American Diabetes Association Research Articles

AimsReporting of impaired fasting glucose (IFG) prevalence and risk factors for progression to diabetes differs between studies, in part, due to the use of multiple definitions of the condition. We aimed to determine the prevalence of diabetes and IFG in men and identify risk factors for the progression to diabetes and regression to normoglycaemia.Materials and MethodsParticipants were from the Geelong Osteoporosis Study. Diabetes was defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L, self-report of diabetes and/or use of antihyperglycaemic medication. IFG was defined using both American Diabetes Association (IFG-ADA: FPG 5.6–6.9 mmol/L) and World Health Organisation (IFG-WHO: FPG 6.1–6.9 mmol/L) criteria. Prevalence of hyperglycaemia at baseline (2001–2006, 1170 men, 20–97 years) was age-standardised to the 2006 Australian population. Multivariable logistic regression models (n = 416) were used to identify risk factors for the progression to diabetes and regression to normoglycaemia over 15 years.ResultsAge-standardised prevalence of IFG-ADA was 18.2% (95% CI 15.7–20.7), 6.2% for IFG-WHO (95% CI 4.8–7.6) and 7.3% for diabetes (95% CI 5.8–8.8). Higher FPG, glycated haemoglobin, age, body fat percent and lower HDL cholesterol were associated with progression to diabetes, whereas younger age and higher HDL cholesterol were associated with regression. A 1.0 mmol/L increase in FPG resulted in a sixfold greater chance of progression to diabetes over follow-up (OR 6.44, 95% CI 2.97–13.94; p < 0.001). A prediction model containing age, FPG, HDL cholesterol and HbA1c predicted an optimal FPG cut point for progression of 5.3 mmol/L.ConclusionThis study reports cut points for predicting progression to diabetes that align with the ADA classification of IFG. These data may support future work investigating diabetes prevention strategies.

Sodium-glucose cotransporter2 inhibitors (SGLT2i) are a class of medications initially developed for glycemic control in type2 diabetes mellitus (T2DM) but found to have broader cardiometabolic impacts. In this review, we discuss the proposed mechanisms of action of SGLT2i and review important trials that have demonstrated improvements in cardiovascular outcomes. SGLT2i have demonstrated benefits in the treatment of major categories of cardiovascular disease (CVD) and have been shown to reduce major adverse cardiovascular events (MACE) in patients with diabetes and CVD or renal disease. Findings have been translated into recommendations in clinical guidelines by the American College of Cardiology (ACC), American Heart Association (AHA), European Society of Cardiology (ESC), and American Diabetes Association (ADA). It is important to consider a patient's comorbid conditions, as well as potential medication side effects, prior to initiating SGT2i. While large trials have established the cardiovascular (CV) and renal benefits of SGLT2i, a number of studies are now exploring their role in acute care settings and novel patient populations.

Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians and the National Diabetes Education Program. This series is intended to highlight best practices and strategies from programs and clinics that have successfully improved the quality of care for people with diabetes or related conditions. Each article in the series is reviewed and follows a standard format developed by the editors of Clinical Diabetes. The following article describes an initiative to improve the rate of lipid profile screening in youth with type 2 diabetes at a tertiary children’s hospital in Southern California.

BackgroundObesity is a major global health challenge, linked to cardiometabolic and neuropsychiatric disorders through mechanisms such as inflammation and insulin resistance. However, little is known about how adiposity and its longitudinal changes interact with glycemic status to shape neuropsychiatric health and brain structural vulnerability. Clarifying these relationships is of high importance, as both obesity and dysglycemia are modifiable risk factors that may jointly accelerate psychiatric disorder and brain aging.MethodsUsing UK Biobank data (n = 423,750, with 32,551 having brain MRI), we examined associations between obesity indicators (body mass index [BMI], waist circumference [WC], body fat percentage [BFP]) and changes in obesity status with incident neuropsychiatric disorders (stroke, dementia, Parkinson’s disease, depression, anxiety) and brain structural measures. Participants were stratified by glycemic status—normal glucose regulation (NGR), prediabetes (Pre-DM), and diabetes (DM)—based on American Diabetes Association criteria. Cox proportional hazards and linear regression models were used.ResultsHigher BMI, WC, and BFP were associated with increased risks of depression and anxiety across all glycemic groups, particularly in NGR. Abdominal obesity was linked to Parkinson’s disease risk in NGR. Conversely, BMI showed an inverse association with dementia in NGR, possibly due to reverse causality. Persistent obesity and weight gain were associated with higher depression and anxiety risks in NGR. In diabetes, higher BFP was strongly linked to reduced grey matter, thalamus, and hippocampus volumes and increased WMHs. This association with BFP represented the most robust imaging signal, highlighting the pronounced vulnerability of brain structure to excess adiposity in diabetes. Similar but weaker patterns were observed in prediabetes and NGR.ConclusionObesity, particularly persistent or increasing adiposity, adversely affects neuropsychiatric health and brain structure, and these effects are significantly modified by glycemic status. Our findings underscore the importance of considering glucose metabolism when assessing obesity-related brain risks, and suggest that early weight management and metabolic control may have broad benefits for preventing neuropsychiatric disorders and mitigating brain aging.

