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The impact of global diabetes prevention efforts has been modest despite the promise of landmark diabetes prevention trials nearly twenty years ago. While national and regional initiatives show potential, challenges remain to adapt large-scale strategies in the real-world that fits individuals and their communities. Additionally, the sedentary lifestyle changes during the COVID-19 pandemic and guidelines that now call for earlier screening (e.g., US Preventative Task Force) will increase the pool of eligible adults worldwide. Thus, a more adaptable, person-centered approach that expands the current toolkit is urgently needed to innovate and revitalize our approach to diabetes prevention. This review identifies key priorities to optimize the population-level delivery of diabetes prevention based on a consensus-based evaluation of the current evidence among experts in global translational programs; key priorities identified include (1) participant eligibility, (2) intervention intensity, (3) delivery components, (4) behavioral economics, (5) technology, and (6) the role of pharmacotherapy. We offer a conceptual framework for a broader, person-centered approach to better address an individual’s risk, readiness, barriers, and digital competency.

ImportanceInterindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glycemic index or load and low-carbohydrate diet interventions have mixed weight loss outcomes. A precision nutrition approach that estimates personalized PPGR to specific foods may be more efficacious for weight loss.ObjectiveTo compare a standardized low-fat vs a personalized diet regarding percentage of weight loss in adults with abnormal glucose metabolism and obesity.Design, Setting, and ParticipantsThe Personal Diet Study was a single-center, population-based, 6-month randomized clinical trial with measurements at baseline (0 months) and 3 and 6 months conducted from February 12, 2018, to October 28, 2021. A total of 269 adults aged 18 to 80 years with a body mass index (calculated as weight in kilograms divided by height in meters squared) ranging from 27 to 50 and a hemoglobin A1c level ranging from 5.7% to 8.0% were recruited. Individuals were excluded if receiving medications other than metformin or with evidence of kidney disease, assessed as an estimated glomerular filtration rate of less than 60 mL/min/1.73 m2 using the Chronic Kidney Disease Epidemiology Collaboration equation, to avoid recruiting patients with advanced type 2 diabetes.InterventionsParticipants were randomized to either a low-fat diet (Main Outcomes and MeasuresThe primary outcome was the percentage of weight loss from baseline to 6 months. Secondary outcomes included changes in body composition (fat mass, fat-free mass, and percentage of body weight), resting energy expenditure, and adaptive thermogenesis. Data were collected at baseline and 3 and 6 months. Analysis was based on intention to treat using linear mixed modeling.ResultsOf a total of 204 adults randomized, 199 (102 in the personalized group vs 97 in the standardized group) contributed data (mean [SD] age, 58 [11] years; 133 women [66.8%]; mean [SD] body mass index, 33.9 [4.8]). Weight change at 6 months was −4.31% (95% CI, −5.37% to −3.24%) for the standardized group and −3.26% (95% CI, −4.25% to −2.26%) for the personalized group, which was not significantly different (difference between groups, 1.05% [95% CI, −0.40% to 2.50%]; P = .16). There were no between-group differences in body composition and adaptive thermogenesis; however, the change in resting energy expenditure was significantly greater in the standardized group from 0 to 6 months (difference between groups, 92.3 [95% CI, 0.9-183.8] kcal/d; P = .05).Conclusions and RelevanceA personalized diet targeting a reduction in PPGR did not result in greater weight loss compared with a low-fat diet at 6 months. Future studies should assess methods of increasing dietary self-monitoring adherence and intervention exposure.Trial RegistrationClinicalTrials.gov Identifier: NCT03336411

