Comparison of Two Electronic Systems for Obtaining Diabetes Care Indicators in Clinical Practice.

We compared the completeness of data captured by physicians in a diabetes outpatient clinic using a general electronic health record system versus one that was specifically geared to diabetes. Use of a diabetes-oriented data system was found to allow for greater capture of crucial variables required for diabetes care than a general electronic record and was well accepted by health care providers.

Risk Factors Associated with Diabetic Retinopathy with and without Macular Edema in Recently Diagnosed Patients with Type 2 Diabetes.

Purpose: To evaluate the risk factors associated with diabetic macular edema (DME) in patients with a recent type 2 diabetes mellitus (T2DM) diagnosis. Patients and Methods: We conducted a case-control study at a third-level hospital in Mexico City. We enrolled patients ≥18 years old, with T2DM less than five years of diagnosis, without disabling complications, and non-smokers. The control group was patients with diabetic retinopathy and without macular edema (DR-DME). Cases were patients with DR+DME. We measured fasting glucose, creatinine, lipid profile, urinary albumin/creatinine ratio (ACR), and HbA1c. An ophthalmological examination consisted of visual acuity measurement, digital three-field fundus photography with an automatic non-mydriatic camera, slit lamp, and Optical coherence tomography (OCT) examination. Results: 183 and 61 patients with DR-DME and DR+DME, respectively, were included in the analysis. The prevalence of mild DR was higher in the DR-DME group, but the frequencies of moderate and severe retinopathy were higher in the DR+DME group. Patients in the DR-DME group had better vision than those in the DR+DME group. Logistic regression analysis revealed that age (OR, 1.07), HbA1c (OR, 1.19), and Albumin-to-Creatinine Ratio (ACR) > 30 mg/g (OR, 3.37) were associated with an increased possibility of DME compared to DR-DME. Conclusion: Our study provides insights into the association between risk factors and DME. We found a statistically strong association between HbA1c levels, age, and ACR. Patients with poor metabolic control should undergo an extensive medical examination to screen for DME, which may be related to the chronicity of DM and renal damage.

Coping and risk perception during the COVID-19 pandemic in type 2 diabetes: Does it influence metabolic control?

Diabetes and poor glycemic control are significant predictors of severity and death in the COVID-19 disease. The perception of this risk in individuals with type 2 diabetes (T2D) could modify coping styles, leading to behaviors associated with better self-care and metabolic control. Theoretically, active coping is associated with better glycemic control in patients with T2D. Nonetheless, information during extreme risk like the COVID-19 pandemic is still limited. Our objective was to evaluate the association between coping styles and risk perception in the COVID-19 pandemic and the change in metabolic parameters. This is a prospective study that included individuals with T2D treated in a tertiary care center during the COVID-19 outbreak who returned to follow-up one year later. We assessed coping styles and risk perception with the Extreme Risk Coping Scale and the risk perception questionnaire. Clinical characteristics and metabolic parameters were registered in both visits. Groups were compared using Kruskal Wallis tests, and changes in metabolic parameters were assessed with Wilcoxon rank sum tests. Our sample included 177 participants at baseline, and 118 concluded the study. Passive coping was more frequent in women. Low-risk perception was associated with higher age, lower psychiatric comorbidities, and lower frequency of psychiatric treatment compared with other risk perception groups. Patients with active coping plus high-risk perception did not have a change in metabolic parameters at follow-up, whereas patients with other coping styles and lower risk perception had an increase in total cholesterol, LDL-cholesterol, and triglycerides. There were no differences by coping group or by risk perception in glycemic control.

Comparison of Metabolic, Lifestyle and Mental Health Parameters in People with Diabetes and Relatives with and without Family Support.