Abstract Background Measurement of HbA1c point-of-care testing (POCT) provides rapid test results during patient/doctor office visits. This added convenience also has potential for broader reach to low-access populations. The European Reference Laboratory for Glycohemoglobin (ERL) has seven different reference methods with different measurement principles which are calibrated with IFCC secondary reference material. Comparisons of the DCA Vantage and Atellica DCA HbA1c methods were analyzed as compared to the ERL value-assigned samples, which were designed to evaluate and standardize results across multiple POCT methods. Methods The DCA Vantage system HbA1c cartridges (CLIA-waived) and Atellica DCA HbA1c Dx (outside the United States) assays are based on a latex immunoagglutination inhibition methodology. To compare these methods a clinical specimen set was acquired from the ERL (N=40, value assigned by ERL). Method comparison studies were performed per CLSI EP09c 3rd edition, 2018. Two replicates of each of the 40 clinical samples were run on each system. All data were used for evaluation in this study. Value assigned samples were reviewed using both IFCC units (mmol/mol) and NGSP units (%), which were derived from the former. Statistical analysis of DCA Vantage vs ERL and Atellica DCA HbA1c vs ERL was performed using a linear mixed effects “means as outcomes” model and coefficient of determination (pseudo-R2). Analysis of the DCA Vantage vs Atellica DCA HbA1c methods was performed using weighted-Deming regression analysis. Results Comparison of the DCA Vantage to ERL methods of testing HbA1c level yielded y = 0.9726 x + 0.1766 % (y = 0.9726 x+ 1.2861 mmol/mol) at 4.62% to 10.69% (27.00 to 93.34 mmol/mol) with R2=0.9999. Also, comparing the Atellica DCA to ERL method of testing HbA1c levels yielded y = 0.9970 x + 0.0702 % (y = 0.9970 x+ 0.6995 mmol/mol) at 4.62% to 10.69% (27.00 to 93.34 mmol/mol) with R2=0.9983. Finally, comparison of the DCA Vantage to Atellica DCA methods of testing HbA1c levels, using weighted-Deming regression analysis, yielded y = 1.00 x + -0.01 % (y = 1.00 x+ 0.21 mmol/mol) at 4.65% to 10.76% (27.32 to 94.11 mmol/mol) with r=0.999. Medical decisions, based on American Diabetes Association, are made at 5.7%, marking the start of pre-diabetes, and up to 6.5% and higher, diagnosing Diabetes type 2 for most people. The 95% prediction ranges observed at these medical decision levels, as compared to the ERL method for the DCA Vantage and Atellica DCA, were determined: at 5.7% (5.40%,6.04% and 5.55%,5.96% respectively) and 6.5% (6.18%,6.81% and 6.35%,6.75%, respectively). Conclusion The Atellica DCA and DCA Vantage HbA1c assays strongly correlate to the European Reference Laboratory method and to each other.