Pleural biopsy findings offer greater diagnostic sensitivity in malignant pleural effusions compared with pleural fluid. The adequacy of pleural biopsy techniques in achieving molecular marker status has not been studied, and such information (termed "actionable" histology) is critical in providing a rational, efficient, and evidence-based approach to diagnostic investigation.What is the adequacy of various pleural biopsy techniques at providing adequate molecular diagnostic information to guide treatment in malignant pleural effusions?This study analyzed anonymized data on 183 patients from four sites across three countries in whom pleural biopsy results had confirmed a malignant diagnosis and molecular profiling was relevant for the diagnosed cancer type. The primary outcome measure was adequacy of pleural biopsy for achieving molecular marker status. Secondary outcomes included clinical factors predictive of achieving a molecular diagnosis.The median age of patients was 71 years (interquartile range, 63-78 years), with 92 of 183 (50%) male. Of the 183 procedures, 105 (57%) were local anesthetic thoracoscopies (LAT), 12 (7%) were CT scan guided, and 66 (36%) were ultrasound guided. Successful molecular marker analysis was associated with mode of biopsy, with LAT having the highst yield and ultrasound-guided biopsy the lowest (LAT vs CT scan guided vs ultrasound guided: LAT yield, 95%; CT scan guided, 86%; and ultrasound guided, 77% [P = .004]). Biopsy technique and size of biopsy sample were independently associated with successful molecular marker analysis. LAT had an adjusted OR for successful diagnosis of 30.16 (95% CI, 3.15-288.56; P = .003) and biopsy sample size an OR of 1.18 (95% CI, 1.02-1.37) per millimeter increase in tissue sample size (P .03).Although previous studies have shown comparable overall diagnostic yields, in the modern era of targeted therapies, this study found that LAT offers far superior results to image-guided techniques at achieving molecular profiling and remains the optimal diagnostic tool.

Background: One of the current methods to diagnose prediabetes and predict diabetes incidence is based on 2-h plasma glucose (2-hPG) value following 75-g oral glucose tolerance test. Evidence demonstrates that 1-hour post-load plasma glucose (1-hPG) ≥ 155 mg/dl (8.6 mmol/L) in those with normal glucose tolerance at 2-hPG is highly predictive for T2D incidence. We conducted a health economic analysis to estimate long-term cost-effectiveness of using 1-hPG as compared to 2-hPG to screen and assess diabetes risk. Methods: The main outcome of the study was cost per quality-adjusted life-year (QALY) gained. We used a Monte Carlo-based Markov simulation model to simulate long-term effects of the two screening strategies on clinical and cost-effectiveness outcomes. The base case model included 20.000 simulated patients over 35-years. Transition probabilities were retrieved from landmark studies. Direct medical costs were sourced from the literature and inflated to 20Euros. Results: In the lifetime analysis, 1-hPG was projected to increase the number of years free from disease (2yr/patient) ; to delay the onset of T2D (1yr/patient) ; to reduce the incidence of T2D complications (0.6 Relative Risk/patient) and to increase the QALY gained (0.58/patient) . Though testing the 1-hPG resulted in higher initial costs owing to a larger number of preventive treatments, long-term diabetes and complications costs were reduced leading to -31,225,719.82€ saving over a lifetime as compared to 2-hPG. The incremental cost-effectiveness ratio was -8,214.7€ per each QALY gained for the overall population. Conclusions: Screening prediabetes by using 1h-PG is feasible and cost-effective resulting in QALYs gained and reduced costs. Notwithstanding the higher initial costs of 1-hPG compared to 2-hPG, due to the incremental number of preventive treatments, long-term diabetes and complications costs were reduced expecting an overall cost saving of -8,214.7€ per each QALY gained. Disclosure M.Andellini: None. M.Manco: None. M.Esposito: None. A.Tozzi: None. M.Bergman: None. M.Ritrovato: None.

Purpose: Although commonly used, HbA1c is insensitive for diagnosing prediabetes and diabetes. Glycemic variability (GV) or a 1-hour plasma glucose level (1-h PG) ≥ 155 mg/dL (8.6 mmol/L) during a 75-gram oral glucose tolerance test (OGTT) better identifies individuals with dysglycemia. The objectives were to (1) compare continuous glucose monitoring (CGM) with the OGTT for detecting dysglycemia in high-risk subjects with HbA1c < 5.7% (39 mmol/mol), and (2) correlate the 1-h PG with CGM-derived GV indices. Research Design and Methods: Subjects (n=15) with a HbA1c < 5.7% (39 mmol/mol) and at least one other risk factor for type 2 diabetes such as overweight, obesity, hypertension, or hyperlipidemia were recruited. A 2-h OGTT was performed within 3-7 days of CGM insertion, which was worn up to 14 days. Results: The average age was 50 ± 14 years, with the majority of participants being men (80%) and Caucasian (67%). The mean HbA1c was 5.3±0.2% (34 mmol/mol). The 1-h PG was highly correlated with 1-h CGM glucose levels (ρ=0.881, pConclusion: 1-h interstitial CGM glucose and 1-h PG can detect dysglycemia in high-risk subjects with HbA1c < 5.7% (39 mmol/mol). CGM may be an alternative screening tool for glucose disorders.

