Association of collaborative care intervention features with depression and metabolic outcomes in the INDEPENDENT study: A mixed methods study.

AIMS: The INtegrating DEPrEssioN and Diabetes treatmENT (INDEPENDENT) trial tested a collaborative care model including electronic clinical decision support (CDS) for treating diabetes and depression in India. We aimed to assess which features of this clinically and cost-effective intervention were associated with improvements in diabetes and depression measures. METHODS: Post-hoc analysis of the INDEPENDENT trial data (189 intervention participants) was conducted to determine each intervention feature's effect: 1. Collaborative case reviews between expert psychiatrists and the care team; 2. Patient care-coordinator contacts; and 3. Clinicians' CDS prompt modifications. Primary outcome was baseline-to-12-months improvements in diabetes control, blood pressure, cholesterol, and depression. Implementer interviews revealed barriers and facilitators of intervention success. Joint displays integrated mixed methods' results. RESULTS: High baseline HbA1c≥ 74.9 mmol/mol (9%) was associated with 5.72 fewer care-coordinator contacts than those with better baseline HbA1c (76.8 mmol/mol, 9.18%, p < 0.001). Prompt modification proportions varied from 38.3% (diabetes) to 1.3% (LDL). Interviews found that providers' and participants' visit frequencies were preference dependent. Qualitative data elucidated patient-level factors that influenced number of clinical contacts and prompt modifications explaining their lack of association with clinical outcomes. CONCLUSION: Our mixed methods approach underlines the importance of the complementarity of different intervention features. Qualitative findings further illuminate reasons for variations in fidelity from the core model.

Effect of a collaborative care model on anxiety symptoms among patients with depression and diabetes in India: The INDEPENDENT randomized clinical trial.

OBJECTIVE: We assessed the impact of a collaborative care intervention on anxiety symptoms among participants in India with comorbid depression, poorly controlled diabetes, and moderate to severe anxiety symptoms. METHOD: We analyzed data from a randomized controlled trial conducted at four diabetes clinics in India. Participants received either collaborative care or usual care. We included only participants who scored ⩾10 on the Generalized Anxiety Disorder-7 (GAD-7) at baseline. We estimated the effect of the intervention on clinically significant reduction in anxiety symptoms; we considered several potential baseline moderators and mediation by anti-depressant use. RESULTS: One hundred and seventy-two participants scored 10 or above on the GAD-7 at baseline. Collaborative care participants were more likely than control participants to achieve a clinically significant reduction in anxiety symptoms at 6 and 12 months (65.7% vs. 41.4% at 12 months, p = 0.002); these differences were not sustained at 18 or 24 months. There was little evidence of moderation by participant characteristics at baseline, and effects were not mediated by anti-depressant use. CONCLUSIONS: Collaborative care for the treatment of depression and type 2 diabetes can lead to clinically significant reductions in anxiety symptoms among patients with anxiety. Effects were notable during the active intervention period but not over the year post-intervention.

Management of Hyperglycemia in COVID-19 and Post-COVID-19 Syndrome - Proposed Guidelines for India.

SARS-CoV-2 virus spread rapidly all over the globe in 2020 and the second wave has taken our nation, India by storm. The pandemic has posed unique challenges in people with metabolic disorders, including diabetes, hypertension, obesity, pulmonary, cardiovascular, kidney and non-alcoholic fatty liver disease. Uncontrolled diabetes, in conjunction with endocrine, inflammatory and metabolic effects of the infection itself has made management of hyperglycemia in COVID-19 infection particularly challenging. Furthermore, the post-COVID-19 syndrome has also emerged as a sequela in COVID-19 survivors, increasing the risk of death, complications and adding further burden on the health care system. With more than a year of experience, we have gained substantial insight; and now provide practical recommendations on the management of hyperglycemia in COVID-19 as well as post COVID-19 syndrome.

New and Unique Clusters of Type 2 Diabetes Identified in Indians.