Purpose: To analyze and compare metabolic, lifestyle and mental health parameters in relatives and people-with-T2DM (PDM) with and without support. Patients and Methods: We included 160 patients with <5 years of diagnosis of T2DM, without disabling complications, and non-smokers, attending a multidisciplinary program for diabetes control, and their accompanying relatives. If the patients or relatives abandoned the program, we contacted them and asked to take laboratory tests and answer surveys regarding anxiety, depression, and perception of their family support. Variables distribution was assessed with the Kolmogorov-Smirnov test. We used ANOVA or Kruskal Wallis Tests, according to variable distribution. Frequencies and percentages are used for categorical values and analyzed with a chi-square test. We separated the participants in four groups: relatives with and without support and PDM with and without support. Results: We included 160 participants, age 51±10, and 54.3% women. Total cholesterol (188±36 vs 204±43 vs 170±34 vs 181±35 mg/dL, p=0.001), LDL-cholesterol (113±35 vs 125±27 vs 101 ±30 vs 109±29, p=0.008), and non-HDL cholesterol (143±32 vs 154 ±30 vs 129±33 vs 135±35 mg/dL, p=0.010) were higher in the group without support. Although patients without family support had lower values, they did not achieve metabolic goals. Weight (75±17 vs 77±19 vs 74.2±10.5 vs 90.2±17.3 kg) and body mass index (28.9±4.8 vs 30.1±4.7 vs 27.4±3.3 vs 33±4.3 kg/m2) were higher in PDM without family support (p<0.001 for both). Conclusion: Support in PDM and their families is important in metabolic control. However, raising awareness among family members to screen for diabetes and changes in lifestyle are points to improve. Including the evaluation of social and family support will allow a more complete assessment to identify barriers to achieving goals.

Long-Term Effects of Anxiety on the Metabolic Control of Recently Diagnosed Type 2 Diabetes Patients: Results from the CAIPaDi Cohort Study.

Introduction: Anxiety disorders (AXD) are among the most prevalent mental health conditions in patients with type 2 diabetes (T2D). Previous data have established an association of other psychiatric conditions with poor metabolic control and increased odds of diabetes-related complications. Nonetheless, follow-up information about the effects of AXD on the metabolic control of patients with TD2 is still limited. Objective: Evaluate the effects of AXD on the metabolic parameters of patients with T2D over 12 months of follow-up in a multidisciplinary comprehensive care model. Methods: Prospective study of T2D subjects enrolled in a comprehensive care program with follow-up at 3 and 12 months of treatment. Patients were assessed using the Mini-International Neuropsychiatric Interview and the Hospital Anxiety and Depression Scale (HADS). We registered clinical and metabolic characteristics from each visit. Metabolic parameters over time were analyzed with a mixed model of repeated measures using AXD and time as interaction variables. Results: Our sample included 2703 patients at baseline, and 1161 (43%) subjects continued the follow-up at 12 months. The AXD group had more females, lower age, and fewer years of formal education compared with subjects without AXD at baseline, 3 and 12 months. Patients with AXD also reported higher mean fasting glucose at three months, and higher HbA1c at three and 12 months. Our MMRM for HbA1c reported significant differences over time in subjects with and without AXD. The differences in means between groups increased from 0.17% at three months to 0.31% at 12 months. The variables from the HADS anxiety score, sex, age, years of diagnosis, and insulin treatment were also associated with HbA1c parameters over time. Conclusion: Patients with AXD had the worst glycemic control at 3 and 12 months of follow-up. HbA1c differences in patients with AXD compared with non-AXD subjects increases over time in association with anxiety symptoms.

Comorbidity Between Recent Diagnosis of Type 2 Diabetes and Non-Psychotic Psychiatric Disorders: Metabolic Characteristics and Clinical Correlates.

Purpose: To describe the metabolic status and clinical characteristics associated with NPPD in patients with less than five years of T2D diagnosis and explore the role of age in the presentation of psychiatric comorbidities. Patients and Methods: This was a cross-sectional study of subjects who attended a comprehensive care program. Patients were assessed using the Mini-International Neuropsychiatric Interview, and clinical and metabolic characteristics were registered. Multivariate logistic regression analyses were conducted to identify risk and protective factors for psychiatric disorders. We performed an analysis to further explore age's influence on our results. Results: We included 1953 patients, and 40.1% had any psychiatric disorder. Younger age, female sex, and personal psychiatric history were associated with NPPD. The use of insulin was reported as a protective factor for eating disorders. Body mass index was associated with any psychiatric disorders and eating disorders. The analysis of age reported that patients younger than 45 years had the worst metabolic parameters and increased odds for NPPD, while patients older than 65 years had the best metabolic measures and decreased odds for psychiatric comorbidity. Conclusion: NPPD were frequent comorbidities in our sample; younger age, female sex, and personal psychiatric history were the most important factors associated with psychiatric comorbidities. Younger subjects experience a higher risk for psychiatric disorders and worst metabolic control.

Detection of sudomotor alterations evaluated by Sudoscan in patients with recently diagnosed type 2 diabetes.

