Cardiovascular comorbidity in rheumatic and musculoskeletal diseases: Where we are and how can we move forward?

Kitas, George D.; Dimiroulas, Theodoros

doi:10.1111/1756-185x.14112

Cited by 4 publications

(5 citation statements)

References 23 publications

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“…These findings emphasize the need for early screening, preventive treatment, and optimized multidisciplinary care when appropriate. 11 Nevertheless, contrary to previously reported, 7 none of our patients suffered from any major cardiovascular events, despite such a high prevalence of cardiovascular comorbidities; this is presumably due to the characteristics of our cohort, comprised by young females, way different than previously reported, in which mean age ranged from 46 to 62. 7 We observed a considerable number of patients with infections particularly tuberculosis, which is fairly common in IIM, particularly in endemic regions, as described previously.…”

contrasting

confidence: 91%

Comorbidities in idiopathic inflammatory myopathies: Data from the MyoCite cohort

Conticini,

Khursheed,

Anuja

et al. 2023

Int J of Rheum Dis

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Idiopathic inflammatory myopathies (IIMs) are a group of heterogeneous and rare disorders affecting multisystems in addition to muscles, often leading to substantial impairment in quality of life. 1 Ethnic and geographic variations influence the autoantibody patterns and clinical spectrum among IIM patients. 2 Patients affected by IIM may suffer from several comorbidities, such as cancer or cardiovascular disease, which may complicate the course of the disease. Certain comorbidities are associated with worse outcomes and increased mortality. 3 Moreover, the presence of comorbidities may impact treatment choices.Previous studies have highlighted an elevated risk of coexisting malignancy 4,5 and cardiovascular disease 6 in the literature. However, the exact prevalence of other comorbidities and their correlation with autoantibodies remains largely unexplored. Our primary objective was to investigate the spectrum of comorbidities among Indian patients diagnosed with IIM in a tertiary care center, to establish the MyoCite Cohort, and to evaluate their potential associations with disease subtypes and antibodies.The MyoCite dataset represents a repository of longitudinal data, encompassing adults and children diagnosed with IIM who received or are currently receiving treatment at a tertiary care hospital in India. A comprehensive account of the methodology has been previously published, incorporating details on patient selection and definitions of disease subsets. 7,8 Through a thorough screening process, both adults and children presenting with myositis were meticulously evaluated. 9 From the MyoCite dataset, we extracted essential demographic information, such as age, gender, disease subtypes, comorbidities, and autoantibodies, to facilitate our investigation.Comorbidities were classified as autoimmune, cardiovascular, cancer, infections, and others. In addition, autoantibodies were classified into myositis-specific antibodies (MSAs), myositis-associated antibodies (MAAs), anti-aminoacyl tRNA synthetase antibodies (ARAs), and anti-nuclear antibodies (ANAs) as well as individual

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contrasting

confidence: 91%

Comorbidities in idiopathic inflammatory myopathies: Data from the MyoCite cohort

Conticini,

Khursheed,

Anuja

et al. 2023

Int J of Rheum Dis

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“…During these sessions, participants will monitor heart rates with their Garmin devices (with staff assistance, as needed) to modify activities to maintain heart rates within the prescribed range. Participants will also report an overall rating of perceived exertion (RPE) for each training session (Borg scale [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. Aerobic exercises are individualized by study staff exercise physiologists and physicians to ensure pain-free range of motion (eg, adapting movements for individuals with chronic joint deformities related to RA).…”

Section: Swet-ra Trial Designmentioning

confidence: 99%

“…and inflammatory factors (12,13). Approximately 50% of RA CVD risk can be explained by the following traditional risks: smoking, hypertension, dyslipidemia, impaired glucose handling, and overweight/obesity (14,15).…”

Section: Introductionmentioning

confidence: 99%

“…Current paradigms for the prevention and management of CVD in individuals with RA attempt to address both traditional and inflammatory factors ( 12 , 13 ). Approximately 50% of RA CVD risk can be explained by the following traditional risks: smoking, hypertension, dyslipidemia, impaired glucose handling, and overweight/obesity ( 14 , 15 ).…”

Section: Introductionmentioning

confidence: 99%

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Remotely Supervised Weight Loss and Exercise Training to Improve Rheumatoid Arthritis Cardiovascular Risk: Rationale and Design of the Supervised Weight Loss Plus Exercise Training‐Rheumatoid Arthritis Trial