Abstract Background Recent guidelines from the American Diabetes Association suggest that a glucose = 200 mg/dL, the presence of metabolic acidosis (pH =7.3), and a beta hydroxybutyrate (B-OHB) = 3 mmol/L are diagnostic for diabetic ketoacidosis (DKA). The determination of B-OHB is especially useful in identifying patients in DKA that are euglycemic (glucose &amp;lt; 200 mg/dL). Known instigators of euglycemic DKA include the use of GLP1 and SGL2 inhibitors, two antihyperglycemic agents that are increasingly prescribed to diabetic patients. The purpose of this study was to assess both the frequency in which patients with concern for DKA meet the new clinical criteria, and to assess the agreement relative to physician diagnosed DKA. Methods Patients presenting to the ED from 1/1/25-1/31/25 to with physician ordered POC ketones were included. B-OHB was assessed on an Abbott Precision Pro at the point of care. Results were extracted from the laboratory information system. Chart review was performed for all patients for diabetes diagnosis, and physician diagnosed acidosis at the time of their encounter. Clinical diagnosis of DKA was made at the discretion of the treating physician. Lab values closest to B-OHB were extracted including anion gap, glucose, HbgA1c, pH, and HCO3. Any use of medications known to influence glucose and ketone concentrations were included (i.e GLP1 inhibitors, SGL2 inhibitors, diuretics, etc.,). DKA criteria from clinical guidelines were assessed relative to physician diagnosed of DKA. Results There were 278 patients enrolled, of which 32 had type 1 diabetes (T1D), 243 had type 2 diabetes (T2D), and 3 had unspecific diabetes type. There was a correlation between B-OHB and anion gap (spearman r = 0.48; 0.37 to 0.58) HCO3 (-0.5; -0.64 to -.032) and glucose (0.27; 0.06 to 0.46). There were 34 patients that were diagnosed clinically with DKA with a median B-OHB of 4.3 (IQR:1.3-5.7) and 244 without DKA with a median of 0.2 (0.1-0.4). B-OHB had an ROC of 0.95 (95% CI: 0.92-0.98) for DKA. At a threshold of 3.0 mmol/L, the positive percent agreement with clinical adjudication was 61.8% (45.0-76.1), the negative percent agreement was 98.4% (95.9-99.4), the PPV was 84% and the NPV was 94.9%. In total there were 14 patients (5.3%) that met guideline definitions for DKA, all of which had a physician diagnosis of DKA. There were additional 20 patients that were diagnosed with DKA but did not fulfill criteria. Of these, 4 patients were diagnosed with euglycemic DKA, with an average glucose of 116 mg/dL and ketone concentrations of 6.1, 4.2, 1.3, and 0.8 mmol/L respectively. 3 of the 4 were observed to be on Empagliflozin. Conclusion The prevalence of DKA as defined by clinical guidelines is relatively rare in patients with clinical suspicion. However, many cases that were adjudicated clinically as DKA did not meet guideline definitions. Euglycemic DKA is rare, and of those diagnosed clinically, only 2 met the ketone threshold of 3 mmol/L, suggesting different thresholds may be necessary.

The link between obesity and metabolic dysfunction is well-established. However, the choice of an anthropometric index best reflective of risk remains debatable. This study aimed to evaluate the predictive performance of several indices for diabetes and hypertension in a population at risk for cardiovascular disease. Data from 1,537 participants was analyzed. The predictive value of 19 indices for diabetes and hypertension was evaluated via area under the receiver operating characteristic curve (AUC) analysis. Analyses were adjusted for major risk factors to evaluate the independent utility of each index. Modified versions of the American Diabetes Association (ADA) diabetes risk assessment tool were examined, where body mass index (BMI) was substituted for indices demonstrating strong or independent predictive values. The Deurenberg formula was the best predictor of diabetes in both male (AUC = 0.67; 95% CI 0.62-0.73) and female (AUC = 0.77; 95% CI 0.73-0.82) participants, and significantly better than BMI. Body roundness index (BRI; aAUC = 0.63; 95% CI 0.56-0.70), waist-to-height ratio (WHtR; aAUC = 0.63; 95% CI 0.57-0.70), and waist-to-height1/2 ratio (WHT.5R; aAUC = 0.63; 95% CI 0.57-0.70) showed independent predictive values for diabetes in female participants. The risk assessment tool's performance was improved when BMI was substituted for these indices. BMI (aAUC = 0.66; 95% CI 0.61-0.70), Deurenberg (aAUC = 0.66; 95% CI 0.61-0.70), and Gallagher (aAUC = 0.66; 95% CI 0.62-0.70) formulas were independent predictors of hypertension in male participants. Several indices showed promising performances for use in diabetes screening. Future research should focus on incorporating these indices in screening tools.