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 (ß=1.01, 0.005-1.02), diastolic blood pressure (ß=0.98, 0.96-0.99), heart rate (ß=1.01, 1.00-1.02), glucose (ß=1.00, 1.00-1.03), albuminuria (ß=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.

Effect of whole-body vibration training on transcutaneous oxygen levels of the foot in patients with type 2 diabetes: A randomized controlled trial.

Whole body vibration (WBV) has been suggested as improving skin and blood flow. This study aimed to determine the effect of exposure to WBV on levels of partial transcutaneous oxygen pressure (TcPO2) in the foot of patients with type 2 diabetes (T2D) within the metabolic control goals. A block randomized, open, two-arm, parallel and controlled clinical trial was conducted. Participants recruited from the Center of Comprehensive Care for the Patient with Diabetes were assessed at the National Institute of Rehabilitation, Mexico City. Control group underwent multidisciplinary care for T2D; experimental group, in addition to the comprehensive diabetes care, was exposed to WBV through an exercise program, attending three times a week for a period of 3 months. TcPO2 was measured in the feet of the participants at baseline and after 12 weeks. A sample of 50 volunteers with recently-diagnosed T2D and similar baseline characteristics (demographic, cardiovascular risk, presence of diabetic polyneuropathy, and indicators of glycemic control and TcPO2) was recruited. The experimental group (n = 27) showed a mean value of 47.7 ± 6.1 mmHg in TcPO2, significantly higher (p = 0.028) than the 44.3 ± 7.5 mmHg of control group (n = 23), at the end of intervention. In conclusion, exposure to WBV promoted an increase and a significant 3 mmHg difference in the foot TcPO2 levels between those subjects with T2D that underwent the 12-week exercise program and those not exposed to the treatment.

miR-145, miR-92a and miR-375 Show Differential Expression in Serum from Patients with Diabetic Retinopathies.

Diabetic retinopathies are important disabling conditions. Micro-RNAs (miRNAs) are regulators of gene expression and diseases can change their expression. Our aim was to analyze the expression of miRNAs in serum and vitreous samples from patients with diabetic retinopathies. The following groups and number of individuals were included: proliferative diabetic retinopathy (PDR) (n = 16), diabetic macular edema (DME) (n = 17), and idiopathic epiretinal membrane (IEM) as non-diabetic controls (n = 23). The initial miRNA expression was explored using TaqMan low-density arrays (TLDAs) with subsequent validation through a quantitative polymerase chain reaction (qPCR). Target genes were identified through bioinformatic tools for enrichment analysis. The TLDAs revealed the following miRNAs with differential expression in terms of PDR vs. IEM: miR-320a-3p, miR-92a-3p, and miR-375-3p in the serum, with miR-541-5p and miR-223-5p in the vitreous samples. DME vs IEM: miR-486-5p, miR-145-5p, miR-197-3p, and miR-125b-5p in the serum, and miR-212-3p in vitreous samples. PDR vs. DME: miR-486-5p, miR-100-5p, miR-328-3p, miR-660-5p, and miR-145 in the serum and none in the vitreous samples. Validation was confirmed only for miR-145, miR-92a, and miR-375 in the serum. The relevant enriched pathways for these three validated miRNAs, miR-145, miR-92a, and miR-375 were the vascular endothelial growth factor and its receptor, hepatocyte growth factor receptor, epidermal growth factor, focal adhesion, and phosphoinositide 3-kinase. Our results support the involvement of miRNAs in the pathophysiology of diabetic retinopathies and reinforce their potential as biomarkers or therapeutic resources.

3D volumetry comparison using 3T magnetic resonance imaging between normal and adenoma-containing pituitary glands.

