Slow colonic transit in systemic sclerosis: an objective assessment of risk factors and clinical phenotype

2021 ◽  
Author(s):  
Jenice X. Cheah ◽  
Jamie Perin ◽  
Elizabeth R. Volkmann ◽  
Laura K. Hummers ◽  
Pankaj J. Pasricha ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systemic Sclerosis ◽  
Clinical Phenotype ◽  
Objective Assessment ◽  
Colonic Transit

scholarly journals AORTIC STENOSIS IN PATIENTS WITH SYSTEMIC SCLEROSIS: PREVALENCE, SEVERITY, AND RISK FACTORS

CHEST Journal ◽  
2020 ◽  
Vol 158 (4) ◽  
pp. A135-A136
Author(s):  
Keegan Olmstead ◽  
Sarah Khan ◽  
Julie Windholz ◽  
Christine Zhou ◽  
Yousef Ahmad ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systemic Sclerosis ◽  
Aortic Stenosis

Systemic sclerosis portends increased risk of conduction and rhythm abnormalities at diagnosis and during disease course: A US population-based cohort

2021 ◽  
pp. 239719832110340
Author(s):  
Yasser A Radwan ◽  
Reto D Kurmann ◽  
Avneek S Sandhu ◽  
Edward A El-Am ◽  
Cynthia S Crowson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Pulmonary Hypertension ◽  
Systemic Sclerosis ◽  
Confidence Interval ◽  
Cumulative Incidence ◽  
Disease Onset ◽  
Population Based ◽  
Hazard Ratio ◽  
Conduction Disorders ◽  
Increased Risk

Objectives: To study the incidence, risk factors, and outcomes of conduction and rhythm disorders in a population-based cohort of patients with systemic sclerosis versus nonsystemic sclerosis comparators. Methods: An incident cohort of patients with systemic sclerosis (1980–2016) from Olmsted County, MN, was compared to age- and sex-matched nonsystemic sclerosis subjects (1:2). Electrocardiograms, Holter electrocardiograms, and a need for cardiac interventions were reviewed to determine the occurrence of any conduction or rhythm abnormalities. Results: Seventy-eight incident systemic sclerosis cases and 156 comparators were identified (mean age 56 years, 91% female). The prevalence of any conduction disorder before systemic sclerosis diagnosis compared to nonsystemic sclerosis subjects was 15% versus 7% ( p = 0.06), and any rhythm disorder was 18% versus 13% ( p = 0.33). During a median follow-up of 10.5 years in patients with systemic sclerosis and 13.0 years in nonsystemic sclerosis comparators, conduction disorders developed in 25 patients with systemic sclerosis with cumulative incidence of 20.5% (95% confidence interval: 12.4%–34.1%) versus 28 nonsystemic sclerosis patients with cumulative incidence of 10.4% (95% confidence interval: 6.2%–17.4%) (hazard ratio: 2.57; 95% confidence interval: 1.48–4.45), while rhythm disorders developed in 27 patients with systemic sclerosis with cumulative incidence of 27.3% (95% confidence interval: 17.9%–41.6%) versus 43 nonsystemic sclerosis patients with cumulative incidence of 18.0% (95% confidence interval: 12.3%–26.4%) (hazard ratio: 1.62; 95% confidence interval: 1.00–2.64). Age, pulmonary hypertension, and smoking were identified as risk factors. Conclusion: Patients with systemic sclerosis have an increased risk of conduction and rhythm disorders both at disease onset and over time, compared to nonsystemic sclerosis patients. These findings warrant increased vigilance and screening for electrocardiogram abnormalities in systemic sclerosis patients with pulmonary hypertension.

scholarly journals POS0841 RISK FACTORS OF LOW BONE MINERAL DENSITY IN WOMEN WITH SYSTEMIC SCLEROSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 674.2-675
Author(s):  
A. Efremova ◽  
N. Toroptsova ◽  
N. Demin ◽  
O. Dobrovolskaya ◽  
O. Nikitinskaya
Keyword(s):  
Risk Factors ◽  
Bone Mineral Density ◽  
Systemic Sclerosis ◽  
Postmenopausal Women ◽  
Bone Mineral ◽  
Cumulative Dose ◽  
Premenopausal Women ◽  
C Reactive Protein ◽  
Mineral Density ◽  
Reactive Protein