Abstract Background Hemoglobin A1c (HbA1c) is a widely used lab test to assist in diagnosing and managing diabetes. However, in patients with known disorders of red blood cell turnover and certain hemoglobin variants, this value is inaccurate. Current American Diabetes Association guidelines state that HbA1c should not be used to diagnose diabetes in these individuals. A 2021 publication by Sivasanskar showed there is a significant quality gap with inappropriate HbA1c test orders among those with sickle cell disease (SCD) at hundreds of healthcare facilities across the United States. We suspect this is also the case for glucose 6-phosphate dehydrogenase (G6PD) deficiency and thalassemias known to affect red blood cell turnover. Multiple recent publications have shown that HbA1c levels at all levels of glucose are much lower for those with G6PD deficiency than for controls. Since both SCD and G6PD deficiency are known to occur in African-Americans to a greater extent than Caucasians, we believe this could be a significant issue in our health care system leading to delayed diagnosis or inappropriate management of diabetes in this population. Methods Using retrospective electronic health record data from one children’s hospital, one additional hospital and several outpatient clinics in our health system, we examined &amp;gt;40,000 orders for glucose and alternate markers from 1955 unique patients with an ICD-10 code for SCD, thalassemia, or anemia caused by enzyme deficiency. The protocol for the study was approved by the Washington University IRB. The majority of these patients were diagnosed with sickle-cell disease or trait (79%) while only 11 (&amp;lt;1%) were diagnosed with G6PD deficiency and the remainder (20%) with thalassemia. Results Of the total orders examined, 95% were for glucose (either alone or as part of a panel with additional tests). For the remaining 5% of orders, 447 were for glucose tolerance testing (gestational), 21 for glucose tolerance testing (non-gestational), 1487 for HbA1c, and 55 for fructosamine. Twenty-nine percent of patients with SCD or trait had at least one HbA1c order and this percentage was higher (51%) in patients with a thalassemia. For the 11 patients with G6PD deficiency, 36% had a HbA1c order. Fructosamine orders occurred for only 25 unique patients, none of whom had G6PD or other anemia of enzyme disorders. Less than 1% patients with thalassemia and only 1.4% of patients with SCD or trait had an order for fructosamine. For the patients in whom fructosamine was ordered, 80% also had one or more HbA1c orders, including nine instances with both tests ordered during the same week. Conclusion The percentage of patients with a disorder of red blood cells and HbA1c orders is significant while fructosamine is rarely ordered. This suggests opportunities for electronic ordering interventions and/or additional provider education regarding appropriate use of alternate markers of glucose control in this group of patients.

Diagnosis and Phenotypes of Idiopathic Diabetes: A Systematic Review.

The relationship between first-trimester progesterone treatment and gestational diabetes.

Metabolic score for insulin resistance (METS-IR) as a predictor of gestational diabetes: Findings from a prospective Iranian cohort study.