Resume Le prediabete est une anomalie metabolique frequemment rencontree. Son depistage est primordial, sachant qu’il est associe a un risque d’evolution vers le diabete « vrai » et/ou d’autres complications, en particulier cardiovasculaires. Le diagnostic de prediabete repose aujourd’hui sur des mesures glycemiques (glycemie a jeun et/ou a la 120e minute d’une surcharge orale en glucose) et/ou sur le dosage de l’hemoglobine glyquee (HbA1c). Plusieurs travaux suggerent que ce mode de diagnostic identifie le prediabete deja (trop) tard dans l’histoire naturelle de la dysglycemie. Une glycemie superieure a 155 mg/dL (8,6 mmol/L) a la 60e minute de l’epreuve d’hyperglycemie orale permet un diagnostic plus precoce, avec des dividendes en termes de prediction du risque de diabete, de maladies cardiovasculaires, et de mortalite. Cette approche pourrait donc etre une alternative rationnelle a la mesure de la glycemie a la 120e minute, en particulier en cas de discordance clinique et/ou biologique des tests de « premiere ligne » (glycemie a jeun ; HbA1c). Elle devrait aussi permettre une intervention therapeutique plus rapide avant le stade de prediabete patent, tel qu’il est defini a ce jour par les societes savantes.

For over 100 years, the oral glucose tolerance test (OGTT) has been the cornerstone for detecting prediabetes and type 2 diabetes (T2DM). In recent decades, controversies have arisen identifying internationally acceptable cut points using fasting plasma glucose (FPG), 2-h post-load glucose (2-h PG), and/or HbA1c for defining intermediate hyperglycemia (prediabetes). Despite this, there has been a steadfast global consensus of the 2-h PG for defining dysglycemic states during the OGTT. This article reviews the history of the OGTT and recent advances in its application, including the glucose challenge test and mathematical modeling for determining the shape of the glucose curve. Pitfalls of the FPG, 2-h PG during the OGTT, and HbA1c are considered as well. Finally, the associations between the 30-minute and 1-hour plasma glucose (1-h PG) levels derived from the OGTT and incidence of diabetes and its complications will be reviewed. The considerable evidence base supports modifying current screening and diagnostic recommendations with the use of the 1-h PG. Measurement of the 1-h PG level could increase the likelihood of identifying high-risk individuals when the pancreatic s-cell function is substantially more intact with the added practical advantage of potentially replacing the conventional 2-h OGTT making it more acceptable in the clinical setting.

Procyclicality of fiscal policy is a common feature in emerging markets, by contrast with high‐income economies, and leads to greater business‐cycle amplitudes. We investigate potential causes of fiscal procyclicality, including a host of economic and institutional variables of especial import in emerging markets. We employ dynamic panel methods in a large sample of countries to investigate what factors are associated with fiscal cyclicality. We find that fiscal procyclicality is mainly due to procyclical fluctuations in government investment expenditure. In addition, we find that procyclical fiscal policy is positively associated with government debt levels, terms‐of‐trade volatility, and costs of foreign borrowing, while negatively associated with better government efficiency. Only a weak association is found between International Monetary Fund program participation and fiscal procyclicality. Finally, we find that certain fiscal rules are associated with lower fiscal procyclicality and, in particular, balanced‐budget rules may help mitigate the adverse cyclicality effects of high terms‐of‐trade volatility and government debt burdens in emerging markets.

Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians, Inc., 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 the establishment of a Diabetes Prevention Clinic for veterans with prediabetes.