Background:Chronic inflammatory rheumatic diseases are risk factors of bone loss and fractures. Systemic sclerosis (SSc) has been recognized to be another potential inflammatory joint disease that may affect bone tissue.Objectives:to evaluate bone mineral density (BMD) and risk factors of low BMD in women with SSc.Methods:173 women, among them 110 postmenopausal (median age 60[55,63] years) and 63 premenopausal (median age 35[31,44] years). BMD was measured at lumbar spine (LS), femoral neck (FN) and total hip (TH) by dual energy X-ray absorptiometry (DXA, Hologic 4500A). Low BMD was diagnosed if the T-score was < -1.0 standard deviation (SD) in postmenopausal women and if the Z-score was < -2.0 SD in premenopausal women. The relationship between BMD and SSc patients’ characteristics was evaluated using univariate linear regression analysis.Results:Low BMD was found in 66% patients: 79% - in postmenopausal and 18% - in premenopausal women. Among postmenopausal persons osteoporosis was discovered in 47% and osteopenia – in 32% cases. In postmenopausal woman BMD of LS, FN and TH were associated with body mass index (BMI) (β=0.27, p=0.010; β=0.47, p<0,001 and β=0.45, p<0,001, respectively), duration of glucocorticoids (GCs) using (β=-0.31, p=0.008; β=-0.34, p=0.003 and β=-0.27, p=0.022, respectively); BMD of FN and TH with C-reactive protein (β= -0.32, p=0.016 and β= -0.29, p=0.029, respectively) and LS BMD with current and cumulative GCs dose (β= -0.24, p=0.039 and β= -0.29, p=0.014, respectively). In premenopausal women BMD of LS, FN and TH were associated with BMI (β=0.51, p<0,001; β=0.45, p=0.003 and β=0.47, p=0.002, respectively), duration of GCs using (β= -0.45, p=0.004; β= -0.47, p=0.003 and β= -0.48, p=0.002, respectively) and GCs cumulative dose (β= -0.48, p=0.002; β= -0.51, p=0.001 and β= -0.46, p=0.004, respectively); BMD of FN and TH with 25(ОН)D level (β=0.52, p=0.008 and β=0.54, p=0.005, respectively), and LS BMD with SSc duration (β= -0.44, p=0.004).Conclusion:Low BMD was diagnosed in 66% of women with SSc. Low BMI, GCs cumulative dose and duration of GCs using were independent risk factors for low BMD in both premenopausal and postmenopausal persons. Additional factors as SSc duration and low vitamin D level were found out for premenopausal and current GCs dose and C-reactive protein level for postmenopausal women.Disclosure of Interests:None declared

scholarly journals 30-Day Potentially Preventable Hospital Readmissions In Older Patients: Clinical Phenotype And Health Care Related Risk Factors

2019 ◽  
Vol Volume 14 ◽  
pp. 1851-1858
Author(s):  
Valeria Calsolaro ◽  
Rachele Antognoli ◽  
Giuseppe Pasqualetti ◽  
Chukwuma Okoye ◽  
Ferruccio Aquilini ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Care ◽  
Older Patients ◽  
Clinical Phenotype ◽  
Hospital Readmissions ◽  
Related Risk

scholarly journals AB0407 CARDIOVASCULAR BURDEN IN SYSTEMIC SCLEROSIS: QRISK3 VERSUS FRAMINGHAM FOR RISK ESTIMATION

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1232.1-1232
Author(s):  
M. Di Battista ◽  
S. Barsotti ◽  
A. Della Rossa ◽  
M. Mosca
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Systemic Sclerosis ◽  
High Risk ◽  
General Population ◽  
Risk Score ◽  
Predictive Accuracy ◽  
Risk Estimation ◽  
Cross Sectional

Background:Cardiovascular (CV) diseases, namely myocardial infarction and stroke, are not among the most known and frequent complications of systemic sclerosis (SSc), but there is growing evidence that SSc patients have a higher prevalence of CV diseases than the general population [1].Objectives:To compare two algorithms for CV risk estimation in a cohort of patients with SSc, finding any correlation with clinical characteristics of the disease.Methods:SSc patients without previous myocardial infarction or stroke were enrolled. Traditional CV risk factors, SSc-specific characteristics and ongoing therapies were assessed. Framingham and QRISK3 algorithms were then used to estimate the risk of develop a CV disease over the next 10 years.Results:Fifty-six SSc patients were enrolled. Framingham reported a median risk score of 9.6% (IQR 8.5), classifying 24 (42.9%) subjects at high risk, with a two-fold increase of the mean relative risk in comparison to general population. QRISK3 showed a median risk score of 15.8% (IQR 19.4), with 36 (64.3%) patients considered at high-risk. Both algorithms revealed a significant role of some traditional risk factors and a noteworthy potential protective role of endothelin receptor antagonists (p=0.003). QRISK3 was also significantly influenced by some SSc-specific characteristics, as limited cutaneous subset (p=0.01), interstitial lung disease (p=0.04) and non-ischemic heart involvement (p=0.03), with the first two that maintain statistically significance in the multivariate analysis (p=0.02 for both).Conclusion:QRISK3 classifies more SSc patients at high-risk to develop CV diseases than Framingham, and it seems to be influenced by some SSc-specific characteristics. If its predictive accuracy were prospectively verified, the use of QRISK3 as a tool in the early detection of SSc patients at high CV risk should be recommended.References:[1]Ngian GS, Sahhar J, Proudman SM, Stevens W, Wicks IP, Van Doornum S. Prevalence of coronary heart disease and cardiovascular risk factors in a national cross-sectional cohort study of systemic sclerosis. Ann Rheum Dis. 2012;71:1980-3.Disclosure of Interests:None declared

Clinical phenotype and genetic risk factors for bipolar disorder with binge eating: an update

2019 ◽  
Vol 19 (9) ◽  
pp. 867-879 ◽  
Author(s):  
Alfredo B. Cuellar-Barboza ◽  
Stacey J. Winham ◽  
Joanna M. Biernacka ◽  
Mark A. Frye ◽  
Susan L. McElroy
Keyword(s):  
Risk Factors ◽  
Bipolar Disorder ◽  
Binge Eating ◽  
Genetic Risk ◽  
Clinical Phenotype ◽  
Genetic Risk Factors
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