is to design and develop an advanced integrated version called-AECRS2.0 that combines eGFR with image phenotypes to compute the composite risk score. Furthermore, AECRS2.0 was benchmarked against QRISK3 which considers eGFR for risk assessment. METHODS: The method consists of three major steps: 1) five, current CUS image phenotypes (CUSIP) measurements using AtheroEdge system (AtheroPoint, CA, USA) consisting of: average carotid intima-media thickness (cIMTave), maximum cIMT (cIMTmax), minimum cIMT (cIMTmin), variability in cIMT (cIMTV), and total plaque area (TPA); 2) five, 10-year CUSIP measurements by combining these current five CUSIP with 11 CCVRF (age, ethnicity, gender, body mass index, systolic blood pressure, smoking, carotid artery type, hemoglobin, low-density lipoprotein cholesterol, total cholesterol, and eGFR); 3) AECRS2.0 risk score computation and its comparison to QRISK3 using area-under-the-curve (AUC). RESULTS: South Asian-Indian 339 patients were retrospectively analyzed by acquiring their left/right common carotid arteries (678 CUS, mean age: 54.25±9.84 years; 75.22% males; 93.51% diabetic with HbA1c ≥6.5%; and mean eGFR 73.84±20.91 mL/min/1.73m2). The proposed AECRS2.0 reported higher AUC (AUC=0.89, P<0.001) compared to QRISK3 (AUC=0.51, P<0.001) by ~74% in CKD patients. CONCLUSIONS: An integrated calculator AECRS2.0 can be used to assess the 10-year CVD/stroke risk in patients suffering from CKD. AECRS2.0 was much superior to QRISK3.

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.

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.

The Platelet-to-Lymphocyte Ratio as an Inflammatory Marker in Rheumatic Diseases.

The platelet-to-lymphocyte ratio (PLR) has emerged as an informative marker revealing shifts in platelet and lymphocyte counts due to acute inflammatory and prothrombotic states. PLR has been extensively examined in neoplastic diseases accompanied by immune suppression and thrombosis, which can be predicted by combined blood cell counts and their ratios. Several large observational studies have demonstrated the value of shifts in PLR in evaluating the severity of systemic inflammation and predicting infections and other comorbidities, in inflammatory rheumatic diseases. The value of PLR as an inflammatory marker increases when its fluctuations are interpreted along with other complementary hematologic indices, particularly the neutrophil-to-lymphocyte ratio (NLR), which provides additional information about the disease activity, presence of neutrophilic inflammation, infectious complications, and severe organ damage in systemic lupus erythematosus. PLR and NLR have high predictive value in rheumatic diseases with predominantly neutrophilic inflammation (e.g., Behçet disease and familial Mediterranean fever). High PLR, along with elevated platelet count, is potentially useful in diagnosing some systemic vasculitides, particularly giant-cell arteritis. A few longitudinal studies on rheumatic diseases have demonstrated a decrease in PLR in response to anti-inflammatory therapies. The main limitations of PLR studies are preanalytical faults, inadequate standardization of laboratory measurements, and inappropriate subject selection. Nonetheless, accumulating evidence suggests that PLR can provide valuable information to clinicians who encounter multisystem manifestations of rheumatic diseases, which are reflected in shifts in platelet, lymphocyte, neutrophil, or monocyte counts. Interpretation of PLR combined with complementary hematologic indices is advisable to more accurately diagnose inflammatory rheumatic diseases and predict related comorbidities.

Systematic review of the predictors of statin adherence for the primary prevention of cardiovascular disease.

INTRODUCTION: Previous research has shown that statin adherence for the primary prevention of CVD is lower compared to secondary prevention populations. Therefore the aim of this systematic review was to review predictors of statin adherence for the primary prevention of CVD. METHODS: A systematic search of papers published between Jan 1984 and May 2017 was conducted in PubMed, PsycINFO, EMbase and CINAHL databases. A study was eligible for inclusion if; 1) it was a study of the general population or of patients with familial hypercholesterolemia, hypertension, diabetes or arthritis; 2) statins were prescribed; 3) adherence was defined and measured as the extent to which patients followed their statin regimen during the period of prescription, and 4) it was an original trial or observational study (excluding case reports). A study was subsequently excluded if 1) results were not presented separately for primary prevention; 2) it was a trial of an intervention (for example patient education). Papers were reviewed by two researchers and consensus agreed with a third. A quality assessment (QA) tool was used to formally assess each included article. To evaluate the effect of predictors, data were quantitatively and qualitatively synthesised. RESULTS: In total 19 studies met the inclusion criteria and nine were evaluated as high quality using the QA tool. The proportion of patients classed as "adherent" ranged from 17.8% to 79.2%. Potential predictors of statin adherence included traditional risk factors for CVD such as age, being male, diabetes and hypertension. Income associated with adherence more strongly in men than women, and highly educated men were more likely and highly educated women less likely to be adherent. Alcohol misuse and high BMI associated with non-adherence. There was no association between polypharmacy and statin adherence. The evidence base for the effect of other lifestyle factors and health beliefs on statin adherence was limited. CONCLUSION: Current evidence suggests that patients with more traditional risk factors for CVD are more likely to be adherent to statins. The implications for future research are discussed.

