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Recent increases in the usage of continuous glucose monitoring technology have provided people living with diabetes and health-care professionals with access to a variety of novel glucose control indicators. Some of these indicators are valuable for research, while others are useful clinically. Time-in-range (TIR) is a metric that denotes the proportion of time per day that a person's glucose level is within a specified goal range. There is evidence relating TIR to risk of complications and it is becoming an excepted endpoint in clinical trials. There is an inverse relationship between TIR and glycated hemoglobin. In addition, the duration and severity of time below range and time above range are also discussed. This paper summarizes recent guidelines regarding the “TIR” goals for different individuals with different types of diabetes. As is always the case, glycemic objectives should be tailored to the individual. Finally, this article discusses the tool of TIR's positioning in India and the specific populations/patient profiles that will benefit from the intervention.

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The ever-increasing transformation of people to a sedentary lifestyle paved the way for a steep increase in diabetes. It is well-documented that advanced diabetes technologies can reduce disease burden and improve the quality of life. However, several reasons are entangled with the lesser acceptance of diabetes technologies. Some of these include inaccessibility, lack of skill, unawareness, fear of being with devices, overall treatment cost, and cost associated with technologies. Among these, the cost of technologies intensifies peoples' unwillingness in using diabetes technologies. Majority of the patients with diabetes, especially in developing countries, are unaware of diabetes-related complications which eventually impose a huge economic burden on them. Diabetes awareness should start from the primary care centers and primary care physicians should encourage using technologies that are proven to be cost-effective in preventing the costly complications of diabetes. Policy-makers and government should take the initiative to provide financial support to people with diabetes in availing technologies. The review provides insights into how diabetes technologies help people with diabetes to reduce the cost burden in the long term. The data were collected from relevant studies based on the cost-effectiveness of diabetes technologies which were published in electronic databases such as PubMed and Google Scholar using the keywords diabetes, cost-effectiveness, economic burden, incremental cost-effectiveness ratio, smartpens, insulin devices, diabetes technologies, and continuous glucose monitoring (CGM). The review discusses studies that highlight the cost effectiveness of telemedicine, smart insulin pens CGM, and insulin pumps.

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With 74.2 million people affected, diabetes represents a major burden on India's health-care system and economy. Effective diabetes management is based on diet, lifestyle, pharmacotherapy, and glucose monitoring that are to be individualized for every patient. However, glucose monitoring rates in India are abysmal. The available monitoring techniques have limitations with respect to mostly being single point-in-time readings that may not be entirely reflective of the state of diabetes control. With advancements in technology, the new monitoring tool – continuous glucose monitoring (CGM) – provides visibility into the glycemic profile 24 × 7 with user-friendly reports that provide information much beyond the glycated hemoglobin (HbA1c) and self-monitoring of blood glucose. This innovative tool also detects the time spent in range by the individual with diabetes. This is the new metric endorsed by all reputed medical organizations for diabetes management with multiple benefits ranging from helping slow down the progression to diabetes-related complications to enabling improvement in overall glycemic control. CGM can be classified into personal and professional types based on its usage. Certain types of CGM can also provide real-time (RT) readings either automatically or on-demand. This review article explores the CGM technologies with RT readings in the context of diabetes care in India. These new technologies have the potential to change the way diabetes is managed today including making smart decisions such as the right choice of diet, apt lifestyle modification, and adequate titration of pharmacotherapy (including insulin) while monitoring glucose levels continuously anytime anywhere without a prick.

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Protein and peptide drugs have tremendous therapeutic potential, and their usage in the treatment of various severe diseases has revolutionized the fields of pharmaceuticals and biotechnology. For successful therapeutic effects, several efforts have been made to deliver protein/peptide drugs through various routes of administration. Parenteral and nonparenteral drug deliveries are regarded as significant routes of drug absorption. However, there is a need to improve nonparenteral drug delivery systems (DDSs) through subsequent routes, including buccal, pulmonary, oral, ocular, transdermal, and nasal routes to increase drug absorption effectively. The study evaluated various DDS routes proposed for the distribution of proteins and peptides in terms of both parenteral and nonparenteral delivery systems. For this purpose, numerous research articles were searched from the year 2000 to 2021 using search engines such as PubMed, Google Scholar, Medline, ISI Web of Knowledge, and Bioline International while applying different keywords such as “protein and peptide drugs,” “drug delivery systems,” “parenteral and nonparenteral routes of drug delivery,” and “physicochemical barriers.” The invasive/parenteral routes have several limitations associated with drug delivery, such as poor patient compliance and the pain and discomfort associated with these routes inconvenience in treating the pediatric population. The oral route is one of the most convenient routes of noninvasive or nonparenteral drug administration; here, no pain and discomfort arise, thus helping in maintaining higher patient compliance or acceptance. The other routes of administration of proteins and peptides through buccal, intranasal, pulmonary, transdermal, rectal, and ocular routes have also been showing successful results. The success of the therapeutics is strongly influenced by the differential delivery of the targeted antigen, the choice of targeting protein or peptide, and the drug-release characteristics of the linker used. Furthermore, there should be an improvement in nonparenteral DDSs so that the drugs might be administered appropriately.