Introduction: There is limited research examining dietary changes in adults with prediabetes who are following a diet personalized to predict postprandial glycemic response (PPGR). Objective: We compared dietary changes in subjects randomized to a low-fat, one-size-fits-all diet ( Standardized ) or to a diet personalized to minimize PPGR ( Personalized ). Methods: Dietary data collected to-date were analyzed from the Personal Diet study, a clinical trial to compare two behavioral weight loss interventions in adults with prediabetes or early-stage type 2 diabetes. All subjects had resting energy expenditure (REE) measured at baseline using indirect calorimetry. Both arms were instructed to restrict energy intake (-500 kcal/day, based on REE and a physical activity factor of 1.4), log daily dietary intake with a smartphone app, and attend scheduled behavioral counseling sessions. The Standardized arm received app feedback about energy and fat intake, while the Personalized arm received app feedback about energy intake and meal specific predicted PPGR determined from a gut microbiome-based machine learning algorithm. At baseline, 3 months, and 6 months, subjects completed one 24-hour dietary recall using the Automated Self-Administered 24-hour Dietary Assessment Tool. Total energy, total carbohydrate, total sugars, fiber, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, and protein were measured using the USDA Food and Nutrient Database for Dietary Studies 2011-2012. Macronutrient intakes were analyzed as percentage of energy (%E). Linear mixed modelling, with random intercepts and slopes and an unstructured covariance pattern, was used to analyze dietary changes within- and between-arms from baseline to 3 and 6 months. Fixed effects were included for study arm, time period, and interaction of study arm and time period. A random effect was included for subjects. Models were adjusted for age and sex. Results: Dietary assessments were completed at baseline (n=66 Personalized ; n=65 Standardized ), 3 months (n=50 Personalized ; n=36 Standardized ), and 6 months (n=47 Personalized ; n=39 Standardized ). The Personalized arm had a greater reduction than the Standardized arm in energy (β: -342 kcal; 95% CI: -672, -12) and %E from carbohydrate (β: -6.2; 95% CI: -11.7, -0.6) and sugars (β: -4.9; 95% CI: -8.8, -1.0) from baseline to 3 months, but there were no between-arm differences in dietary measures at 6 months. Within-arm, Personalized had decreases in energy (β: -327 kcal; 95% CI: -546, -108) and %E from carbohydrate (β: -4.6; 95% CI: -8.2, -0.9) from baseline to 3 months. In the Standardized arm, %E from sugars increased from baseline to 3 months (β: 3.0; 95% CI: 0.02, 5.9). Conclusions: Personalized had greater reductions than Standardized in energy and %E from carbohydrate and sugars over the first 3 months of the intervention, but dietary changes were similar by 6 months.

Individuals with high 1-hour post-load glucose (1-h PG 155 mg/dl; 8.6 mmol/l) during an oral glucose tolerance test are at increased risk of type 2 diabetes (T2D) and cardiovascular complications, hepatic steatosis, and mortality. However,the clinical relevance of 1-h PG for the severity of hepatic fibrosis risk remains undefined.Cross-sectional data of the CATAMERI study (n = 2335) were analyzed. Participants underwent anthropometric measurements, liver enzyme determinations, cardiometabolic profiling, and a75-gram oral glucose tolerance test, including fasting, 1-h and 2-h PG determinations and measurement of FIB-4 score to assess degree of hepatic fibrosis. Multivariable logistic regression analysis was performed to evaluate risk of advanced hepatic fibrosis with worsening glycemic status.We stratifiedthe study group into 6 categories based on glycemic status: normal glucose tolerance (NGT) 1h-PG Low, NGT 1h-PG High, iIFG 1h-PG Low, iIFG 1h-PG High, IGT, and newly detected T2D. Anthropometric and cardiometabolic profiles worsened gradually with glycemic status. Moreover, compared to NGT-1h-PG Low group, worsening glycemic status was significantly associated with the severity of fibrosis, independent of other significant clinical risk factors.1-PG is a valuable tool for stratifying subjects with NGT or IFG at heightened risk of hepatic fibrosis requiring further evaluation with elastography.

