Platform for precise, personalised glucose forecasting through continuous glucose and physical activity monitoring and deep learning.

Emerging research has demonstrated the advantage of continuous glucose monitoring for use in artificial pancreas and diabetes management in general. Recent studies demonstrate that glucose level forecasting using deep learning can help avoid postprandial hyperglycemia (≥ 180 mg/dL) or hypoglycemia (≤70 mg/dL) from delayed or increased insulin dosing in artificial pancreas. In this paper, a novel hybrid deep learning framework with integration of content-based attention learning is presented, to effectively predict the glucose measurements with prediction horizons (PH) = 15, 30 and, 60 minutes for T1D and T2D patients based on past data.

Impact of glycemic control over cardiac autonomic neuropathy.

Purpose: Cardiovascular autonomic neuropathy (CAN) is one of the most common and serious complications associated with diabetes and is defined as the impairment of the autonomic control of the cardiovascular system, whose prevalence in Indian population has been reported to be > 50%. The risk factors associated with CAN include hyperglycemia, duration of diabetes, hypertension, dyslipidemia, and obesity. This study was conducted to examine the association of CAN with its determinants among diabetics.

Consensus on Initiation and Intensification of Premix Insulin in Type 2 Diabetes Management.

Introduction: Premix insulin is the most commonly used insulin preparation in India. The first Indian premix guidelines were developed in 2009 and thereafter were updated in 2013. There is a need to revisit the Indian premix insulin guidelines, in view of emerging evidence and introduction of newer co-formulations.