Type 2 diabetes (T2D), the most common form of diabetes, is recognized as being a heterogenous disorder, and presents a universal threat to health. In T2D, the pathophysiology and phenotype differ significantly by ethnicity, particularly among Asian Indians, who are known to have the 'Asian Indian phenotype', which makes them more susceptible to develop T2D than white Caucasians. The recent subclassification of T2D into different subtypes or clusters, which behave differently with respect to clinical presentation and risk of developing complications is a remarkable development. Five unique "clusters" of individuals with diabetes were described in the Scandinavian population [Severe Autoimmune Diabetes (SAID), Severe Insulin Deficient Diabetes (SIDD), Severe Insulin Resistant Diabetes (SIRD), Mild Obesity-related Diabetes (MOD) and Mild Age-Related Diabetes (MARD)]. For the first time in India, identification of clusters of diabetes was done on 19,084 individuals with T2D, using 8 clinically relevant variables (age at diagnosis, BMI, waist circumference, HbA1c, triglycerides, HDL cholesterol and fasting and stimulated C-peptide). Four replicable clusters were identified [SIDD, MARD, IROD (Insulin Resistant Obese Diabetes) and CIRDD (Combined Insulin Resistant and Deficient Diabetes)], two of which were unique to the Indian population (IROD and CIRDD). Clustering of T2D helps i) to accurately subclassify diabetes into different subtypes, ii) plan therapies based on the pathophysiology, iii) predict prognosis and prevent diabetic complications and iv) helps in our approach to precision diabetes. Further studies would help us to refine the usefulness of these clusters of T2D particularly in the Indian population, with respect to selection of appropriate therapies and hopefully in the prevention of complications of diabetes.

Simple, Mobile-based Artificial Intelligence Algorithm in the detection of Diabetic Retinopathy (SMART) study.

INTRODUCTION: The aim of this study is to evaluate the performance of the offline smart phone-based Medios artificial intelligence (AI) algorithm in the diagnosis of diabetic retinopathy (DR) using non-mydriatic (NM) retinal images. METHODS: This cross-sectional study prospectively enrolled 922 individuals with diabetes mellitus. NM retinal images (disc and macula centered) from each eye were captured using the Remidio NM fundus-on-phone (FOP) camera. The images were run offline and the diagnosis of the AI was recorded (DR present or absent). The diagnosis of the AI was compared with the image diagnosis of five retina specialists (majority diagnosis considered as ground truth). RESULTS: Analysis included images from 900 individuals (252 had DR). For any DR, the sensitivity and specificity of the AI algorithm was found to be 83.3% (95% CI 80.9% to 85.7%) and 95.5% (95% CI 94.1% to 96.8%). The sensitivity and specificity of the AI algorithm in detecting referable DR (RDR) was 93% (95% CI 91.3% to 94.7%) and 92.5% (95% CI 90.8% to 94.2%). CONCLUSION: The Medios AI has a high sensitivity and specificity in the detection of RDR using NM retinal images.

Adaptations and patient responses to behavioral intervention components in a depression-focused chronic disease care model implemented in India.

Integrated care models offer one approach to treat patients with chronic multimorbidity. However, because these models consist of multiple components designed to provide individualized care, they should be adapted to best meet the needs of patients in diverse settings. This paper presents qualitative and quantitative data from a realist process evaluation embedded in the INtegrating DEPrEssioN and Diabetes treatmENT (INDEPENDENT) study to uncover what worked, for whom, how, and in what circumstances. We aimed to examine adaptations made to a care coordinator-led behavioral intervention, and how patients responded to adaptations, through a secondary analysis of these data. A purposive sample of 62 patients and 3 care coordinators were recruited based on their involvement with the INDEPENDENT care model across two clinics. Patients were interviewed and surveyed about their experiences in the care model and care coordinators were interviewed about their experiences implementing intervention components. Interview data were coded for reported modifications in intervention content, tools, and delivery; then, these adaptations were categorized by how they served to enhance implementation in the Indian context. Adaptations made in the delivery of this care model served two functions: (a) to improve health promotion communication between care coordinators and patients and (b) to improve patient engagement. Patients' expressed needs were consistent with what care coordinators perceived. Patients were satisfied with adaptations designed to improve intervention fit for local contexts. Study findings demonstrate that adapting components of an integrated care model can enhance patient satisfaction and engagement with behavioral interventions.