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In people with diabetes, the most efficient therapeutic option available to reduce hyperglycemia continues to be insulin, even though they experience numerous challenges with the use of insulin. Beginning with the syringe for injecting insulin, progressing to insulin pens, insulin pumps, and sensor-augmented pumps, the growth of diabetes technologies accelerated with the introduction of hybrid closed-loop systems, integration with consumer electronics, and cloud-based data systems. There has been a high-speed evolution in diabetes technologies to improve the quality of life and to extend the endurance of subjects with diabetes. Although there were commendable developments in the currently available devices, many of those were prohibitively expensive. The ultimate dream is to develop an artificial pancreas capable of 100% time in range and 0% time below range and affordable to everyone. Even though the mission demands enormous commitment and time, it has the potential to transform diabetes therapy.

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Diabetes irrespective of its type is a lifelong disease, and when left undiagnosed, untreated, or poorly controlled, diabetes leads to severe complications predominantly arising from persistent hyperglycemia along with other contributing factors including hypoglycemia, dyslipidemia, hypertension, and obesity. With the complexity of therapies, the necessity of monitoring and the daily routines to be followed along with diet and lifestyle modifications, most patients are worn out at some point and move to unproven easy remedies. Several systematic reviews have been published that assessed the impact and efficacy of various “complementary and alternative medicine” (CAM) therapies on preventing and treating diabetes. CAM practices and practitioners, underdeveloped research, poor quality of clinical trials, false claims and fake publicity, absence of proper communication with health practitioners, etc., are all known to be contributing risk factors toward the failure of CAM therapies. It is crucial that health-care professionals be aware of the increase in the number of patients who resort to CAM practices. With the use of CAM therapies among diabetes patients being prevalent, care providers are encouraged to consider their potential risks and benefits. Modern health-care practitioners need to be aware of these practices and be prepared to counsel such patients, when needed, about the available options. They should be able to assess as well as present information to the patients regarding the expected risks, side effects, benefits, and choices regarding self-management and the cost to the patient, helping them to make an informed choice. This review article brings up the issues concerning the scientifically unproven practices with a focus on the population with diabetes.

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Background: The success of insulin therapy in achieving glycemic control highly relies on proper insulin injection practices. Proper insulin injection technique is crucial for optimizing the efficacy of insulin therapy. Therefore, it becomes imperative to train people with diabetes on standard insulin injection techniques. In some clinic settings, the education about the technique of injection may be delivered only once, and there is possibility that the patients can still commit mistakes while administering insulin. Ensuring proper insulin injection practices can help improve hemoglobin A1c (HbA1c) and achieve good glycemic control. Aim and Objective: This study aimed to assess the significance of wrong insulin injection techniques on poor glycemic control, and the impact of brief education sessions in inculcating proper insulin injection practices among patients with Type 2 diabetes mellitus (T2DM) was assessed in a real-world diabetes care setting. Methods: A retrospective analysis was conducted for the past 2 years among T2DM patients who exhibited improper injection techniques despite attending a 15-min training session. They were asked to fill in a questionnaire as well as their injection sites were examined. They were again made to attend the session and followed up for the succeeding 6 months to understand the underlying benefits of such training episodes. Results: Among people with T2DM, 126 individuals were identified with wrong injection practices. The mean HbA1c was 10.42% ± 2.33%, mean fasting blood glucose 199.60 ± 82.46 mg/dL, and mean postprandial blood glucose 236.70 ± 96.11 mg/dL. The participants' average number of insulin shots a day was 2.85 ± 1.11. The site of injection was incorrect in 20.17% of the patients; in 35.65%, the procedure of injecting was incorrect; and 11.97% did not follow injection site rotation. 18.80% of the patients presented with lipodystrophy or lipoatrophy. Conclusion: Improvement of insulin injection technique requires the involvement of all the key stakeholders in insulin therapy, these being diabetes educators and/or nurses, physicians, patients, and needle/device manufacturers. However, there is a need for clear guidance for diabetes educators and other health-care professionals so that they can, in turn, educate their patients to successfully self-manage their insulin therapy.

