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Introduction: Diabetic peripheral neuropathy (DPN) causes morbidity and affects the quality of life. Before diabetes diagnosis, neuropathic damage may be present. Sudoscan provides accurate measurement of the sudomotor function. This study aimed to assess the abnormalities detected by Sudoscan, offered estimates of DPN prevalence, and investigated the relationship between metabolic and clinical parameters. Additionally, we evaluated the diagnostic accuracy of the Sudoscan compared with monofilament and tuning fork tests for detecting DPN., Research Design and Methods: Cross-sectional descriptive study including patients with type 2 diabetes for <5 years since diagnosis. We investigated the presence of DPN using a 128 Hz tuning fork test, the 10 g monofilament, and the sudomotor dysfunction in feet using Sudoscan. We compared patients with and without alterations in the Sudoscan. A logistic regression model analyzed variables independently associated with sudomotor dysfunction., Results: From 2013 to 2020, 2243 patients were included, 55.1% women, age 51.8 years, and 17.1% with normal weight. Monofilament tests and/or tuning fork examination were abnormal in 29% (95% CI 0.23% to 0.27%) and 619 patients (27.6%, 0.25% to 0.29%) had sudomotor alterations. In logistic regression analysis, age (β=1.01, 0.005-1.02), diastolic blood pressure (β=0.98, 0.96-0.99), heart rate (β=1.01, 1.00-1.02), glucose (β=1.00, 1.00-1.03), albuminuria (β=1.001, 1.000-1.001), beta-blockers=1.98, 1.21-3.24) and fibrate use=0.61, 0.43-0.87) were associated with sudomotor dysfunction. The AUC (area under the curve) for Sudoscan was 0.495 (0.469-0.522), with sensitivity and specificity of 24% and 71%, respectively., Conclusion: The Sudoscan identified an important proportion of patients with dysfunction, allowing prompt intervention to decrease the risk for complications., Trial Registration Number: NCT02836808., Competing Interests: Competing interests: CAA-S is part of the Editorial Board of BMJ Open Diabetes Research and Care., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Introduction: To assess the cost-effectiveness of a multidisciplinary and comprehensive innovative diabetes care program (CAIPaDi) versus usual treatment in public health institutions., Research Design and Methods: Using a cost-effectiveness analysis, we compared the CAIPaDi program versus usual treatment given in Mexican public health institutions. The analysis was based on the IQVIA Core Diabetes Model, a validated simulation model used to estimate long-term clinical outcomes. Data were prospectively obtained from the CAIPaDi program and from public databases and published papers. Health outcomes were expressed in terms of life-years gained and quality-adjusted life years (QALYs). Health and economic outcomes were estimated from a public perspective and discounted at 5% per year over a 20-year horizon. Costs are reported in US dollars (US$) of 2019. A probabilistic sensitivity analysis was performed using life-years gained and QALYs., Results: The CAIPaDi costs on average US$559 (95% CI: -$879 to -$239) less than the usual treatment (95% CI: -$879 to -$239) and produced a difference in mean life-years gained (0.48, 95% CI: 0.45 to 0.52) and mean QALYs (1.43, 95% CI: 1.40 to 1.46). The cost-effectiveness ratio resulted in a saving per life-year gained of -US$1155 (95% CI: -$1962 to -$460). Mean differences in QALYs resulted in a saving per QALY of -US$735 (95% CI: -$1193 to -$305). Probabilistic sensitivity analysis proved the results are robust on both life-years gained and QALYs., Conclusions: CAIPaDi has a better cost-effectiveness ratio than the usual therapy in Mexican public health institutions., Competing Interests: Competing interests: CAA-S is an editorial board member for the BMJ Open Diabetes Research & Care Journal. There are no other potential conflicts of interest relevant to this article., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Lipid control is essential in type 2 diabetes mellitus (T2DM). The aim of this study is to investigate factors associated with lipid therapy adherence and achievement of goals in real-life setting among patients with recently diagnosed T2DM., Research Design and Methods: This is a longitudinal analysis in a center of comprehensive care for patients with diabetes. We include patients with T2DM, <5 years of diagnosis, without disabling complications (eg, amputation, myocardial infarct, stroke, proliferative retinopathy, glomerular filtration rate <60 mL/min/m 2 ) and completed 2-year follow-up. The comprehensive diabetes care model includes 9 interventions in 4 initial visits and annual evaluations. Endocrinologists follow the clinic's guideline and adapt therapy to reach risk-based treatment goal. The main outcome measures were the proportion of patients meeting low-density lipoprotein cholesterol (c-LDL) (<100 mg/dL) and triglycerides (<150 mg/dL) and proportion of patients taking statin, fibrate or combination at baseline, 3 months and annual evaluations., Results: We included 288 consecutive patients (54±9 years, 53.8% women), time since T2DM diagnosis 1 (0-5) year. Baseline, 10.8% patients were receiving statin therapy (46.5% moderate-intensity therapy and 4.6% high-intensity therapy), 8.3% fibrates and 4.2% combined treatment. The proportion of patients with combined treatment increased to 41.6% at 3 months, decreased to 20.8% at 1 year and increased to 38.9% at 2 years of evaluation. Patients receiving treatment met LDL and triglycerides goals at 3 months (17% vs 59.7%, relative ratio (RR)=0.89, 95% CI 0.71 to 1.12), at 1 year (17% vs 26.7%, RR=0.62, 95% CI 0.41 to 0.95) and at 2 years (17% vs 29.9%, RR=0.63, 95% CI 0.43 to 0.93). Main reasons for medication suspension: patient considered treatment was not important (37.5%) and other physician suspended treatment (31.3%)., Conclusion: 88.2% of patients with T2DM required lipid-lowering drugs. Education for patients and physicians is critical to achieve and maintain diabetes goals., Trial Registration Number: NCT02836808., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings., Research Design and Methods: We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999-2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup., Results: SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89)., Conclusions: Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications., Competing Interests: Competing interests: JPB-L, AV-V and NEA-V are enrolled at the PECEM program of the Faculty of Medicine at UNAM. JPB-L and AV-V are supported by CONACyT., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)