Cross-sectional survey of biosimilar insulin utilization in Asia: The Joint Asia Diabetes Evaluation Program.

AIMS/INTRODUCTION: Biosimilar insulin can reduce treatment costs, although the extent of its use is largely unknown. We examined biosimilar insulin use and its associations with the quality of glycemic control using the Joint Asia Diabetes Evaluation register. MATERIALS AND METHODS: We carried out a cross-sectional analysis in 81,531 patients with type 1 and type 2 diabetes enrolled into the Joint Asia Diabetes Evaluation Program from 2007 to 2014. All insulin related terms are extracted from the Joint Asia Diabetes Evaluation portal, and compared clinical profiles between biosimilar and originator insulin users. Multivariate analysis was performed to assess the association of biosimilar insulin compared with originator insulin with dosage, glycated hemoglobin and hypoglycemia events. RESULTS: Amongst 81,531 patients, 20.5% (n = 16,738) were insulin-treated. In four countries with high use of biosimilar insulin, 4.7% (n = 719) of insulin users (n = 10,197) were treated with biosimilar insulin (India n = 507, 70.3%; the Philippines n = 90, 12.5%; China n = 62, 8.6%; Vietnam n = 60, 8.3%). Biosimilar insulin users were younger and had higher body mass index, glycated hemoglobin, insulin dosage and more frequent hypoglycemia than originator insulin users. These associations were non-significant after adjustment for confounders. Only age, college education, diabetes education, lipid control, physical activity and history of cardiovascular complications were independently associated with these quality measures. CONCLUSIONS: Biosimilar insulin use is not uncommon in Asia. Data exclusion due to incomplete capturing of brand names suggests possibly higher use. The multiple determinants of the quality of glycemic control call for establishment of prospective cohorts and diabetes registers to monitor the safety and efficacy of different brands of biosimilar insulin and their impacts on clinical outcomes.

Influence of cytokine status on insulin resistance and circulating endothelial progenitor cells in type 2 diabetes mellitus.

BACKGROUND: Type 2 diabetes mellitus (T2DM), a chronic metabolic disorder caused by insulin resistance (IR) and elevated blood glucose level, may lead to endothelial dysfunction. This can result in the development of various vascular complications, even in clinically controlled glycemic state. AIM: It has been experimentally proven that cytokine influences both IR and endothelial progenitor cell (EPC) dysfunction in T2DM patients. The present study evaluated the effect of clinical and metabolic risk factors and cytokine levels on IR and EPC, which are used as critical early biomarkers for estimating the risks associated with T2DM. METHODS: The study involved 58 T2DM patients. They were further subdivided into three groups based on IR score: 32 (55.17%) with normal, 11 (18.97%) with mild-moderate and 15 (25.86%) with severe IR. The relationship of clinical, metabolic and immune mediators with IR and EPCs was verified. RESULTS: HbA1c% was significantly elevated in severe (P=0.022) and mild-moderate IR groups (P= 0.012) than the normal group. The IR normal group had significantly elevated TNF levels compared to mild-moderate and severe groups. The regression analysis indicated that patients with increased body mass index (BMI) were 19.5% more likely to be significantly associated with severe IR. Association studies demonstrated that IL6 and IL10 values correlated with EPCs. CONCLUSION: IL6 and IL10 were associated with circulating EPCs than IR and other clinical characteristics including glycemic control (glycated hemoglobin). TNF-α was associated with IR, but had no relationship with EPCs. The effect of cytokine status on IR and circulating EPCs in T2DM may indicate the risk of vascular complications.