BACKGROUND: Computed-assisted three-dimensional data (3D) allows for an accurate evaluation of volumes compared with traditional measurements. AIMS: An in vitro method comparison between geometric volume and 3D volumetry to obtain reference data for pituitary volumes in normal pituitary glands (PGs) and PGs containing adenomas. DESIGN: Prospective, transverse, analytical study. MATERIALS AND METHODS: Forty-eight subjects underwent brain magnetic resonance imaging (MRI) with 3D sequencing for computer-aided volumetry. PG phantom volumes by both methods were compared. Using the best volumetric method, volumes of normal PGs and PGs with adenoma were compared. Statistical analysis used the Bland-Altman method, t-statistics, effect size and linear regression analysis. RESULTS: Method comparison between 3D volumetry and geometric volume revealed a lower bias and precision for 3D volumetry. A total of 27 patients exhibited normal PGs (mean age, 42.07 ± 16.17 years), although length, height, width, geometric volume and 3D volumetry were greater in women than in men. A total of 21 patients exhibited adenomas (mean age 39.62 ± 10.79 years), and length, height, width, geometric volume and 3D volumetry were greater in men than in women, with significant volumetric differences. Age did not influence pituitary volumes on linear regression analysis. CONCLUSIONS: Results from the present study showed that 3D volumetry was more accurate than the geometric method. In addition, the upper normal limits of PGs overlapped with lower volume limits during early stage microadenomas.

Feasibility and acceptance of a virtual multidisciplinary care programme for patients with type 2 diabetes during the COVID-19 pandemic.

BACKGROUND AND AIMS: Type 2 diabetes mellitus is one of the major public health concerns. The current lifestyle and advances in technology resulted in the development of a virtual mode of professional healthcare, which is an effective alternative method of management of patients. This study aimed to assess the feasibility of implementation of a virtual comprehensive care programme during the COVID-19 pandemic, patients' acceptance and the changes in self-care behaviours, metabolic parameters and emotional factors. METHODS: The programme employed in this study included nine health interventions in 1 day. Due to the COVID-19 pandemic, the mode of interventions, including questionnaires, patient evaluations and a satisfaction survey, was modified to the virtual form in 2020. This study assessed the changes in self-care behaviours, metabolic parameters and emotional factors and compared the data pertaining to patients who received virtual healthcare in 2020 with those who received face-to-face modality of medical care in 2019. RESULTS: During June to November 2020, 130 patients received healthcare by means of the virtual modality. The change in modality of healthcare was feasible and 75% of the patients displayed good acceptance of the same. The evaluation of self-care behaviours included self-monitoring blood glucose (SMBG) levels, foot care and regular exercise. The duration of exercise decreased from 120 to 0 min/week (p < 0.001). However, there was no change in metabolic parameters. Regarding the mental health parameters, we observed an increase in the proportion of patients with anxiety (21.5% versus 11.1%), depressive symptoms (10.8% versus 4.3%), diabetes distress (18.5% versus 11.1%) and prescription of psychotropic drugs (32.8% versus 18.2%) (p < 0.05) in virtual versus face-to-face, respectively. CONCLUSION: The virtual comprehensive care programme for the management of patients with diabetes is a feasible approach that allows healthcare professionals to provide an adequate care during the COVID-19 pandemic.

Use of an electronic integral monitoring system for patients with diabetes to identify factors associated with an adequate glycemic goal and to measure quality of care.

AIMS: To evaluate the use of the electronic integral monitoring system (SMID) to identify factors associated to glycemic control and its impact in the quality of care in patients with type 2 diabetes (T2D). METHODS: T2D patients registered in SMID were analyzed. Biochemical, clinical and lifestyle variables were recorded. Factors associated to HbA1c ≤7% were explored. Quality of care of the clinic was measured according to the National Committee for Quality Assurance Criteria (NCQA) that requires a score of 75 to achieve a good quality of care. RESULTS: 511 patients were included. Prescription of basal insulin, SGLT-2 inhibitors and barriers to follow nutritional plan were associated with decreased probability of having adequate glycemic control. Patients in the maintenance stage of motivation had higher probability of having HbA1c ≤7%. According to NCQA evaluation 60 points were achieved. Glucose goals were not met; 35.9% had HbA1c ≥9% and 17% HbA1c <7%. While foot evaluation, smoking approach, blood pressure and lipids goals were accomplished; eye and renal evaluations were borderline. CONCLUSION: Glycemic control in patients with long standing T2D and multiple comorbidities is challenging, which directly impacts in the quality of care. Professionals should focus in reinforcing non-pharmacological interventions to optimize glycemic targets.

Clinician prescription of lipid-lowering drugs and achievement of treatment goals in patients with newly diagnosed type 2 diabetes mellitus.

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/m2) 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.

Cost-effectiveness of a self-management and comprehensive training intervention in patients with type 2 diabetes up to 5 years of diagnosis in a specialized hospital in Mexico City.

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.