ObjectiveThis study aimed to investigate the association of soluble death receptors (FAS, TNFR1, and TRAIL-R2) with β-cell function in individuals with naïve prediabetes and newly diagnosed, treatment – naïve type 2 diabetes, and to assess the strength of this association to determine the independent variable that contributes to the variance of HOMA-B.Methods and materialsThis was a cross-sectional study done at the Endocrine Clinics of National Hospital. There were two groups: group 1 included 49 newly diagnosed, drug-naive prediabetic patients, and group 2 consisted of 29 newly diagnosed, drug-naive,T2DM patients. Written informed consent was obtained from all participants. This study was approved by the Medical Ethics Committee of Damascus University (No. m/471 -12/5/2021) and registered with the Australian New Zealand Clinical Trials Registry (Trial ID: ACTRN12624001135505).Inclusion criteria included newly diagnosed prediabetic or T2DM subjects who had received no treatment, based on the 2015 American Diabetes Association criteria. Exclusion criteria entailed past histories of severe cardiovascular, renal, tumor, or autoimmune diseases and use of drug therapies including oral hypoglycemic agents.General and demographic information (Sex, age, BMI) was obtained, and blood samples were taken after fasting for 12 h. Fasting plasma glucose (FPG) levels were measured using an automatic analyzer (AMS, Italy). HbA1c levels were measured photometrically using the HemoCue (HbA1c 501 analyzer,America).Insulin levels were determined via an ELISA kit (Diametra, Italy), and soluble death receptors (TNFR1, Fas, TRAIL-R2) were measured using ELISA kits (Raybiotech, USA). The following formula calculates Homeostatic Model Assessment of Beta Cell Function( HOMA-B), HOMA-B (%) = [360 × basal insulin (µIU/mL)] / [basal glucose (mg/dL) – 63].Statistical analyses were carried out in SPSS version 25. Distribution of the data was carried out using the Kolmogorov–Smirnov test for normality. Student t test for independent samples were done for normally distributed data, while Mann–Whitney U test was used for nonnormal variables. The relationships between HOMA-B and FBG in addition to other variables with significance level were performed using linear regressions with p values < 0.05 were deemed to be statistically significant.ResultsThe levels of TNFR1, Fas, and TRAIL-R2 were significantly higher in T2DM compared with prediabetes (p < 0.0001). TNFR1 and Fas exhibited a strong negative correlation with HOMA-B in both groups. Regression analysis indicated that Fas, followed by TRAIL-R2, was the main predictor of β-cell function. They combined accounted for 60% and 42% of the HOMA-B variance in prediabetes and T2DM, respectively.ConclusionElevated soluble death receptor levels, particularly Fas, are a marker of impaired β-cell function in prediabetes and T2DM. These observations suggest that death receptors-mediated apoptosis may play a role in the progression of β-cell dysfunction from prediabetes to T2DM and point toward possible use of these markers as early indicators of β-cell dysfunction.

To determine the effects of first-degree family history of diabetes on diabetes incidence in Diabetes Prevention Program (DPP) and Diabetes Prevention Program Outcomes Study (DPPOS) participants. In the DPP, adults with prediabetes were randomized to an intensive lifestyle intervention, metformin, or placebo and followed for incident diabetes. On study completion 88% of eligible DPP participants reenrolled in DPPOS for long-term follow-up. The present analysis includes all 3,072 participants with family history information through DPPOS, with a median follow-up of 21 years (1,975 had parental history of diabetes [PH] [312 biparental, 947 maternal, 716 paternal], 226 had only sibling history [SH], and 871 denied any family history). The primary outcome is incident diabetes based on American Diabetes Association criteria, with adjustment for demographic and clinical variables, DPP randomization arm, and polygenic risk score (PRS). Adjusted hazard ratio (HR) was 1.21 (95% CI 1.06, 1.38) for any family history, 1.19 (1.04, 1.35) for PH, and 1.15 (0.91, 1.44) for SH. Biparental history conferred greater hazard (HR 1.44 [95% CI 1.22, 1.69]) than maternal (1.22 [1.08, 1.38]) or paternal (1.22 [1.08, 1.39]) diabetes history alone. PRS explained 32% of the association of any family history with diabetes risk. PH increased type 2 diabetes risk after DPP treatment group was controlled for. That effect was only partially explained by PRS, suggesting that rare gene variants, familial, and environmental factors may contribute to type 2 diabetes risk in people with prediabetes.

Purpose of the study: The aim of this literature review is to synthesize current knowledge on the clinical management of athletes with T2DM, focusing on pharmacological strategies, exercise recommendations, nutritional interventions, self-monitoring technologies, and interdisciplinary education to ensure safety and performance optimization. Materials and methods: A literature review was conducted using databases such as PubMed, Google Scholar, and Scopus. Articles published between 2000 and 2024 were included if they addressed physical activity, training strategies, medication management, or patient education in individuals with T2DM—particularly in athletic or physically active populations. Key publications included guidelines from the American College of Sports Medicine (ACSM), American Diabetes Association (ADA), and peer-reviewed reviews from Diabetes Spectrum, MDPI Sports, and Medical Sciences Sports Exercise. Results: The reviewed literature confirms that regular physical activity improves insulin sensitivity and glycemic control in patients with T2DM. However, exercise regimens must be personalized to avoid glycemic complications. Pharmacotherapy should consider the risk of hypoglycemia and dehydration, especially when using insulin or SGLT2 inhibitors. Nutritional strategies, such as pre-exercise carbohydrate intake and hydration protocols, are critical. Technological tools like continuous glucose monitoring (CGM) enhance real-time decision-making. Multidisciplinary education increases adherence and safety in diabetes care among athletes. Conclusions: Athletes with T2DM can achieve excellent glycemic control and high levels of performance if therapeutic strategies are personalized, evidence-based, and supported by education and technology. Further clinical studies are needed to develop sport-specific recommendations for this unique population.

