With the widespread adoption of CGM (continuous glucose monitoring), glycemic control can now be evaluated across a continuous time axis rather than at isolated time points. This shift has led to the emergence of time-based glycemic metrics, which quantify the proportion of time glucose levels remain within predefined ranges and provide a more comprehensive assessment of glycemic exposure. Among these metrics, time in range (TIR; 70–180 mg/dL) has become the standard indicator for overall glycemic control, as it integrates both hypoglycemic and hyperglycemic exposure and shows robust associations with microvascular complications independent of HbA1c. However, TIR alone may be insufficient to discriminate qualitative differences in glycemic control among individuals who have already achieved stable or near-target glucose levels. In this context, time in tight range (TITR; 70–140 mg/dL), reflecting glucose levels closer to normal physiology, has been proposed as a complementary metric. This article discusses the conceptual framework and clinical implications of time-based glycemic metrics, with a particular focus on the distinct and complementary roles of TIR and TITR.
Alongside time in range (TIR, 70–180 mg/dL), an established continuous glucose monitoring (CGM) metric, time in tight range (TITR, 70–140 mg/dL) was originally proposed to reflect glucose exposure closer to physiological normoglycemia, although its clinical applicability has often been considered limited to intensive glycemic control settings. Physiological CGM data show that individuals with normoglycemia spend most of their time below 140 mg/dL, and longitudinal studies in high-risk populations demonstrate that time above 140 mg/dL predicts progression to diabetes. While concerns have been raised that increases in TITR may coincide with higher glycemic variability, particularly in hyperglycemic states, this interpretation is context dependent. In recent analyses, at an HbA1c level of approximately 7.0%, TIR varied widely according to glycemic variability, whereas TITR converged within a relatively narrow range (about 47~48%), indicating a variability-independent reference zone. Moreover, TITR outperformed TIR in predicting attainment of the HbA1c 7.0% target. TITR is already widely recognized as a superior metric in settings of tight glycemic control. Beyond this established role, emerging evidence suggests that TITR also provides complementary and clinically meaningful information across common glycemic targets and hyperglycemic states, thereby enhancing interpretation of glucose distribution beyond conventional CGM metrics.
Type 2 diabetes is increasingly recognized as a heterogeneous syndrome rather than a single disease. Clinical phenotype-based clustering, exemplified by the Ahlqvist model, has demonstrated that subgroups defined by simple variables exhibit distinct complication risks and treatment responses, yet this approach is limited by information loss due to categorization, static classification, and poor transferability across ethnicities. Genome-wide association studies have identified more than 1,200 independent risk signals and revealed genetically driven pathophysiological clusters enriched in cell-type-specific regulatory regions. In addition, partitioned polygenic risk scores show significant associations with vascular complications across ancestries. Multi-omics integration—spanning metabolomics, transcriptomics, epigenomics, and the gut microbiome—has further uncovered subtype-specific signatures that single-omics approaches cannot capture, though the translational gap between complex omics panels and clinically actionable biomarkers remains substantial. Artificial intelligence (AI) and machine learning methods, including ensemble models, deep survival analysis, foundation models trained on continuous glucose monitoring data, and multimodal fusion architectures, are enabling the integration of high-dimensional, heterogeneous data for complication prediction with performance surpassing conventional risk calculators. Recent studies combining polygenic risk scores with clinical variables in deep-learning frameworks have demonstrated significant improvements in predicting cardiovascular and renal complications, with evidence that genetic risk modifies the benefit of standard interventions. However, most models have been developed in European-ancestry populations, and their predictive accuracy diminishes substantially when applied to East Asian populations, where nonobese phenotypes and beta-cell dysfunction predominate. Korea possesses unique strengths to address these challenges, including nationwide health-insurance data, population-based genomic cohorts, and regulatory-approved AI-based retinal biomarkers that could serve as platforms for integrating genomic information. Realizing AI-driven precision diabetes care will require the concurrent development of population-specific prediction models, prospective multi-institutional validation, and robust data-governance frameworks.
