Differences in Utilization of Nonvideo Telemedicine Visits for Dermatologic Concerns in Underserved Populations During the COVID-19 Pandemic.

Background: Usage of telemedicine for virtual dermatology care during the COVID-19 pandemic on a national scale is poorly characterized, particularly for nonvideo encounters. Objective: We sought to compare utilization of telephone and asynchronous virtual care for dermatologic concerns 3 months before (December 2019-February 2020) and during the pandemic (March-May 2020) across patient populations. Methods: A retrospective study was performed using a national claims database with >280 million patients within the COVID-19 Research Database to identify monthly telephone and asynchronous virtual visits by diagnosis, age, income, and patient race/ethnicity. Results: Although overall visits for dermatologic concerns decreased by 27.2% during the pandemic, telephone and asynchronous visits increased significantly. Patients most likely to use telephone visits during the pandemic were of older age (relative risk ratio [RRR] = 1.043, p < 0.001), African American race (RRR = 2.03, p < 0.001), and household income <$29,000 (RRR = 1.51, p < 0.001). Limitations: Racial and ethnic data were available for 39.04% of patients and income data for 38.1% of patients. Conclusions: Underserved populations including African Americans, elderly, and low-income patients were more likely to utilize telephone formats during the pandemic. Further studies are needed to determine the reasons for these observed differences and whether there is differential quality between nonvideo and video telemedicine encounters to ensure that all patients are given equal access to the highest quality of virtual care.

Towards gender equity in artificial intelligence and machine learning applications in dermatology.

There has been increased excitement around the use of machine learning (ML) and artificial intelligence (AI) in dermatology for the diagnosis of skin cancers and assessment of other dermatologic conditions. As these technologies continue to expand, it is essential to ensure they do not create or widen sex- and gender-based disparities in care. While desirable bias may result from the explicit inclusion of sex or gender in diagnostic criteria of diseases with gender-based differences, undesirable biases can result from usage of datasets with an underrepresentation of certain groups. We believe that sex and gender differences should be taken into consideration in ML/AI algorithms in dermatology because there are important differences in the epidemiology and clinical presentation of dermatologic conditions including skin cancers, sex-specific cancers, and autoimmune conditions. We present recommendations for ensuring sex and gender equity in the development of ML/AI tools in dermatology to increase desirable bias and avoid undesirable bias.

Cutaneous lupus erythematosus and cardiovascular disease: current knowledge and insights into pathogenesis.

Multiple autoinflammatory diseases, including psoriasis, psoriatic arthritis, and systemic lupus erythematosus, have been linked to increased risk of cardiovascular disease. Inflammation is known to play a key role in the pathogenesis of atherosclerosis, thus the contribution of systemic immune dysregulation, which characterizes such inflammatory conditions, towards the development of cardiovascular disease has garnered considerable interest. Cutaneous lupus erythematosus (CLE) is a chronic inflammatory skin disease, but risk of cardiovascular disease amongst patients with cutaneous lupus is less well known. Observational studies, including those of large nationwide cohorts, have been conducted to examine cardiovascular disease risk in CLE, with varying findings. As with other inflammatory diseases, immunologic mechanisms may provide plausible causal links between CLE and cardiovascular risk. On a macrolevel, several disease-related characteristics may also contribute to cardiovascular risk amongst CLE patients. This represents an area of research that should be prioritized, as understanding cardiovascular disease risk has important clinical implications for CLE patients.

Development of a working core outcome set for cutaneous lupus erythematosus: a practical approach to an urgent unmet need.

OBJECTIVE: The lack of standardised outcomes and outcome measures for cutaneous lupus erythematosus (CLE) represents a substantial barrier to clinical trial design, comparative analysis and approval of novel investigative treatments. We aimed to develop a working core outcome set (COS) for CLE randomised controlled trials and longitudinal observational studies. METHODS: We conducted a multistage literature review of CLE and SLE studies to generate candidate domains and outcome measures. Domains were narrowed to a working core domain set. Outcome measures for core domains were identified and examined. RESULTS: Proposed core domains include skin-specific disease activity and damage, investigator global assessment (IGA) of disease activity, symptoms (encompassing itch, pain and photosensitivity), health-related quality of life (HRQoL) and patient global assessment (PtGA) of disease activity. Recommended physician-reported outcome measures include the Cutaneous Lupus Erythematous Disease Area and Severity Index (CLASI) and Cutaneous Lupus Activity IGA (CLA-IGA). For the domains of symptoms, HRQoL and PtGA of disease activity, we were unable to recommend one clearly superior instrument. CONCLUSION: This work represents a starting point for further refinement pending formal consensus activities and more rigorous evaluations of outcome measure quality. In the interim, the proposed working COS can serve as a much-needed guide for upcoming CLE clinical trials.

Hyaluronidase Injections for Oral Microstomia in Systemic Sclerosis and Mixed Connective Tissue Disease.

This case series evaluates hyaluronidase for oral microstomia in a cohort of patients with autoimmune sclerosing disease.