Introduction: Individuals with obesity and diabetes have increased risk for atherosclerosis; contributed by chronic systemic inflammation and elevated glycemic variability (GV). Bariatric surgery reduces circulating inflammatory markers. We aimed to determine the differences in GV and the expression of inflammatory genes from circulating white blood cells (WBC) after sleeve gastrectomy (SG) in those with and without non-insulin dependent diabetes. Methods: We conducted a prospective cohort study in subjects with obesity and type 2 diabetes (n=10) and subjects with obesity and no diabetes (n=11). Research visits occurred before SG and 6 months postoperatively. Elevated GV was defined by oral glucose tolerance test derived 1-h plasma glucose ≥155 mg/dL and elevated continuous glucose monitor derived GV index-MAGE (reference range 0-2.8 mmol/l). Bulk RNA-sequencing was performed on total WBCs, isolated neutrophils, monocytes, and lymphocytes to analyze genetic expression changes in chronic 6-month weight loss from baseline. Results: At 6 months, SG caused equivalent weight loss from baseline in both groups (22%). However, HbA1c, 1-h plasma glucose, and MAGE levels were different after SG between both groups. HbA1c decreased by 3.0±1.3% in the diabetes group (p94% of total genes) were different between both groups. Furthermore, our gene set analysis showed downregulated expression of WBC genes enriched in inflammatory pathways primarily in subjects without diabetes. Conclusion: Diabetes dampens the weight-loss induced changes to transcriptomes from WBC subsets that contribute to cardiovascular disease. Elevated GV after SG may contribute to these attenuated changes.

BackgroundIt is critical to assess implementation fidelity for complex interventions to understand the reasons for their success or failure. However, few interventions systematically report implementation evaluation. Therefore, we conducted a concurrent process evaluation of CHORD (Community Health Outreach to Reduce Diabetes), a pragmatic, cluster-randomized, controlled trial to test the impact of a Community Health Workers (CHW) led, health coaching intervention on preventing incident type 2 Diabetes Mellitus (DM). MethodsThe study population included primary care (PC) patients with prediabetes at 2 safety-net hospitals - VA NY Harbor and Bellevue (BH). PC teams were randomized to receive the one-year intervention or usual care. Of the 559 patients in the intervention group to date, 79.4% completed an intake survey, constituting the analytic sample for fidelity assessment. The Conceptual Framework for Implementation Fidelity (CFIF) was applied to measure implementation fidelity and factors moderating fidelity of four core intervention components: patient goal setting, education topic coaching, PC visits, and referrals to address social determinants of health, using descriptive statistics and regression models.ResultsBH contributed 60.0% of the sample and VA contributed 40.0%. Content adherence was high for three components with nearly 80.0% of patients setting >1 goal, having >1 PC visit and receiving coaching on >1 education topic. Only 45.0% patients received >1 referral. After adjusting for patient gender, language, race, ethnicity, and age, the study site moderated adherence to goal setting (77.4% BH vs. 87.7% VA), educational coaching (78.9% BH vs. 88.3% VA), number of successful CHW-patient encounters (6 BH vs 4 VA) and percent of patients receiving all four components (41.1% BH vs. 25.7% VA). ConclusionsThe CFIF enabled analysis of implementation fidelity of a complex, behavioral intervention. The fidelity of CHORD implementation varied across its four components and was moderated by site. Despite implementation in a research setting, interventions may not completely adhere to their core components, which can influence outcomes. Our study emphasizes the importance of examining implementation fidelity of interventions and of assessing moderating factors. Our study also empirically tested the CFIF using quantitative concurrent intervention fidelity evaluation.Trial registration: The trial was registered with ClinicalTrials.gov on 12/30/2016 and the registration number is NCT03006666. The link to trial registration is: https://clinicaltrials.gov/ct2/show/NCT03006666