While many healthcare professionals and diabetes educators recognize the critical need to screen for and intervene in health-related social needs (HRSNs) among patients with diabetes, the practical implementation of screening and referral to community social services remains limited in clinical settings. Various obstacles hinder effective screening, including a lack of community resources, time constraints for educators, limited reimbursement systems, workforce shortages, and a lack of specialized training. Beyond these systemic issues, a significant barrier is the shame and stigma patients may experience when discussing sensitive socioeconomic vulnerabilities. The process of screening for HRSNs should be viewed not merely as data collection, but as a therapeutic intervention designed to deeply understand the patient’s life and build a foundation of trust. This article introduces the “empathic inquiry” approach, developed by the Oregon Primary Care Association (OPCA), as a strategy to avoid shame and stigma while mitigating psychological resistance during the screening and referral process. Engaging in empathetic dialogue regarding social needs is a valuable therapeutic tool in its own right, fostering patient engagement and strengthening therapeutic alliances even when immediate external resource linkage is not possible.
Medical data can be categorized into structured, unstructured, time-series, image/video, and multimodal data, each of which imposes distinct constraints and offers specific opportunities for artificial intelligence (AI) model design, learning strategies, and validation methods. Recent studies have demonstrated that multimodal approaches significantly enhance predictive performance and clinical usability compared with single-modality models, while emphasizing the critical importance of data quality, governance, and interoperability. This review summarizes the major learning paradigms employed in medical AI, including supervised, unsupervised, semi-supervised, self-supervised, transfer, and reinforcement learning, from the perspectives of data characteristics and clinical context. Labeling costs, data bias, and the need for explainability play a decisive role in the selection of appropriate learning strategies. In particular, self-supervised learning and large-scale language models are increasingly recognized as central drivers of future developments in medical AI. The roles of medical AI are categorized into expertimitating AI, which supports and reproduces expert clinical judgment, and exploratory (emergent) AI, which transcends human empirical limitations by deriving optimized data-driven policies. Moreover, medical AI is expanding beyond diagnostic and therapeutic support into healthcare administration, education, and research, and this review proposes that its ultimate evolution should be toward augmented intelligence grounded in human–AI collaboration.
As of 2024, the population aged 65 and older accounts for 19.2% of South Korea’s total population. This figure is projected to rise steadily, surpassing 30% in 2036 and 40% by 2050. The period of living with illness is also significant, recorded at 16.2 years for men and 20.2 years for women. Notably, the prevalence of diabetes has increased in both genders, reaching 13.3% for men (a 1.3% increase) and 7.8% for women (a 0.9% increase). Self-management of glycemic control in diabetic patients encompasses self-care behaviors such as diet, medication, exercise, and self-monitoring of blood glucose. However, elderly patients may hold negative views toward active self-management; they often find it difficult to change lifelong habits and may believe their remaining life expectancy is not long enough to warrant concern over long-term complications. Furthermore, they face challenges such as polypharmacy (taking multiple medications), physical changes, cognitive impairment, economic difficulties, and shifting family structures. The implementation of active self-care behaviors and self-efficacy plays a pivotal role in successful blood glucose management. These factors not only prevent or delay complications but also positively impact the quality of life for diabetic patients. Therefore, during patient education, it is essential to guide elderly patients toward available resources and support their utilization. This approach will improve their quality of life, ensuring a healthy old age and a dignified end of life.
Diabetes and obesity require sustained, behavior-centered management, yet real-world care is constrained by limited visit time, access barriers, and challenges in long-term adherence. Digital therapeutics (DTx.) deliver evidence-based, software-driven interventions and are increasingly regulated as SaMD (Software as a Medical Device). This review summarizes the evidence and implementation considerations of DTx. in diabetes and obesity. In diabetes, DTx. improve HbA1c in randomized trials, with larger effects in type 2 diabetes. In obesity, regulated app-based programs have demonstrated clinically relevant weight loss, but attrition and intervention heterogeneity remain challenges. DTx. can complement standard care by extending structured therapeutic support into daily life; priorities include long-term effectiveness, workflow integration, equity, and governance of safety/cybersecurity and software change.