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Background: Despite massive vaccination programs implemented to abate COVID-19, breakthrough infections among the vaccinated individuals continue to be a source of worry. Aims and Objective: Therefore, our study aimed to investigate the severity of breakthrough and nonbreakthrough infections of SARS-CoV-2 post-COVID-19 vaccinations among health-care workers, COVID-19 frontline warriors, and the general population in South India. Materials and Methods: A survey was jointly conducted by Jothydev's Diabetes Research Centre and Sree Gokulam Medical College and Research Foundation (Thiruvananthapuram, Kerala, India), to assess the severity of nonbreakthrough and breakthrough infections of COVID-19 after vaccination, especially among health-care workers across South India. Results: Of the 225 vaccinated individuals who responded to the survey, 89.3% were vaccinated with Covishield, 8.9% were vaccinated with Covaxin, and 1.7% with other vaccines. One hundred and fifty-three respondents to the survey had COVID-19 infections. Of these, 82 (53.6%) COVID-19 infections were observed in the health care workers (partially and fully vaccinated) and other COVID-19 frontline warriors. One hundred and forty-two people who developed COVID-19 were vaccinated with Covishield, in which 55 (38.7%) developed COVID-19 after the first dose and 87 (61.3%) developed it after the second dose of vaccination. In the Covaxin group, six people (60%) were affected with COVID-19 after the first dose and 4 (40%) people after the second dose. Only one person out of the four vaccinated with other vaccines developed a breakthrough infection. 65 (72.9%) of the individuals vaccinated with Covishield and 2 (50%) of the individuals vaccinated with Covaxin, and one from other categories of vaccines had reported breakthrough infections, infections occurring ≥14 days after completing the recommended doses of COVID-19 vaccinations. Preexisting comorbidities in the people vaccinated with Covishield. Breakthrough infections included in people with diabetes (n = 14), diabetes and high blood pressure (n = 9), asthma (n = 2), and other diseases including (lung disease, malignancy, kidney diseases, and combined comorbidities) (n = 11), and one person with diabetes in Covaxin vaccinated with one person with diabetes and high blood pressure in the other vaccines group. Breakthrough infections cases (52.3%) were mild to moderate (44.5%) and did not require hospitalization. Conclusion: The incidence of severe or critical COVID-19 illness remained low in fully vaccinated patients, even among patients with comorbidities. Nevertheless, the public should follow strict COVID-19 preventive measures, regardless of vaccination status, to reduce transmission and exposure among persons who might not have achieved protective immunity after vaccination.

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There have been recent publications indicating the association between diabetic retinopathy (DR) and glucagon-like peptide receptor agonists (GLP-1RAs) raising the concern regarding the use of GLP-1RAs in patients with type-2 diabetes mellitus. After a thorough critical appraisal of those publications, it seems that the evidence generated has certain caveats which led to misinterpretation of the results. In this article, we aim to demystify the myths and bring out the facts in line with the totality of the evidence between the use of GLP-1Ras and DR.

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We report a case of a 55-year-old newly diagnosed Type 2 diabetes mellitus (T2DM) patient with elevated glycated hemoglobin (HbA1c) of 12.1%. He received care at Zest Online Diabetes Clinic after facing challenges with access to care. He received lifestyle and medical treatment with the Zest mobile application for 3 months. The Zest model of treatment focuses on nutrition, physical activity, medication, and education to support self-management. The Zest care delivery model also involved a multidisciplinary team of experts: A dietitian, endocrinologist, nurse, and a digital coach to provide quality care remotely. After 3 months of receiving care, he returned with an HbA1c of 5.3%, net weight loss of 1.3 kg, and also a reduction in medication. This case report provides preliminary evidence that the Zest model: carbohydrate restriction, physical activity, diabetes self-management education, and behavioral coaching can effectively and safely treat T2DM through a digital platform.

