Autoimmune-mediated glucose intolerance in a mouse model of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by the production of autoantibodies against self-antigens such as double-stranded DNA and phospholipids. Classical comorbidities of SLE include glomerulonephritis, infection, cardiovascular disease, arthritis, skin disorders, and neurological disease. In addition to these classical comorbidities, there is emerging evidence that SLE patients are at higher risk of developing insulin resistance and other components of the metabolic syndrome. Visceral adipose tissue inflammation is a central mediator of insulin resistance in the obese setting, but the mechanism behind the pathogenesis of metabolic disease in the SLE patient population is unclear. We hypothesize that lupus-associated changes in the adaptive immune system are associated with disruption in glucose homeostasis in the context of SLE. To test this hypothesis, we assessed the metabolic and immunological phenotype of SLE-prone B6.SLE mice. B6.SLE mice fed a low-fat diet had significantly worsened glucose tolerance, increased adipose tissue insulin resistance, increased ß-cell insulin secretion, and increased adipocyte size compared with their respective B6 controls. Independently of diet, B cells isolated from the white adipose tissue of B6.SLE mice were skewed toward IgG production, and the level of IgG1 was elevated in the serum of SLE-prone mice. These data show that B6.SLE mice develop defects in glucose homeostasis even when fed a low-fat diet and suggest that B cells may play a role in this metabolic dysfunction.

Adherence to chronic opioid therapy prescribing guidelines in a primary care clinic.

OBJECTIVE: Characterize primary care patients prescribed opioids for chronic noncancer pain (CNCP), explore guideline-recommended opioid-monitoring practices, and investigate predictors of pain agreements. DESIGN: Retrospective chart review. SETTING: Primary care clinic at a tertiary academic medical center. PATIENTS: Adults prescribed chronic opioids (three or more monthly prescriptions within a year) for CNCP between April 1, 2014 and April 1, 2015. Patients without CNCP served as controls. MAIN OUTCOME MEASURE: Patient demographics, medical diagnoses, tobacco status, provider status, documentation of guideline-recommended opioid-monitoring practices, pain agreement status, and opioid prescription. Univariate statistics were used to explore differences in patient demographics, comorbidities, and guideline-recommended opioid-monitoring practices by chronic pain and pain agreement status. Logistic regression was used to investigate predictors of agreement status. RESULTS: The clinic had 834 (9 percent) patients on chronic opioids, with 335 on a pain agreement. Documentation of opioid-monitoring practices was lacking. Logistic regression indicated that patients were significantly more likely to be on an agreement if they were Caucasian (adjusted odds ratio [OR] 2.17 [95% CI 1.41, 3.39]), had a baseline urine drug screen (adjusted OR 10.72 [95% CI 6.16, 19.41]), were prescribed a schedule II controlled medication (adjusted OR 11.92 [95% CI 6.93, 21.62]), and had risk assessed to some degree (adjusted OR 3.06 [95% CI 1.90, 4.96]). CONCLUSIONS: Aside from race, most patient characteristics were not predictive of pain agreement implementation. However, controlled medication of higher schedules and the use of certain guideline-recommended practices were associated with an agreement. Studies are needed to examine whether pain agreement or guideline-adherence influence clinical outcomes.