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Annals of Medicine Dec 2023The notion of prediabetes, defined by the ADA as glycated hemoglobin A1c (HbA1c) of 5.7-6.4%, implies increased vascular inflammatory and immunologic processes and...
BACKGROUND AND OBJECTIVE
The notion of prediabetes, defined by the ADA as glycated hemoglobin A1c (HbA1c) of 5.7-6.4%, implies increased vascular inflammatory and immunologic processes and higher risk for developing diabetes mellitus and major cardiovascular events. We aimed to determine the risk factors associated with rapid progression of normal and prediabetes patients to type 2 diabetes mellitus (T2DM).
METHODS
Retrospective cohort study in a single 8-hospital health system in southeast Michigan, between 2006 and 2020. All patients with HbA1c <6.5% at baseline and at least 2 other HbA1c measurements were clustered in five trajectories encompassing more than 95% of the study population. Multivariate linear regression analysis was performed to examine the association of demographic and comorbidities with HbA1c trajectories progressing to diabetes.
RESULTS
A total of 5,347 prediabetic patients were clustered based on their HbA1c progression (C1: 4,853, C2: 253, C66: 102, C12: 85, C68: 54). The largest cluster (C1) had a baseline median HbA1c value of 6.0% and exhibited stable HbA1c levels in prediabetic range across all subsequent years. The smallest cluster (C68) had the lowest median baseline HbA1c value and also remained stable across subsequent years. The proportion of normal HbA1c in each of the pre-diabetic trajectories ranged from 0 to 12.7%, whereas 81.5% of the reference cluster (C68) were normal HbA1c at baseline. The C2 (steady rising) trajectory was significantly associated with BMI (adj OR 1.10, 95%CI 1.03-1.17), and family history of DM (adj OR 2.75, 95%CI 1.32-5.74). With respect to the late rising trajectories, baseline BMI was significantly associated with both C66 and C12 trajectory (adj OR 1.10, 95%CI 1.03-1.18) and (adj OR 1.13, 95%CI 1.05-1.23) respectively, whereas, the C12 trajectory was also significantly associated with age (adj OR 1.62, 95%CI 1.04-2.53) and history of MACE (adj OR 3.20, 95%CI 1.14-8.93).
CONCLUSIONS
We suggest that perhaps a more aggressive preventative approach should be considered in patients with a family history of T2DM who have high BMI and year-to-year increase in HbA1c, whether they have normal hemoglobin A1c or they have prediabetes.KEY MESSAGESProgression to diabetes from normal or prediabetic hemoglobin A1c within four years is associated with baseline BMI.A steady rise in HbA1c during a four-year period is associated with age and family history of T2DM, whereas age and personal history of MACE are associated with a rapid rise in HbA1c.A more aggressive preventative approach should be considered in patients with a family history of T2DM who have high BMI and year-to-year increase in HbA1c.
Topics: Humans; Diabetes Mellitus, Type 2; Glycated Hemoglobin; Prediabetic State; Retrospective Studies; Risk Factors
PubMed: 36621941
DOI: 10.1080/07853890.2022.2164347 -
Frontiers in Endocrinology 2023Numerous studies have shown the beneficial effects of exercise on glycemic control in people with prediabetes. However, the most effective exercise modality for... (Meta-Analysis)
Meta-Analysis
Effect of physical activity and different exercise modalities on glycemic control in people with prediabetes: a systematic review and meta-analysis of randomized controlled trials.
BACKGROUND
Numerous studies have shown the beneficial effects of exercise on glycemic control in people with prediabetes. However, the most effective exercise modality for improving glycemic control remains unclear. We aimed to assess which exercise training modality is most effective in improving glycemic control in a population with prediabetes.
METHODS
We conducted searches in Pubmed/MEDLINE, EMBASE, SPORTDiscus, Web of Science, PEDro, BVS, and the Cochrane Library from inception to June 2022. Included studies reported fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), and 2-hour postprandial (2hPP) levels and implemented an exercise program lasting at least 12 weeks in adults with prediabetes. We performed a direct meta-analysis using a random-effects model and a network meta-analysis. Cochran's Q statistic and the inconsistency I test were used to assess the heterogenicity between studies.