The worldwide incidence of diabetes mellitus is steadily increasing, largely attributable to environmental changes, including shifts in dietary patterns and food environments. Notably, global consumption of ultra-processed foods (UPFs) has increased rapidly in recent decades. This review summarizes the concept of UPFs using the NOVA classification and examines the association between UPF intake and diabetes. Evidence from multiple prospective cohort studies and recent meta-analyses consistently demonstrate that higher UPF intake is associated with a significantly increased risk of incident diabetes. Given the difficulty of completely avoiding UPFs in modern eating environments, dietary strategies emphasizing substitution of UPFs with unprocessed or minimally processed foods, or less processed alternatives, may be feasible and effective. Accordingly, this review proposes practical guidance for managing UPF intake across three stages—food purchasing, cooking, and consumption—to support diabetes prevention and management. Incorporating the level of food processing into food choices and overall eating patterns may represent a meaningful approach to diabetes risk management. The stage-based strategies presented here may serve as practical guidance for nutrition education and counseling in clinical settings.
Diabetic kidney disease (DKD) is a common and serious complication of diabetes, leading to endstage kidney disease and heightened cardiovascular (CV) risk. Traditional management, including strict glycemic and blood pressure control with renin–angiotensin–aldosterone system (RAAS) blockade, has only partially mitigated progression. Recent therapeutic advances, notably sodium glucose cotransporter 2 (SGLT2) inhibitors and the non-steroidal mineralocorticoid receptor antagonist (MRA) finerenone, have transformed the DKD treatment landscape. Finerenone selectively antagonizes the mineralocorticoid receptor, reducing pro-inflammatory and pro-fibrotic signaling in kidneys and heart. In the phase 3 FIDELIO-DKD trial (patients with type 2 diabetes and chronic kidney disease [CKD]), finerenone significantly slowed CKD progression and reduced a composite kidney outcome by 18% relative risk versus placebo. The FIGARO-DKD trial (including earlier-stage CKD) demonstrated a significant reduction in major CV events with finerenone. Pooled analysis confirmed improved cardiorenal outcomes. The efficacy of finerenone is additive to RAAS blockers and SGLT2 inhibitors, as combination therapy further decreases albuminuria without excessive adverse effects. Compared to steroidal MRAs (spironolactone), finerenone shows a more favorable safety profile—lower risk of hyperkalemia and no anti-androgenic side effects. Incorporating finerenone into DKD management marks a new paradigm, offering improved renal and CV protection on top of existing standard care. Proper patient selection (estimated glomerular filtration rate ≥ 25 mL/min/1.73 m2, persistent albuminuria despite maximal RAAS blockade, normal serum potassium) and monitoring for hyperkalemia are essential. Future research should explore finerenone in broader CKD populations, optimal combination strategies, and long-term outcomes to further refine DKD therapy.
Diabetic retinopathy (DR) is one of the most common and vision-threatening complications of diabetes, affecting approximately one-third of patients. Systemic management of diabetes plays a crucial role in delaying the onset and progression of DR. Intensive glycemic control, as demonstrated in the DCCT (Diabetes Control and Complications Trial) and the UKPDS (United Kingdom Prospective Diabetes Study), significantly reduces long-term risk of retinopathy. However, rapid glucose lowering, particularly in patients with preexisting DR, may lead to an early worsening phenomenon. This transient deterioration is thought to be related to hypoglycemia, hemodynamic changes, and synergistic effects of insulin and vascular endothelial growth factor. In addition to glucose control, strict management of blood pressure and lipid profiles, including use of fenofibrate, further reduces the risk of progression. The role of glucagonlike peptide-1 receptor agonists in DR remains controversial, with early signals of worsening observed in SUSTAIN-6 but not consistently demonstrated in meta-analyses. Current evidence emphasizes the long-term benefits of early intensive systemic management, despite short-term risks. A patient-specific multifactorial management approach effectively reduces the risk of onset and progression of DR.