The global prevalence of Diabetes Mellitus is rising; this complex metabolic disorder marked with hyperglycemia comes with increased morbidity and more associated health risks. Type 1 Diabetes Mellitus, an autoimmune disorder primarily affecting young individuals, lacks innovative pharmacological therapies. While current treatments for Type 2 Diabetes Mellitus-including lifestyle interventions and medications-can be effective, many patients still struggle with glycemic control. This review aims to highlight recent advances in diabetes mellitus management, emphasizing novel therapeutics and drug delivery systems that aim to decrease dosage frequency, target the manifestation of side effects, and enhance anti-diabetic effectiveness. We conducted a comprehensive review of over 300 articles published between 2017 and 2025, utilizing databases such as PubMed and ScienceDirect. Recent therapeutic innovations include nanocarrier-mediated drug delivery, microneedle patches, and mRNA- and gene-based systems. These technologies aim to improve glycemic control, reduce dosing frequency, and minimize side effects. The 2024 American Diabetes Association Standards of Care introduced updated diagnostic criteria and management recommendations, which are summarized herein. This review outlines key developments in pharmacological and delivery strategies of the past 5 years, targeting all types of diabetes. Special focus is placed on emerging therapies such as mRNA, nanotechnology, and innovative delivery systems, which may transform future diabetes management. The content is designed to support clinicians, researchers, and healthcare professionals in developing future therapeutic strategies.

Association of diabetes with sarcopenia in patients on hemodialysis: A nationwide cross-sectional study in Portugal.

Background/Objectives: Gut microbiota is profoundly influenced by dysglycemic states, including prediabetes (preDM) and type 2 diabetes (T2D). Although short-chain fatty acids (SCFAs) may serve as proxies reflecting these microbial changes, their predictive role remains elusive. This study aimed to evaluate the association between fecal SCFA concentrations and glycemic status (preDM and T2D), using individuals with normoglycemia (NonDM) as the reference group in a Mediterranean adult population. Methods: This study included a total of 88 participants from the Di@bet.es study who were classified into three groups according to the American Diabetes Association criteria: NonDM (45%), preDM (27%), and T2D (28%), respectively. We evaluated gut microbiota populations through massive sequencing and determined SCFAs concentration using gas chromatography–mass spectrometry. Adjusted multiple logistic regression models were used to estimate associations between SCFAs and metabolic status. Results: The mean age of subjects with preDM and T2D was approximately 68 years, older than that of NonDM participants (about 60 years). About 50% of the subjects in the NonDM and preDM groups were female, whereas in the T2D group, females represented about 25%. The analysis revealed that only fecal acetic acid was significantly reduced in T2D compared to NonDM (p = 0.036) and preDM (p = 0.018) groups. Remarkably, fecal acetic acid was negatively associated with T2D risk when taking preDM as the reference state (OR = 0.561 [95% CI: 0.371–0.846], p = 0.009). Intriguingly, fecal acetic acid was identified as a significant positive predictor of preDM risk, taking the NonDM group as reference (OR = 1.422; p = 0.028), while propionic acid was inversely associated with preDM (OR = 0.714; p = 0.028). Conclusions: Our analysis showed that fecal acetic acid levels were associated with a reduced risk of T2D but also with an increased risk of preDM; however, the biological relevance of these findings remains uncertain.

Continuous glucose monitoring: criteria for the diagnosis of type 2 diabetes mellitus with clinical obesity after gestational diabetes.