Objectives To describe challenges and lessons learned in conducting a remote behavioral weight loss trial. Methods The Personal Diet Study is an ongoing randomized clinical trial which aims to compare two mobile health (mHealth) weight loss approaches, standardized diet vs. personalized feedback, on glycemic response. Over a six-month period, participants attended dietitian-led group meetings via remote videoconferencing and were encouraged to self-monitor dietary intake using a smartphone app. Descriptive statistics were used to report adherence to counseling sessions and self-monitoring. Challenges were tracked during weekly project meetings. Results Challenges in connecting to and engaging in the videoconferencing sessions were noted. To address these issues, we provided a step-by-step user manual and video tutorials regarding use of WebEx, encouraged alternative means to join sessions, and sent reminder emails/texts about the WebEx sessions and asking participants to join sessions early. Self-monitoring app-related issue included inability to find specific foods in the app database. To overcome this, the study team incorporated commonly consumed foods as “favorites” in the app database, provided a manual and video tutorials regarding use of the app and checked the self-monitoring app dashboard weekly to identify nonadherent participants and intervened as appropriate. Among 135 participants included in the analysis, the median attendance rate for the 14 remote sessions was 85.7% (IQR: 64.3%–92.9%). Conclusions Experience and lessons shared in this report may provide critical and timely guidance to other behavioral researchers and interventionists seeking to adapt behavioral counseling programs for remote delivery in the age of COVID-19.

Prediabetes affects at least 1 in 3 adults in the U.S. and 1 in 5 in Europe. Although guidelines advocate aggressive management of lipid parameters in diabetes, most guidelines do not address treatment of dyslipidemia in prediabetes despite the increased atherosclerotic cardiovascular disease (ASCVD) risk. Several criteria are used to diagnose prediabetes: impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and HbA1c of 5.7-6.4%. Individuals with prediabetes have a greater risk of diabetes, a higher prevalence of dyslipidemia with a more atherogenic lipid profile and an increased risk of ASCVD. In addition to calculating ASCVD risk using traditional methods, an OGTT may further stratify risk. Those with 1-hour plasma glucose ≥8.6 mmol/L (155 mg/dL) and/or 2-hour ≥7.8 mmol/L (140 mg/dL) (IGT) have a greater risk of ASCVD. Diet and lifestyle modification are fundamental in prediabetes. Statins, ezetimibe and PCSK9 inhibitors are recommended in people requiring pharmacotherapy. Although high-intensity statins may increase risk of diabetes, this is acceptable because of the greater reduction of ASCVD. The LDL-C goal in prediabetes should be individualized. In those with IGT and/or elevated 1-hour plasma glucose, the same intensive approach to dyslipidemia as recommended for diabetes should be considered, particularly if other ASCVD risk factors are present.

Accruing evidence indicates that accumulation of advanced glycation end products (AGEs) and activation of the receptor for AGEs (RAGE) play a significant role in obesity and type 2 diabetes. The concentrations of circulating RAGE isoforms, such as soluble RAGE (sRAGE), cleaved RAGE (cRAGE), and endogenous secretory RAGE (esRAGE), collectively sRAGE isoforms, may be implicit in weight loss and energy compensation resulting from caloric restriction.We aimed to evaluate whether baseline concentrations of sRAGE isoforms predicted changes (∆) in body composition [fat mass (FM), fat-free mass (FFM)], resting energy expenditure (REE), and adaptive thermogenesis (AT) during weight loss.Data were collected during a behavioral weight loss intervention in adults with obesity. At baseline and 3 mo, participants were assessed for body composition (bioelectrical impedance analysis) and REE (indirect calorimetry), and plasma was assayed for concentrations of sRAGE isoforms (sRAGE, esRAGE, cRAGE). AT was calculated using various mathematical models that included measured and predicted REE. A linear regression model that adjusted for age, sex, glycated hemoglobin (HbA1c), and randomization arm was used to test the associations between sRAGE isoforms and metabolic outcomes.Participants (This study demonstrates a novel link between RAGE and energy expenditure in human participants undergoing weight loss.This trial was registered at clinicaltrials.gov as NCT03336411.