Gestational diabetes mellitus (GDM) is a significant health issue that extends beyond a simple pregnancy complication, posing both short- and long-term risks for mothers and their children. When not properly managed, GDM can lead to increasing susceptibility to chronic diseases later in life. These outcomes highlight the need for early detection, prevention, and comprehensive intervention. Addressing GDM effectively requires more than medical treatment alone; it demands a multidisciplinary approach that incorporates psychosocial, educational, and community-based support. Pregnant women with GDM often experience greater psychological distress than non-diabetic pregnant women. Common mental health challenges include anxiety, depression, guilt, shame, and reduced self-esteem. These issues arise from the daily pressures of blood glucose control and the physical and emotional changes associated with pregnancy. Dietary restrictions, reduced social participation, and societal stigma can intensify feelings of loneliness and isolation. Limited access to reliable information and a lack of strong social support systems further hinder effective self-management. To improve outcomes, GDM require integrated, personalized welfare services such as nutrition and exercise education, counseling, mental health support, community resource linkage, and caregiving assistance from the moment of diagnosis. Collaborative efforts among hospitals, local governments, and national agencies can create an accessible and practical service system that enhances quality of life and supports healthy fetal development. Currently, national support for GDM remains limited to coverage of consumable medical supplies, leaving many women burdened by the ongoing time and financial demands of treatment and management, as well as challenges in maintaining employment.
Diabetic retinopathy (DR) remains a leading cause of visual loss among working-age adults. However, DR screening adherence is suboptimal due to inconvenient care pathways and fragmented information flow between internal medicine and ophthalmology. To address these challenges, we describe the design, implementation, and early experience of AfterNOON, a patient-centered digital platform that coordinates DR screening across internal medicine in general hospitals and local eye clinics. Design principles included patient-experience optimization, minimal clinician workload, and closed-loop care coordination using standardized reports, electric medical record system integration, and a messengerbased patient channel. Since AfterNOON service launch in March 2024 with 11 clinics, the network expanded to over 230 local ophthalmology clinics and multiple tertiary/general hospitals nationwide. Patients can book screening without application installation; ophthalmologists submit standardized reports that are returned to patients and referring physicians; internal medicine teams can track outcomes through a dashboard. Early feedback indicates shorter referral-to-test intervals and higher visibility of results. These outcomes demonstrates that a lightweight, interoperable digital pathway centered on patient experience and care coordination can enhance DR screening adherence and information return to internal medicine. Wider evaluation using effectiveness–acceptability–sustainability metrics and policy alignment is warranted.
The prevalence of sarcopenia is significantly higher in older adults with type 2 diabetes mellitus (T2DM) than in non-diabetic populations, contributing to functional decline, poor glycemic control, and increased morbidity and mortality. This review summarizes current evidence and clinical nutrition strategies for the prevention and management of sarcopenia in older adults with T2DM. Energy deficiency accelerates muscle protein breakdown, and adequate caloric intake ≥ 30 kcal/kg/day is recommended. Protein intake of 1.0~1.2 g/kg/day, evenly distributed across meals, supports muscle synthesis and function. Vitamin D supplementation and omega-3 fatty acids may have synergistic benefits when combined with adequate protein intake and exercise. In sarcopenic obesity, a hypocaloric but protein-preserving diet and resistance training are crucial. Adherence to a Mediterranean-style dietary pattern, emphasizing vegetables, whole grains, fish, and unsaturated fats, is associated with lower frailty and better physical performance. Integrated multidisciplinary approaches involving medicine, nutrition, exercise, and nursing are essential for optimizing outcomes. Future research should focus on optimal nutrient targets and long-term combined interventions in this growing population.