AimsSome studies found that the association of fasting blood glucose (FPG) or glycosylated haemoglobin (HbA1c) elevation with diabetic complications was not statistically significant after controlling for the confounding caused by 2‐h post‐load glucose (2hPG) elevation. Furthermore, inclusion of HbA1c as a diagnostic measure for diabetes has raised some concerns about over‐diagnosis and over‐treatment. This study aimed to quantify the contributions of 2hPG, FPG and HbA1c elevations to the prevalence of diabetes and pre‐diabetes respectively, by synthesising global data, which can serve as essential parameters in cost‐effectiveness analysis and inform updates of practice guidelines about prevention and control of diabetes.Materials and MethodsThe levels of 2hPG, FPG and HbA1c were classified as either ‘elevated’ or ‘normal.’ Each distinct combination of these markers (e.g., ‘elevated 2hPG, normal FPG and normal HbA1c’) defined a unique subgroup, resulting in a total of seven subgroups for both diabetes and pre‐diabetes. The contribution of 2hPG elevation to diabetes prevalence was calculated as its proportion among all diabetes cases; the same approach was applied to FPG and HbA1c elevations, as well as to pre‐diabetes prevalence. To retrieve global data, five electronic databases (i.e., PubMed, EMBASE, Web of Science, China National Knowledge Infrastructure and Wan Fang) were searched from their inception to February 2024. Studies that fulfilled the following criteria were considered eligible: (1) were conducted in adults without previously diagnosed diabetes; (2) were cross‐sectional studies or baseline surveys of cohort studies (which can be regarded as a special type of cross‐sectional studies); and (3) reported directly or allowed for calculation of the proportion of each subgroup out of all diabetes and/or the proportion of each subgroup out of all pre‐diabetes. A 10‐item tool selected from literature was used to appraise the quality of included data. The proportions of each subgroup among all diabetes cases were meta‐analysed across eligible studies with the random‐effects model using the MetaXL software. Similar meta‐analyses were conducted for pre‐diabetes.ResultsThirty‐two eligible studies were identified, with 25 reporting on newly detected diabetes (n = 289 094) and 15 on pre‐diabetes (n = 221 988) and the majority of them using identical diagnostic cutoffs proposed by the American Diabetes Association (ADA). The mean age of participants ranged from 24 to 68 years (median of mean ages: 51). Twenty‐four studies (75%) were assessed as at low risk for ≥7 out of the 10 quality items. In the general population, based on the ADA criteria, the weighted prevalence of diabetes and pre‐diabetes was 15% and 69%, respectively. Among those with newly detected diabetes (n = 24 214), 69% had elevated 2hPG, 44% elevated FPG and 61% elevated HbA1c; 7% had isolated FPG elevation; 20% had isolated HbA1c elevation. Among those with newly detected pre‐diabetes (n = 133 621), 33% had elevated 2hPG, 51% elevated FPG and 68% elevated HbA1c; 17% had isolated FPG elevation; 34% had isolated HbA1c elevation. Sensitivity analyses stratified by participant comorbidities and study quality produced results consistent with the main findings.ConclusionsThe largest contributors to the prevalence of diabetes and pre‐diabetes are 2hPG and HbA1c, respectively. Isolated FPG and HbA1c elevations account for over a quarter of all diabetes and more than half of all pre‐diabetes.

To validate the Diabetes Risk Assessment in Dentistry Score (DDS) in a US population-based sample and compare its performance with the American Diabetes Association (ADA) risk calculator and the Leicester Risk Assessment (LRA). Data were obtained from the National Health and Nutrition Examination Survey (NHANES) covering the 2009-2014 cycles. The study focused on participants aged 40 years and older who included complete data for DDS and ADA risk score assessment. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), while decision curve analysis (DCA) was used to evaluate the clinical utility of the model. Of the 6259 participants included, the average age was 57.3 years (±12.0 years, range: 40-80 years) and the sample was evenly distributed by sex (50.8% female). DDS showed limited discriminative ability with an AUC of 0.64 (95% confidence interval [CI]: 0.62-0.65), and DCA analysis showed higher net benefit than the 'Treat None' strategy across most probability thresholds, indicating added clinical value in decision making. The ADA risk calculator and LRA showed an AUC of 0.61 (95% CI: 0.59-0.63) and 0.631 (95% CI: 0.615-0.647), which were below the DDS performance. The DDS demonstrated acceptable performance for American adults aged 40 years or older, and showed marginally superior performance compared with the ADA diabetes risk calculator and LRA, highlighting its potential utility in dental practice settings as a complementary screening tool.