For over 100 years, the oral glucose tolerance test (OGTT) has been the cornerstone for detecting prediabetes and type 2 diabetes (T2DM). In recent decades, controversies have arisen identifying internationally acceptable cut points using fasting plasma glucose (FPG), 2-h post-load glucose (2-h PG), and/or HbA1c for defining intermediate hyperglycemia (prediabetes). Despite this, there has been a steadfast global consensus of the 2-h PG for defining dysglycemic states during the OGTT. This article reviews the history of the OGTT and recent advances in its application, including the glucose challenge test and mathematical modeling for determining the shape of the glucose curve. Pitfalls of the FPG, 2-h PG during the OGTT, and HbA1c are considered as well. Finally, the associations between the 30-minute and 1-hour plasma glucose (1-h PG) levels derived from the OGTT and incidence of diabetes and its complications will be reviewed. The considerable evidence base supports modifying current screening and diagnostic recommendations with the use of the 1‐h PG. Measurement of the 1‐h PG level could increase the likelihood of identifying high-risk individuals when the pancreatic ß-cell function is substantially more intact with the added practical advantage of potentially replacing the conventional 2‐h OGTT making it more acceptable in the clinical setting.

Many health care providers screen high-risk individuals exclusively with an HbA1c despite its insensitivity for detecting dysglycemia. The 2 cases presented describe the inherent caveats of interpreting HbA1c without performing an oral glucose tolerance test (OGTT). The first case reflects the risk of overdiagnosing type 2 diabetes (T2D) in an older African American male in whom HbA1c levels, although variable, were primarily in the mid-prediabetes range (5.7-6.4% [39-46 mmol/mol]) for many years although the initial OGTT demonstrated borderline impaired fasting glucose with a fasting plasma glucose of 102 mg/dL [5.7 mmol/L]) without evidence for impaired glucose tolerance (2-hour glucose ≥140-199 mg/dl ([7.8-11.1 mmol/L]). Because subsequent HbA1c levels were diagnostic of T2D (6.5%-6.6% [48-49 mmol/mol]), a second OGTT performed was normal. The second case illustrates the risk of underdiagnosing T2D in a male with HIV having normal HbA1c levels over many years who underwent an OGTT when mild prediabetes (HbA1c = 5.7% [39 mmol/mol]) developed that was diagnostic of T2D. To avoid inadvertent mistreatment, it is therefore essential to perform an OGTT, despite its limitations, in high-risk individuals, particularly when glucose or fructosamine and HbA1c values are discordant. Innate differences in the relationship between fructosamine or fasting glucose to HbA1c are demonstrated by the glycation gap or hemoglobin glycation index.

Objective: Glycemic variability (GV) and 1 hour plasma glucose (1-h PG) ≥ 8.6 mmol/L during a 75-gram oral glucose tolerance test (OGTT) are associated with increased risk for type 2 diabetes (T2D). GV may be overlooked in high-risk individuals. The objectives of this study are: (1) to determine if continuous glucose monitoring (CGM) using the Abbott Freestyle Libre Pro can replace the OGTT in high-risk subjects with HbA1c < 5.7%; and (2) to determine if GV indices correlate with the OGTT-derived 1-h PG ≥ 8.6 mmol/L. Methods: Subjects were recruited with a HbA1c < 5.7% and at least one other risk factor including: overweight or obesity, PCOS, fatty liver, hypertension, family history of T2D, or history of gestational diabetes. The CGM, placed days prior to the OGTT, was worn up to 14 days. Anthropometric and vital signs were measured. HbA1c, fasting, 1-h and 2-h PG levels during an OGTT were obtained. Results: The 1-h PG correlated significantly with CGM glucose levels (r=0.883, p Conclusions: The 1-h CGM glucose and elevated GV indices significantly correlate with 1-h PG (> 8.6 mmol/L) in high-risk subjects with HbA1c < 5.7%. CGM could potentially replace the OGTT for detecting early dysglycemia in those with HbA1c < 5.7%. Disclosure B. Dorcely: None. E. Sifonte: None. A. Divakaran: None. K. Katz: None. R. Jagannathan: None. I.J. Goldberg: None. M. Bergman: None. Funding Abbott Diabetes Care; New York University Clinical and Translational Science Award (UL1 TR001445)