Person:

Solomon, Daniel

Introduction: Obesity's association with hand osteoarthritis cannot be fully explained by mechanical loading. We examined the relationship between adipokines and radiographic hand osteoarthritis severity and pain. Methods: In a pilot study of 44 hand osteoarthritis patients (39 women and 5 men), serum adipokine concentrations and hand x-ray Kallman-scores were analyzed using linear regression models. Secondary analyses examined correlates of hand pain. Results: The cohort had a mean age of 63.5 years for women and 72.6 for men; mean (standard deviation) Kallman-scores were 43.3(17.4) for women and 46.2(10.8) for men. Mean body-mass-index was 30 kg/m2 for women and men. Mean leptin concentration was 32.2 ng/ml (women) and 18.5 ng/ml (men); mean adiponectin-total was 7.9 ng/ml (women) and 5.3 ng/ml (men); mean resistin was 7.3 ng/ml (women) and 9.4 ng/ml (men). No association was found between Kallman-scores and adipokine concentrations (R2 = 0.00–0.04 unadjusted analysis, all p-values>0.22). Secondary analyses showed mean visual-analog-scale pain of 4.8(2.4) for women and 6.6(0.9) for men. Leptin, BMI, and history of coronary artery disease were found to be associated with visual-analog-scale scores for chronic hand pain (R2 = 0.36 unadjusted analysis, p-values≤0.04). Conclusion: In this pilot study, we found that adipokine serum concentrations were not associated with hand osteoarthritis radiographic severity; the most important correlates of joint damage were age and disease duration. Leptin serum concentration, BMI, and coronary artery disease were associated with the intensity of chronic hand OA pain.

Objective: Gout patients have a high burden of co-morbid conditions including diabetes mellitus (DM), chronic kidney disease (CKD), and cardiovascular disease (CVD). We sought to evaluate the association between changes in serum uric acid (SUA) levels over time and the risk of incident DM, CVD, and renal function decline in gout patients. Methods: An observational cohort study was conducted among enrollees of private health insurance programs in the US between 2004 and 2015. Gout patients were included on the index date of a SUA measurement ≥6.8 mg/dl. The exposure of interest was cumulative change in SUA levels from baseline. Hazard ratios (HR) and 95% confidence intervals (CI) for incident DM, incident CVD, and renal function decline (≥30% reduction in glomerular filtration rate) were derived using marginal structural models with stabilized inverse probability weights accounting for baseline confounders (age, gender, co-morbidities, co-medications) and time-varying confounders (serum creatinine, blood urea nitrogen, glycated hemoglobin). Results: Among 26,341 patients with gout, the average age was 62, 75% were men, and the median baseline SUA was 8.6 mg/dl (interquartile range 7.7 to 9.5). The incidence rates/100 person-years (95% CI) were 1.63 (1.51–1.75) for DM, 0.77 (0.70–0.84) for CVD, and 4.32 (4.14–4.49) for renal function decline. The adjusted HR (95% CI) per 3 mg/dl reduction in SUA, corresponding on average to achieving the target level of <6 mg/dl in this population, was 1.04 (0.92–1.17) for DM, 1.07 (0.89–1.29) for CVD, and 0.85 (0.78–0.92) for renal function decline. Conclusions: Reduction in SUA in patients with gout may be associated with a reduced risk of renal function decline, but not with DM or CVD.