Barriers to adherence to a nutritional plan and strategies to overcome them in patients with type 2 diabetes mellitus; results after two years of follow-up.

INTRODUCTION: Lifestyle changes in medical nutrition therapy (MNT) are associated to HbA1c decreases ranging from 0.3 to 2%. Evidence shows that people with barriers are less likely to adhere to a long-term nutritional plan. Little information is available on the barriers that prevent the implementation of a healthy nutritional plan, and the strategies used to overcome them. OBJECTIVE: To report the longitudinal changes in perceptions of barriers to adherence to a nutritional plan in T2DM. METHODS: A prospective cohort study with intervention. Follow-up was assessed at two years, and all patients received comprehensive care according to the CAIPaDi model. A questionnaire was used to detect the most common barriers to adherence to a nutritional plan at baseline and at 3 months and 1 and 2 years of follow-up. The analysis included data from 320 patients with complete evaluations from baseline to 2 years. Patients with T2DM aged 53.8±9.1 years (55.9% women), BMI 29.2±4.4kg/m2, and time since the diagnosis 1 (0-5) years were included in the study. RESULTS: At baseline, 78.4% of patients reported any barrier that limited adherence to a nutritional plan. The most common were "Lack of information on an adequate diet" (24.7%), "I eat away from home most of the time" (19.7%), and "Denial or refusal to make changes in my diet" (14.4%). After a structured nutritional intervention including strategies to eliminate each barrier, a 37% reduction (p<0.001) was seen in barriers at 2 years of follow-up. Patients with persistent barriers at two years had a greater proportion of HbA1c values >7% (24.7%) and triglyceride levels >150mg/dL (27.5%) out of the control range as compared to those with no barriers (11.6% and 14.4% respectively, p<0.05). CONCLUSIONS: Identification of barriers to adherence to a nutritional plan may allow healthcare professionals design interventions with the specific behavioral components needed to overcome such barrier, thus improving adherence to the nutritional plan with the resultant long-term changes.

Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach.

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.

Implementation barriers for mHealth for non-communicable diseases management in low and middle income countries: a scoping review and field-based views from implementers.

Background: Mobile health (mHealth) has been hailed as a potential gamechanger for non-communicable disease (NCD) management, especially in low- and middle-income countries (LMIC). Individual studies illustrate barriers to implementation and scale-up, but an overview of implementation issues for NCD mHealth interventions in LMIC is lacking. This paper explores implementation issues from two perspectives: information in published papers and field-based knowledge by people working in this field. Methods: Through a scoping review publications on mHealth interventions for NCDs in LMIC were identified and assessed with the WHO mHealth Evidence Reporting and Assessment (mERA) tool. A two-stage web-based survey on implementation barriers was performed within a NCD research network and through two online platforms on mHealth targeting researchers and implementors. Results: 16 studies were included in the scoping review. Short Message Service (SMS) messaging was the main implementation tool. Most studies focused on patient-centered outcomes. Most studies did not report on process measures and on contextual conditions influencing implementation decisions. Few publications reported on implementation barriers. The websurvey included twelve projects and the responses revealed additional information, especially on practical barriers related to the patients' characteristics, low demand, technical requirements, integration with health services and with the wider context. Many interventions used low-cost software and devices with limited capacity that not allowed linkage with routine data or patient records, which incurred fragmented delivery and increased workload. Conclusion: Text messaging is a dominant mHealth tool for patient-directed of quality improvement interventions in LMIC. Publications report little on implementation barriers, while a questionnaire among implementors reveals significant barriers and strategies to address them. This information is relevant for decisions on scale-up of mHealth in the domain of NCD. Further knowledge should be gathered on implementation issues, and the conditions that allow universal coverage.

Long-term effectiveness of a type 2 diabetes comprehensive care program. The CAIPaDi model.