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Background: Patients with diabetes mellitus (DM) need to be regularly monitored for analyzing their levels of glycemic control as well as for ruling out the risk of hypoglycemia. Assessing the time in range (TIR) (70–180 mg/dL) is a novel measure of pointing out these risks. Aim: This research aims to detect hypoglycemia in routine clinical practice based on continuous glucose monitoring (CGM). Besides detecting hypoglycemia in patients with near-normal A1C levels, this study also aims to look at the incidence and occurrence of hypoglycemia in individuals with higher A1C. Methodology: HbA1c levels were recorded for n = 227 adult participants and used to categorize them into groups based on their levels of diabetes control (HbA1c groups of <7%, 7%–8%, 8%–9%, and >9%). Their 24-h blood glucose levels were measured through CGM with a flash glucose monitor (FGM) device. Data from the FGM device were downloaded, and TIR values in different participant groups were further determined. Statistical analysis of these results was done to calculate their significance in terms of P value. Results: 17.6% of participants had good glycemic control (HbA1c below 7%), 22.5% had HbA1c levels within the range of 7%–8%, 33.5% had their HbA1c within the range of 8%–9%, and 26% of the participants presented with poor glycemic control with HbA1c above 9%. Participants with HbA1c levels below 7% spent the maximum time below range (TBR) compared with participants in the other groups (P = 0.0016). Participants with poor glycemic control spent the minimum TBR (P = 0.0001). Those having HbA1c levels within the range of 7–8 (P = 1.00) and 8–9 (P = 0.0008) spent nearly 10% of their TBR indicating time spent in hypoglycemia and the risk of more severe hypoglycemia. No statistical differences in the time spent below range were found between male and female participants and based on treatment regimen. 77.5% of patients having A1C levels below 7%, 54% of patients with A1C levels between 7% and 8%, between 8-9%, and 40.6% of patients with A1C levels above 9% spent more than 5% of their TBR. Conclusion: In our research, it was found that although individuals with HbA1c levels below 7% were at maximum risk of hypoglycemia spending more than 5% of their TBR, patients with poor glycemic control also spent a significant amount of TBR. Thus, all patients with DM are at an increased risk of hypoglycemia regardless of their levels of glycemic control and the type of treatment regimen.

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Health inequalities have been a longstanding challenge for decades with widening disparities in recent years. Much focus is rightly placed on inequalities based on race/ethnicity, but it is clear that racial disparities and socioeconomic deprivation are interlinked. The connection between systematic and personal bias against individuals from the most deprived groups, irrespective of ethnicity, clearly exists. Socioeconomic deprivation appears to be an influential factor driving health disparities, with implicit bias directed against individuals living in poverty. This is reflected in access to diabetes technologies such as insulin pump therapy, continuous glucose monitoring systems, and automated insulin delivery where those from ethnic minority backgrounds and those in areas of highest deprivation are least able to access or benefit from such technological advancements. Inequalities are further reinforced by government cuts in spending. Between 2009 and 2020, net expenditure per person in local authorities in the 10% most deprived areas fell by 31% compared with a 16% decrease in the least deprived areas. These regressive cuts included a failure of health-care spending to rise in accord with historical patterns. Compounding the challenges were cuts to public health funding and reductions in welfare payments to families most in need. These widening health inequalities are unacceptable and unfair within a national health system where all individuals are entitled to the same level of care. Improved access to specialist diabetes care teams and to life-enhancing technologies could improve the health of all people with diabetes and reduce its human and financial cost.

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Introduction: The burden of diabetes mellitus (DM) is gradually increasing globally and in developing countries like India. According to the International Diabetes Federation 2019 report, around 77 million people in India are diagnosed with diabetes with a projected increase to 34 million by 2045. Appropriate implementation and practice of lifestyle measures like exercise plays a key role as a supporting factor in effective diabetes management. The main objective of the study was to determine the relation between the exercise barriers and level of disease perception on the disease among people with diabetes. Methodology: This is a correlational descriptive study conducted among patients with type 2 DM (T2DM), who are attendees of the medicine outpatient department of a tertiary care hospital in Bhubaneswar. The samples were selected through purposive sampling technique. A self-structured sociodemographic profile, Standardized Appraisal of Diabetes Scale, and Personal Diabetes Questionnaire were used to collect data from the participants. Results: The results showed that male (77 [60.2%] among the 128) patients are more susceptible to DM than the females. Majority of the study cohort had a negative appraisal on the DM with a mean value of 17.98 (standard deviation [SD] =1.29). While considering the exercise barriers, the majority of the patients had more exercise barriers with a high mean of 36.77 (SD = 1.04). Here, the correlation between the exercise barrier and level of perception shows a nonsignificant weak negative correlation. The cohort reported that their nonsupportive family and friends are the major exercise barriers with a mean value of 6. Conclusion: Exercise, together with medical nutrition therapy, forms the cornerstone of diabetes therapy. The study results identified a lot of barriers among patients with diabetes that hinders exercise in daily life, and it had a significant association with the diabetes control.