Nonlinear model for the carotid artery disease 10-year risk prediction by fusing conventional cardiovascular factors to carotid ultrasound image phenotypes: A Japanese diabetes cohort study.

MOTIVATION: This study presents a novel nonlinear model which can predict 10-year carotid ultrasound image-based phenotypes by fusing nine traditional cardiovascular risk factors (ethnicity, gender, age, artery type, body mass index, hemoglobin A1c, hypertension, low-density lipoprotein, and smoking) with five types of carotid automated image phenotypes (three types of carotid intima-media thickness (IMT), wall variability, and total plaque area). METHODOLOGY: Two-step process was adapted: First, five baseline carotid image-based phenotypes were automatically measured using AtheroEdge™ (AtheroPoint™ , CA, USA) system by two operators (novice and experienced) and an expert. Second, based on the annual progression rates of cIMT due to nine traditional cardiovascular risk factors, a novel nonlinear model was adapted for 10-year predictions of carotid phenotypes. RESULTS: Institute review board (IRB) approved 204 Japanese patients' left/right common carotid artery (407 ultrasound scans) was collected with a mean age of 69 ± 11 years. Age and hemoglobin were reported to have a high influence on the 10-year carotid phenotypes. Mean correlation coefficient (CC) between 10-year carotid image-based phenotype and age was improved by 39.35% in males and 25.38% in females. The area under the curves for the 10-year measurements of five phenotypes IMTave10yr , IMTmax10yr , IMTmin10yr , IMTV10yr , and TPA10yr were 0.96, 0.94, 0.90, 1.0, and 1.0. Inter-operator variability between two operators showed significant CC (P < 0.0001). CONCLUSIONS: A nonlinear model was developed and validated by fusing nine conventional CV risk factors with current carotid image-based phenotypes for predicting the 10-year carotid ultrasound image-based phenotypes which may be used risk assessment.

Cardiovascular magnetic resonance in the diagnosis and management of cardiac and vascular involvement in the systemic vasculitides.

PURPOSE OF REVIEW: Cardiac manifestations in systemic vasculitides, either primary or secondary due to infection, malignancy or autoimmune rheumatic diseases may be life-threatening. Cardiovascular (CVD) magnetic resonance (CMR) has been recently proposed as an ideal noninvasive tool to evaluate systemic vasculitides. In the present article, we present an overview of CMR in the diagnosis and follow-up of cardiac involvement in systemic vasculitides. RECENT FINDINGS: CMR is a noninvasive, nonradiating modality, capable to assess cardiac function, perfusion and tissue characterization that can be of great diagnostic value in both primary and secondary systemic vasculitides. It has been already documented that CMR is superior to other imaging modalities, because it has great versatility and higher spatial resolution that allows the detection of early CVD phenomena occurring during systemic vasculitides. Magnetic resonance angiography and oedema-fibrosis imaging detect early CVD involvement such as acute and/or chronic inflammation, coronary macro-micro-circulation abnormalities and/or small vessel vasculitis. SUMMARY: CMR due to its great versatility gives valuable information about cardiac function, perfusion, type of fibrosis and vascular integrity that may significantly contribute to treatment decisions beyond vascular scores, other disease activity or severity indices or the acute phase response.

Comparison of the effects of exercise and anti-TNF treatment on cardiovascular health in rheumatoid arthritis: results from two controlled trials.

People with rheumatoid arthritis (RA) are at increased risk for cardiovascular disease (CVD). Both pharmacological treatment and exercise are suggested in the management of CVD risk in RA. This study explored the effects of exercise and anti-TNF treatment on CVD risk in RA. Twenty RA patients (70% female, 50 (10) years) completed a 3-month exercise intervention and 23 RA patients (65% female, 54 (15) years) started anti-TNF treatment. Markers of disease activity, CVD risk, and vascular function were assessed before and after 3-months of intervention/treatment. Both exercise and anti-TNF treatment improved functional ability and fatigue, anti-TNF treatment was more successful in improving inflammation, disease activity, functional ability and pain. Exercise induced a reduction in overall CVD risk and improvement in vascular function, which was significantly different from anti-TNF treatment where no such changes were found. These findings showed that exercise and anti-TNF had differential effects on CVD risk in RA, and should be combined for optimal CVD risk reduction. Whereas anti-TNF treatment is likely to impact on CVD risk through reducing the systemic inflammatory load, exercise should be recommended to people with RA as an effective self-management strategy to reduce CVD risk further. Once RA patients have responded successfully to anti-TNF treatment, increasing exercise should be encouraged to reduce the risk for CVD. Thus, supporting exercise programmes when the disease is controlled, is likely to enhance the uptake and the maintenance of exercise, which will result in additional benefits to cardiovascular health and wellbeing in people with RA.