AIMS: To evaluate the effectiveness of a comprehensive care program to achieve and maintain goals in patients with type 2 diabetes. METHODS: The CAIPaDi program includes 9 interventions delivered in 7 h. It seeks to achieve metabolic goals, identify and resolve barriers that would make implementation difficult, and provide self-efficacy and empowerment to patients by identifying personal profiles to establish individualized strategies. The program consists of a 4 intervention visits (1, 2, 3, and 4 months) and two follow up visits (12 and 24 months). Outcomes are compared between every visit. Main outcome was the attainment of the USA National Committee for Quality Assurance treatment goals. RESULTS: 1104 patients completed the first 4 visits, 545 the 12 month evaluation, and 218 the 24 month evaluation. After the conclusion of the four monthly sessions, 80.6% had HbA1c <7%, 72.1% had BP <130/80 mmHg and 71.6% had LDL- cholesterol <100 mg/dl. After twelve months, the percentage of goals achieved were 65.9%, 67.7% and 43.3% respectively (p < 0.001). For the 2-year evaluation the percentages were 61.0%, 70.6%, and 40.8% respectively (p < 0.001). All patients had renal, eye, foot and dental evaluations. Empowerment and quality of life showed significant changes; anxiety and depression scores remained low at annual follow-ups. CONCLUSIONS: The CAIPaDI program results in sustained improvement and maintenance of treatment goals.

Assessment of a Multidisciplinary Intervention in Patients With BMI ≥35 kg/m2 and Recently Diagnosed Type 2 Diabetes.

CONTEXT: Patients with a body mass index (BMI) ≥35 kg/m2 have lower benefits with intensive treatments and metabolic control goals are more difficult to reach. OBJECTIVE: Evaluate the effect of a comprehensive care program in patients with a BMI ≥35 kg/m2. DESIGN: Prospective cohort study. SETTING: Comprehensive Care Center in a National Institute of Health. PATIENTS: Patients with type 2 diabetes, ≤5 years of diagnosis, without disabling complications, nonsmokers, and a BMI <45 kg/m2. INTERVENTIONS: Exercise and nutritional interventions are modified for patients with a higher BMI to achieve metabolic control. MAIN OUTCOME MEASURES: Main outcome is achievement of treatment goals defined as HbA1c <7%, low-density lipoprotein cholesterol (LDL-c) <100 mg/dL, and blood pressure <130/80 mm Hg. Secondary measures were the percentage of patients achieving three metabolic goals. RESULTS: A total of 587 patients with annual evaluation were included. Mean age was 55.3 ± 9.5 years, 56.6% women, time since diagnosis of 1 year (0 to 5). BMI <35 kg/m2 group included 521 patients and BMI ≥35 kg/m2 group included 66 patients. In the BMI ≥35 kg/m2 group, we observed a greater decrease in weight and fat mass at 3 months compared with <35 kg/m2 group, but the HbA1c, LDL-c, or blood pressure goals were similar at 3 months and 1 year between groups. CONCLUSIONS: Comprehensive interventions are equally effective in patients with recently diagnosed type 2 diabetes with BMI ≥35 kg/m2 compared with patients with a lower BMI.

High adiponectin concentrations are associated with the metabolically healthy obese phenotype.

CONTEXT: In the ob/ob mice, keeping adiponectin concentrations in the physiological range (through overexpression of this gene in the adipose tissue) results in expansion of fat mass and protection against metabolic co-morbidities. OBJECTIVE: The aim of the study was to test in humans whether plasma adiponectin levels, similar to those found in lean subjects, are associated with the metabolically healthy obese phenotype. DESIGN AND SETTING: A cross-sectional analysis was performed of a cohort of obese and nonobese subjects aged 18-70 yr. A medical history was taken, and glucose, plasma lipids, and total adiponectin were measured. PARTICIPANTS: We studied 189 men and 527 women. The majority were obese (n = 470, 65.6%). The metabolically healthy obese phenotype was found in 38 men and 133 women. This is defined as a body mass index (BMI) above 30 kg/m(2) plus high-density lipoprotein cholesterol of at least 40 mg/dl in the absence of type 2 diabetes and arterial hypertension. RESULTS: Twenty percent of the cases with a BMI above 40 kg/m(2) had adiponectin concentrations above the median value of normal BMI subjects. Adiponectin levels above 12.49 mg/liter in obese women (odds ratio, 3.02; 95% confidence interval, 1.95-4.67; P < 0.001) and above 8.07 mg/liter in obese men (odds ratio, 2.14; 95% confidence interval, 1.1-4.06; P = 0.01) increased the probability of being metabolically healthy. The association remained significant (beta, 0.673 +/- 0.205, P < 0.001) in a logistic regression model (r(2) = 0.25, P < 0.001) after controlling for the confounding effect of age, insulin, and waist circumference. CONCLUSIONS: Certain obese individuals have adiponectin levels similar to those found in normal BMI subjects; this is associated with the metabolically healthy obese phenotype.