This article summarizes key updates from the KDIGO 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease. The update summary highlights revisions of recommendations on ... Description: The KDIGO 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease is an update of the 2020 guideline from Kidney Disease: Improving Global Outcomes (KDIGO). ...

Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 Indians, a less explored but high-risk group. We identified a new type 2 diabetes–associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; P = 3.32 × 10⁻⁹). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; P = 6.3 × 10⁻¹²) within TMEM163 that encodes a probable vesicular transporter in nerve terminals. TMEM163 variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors RAB3GAP1 and ACMSD; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated (P < 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D.

This synopsis of a Kidney Disease: Improving Global Outcomes (KDIGO) guideline focuses on key recommendations and practice points for the management of patients with diabetes and chronic kidney dis... Description: The Kidney Disease: Improving Global Outcomes (KDIGO) organization developed a clinical practice guideline in 2020 for the management of patients with diabetes and chronic kidney disea...

Background: Cardio-metabolic diseases (CMDs) are a growing public health problem, but data on incidence, trends, and costs in developing countries is scarce. Comprehensive and standardised surveillance for non-communicable diseases was recommended at the United Nations High-level meeting in 2011.Aims: To develop a model surveillance system for CMDs and risk factors that could be adopted for continued assessment of burdens from multiple perspectives in South-Asian countries.Methods: Design: Hybrid model with two cross-sectional serial surveys three years apart to monitor trend, with a three-year prospective follow-up of the first cohort.Sites: Three urban settings (Chennai and New Delhi in India; Karachi in Pakistan), 4000 participants in each site stratified by gender and age.Sampling methodology: Multi-stage cluster random sampling; followed by within-household participant selection through a combination of Health Information National Trends Study (HINTS) and Kish methods.Culturally-appropriate and methodologically-relevant data collection instruments were developed to gather information on CMDs and their risk factors; quality of life, health-care utilisation and costs, along with objective measures of anthropometric, clinical and biochemical parameters. The cohort follow-up is designed as a pilot study to understand the feasibility of estimating incidence of risk factors, disease events, morbidity, and mortality.Results: The overall participant response rate in the first cross-sectional survey was 94.1% (Chennai 92.4%, n = 4943; Delhi 95.7%, n = 4425; Karachi 94.3%, n = 4016). 51.8% of the participants were females, 61.6% < 45years, 27.5% 45–60years and 10.9% >60 years.Discussion: This surveillance model will generate data on prevalence and trends; help study the complex life-course patterns of CMDs, and provide a platform for developing and testing interventions and tools for prevention and control of CMDs in South-Asia. It will also help understanding the challenges and opportunities in establishing a surveillance system across countries.

Despite improvements in risk factors and reductions in diabetes complications in the United States, large gaps exist in achievement of these goals globally, particularly in low- and middle-income c... This article has been corrected. The original version (PDF) is appended to this article as a Supplement. Background: Achievement of diabetes care goals is suboptimal globally. Diabetes-focused qual...

Background: The high burden of undetected and undertreated hypertension and diabetes mellitus is a major health challenge worldwide. The mP ower Heart Project aimed to develop and test a feasible and scalable intervention for hypertension and diabetes mellitus by task‐sharing with the use of a mobile phone–based clinical decision support system at Community Health Centers in Himachal Pradesh, India. Methods and Results: The development of the intervention and mobile phone–based clinical decision support system was carried out using mixed methods in five Community Health Centers. The intervention was subsequently evaluated using pre–post evaluation design. During intervention, a nurse care coordinator screened, examined, and entered patient parameters into mobile phone–based clinical decision support system to generate a prescription, which was vetted by a physician. The change in systolic blood pressure, diastolic blood pressure, and fasting plasma glucose ( FPG ) over 18 months of intervention was quantified using generalized estimating equations models. During intervention, 6797 participants were enrolled. Six thousand sixteen participants had hypertension (mean systolic blood pressure: 146.1 mm Hg, 95% CI : 145.7, 146.5; diastolic blood pressure: 89.52 mm Hg, 95% CI : 89.33, 89.72), of which 3152 (52%) subjects were newly detected. Similarly, 1516 participants had diabetes mellitus (mean FPG : 177.9 mg/dL, 95% CI : 175.8, 180.0), of which 450 (30%) subjects were newly detected. The changes in systolic blood pressure, diastolic blood pressure, and FPG observed at 18 months of follow‐up were −14.6 mm Hg (95% CI : −15.3, −13.8), −7.6 mm Hg ( CI : −8.0, −7.2), and −50.0 mg/dL (95% CI : −54.6, −45.5), respectively, and were statistically significant even after adjusting for age, sex, and Community Health Center. Conclusions: A nurse‐facilitated, mobile phone–based clinical decision support system‐enabled intervention in primary care was associated with improvements in blood pressure and blood glucose control and has the potential to scale‐up in resource poor settings. Clinical Trial Registration: URL : https://www.clinicaltrials.gov . Unique identifiers: NCT 01794052. Clinical Trial Registry—India: CTRI /2013/02/003412.