Andonian

Ross

Zidek

et al. 2023

ACR Open Rheumatology

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Patients with rheumatoid arthritis (RA) remain at an increased risk for cardiovascular disease (CVD) and mortality. RA CVD results from a combination of traditional risk factors and RA‐related systemic inflammation. One hypothetical means of improving overall RA CVD risk is through reduction of excess body weight and increased physical activity. Together, weight loss and physical activity can improve traditional cardiometabolic health through fat mass loss, while also improving skeletal muscle health. Additionally, disease‐related CVD risk may improve as both fat mass loss and exercise reduce systemic inflammation. To explore this hypothesis, 26 older persons with RA and overweight/obesity will be randomized to 16 weeks of a usual care control arm or to a remotely Supervised Weight Loss Plus Exercise Training (SWET) program. A caloric restriction diet (targeting 7% weight loss) will occur via a dietitian‐led intervention, with weekly weigh‐ins and group support sessions. Exercise training will consist of both aerobic training (150 minutes/week moderate‐to‐vigorous exercise) and resistance training (twice weekly). The SWET remote program will be delivered via a combination of video conference, the study YouTube channel, and study mobile applications. The primary cardiometabolic outcome is the metabolic syndrome Z score, calculated from blood pressure, waist circumference, high‐density lipoprotein cholesterol, triglycerides, and glucose. RA‐specific CVD risk will be assessed with measures of systemic inflammation, disease activity, patient‐reported outcomes, and immune cell function. The SWET‐RA trial will be the first to assess whether a remotely supervised, combined lifestyle intervention improves cardiometabolic health in an at‐risk population of older individuals with RA and overweight/obesity.

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“…Although musculoskeletal and overall outcomes have been improving over the last decades in patients with IMIDs, the risk of fatal and nonfatal CVD events remains higher compared to general population. 31 Amongst others, the inability to efficiently perform composite CVD risk assessment in patients with IMIDs using traditional population-based risk tools may have significant input in these observations. The most widely used in the general population cardiovascular risk calculators are the Systematic Coronary Risk Evaluation (SCORE) calculator, 32 and the Framingham Risk Score 33 which has been previously replaced by the American College of Cardiology and American Heart Association (ACC/AHA) Pooled Cohort Equation risk calculator in the 2013 ACC/AHA guidelines on CVD prevention.…”

Section: Assessment Of Cvd Risk In Imidsmentioning

confidence: 99%

Monitoring and Managing Cardiovascular Risk in Immune Mediated Inflammatory Diseases

Anyfanti¹,

Dara²,

Angeloudi³

et al. 2021

JIR

Self Cite

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Cardiovascular disease (CVD) is common in immune-mediated inflammatory diseases (IMIDs) and it is predominately attributed to the interplay between chronic inflammation and traditional CVD risk factors. CVD has significant impact on the survival of patients with IMIDs as it is associated with increased morbidity and mortality. Despite recommendations for monitoring and managing CVD in patients with IMIDs, the individual CVD risk assessment remains problematic as CVD risk calculators for the general population consistently underestimate the risk in patients with IMIDs. Application of new technologies utilizing artificial intelligence techniques have shown promising potential for tailoring predictive medicine to the individual patient, but further validation of their role in clinical decision-making is warranted. In the meantime, individuals with IMIDs should be encouraged to adopt behavioral interventions targeting at modifiable lifestyle CVD risk factors, whereas rheumatologists need to be well aware of the unfavorable effects of antirheumatic medication on various CVD risk factors and outcomes. In the current paper, we aim to provide an overview of current and emerging strategies for mitigating CVD risk in patients with IMIDs, based on a practical approach.

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Cardiovascular comorbidity in rheumatic and musculoskeletal diseases: Where we are and how can we move forward?

Cited by 4 publications

References 23 publications

Comorbidities in idiopathic inflammatory myopathies: Data from the MyoCite cohort

Comorbidities in idiopathic inflammatory myopathies: Data from the MyoCite cohort

Remotely Supervised Weight Loss and Exercise Training to Improve Rheumatoid Arthritis Cardiovascular Risk: Rationale and Design of the Supervised Weight Loss Plus Exercise Training‐Rheumatoid Arthritis Trial

Monitoring and Managing Cardiovascular Risk in Immune Mediated Inflammatory Diseases

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