Exercise is an effective lifestyle intervention for managing diabetes. It improves body composition, muscle strength, insulin sensitivity, and glycated hemoglobin levels. However, fluctuations in blood glucose during exercise can discourage participation among individuals with diabetes. The direction and extent of these changes depend on pre-exercise glucose levels, insulin dosage, medications, and exercise type, intensity, and duration. Aerobic exercise lowers glucose by enhancing insulin sensitivity for up to 72 hours post-activity, whereas resistance training may reduce the risk of exercise-induced hypoglycemia. During resistance exercise, catecholamines (epinephrine and norepinephrine) are released, stimulating hepatic glucose production, inhibiting peripheral glucose uptake, and increasing lactate formation through anaerobic glycolysis. Consequently, blood glucose may decrease only slightly or even rise transiently during and after exercise recovery. Resistance training enhances glucose regulation by promoting GLUT4 translocation and increasing muscle mass, leading to improved insulin sensitivity, reduced adiposity, and greater muscular strength. Individualized resistance training with proper glycemic monitoring is therefore an essential component of optimal diabetes management.
Diabetic neuropathy (DN) is one of the most common and debilitating complications of diabetes, and its prevalence is expected to increase with the growing global diabetes burden. DN is regarded as a neurodegenerative disorder; however, a definitive disease-modifying therapy remains unavailable. Therefore, early recognition and appropriate management are crucial to prevent irreversible nerve damage and to improve clinical outcomes. Despite advances in diagnostic techniques, the early detection of DN remains challenging. Research has been devoted to identifying novel biomarkers that reflect the complex pathophysiological mechanisms underlying DN. Following the early metabolic disturbances triggered by nutritional excess, multiple pathogenic pathways become activated, leading to chronic lowgrade inflammation. Numerous studies have explored inflammatory biomarkers, including cytokines, chemokines, and immune receptors, which play key roles in the development and progression of DN. Furthermore, growing evidence highlights the pivotal involvement of immune cells mediating neuro– immune crosstalk, supported by molecular data elucidating the underlying mechanisms. This review summarizes recent advances in the discovery of novel biomarkers for early diagnosis of DN, with a lowparticular emphasis on neuroinflammation-related pathways.
Generally, task performance and cognitive function begin to decline from around the age of 80, and dementia prevalence rises steeply thereafter. Nevertheless, multiple daily injections (MDIs) are still prescribed for many patients aged ≥ 80. MDI can improve glycemic control compared with a single injection or none; however, the risks of hypoglycemia and adverse events also increase. Therefore, when considering MDI in very old adults, a comprehensive assessment of physical function, performance status, and cognition is essential. In patients with cognitive impairment, initiating therapy with a longacting insulin and gradually transitioning to MDI may enhance adherence. Above all, expansion of community and social resources is needed to support patients who cannot self-inject.
Sarcopenia significantly affects older adults, particularly those with diabetes, contributing to increased risks of disability and mortality. Early detection and prevention are critical. Guidelines from EWGSOP2 (European Working Group on Sarcopenia in Older People 2) and AWGS (Asian Working Group for Sarcopenia) recommend initial screening using handgrip strength, calf circumference, gait speed, and tools such as the SARC-F (strength, assistance with walking, rising from a chair, climbing stairs, and falls) questionnaire. Resistance and aerobic exercise are key interventions, improving muscle mass, strength, and insulin sensitivity. Exercise regimens should be individualized, consideringcomorbidities such as neuropathy, cardiovascular disease, and hypoglycemia. Nutritional strategies are equally essential, recommending; higher protein intake (1.2~1.5 g/kg/day), leucine-rich branched-chain amino acids, vitamin D, omega-3 fatty acids, and HMB (β-hydroxy β-methylbutyrate) supplementation, particularly given the frequent nutritional deficiencies in elderly diabetic patients. Lifestyle modifications—including smoking cessation, alcohol moderation, improved sleep hygiene, and psychological support—further enhance prevention. A multidisciplinary approach involving endocrinologists, dietitians, physiotherapists, and social workers is vital to optimize outcomes. Although no pharmacological treatment has been approved, emerging therapies such as testosterone analogs, selective androgen receptor modulators, myostatin inhibitors, ghrelin agonists, and antidiabetic agents like metformin and glucagon-like peptide-1 receptor agonists show promise. Comprehensive and proactive management of sarcopenia should be prioritized as an integral component of diabetes care.
