Relationships Between SLE Disease Activity and Damage, Depression and Work Productivity Impairment in the Georgians Organized Against Lupus Study

Systemic lupus erythematous (SLE) is an autoimmune and inflammatory disease that can affect all organs of the body. The purpose of this quantitative cross-sectional study was to examine SLE-related issues associated with depression and work-productivity impairment, and to assess if depression mediated the relationship between SLE disease activity and damage and work-productivity impairment. Participants were 257 residents of the state of Georgia in the United States with SLE and were recruited from the Georgians Organized Against Lupus study. Bandura\u27s social cognitive theory was the guiding theoretical framework of the study. Findings showed that the majority of participants worked full time (78.2%), identified as Black (72.8%), female (94.2%), above poverty level (77.4%), and had private health insurance (70.0%). Mean and median score results indicated that participants missed, on average, slightly less than half a day of work every 7 days, and had mild-to-moderate levels of work productivity impairment. Mean and median scores showed that participants reported mild-to-moderate levels of SLE disease activity and damage and depression. Linear regression results revealed significant relationships between SLE activity and damage and work productivity impairment. Hierarchical linear regression for mediation findings indicated that depression partially mediated the relationship between SLE disease activity and damage and work productivity impairment. The findings from this study might help to increase stakeholder awareness of SLE disease activity and damage and SLE effects on depression and work functioning

Relationships between SLE Disease Activity and Damage, Depression and Work Productivity Impairment in the Georgians Organized against Lupus Study

Systemic lupus erythematous (SLE) is an autoimmune and inflammatory disease that can affect all organs of the body. The purpose of this quantitative cross-sectional study was to examine SLE-related issues associated with depression and work-productivity impairment, and to assess if depression mediated the relationship between SLE disease activity and damage and work-productivity impairment. Participants were 257 residents of the state of Georgia in the United States with SLE and were recruited from the Georgians Organized Against Lupus study. Bandura’s social cognitive theory was the guiding theoretical framework of the study. Findings showed that the majority of participants worked full time (78.2%), identified as Black (72.8%), female (94.2%), above poverty level (77.4%), and had private health insurance (70.0%). Mean and median score results indicated that participants missed, on average, slightly less than half a day of work every 7 days, and had mild-to-moderate levels of work productivity impairment. Mean and median scores showed that participants reported mild-to-moderate levels of SLE disease activity and damage and depression. Linear regression results revealed significant relationships between SLE activity and damage and work productivity impairment. Hierarchical linear regression for mediation findings indicated that depression partially mediated the relationship between SLE disease activity and damage and work productivity impairment. The findings from this study might help to increase stakeholder awareness of SLE disease activity and damage and SLE effects on depression and work functioning

Addressing Lupus Health Disparities: The MONARCAS Community and Academic Collaborative Program

Purpose: The Centers for Disease Control (CDC) Popular Opinion Leader (POL) model was implemented in a lupus education program (MONARCAS) for the Latino community. The program aim was to increase lupus awareness by training high school students, community health workers, and parents. Methods: A curriculum was developed training POLs to disseminate concepts about lupus signs and symptoms. Pre- and post-program questions assessed lupus knowledge and message dissemination. Results: POL groups represented distinct demographic characteristics with Spanish or English language dominance. POLs reported increased lupus knowledge and program satisfaction. Conclusions: Future program goals should aim to increase understanding and improving access to care for Latino communities affected by lupus

Evaluation of structured data from electronic health records to identify clinical classification criteria attributes for systemic lupus erythematosus

Objective Our objective was to develop algorithms to identify lupus clinical classification criteria attributes using structured data found in the electronic health record (EHR) and determine whether they could be used to describe a cohort of people with lupus and discriminate them from a defined healthy control cohort.Methods We created gold standard lupus and healthy patient cohorts that were fully adjudicated for the American College of Rheumatology (ACR), Systemic Lupus International Collaborating Clinics (SLICC) and European League Against Rheumatism/ACR (EULAR/ACR) classification criteria and had matched EHR data. We implemented rule-based algorithms using structured data within the EHR system for each attribute of the three classification criteria. Individual criteria attribute and classification criteria algorithms as a whole were assessed over our combined cohorts and the overall performance of the algorithms was measured through sensitivity and specificity.Results Individual classification criteria attributes had a wide range of sensitivities, 7% (oral ulcers) to 97% (haematological disorders) and specificities, 56% (haematological disorders) to 98% (photosensitivity), but all could be identified in EHR data. In general, algorithms based on laboratory results performed better than those primarily based on diagnosis codes. All three classification criteria systems effectively distinguished members of our case and control cohorts, but the SLICC criteria-based algorithm had the highest overall performance (76% sensitivity, 99% specificity).Conclusions It is possible to characterise disease manifestations in people with lupus using classification criteria-based algorithms that assess structured EHR data. These algorithms may reduce chart review burden and are a foundation for identifying subpopulations of patients with lupus based on disease presentation to support precision medicine applications