Background: Elevated serum uric acid (SUA) levels have been independently associated with cardiovascular disease. Stress myocardial perfusion positron emission tomography (PET) allows for measurement of absolute myocardial blood flow (MBF) and quantification of global left ventricular coronary flow reserve (CFR). A CFR <2.0 is considered impaired coronary vascular function, and it is associated with increased cardiovascular risk. We evaluated the relationship between SUA and PET-measured markers of coronary vascular function. Methods: We studied adults undergoing a stress myocardial perfusion PET on clinical grounds (1/2006-3/2014) who also had ≥1 SUA measurement within 180 days from the PET date. Multivariable linear regression estimated the association between SUA and PET-derived MBF and CFR. We also stratified analyses by diabetes status. Results: We included 382 patients with mean (SD) age of 68.4 (12.4) years and mean (SD) SUA level of 7.2 (2.6) mg/dl. 36% were female and 29% had gout. Median [IQR] CFR was reduced at 1.6 [1.2, 2.0] and median [IQR] stress MBF was 1.5 [1.1, 2.1] ml/min/g. In the adjusted analysis, SUA was inversely associated with stress MBF (β = -0.14, p = 0.01) but not with CFR. Among patients without diabetes (n = 215), SUA had a negative association with CFR (β = -0.15, p = 0.02) and stress MBF (β = -0.19, p = 0.01) adjusting for age, sex, extent of myocardial scar and ischemia, serum creatinine and gout. In diabetic patients (n = 167), SUA was not associated with either CFR or MBF. Conclusions: In this cross-sectional study, higher SUA is modestly associated with worse CFR and stress MBF among patients without diabetes.

Introduction: Numerous studies across different health systems have documented that many patients with rheumatoid arthritis (RA) do not receive disease-modifying anti-rheumatic drugs (DMARDs). Relatively little is known about correlates of DMARD use and whether there are socioeconomic and demographic disparities. We examined DMARD use during 2001 to 2006 in the Medicare Current Beneficiary Survey (MCBS), a longitudinal US survey of randomly selected Medicare beneficiaries. Methods: Participants in MCBS with RA were included in the analyses, and DMARD use was based on an in-home assessment of all medications. Variables included as potential correlates of DMARD use in weighted regression models included race/ethnicity, insurance, income, education, rheumatology visit, region, age, gender, comorbidity index, and calendar year. Results: The cohort consisted of 509 MCBS participants with a diagnosis code for RA. Their median age was 70 years, 72% were female, and 24% saw a rheumatologist. Rates of DMARD use ranged from 37% among those <75 years of age to 25% of those age 75 to 84 and 4% of those age 85 and older. The multivariable adjusted predictors of DMARD use include: visit with a rheumatologist in the prior year (odds ratio, OR, 7.74, 95% CI, 5.37, 11.1) and older patient age (compared with <75 years, ages 75 to 84, OR 0.58, 95% CI 0.37, 0.92, and 85 and over, OR 0.09, 95% CI 0.02, 0.31). In those without a rheumatology visit, lower income and older age were associated with a significantly reduced probability of DMARD use; no association of DMARD use with income or age was observed for subjects seen by rheumatologists. Race and ethnicity were not significantly associated with receipt of DMARDs. Conclusions: Among individuals not seeing rheumatologists, lower income and older age were associated with a reduced probability of DMARD use.

The objective of this work was to assess the convergent validity of a previously developed rheumatoid arthritis medical records-based index of severity (RARBIS) by comparing it with the 28-joint Disease Activity Score (DAS28). This study was conducted in subjects within the Brigham and Women's Hospital Rheumatoid Arthritis Sequential Study (BRASS). We selected 100 patients with rheumatoid arthritis (RA) from the BRASS with DAS28 scores equally distributed in four quartiles. The medical records were reviewed to calculate the RARBIS, which includes indicators from the following categories: prior surgical history, radiologic and laboratory findings, clinical and functional status, and extra-articular manifestations. The Spearman correlation between the RARBIS and the DAS28 was assessed in the total study population and in relevant subgroups. We re-weighted on subscales and recalculated the RARBIS score. This was performed based on findings of correlations between the DAS28 and subscales; and also the result from a multiple linear regression with the DAS28 (as a dependent variable) and five subscales (as independent variables). The mean RARBIS was 4.36 (range 0–11). Among the total study cohort, the RARBIS was moderately correlated with the DAS28 (r = 0.41, 95% confidence interval [CI] 0.23–0.56). In subgroup analyses, including age, gender, rheumatoid factor status, and disease duration, we found no statistically significant differences in the correlations. After re-weighting, the correlation between the RARBIS and the DAS28 was somewhat improved (r = 0.48, 95% CI 0.31–0.62). In conclusion, the RARBIS correlated moderately well with the DAS28 in this population. The RARBIS has both face and convergent validity for patients with RA and relevant subgroups and may have application for medical records studies in patients with RA.