International Guideline Adherence in Girls with Turner Syndrome: Multiple Subspecialty Clinics Versus Coordinated Multidisciplinary Clinic.

OBJECTIVE: To evaluate the 2016 Cincinnati International Turner syndrome (TS) consensus guideline adherence within our pediatric tertiary referral center and determine if patients managed in our single-day, coordinated multidisciplinary clinic (MDC) format showed superior adherence rates when compared with those managed outside our MDC format. METHODS: We retrospectively reviewed the charts of patients with TS followed at our center from January 1, 2018, to April 30, 2020. The individual and overall adherence rates of 9 age-appropriate screening recommendations were evaluated along with rates of TS comorbidities within our cohort. RESULTS: A total of 111 girls met the study criteria. Sixty-eight were managed in the MDC and 43 were managed outside the MDC. Only 42% of all the girls met all 9 evaluated age-appropriate screening recommendations, of 47 girls, 33 (70%) were managed in MDC compared with 14 (30%) who were managed in the non-MDC. Girls managed in the MDC had higher screening adherence rates versus non-MDC girls for 7 of the 9 evaluated screenings with especially large differences noted for thyroid stimulating hormone (95% vs 78%, P = .034), auditory evaluation (97% vs 65%, P < .001), and HgA1c levels (82% vs 54%, P = .014). CONCLUSION: Girls managed in the MDC format showed higher rates of screening guideline adherence, both overall and with multiple specific screening tests, than those managed outside the MDC format. Overall guideline adherence remained low (42%), highlighting the need for continued optimization and improvement in guideline adherence in this unique subset of the population.

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review.

BACKGROUND: Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies. METHODS: We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment. RESULTS: Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation. CONCLUSIONS: Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.

Islet autoantibodies are markers found in the blood when insulin-producing cells in the pancreas become damaged and can be used to predict future development of type 1 diabetes. We evaluated published literature to determine whether characteristics of islet antibodies (type, levels, numbers) could improve prediction and help understand differences in how individuals with type 1 diabetes respond to treatments. We found existing evidence shows that islet autoantibody type and number are most useful to predict disease progression before diagnosis. In addition, the age when islet autoantibodies first appear strongly influences rate of progression. These findings provide important information for patients and care providers on how islet autoantibodies can be used to understand future type 1 diabetes development and to identify individuals who have the potential to benefit from intervention or prevention therapy.