The integration of artificial intelligence (AI) into health care has revolutionized clinical diagnostics, treatment protocols, and patient management. AI-driven innovations enhance medical efficiency, enabling precision medicine, and automating administrative workflows. However, this rapid advancement has triggered an intensely competitive race among multinational corporations, research institutions, and startups, each striving for dominance in AI-driven healthcare solutions. For example, Google’s DeepMind, IBM Watson Health, and various biotech firms have been engaged in AI-driven drug discovery and diagnostics, leading to significant market consolidation. This review explores the evolving landscape of AI in healthcare, addressing the economic, geopolitical, and regulatory factors that shape its trajectory. It critically examines intellectual property conflicts, ethical dilemmas, and disparities in AI deployment, highlighting concerns over algorithmic bias, data accessibility, and the monopolization of healthcare technologies. For instance, the acquisition of AI-powered healthcare startups by major tech companies limits competition and data access, thereby restricting innovation. Furthermore, the study underscores the societal trust challenges posed by AI’s “black box” decision-making and the ambiguity surrounding legal accountability. While AI presents unparalleled opportunities for improving global healthcare, its long-term impact hinges on balancing innovation with ethical governance, equitable access, and patient-centered medical care. Real-world AI successes, such as AI-assisted radiology tools improving early cancer detection and machine learning models optimizing personalized diabetes management, demonstrate AI’s potential benefits. This review calls for transparent AI policies, robust regulatory frameworks, and fair data-sharing initiatives to ensure AI serves as a tool for advancing public health rather than a vehicle for corporate or geopolitical supremacy.
There is an increasing need to investigate fasting outcomes for Muslims with type 2 diabetes (T2D) who choose to fast during Ramadan. Although sulfonylureas (SUs) are widely used in T2D, concerns persist regarding their risk of hypoglycemia during prolonged fasting. Modern second-generation agents, particularly Gliclazide modified release (MR), have demonstrated improved pharmacokinetic stability and a lower risk of hypoglycemia compared with older sulfonylureas, such as glibenclamide. This study seeks to understand the reported fasting outcomes of patients using second-generation sulfonylureas during Ramadan. The Diabetes and Ramadan (DaR) global survey was conducted in 14 countries and investigated patients with T2D who fasted during Ramadan in 2020 and 2022. The survey was administered by health care practitioners after Ramadan and compared those who used second-generation sulfonylureas with those deemed to be in the low-risk group (LRG). After excluding individuals with cardiovascular, renal, or foot complications, as well as those treated with insulin, 5,294 individuals were included in the analysis (mean age ≈53 years). Participants on sulfonylureas and those in the LRG showed similar fasting adherence, with over 90% completing the Ramadan fast. Among sulfonylurea users, Gliclazide MR had the highest proportion of fasting for the full month (77%) and the lowest reported incidence of hypoglycemia (10.3%), comparable to the LRG (7.9%, p = 0.2). Fasting outcomes among participants using second-generation sulfonylureas were comparable to those on lower-risk oral agents during the Ramadan fasting period. Gliclazide MR demonstrated the most favorable profile, with the highest fasting blood glucose control rate and the lowest frequency of hypoglycemia among the sulfonylurea group. These findings support the safe use of modern sulfonylureas during Ramadan, provided it is under appropriate medical supervision. Further prospective and randomized studies are warranted to confirm the comparative safety and optimize treatment selection for individuals with T2D who fast.