Effective glycemic control is essential for preventing complications in patients with diabetes. In recent years, postprandial hyperglycemia has been recognized as a risk factor for cardiovascular disease, in addition to glycated hemoglobin. This has led to growing interest in the prevention of ‘glucose spikes’ which refer to sharp increases in blood glucose level after meals. Postprandial glycemic responses are influenced by multiple factors, including the quantity and structural characteristics of carbohydrates consumed, the rate of gastric emptying, and the digestion and absorption of carbohydrates. Therefore, strategies to prevent glucose spikes should include regulating total carbohydrate intake, selecting low-glycemic-index carbohydrate sources, and limiting rapidly digestible and absorbable sugars. A balanced meal containing appropriate proportions of carbohydrates, proteins, and fats is recommended to delay gastric emptying and stimulate insulin secretion. Increased dietary fiber intake also contributes to improved glycemic control. Short-chain fatty acids and polyphenols, which are involved in various metabolic processes, help attenuate postprandial glycemic responses. Thus, incorporating vegetables and fruits rich in dietary fiber and polyphenols into the diet is advisable as part of a comprehensive dietary strategy for glycemic control in individuals with diabetes.
Diabetes is a chronic disease with increasing global prevalence, yet its psychological impact remains underrecognized in clinical practice. Individuals with diabetes have a 2~3 times higher risk of suicide than the general population, yet structured mental health screening and intervention remain limited. Recent Korean data indicate that suicide incidence in type 1 diabetes is even higher than in cancer, underscoring the urgent need for targeted approaches. Suicidal risk is particularly increased among patients with low income, mid-range disease duration (2~9 years), and comorbid depression. However, current diabetes management models rarely integrate mental health assessment or intervention. This opinion highlights the necessity of routine psychological screening, interprofessional collaboration, and structural policy reforms to address suicide risk in people with diabetes. It calls for expanding national disease management programs to incorporate mental health metrics, supporting healthcare providers, and establishing digital behavioral alert systems. A comprehensive approach to diabetes management should encompass both physical complications and mental health, recognizing the full spectrum of patient needs. Managing the ‘invisible complication’ of suicide is the next frontier in comprehensive diabetes management.
Background: Pharmacists are less often involved in diabetes education than primary clinicians. This study aims to evaluate the impact of medication education provided by pharmacists to caregivers at a type 1 diabetes camp for children and adolescents.Methods: A type 1 diabetes camp for children and adolescents living in Busan, Ulsan, and Gyeongsangnam-do regions of Republic of Korea was held. The caregivers received a 30-minute lecture about diabetes medication on the second day of the camp, followed by a survey measuring the levels of understanding and satisfaction with the education on a 5-point Likert scale.Results: There were 35 caregivers of 35 children who received the camp’s medication education and agreed to participate in the study. Among the children, 42.9% (n=15) had been diagnosed with diabetes less than one year prior. Only 17.1% of caregivers (n=6) reported having previously received medication education from a pharmacist. The caregivers’ understanding of diabetes medications before education was rated as 17 of a total score of 25 points, and the understanding after education was 19.77 points. There was no significant difference in understanding scores according to subject characteristics. Regarding satisfaction, 34 caregivers responded with a mean score of 18 of 20.Conclusion: Pharmaceutical education for caregivers at a diabetes camp was shown to be effective. It is expected that patient understanding of medications will further improve through repeated participation of both patients and pharmacists in the diabetes camp.