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Context: Monitoring blood glucose levels is an important aspect in the overall management of an individual with diabetes mellitus. Continuous glucose monitoring (CGM) system is an effective tool that enables physicians to do so by way of regular automated checks of sensor glucose (SG). Aims: In this article, we discuss in detail on how CGM technology works, practical aspects of its application and how CGM data are interpreted. We describe the different glucose sensors available in India and suggest when and whom to use them. We also evaluate the effectiveness of CGM-assisted titration of insulin dose in our hyperglycemic patients and discuss the results. Settings and Design: This is a single-center retrospective observational study of insulin-treated patients with diabetes attending the endocrinology outpatient department, who opted for a CGM-assisted insulin dose titration. Subjects and Methods: Monitoring was done using the Freestyle libre pro^™ CGM system and insulin doses were titrated on regular follow-ups every 3–4 days for a total of 2 weeks. Patients who had an average SG level of more than 250 mg/dl on day 1 of monitoring, and had CGM data for a minimum of 12 days were included (n = 73). Data were analyzed using CGM-specific glucometrics including average SG and estimated A1c (eA1c) reduction, and changes in the percentage time in range (TIR), time below range (TBR), and time above range (TAR). Statistical Analysis Used: Not applicable. Results: When compared to day 1, the last day (D12–14) of CGM-assisted insulin dose titration showed: 1. An average SG reduction of 164.1 mg/dl (321.34 mg/dl → 157.24 mg/dl). 2. An eA1c reduction of 4.98% (12.08% → 7.1%). 3. An average TIR improvement of 51.21% (3.8% → 55.01%). 4. An average TAR reduction of 62.06% (96.12% → 34.06%). 5. An average increase in TBR from 0% to 10.21%. Target TIR >70% was achieved by 31/73 patients on D12-14, compared to 0/73 on day 1. Target TAR <25% was achieved by 43/73 patients on D12-14, compared to 0/73 on day 1. Target TBR <5% was not achieved by 21/73 patients on D12-14 when compared to 0/73 on day 1. Conclusions: CGM is a novel, easy-to-use, useful technology easily available in India for all patients with diabetes. We have demonstrated that quick and effective glycemic reduction is possible with CGM-assisted insulin dose titration within a short period of 2 weeks.

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COVID-19 has bidirectional relationship with diabetes. In addition to the worsening of preexisting diabetes, a lot of new cases of diabetes are reported. Differentiation of newly detected diabetes from new-onset diabetes after COVID is associated with various challenges. We are proposing criteria for the diagnosis of New-onset diabetes after COVID, which will be useful for medical practitioners worldwide.

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Background: Cardiovascular (CV) risk assessment is the cornerstone for choosing the most appropriate antihyperglycemic agent. One of the major obstacles in the use of such scores is that the process is time-consuming, which is a deterrent in a busy clinic. The aim of the present analysis was to explore a means of reducing the number of inputs to make the scoring faster and more acceptable to physicians. Materials and Methods: We used the MARK survey dataset to assess the utility of the QRISK 3 CV risk score in the Indian population (n = 1538); participants were recruited from five zones (east, west, north, south, and central). Machine learning (ML) techniques were used to analyze the existing MARK data. The XGBoost algorithm was used to create the model needed to identify the clinical parameters of interest. Dimension reduction techniques were employed to identify the clinical parameters of importance based on the accrued gain values. As the final step, a confusion matrix was created to assess the model's accuracy and precision. Results: We identified 10 parameters of clinical interest that could predict the 10-year CV risk and were comparable with the QRISK 3 score (with 22 parameters). The parameters identified by ML were age, sex, body mass index, smoking status, blood pressure, treatment with antihypertensive agents, angina, total cholesterol, the total cholesterol/high-density lipoprotein ratio, and chronic kidney disease. This dimension reduction was possible with a model accuracy of 94.4%. Conclusion: There were 10 routinely assessed parameters identified with ML techniques that can assist physicians in determining the CV risk of type 2 diabetes patients within a short period of time.

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COVID-19 has bidirectional relationship with diabetes. In addition to the worsening of preexisting diabetes, a lot of new cases of diabetes are reported. Differentiation of newly detected diabetes from new-onset diabetes after COVID is associated with various challenges. We are proposing criteria for the diagnosis of New-onset diabetes after COVID, which will be useful for medical practitioners worldwide.

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