Objective: The cardiovascular outcomes and value in the real world with GLP-1 receptor agonists study characterized demographics and medication usage patterns in treatment intensified (add-on to metformin) adults with type 2 diabetes (T2D) in India. Materials and Methods: This study was a retrospective, real-world analysis of data extracted from medical records at five healthcare centers across India during the study period (January 30, 2008–December 31, 2017). Data were collected at 6/12 months before baseline in the overall population and among subgroups defined by glucose-lowering agent (GLA) classes; summarized descriptively. Results: Data from 1000 adults were collected in reverse chronological order. At baseline, the mean age, glycated hemoglobin (HbA 1c ), T2D duration, and body mass index (BMI) of the study population were 51.4 years, 7.9%, 2.6 years, and 27.7 kg/m 2 , respectively. Overall, 81.4% of patients received one GLA and 71.4% had HbA 1c ≥7.0%. Among the subgroups, patients in sulphonylurea subgroup were older (52.5 years), those in glucagon-like peptide-1 receptor agonists (GLP-1RA) subgroup had higher BMI (35.9 kg/m 2 ), and, those in insulin subgroup had higher HbA 1c (9.5%); most frequently prescribed GLA postmetformin was dipeptidyl peptidase-4 inhibitors (42.7%). The utilization of GLP-1RAs/sodium-glucose cotransporter-2 inhibitors was low ( n = 10 and 145, respectively). Among the subgroups, receiving ≥3 GLAs was more common in the GLP-1RA subgroup. Conclusion: Glycemic control in Indian patients with T2D remains inadequate, with underutilization of GLAs with cardiovascular (CV) benefits. Further studies are needed to better estimate CV disease risk in this population and to grasp the reasons for underutilizing GLAs for relevant comorbidities. Trial registration: NCT05542420.
The 18 th International Conference on Advanced Technologies and Treatments for Diabetes (ATTD 2025) highlighted groundbreaking advancements – including closed-loop insulin delivery systems, artificial intelligence (AI)-integrated monitoring platforms, continuous glucose and ketone monitoring (CGM/CKM), and regenerative cellular therapies – that are redefining global diabetes care. While these innovations significantly enhance glycemic control, patient autonomy, and clinical decision-making, equitable access remains a critical challenge, particularly in low- and middle-income countries (LMICs). The objective of the study was to synthesize key clinical and technological insights from ATTD 2025, with a focus on their applicability in LMICs. This review evaluates the efficacy and adoption potential of automated insulin delivery (AID) systems, AI-driven decision tools, next-generation CGM/CKM devices, and beta-cell replacement strategies, while also examining regulatory, infrastructural, and ethical considerations – using India as a case study for scalable implementation. Early adoption of AID systems in pediatric populations demonstrates substantial improvements in time-in-range (TIR) and psychosocial outcomes. CKM technologies offer earlier detection of diabetic ketoacidosis, and AI-powered platforms are driving personalized, real-time diabetes management. Despite these benefits, widespread adoption in LMICs is constrained by fragmented regulatory frameworks, affordability issues, limited reimbursement, and health system disparities. India’s emerging regulatory reforms, AI sandbox programs, and expanding digital health infrastructure suggest a replicable model for contextualizing global innovations. Bridging the diabetes technology divide in LMICs requires a systems-level approach that aligns innovation with affordability, digital readiness, and policy support. Multisectoral collaboration – including regulatory adaptation, public–private partnerships, and patient-centered design – is essential to achieving inclusive, sustainable access to next-generation diabetes care.
The coronavirus disease 2019 (COVID-19) pandemic became superimposed on the pre-existing obesity and diabetes mellitus (DM) pandemics. Since COVID-19 infection alters the metabolic equilibrium, it may induce pathophysiologic mechanisms that potentiate new-onset DM, and we evaluated this issue. A systematic review of the literature published from the 1 January 2020 until the 20 July 2023 was performed (PROSPERO registration number CRD42022341638). We included only full-text articles of both human clinical and randomized controlled trials published in English and enrolling adults (age > 18 years old) with ongoing or preceding COVID-19 in whom hyperglycemia was detected. The search was based on the following criteria: “(new-onset diabetes mellitus OR new-onset DM) AND (COVID-19) AND adults”. Articles on MEDLINE (n = 70) and the Web of Science database (n = 16) were included and analyzed by two researchers who selected 20 relevant articles. We found evidence of a bidirectional relationship between COVID-19 and DM. This link operates as a pathophysiological mechanism supported by epidemiological data and also by the clinical and biological findings obtained from the affected individuals. The COVID-19 pandemic raised the incidence of DM through different pathophysiological and psychosocial factors.