RESULTS
Twenty trials were included, with 15 trials (comprising 775 participants with prediabetes) combined in the meta-analysis, and 13 in the network meta-analysis. The meta-analysis results did not show a statistically significant reduction in fasting plasma glucose (FPG) after aerobic training (AT) intervention compared to a control group (mean (95%CI) difference = -5.18 (-13.48; 3.12) mg/dL, Z=1.22, p=0.22). However, a difference of -7.25 (-13.79; -0.71) mg/dL, p=0.03, in FPG after interval training (IT) intervention was detected compared to a control group. After resistance training (RT) intervention, FPG was significantly lower -6.71 (-12.65,-0.77) mg/dL, Z=2.21, p=0.03, and HbA1c by -0.13 (-0.55, 0.29), p=0.54, compared to the control group. The impact of RT compared to no intervention on 2hPP was not statistically significant (p=0.26). The network meta-analysis did not show statistical significance. Most of the studies presented an unclear risk of bias, and a low and very low-quality of evidence. According to the GRADE criteria, the strength of the body of evidence was low.
CONCLUSION
Resistance training and IT had demonstrated benefits on glycemic indices, especially on FPG, in a population with prediabetes. Further studies with larger sample sizes and a more robust methodology that compare different types of exercise modalities, frequencies, and durations, are needed to establish a beneficial exercise intervention.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=370688, identifier CRD42022370688.
Topics: Adult; Humans; Prediabetic State; Glycated Hemoglobin; Blood Glucose; Glycemic Control; Randomized Controlled Trials as Topic; Exercise
PubMed: 37842295
DOI: 10.3389/fendo.2023.1233312 -
Diabetologia Jan 2024The identification of people who are at high risk of developing type 2 diabetes is a key part of population-level prevention strategies. Previous studies have evaluated...
AIMS/HYPOTHESIS
The identification of people who are at high risk of developing type 2 diabetes is a key part of population-level prevention strategies. Previous studies have evaluated the predictive utility of omics measurements, such as metabolites, proteins or polygenic scores, but have considered these separately. The improvement that combined omics biomarkers can provide over and above current clinical standard models is unclear. The aim of this study was to test the predictive performance of genome, proteome, metabolome and clinical biomarkers when added to established clinical prediction models for type 2 diabetes.
METHODS
We developed sparse interpretable prediction models in a prospective, nested type 2 diabetes case-cohort study (N=1105, incident type 2 diabetes cases=375) with 10,792 person-years of follow-up, selecting from 5759 features across the genome, proteome, metabolome and clinical biomarkers using least absolute shrinkage and selection operator (LASSO) regression. We compared the predictive performance of omics-derived predictors with a clinical model including the variables from the Cambridge Diabetes Risk Score and HbA.
RESULTS
Among single omics prediction models that did not include clinical risk factors, the top ten proteins alone achieved the highest performance (concordance index [C index]=0.82 [95% CI 0.75, 0.88]), suggesting the proteome as the most informative single omic layer in the absence of clinical information. However, the largest improvement in prediction of type 2 diabetes incidence over and above the clinical model was achieved by the top ten features across several omic layers (C index=0.87 [95% CI 0.82, 0.92], Δ C index=0.05, p=0.045). This improvement by the top ten omic features was also evident in individuals with HbA <42 mmol/mol (6.0%), the threshold for prediabetes (C index=0.84 [95% CI 0.77, 0.90], Δ C index=0.07, p=0.03), the group in whom prediction would be most useful since they are not targeted for preventative interventions by current clinical guidelines. In this subgroup, the type 2 diabetes polygenic risk score was the major contributor to the improvement in prediction, and achieved a comparable improvement in performance when added onto the clinical model alone (C index=0.83 [95% CI 0.75, 0.90], Δ C index=0.06, p=0.002). However, compared with those with prediabetes, individuals at high polygenic risk in this group had only around half the absolute risk for type 2 diabetes over a 20 year period.
CONCLUSIONS/INTERPRETATION
Omic approaches provided marginal improvements in prediction of incident type 2 diabetes. However, while a polygenic risk score does improve prediction in people with an HbA in the normoglycaemic range, the group in whom prediction would be most useful, even individuals with a high polygenic burden in that subgroup had a low absolute type 2 diabetes risk. This suggests a limited feasibility of implementing targeted population-based genetic screening for preventative interventions.
Topics: Humans; Diabetes Mellitus, Type 2; Prediabetic State; Prospective Studies; Cohort Studies; Proteome; Multiomics; Risk Factors; Biomarkers
PubMed: 37889320
DOI: 10.1007/s00125-023-06027-x -
Journal of Affective Disorders Jun 2024The association between diabetes and depressive symptoms is well recognized. However, the impact of depressive symptoms on prediabetes remains unclear. This study aims...
INTRODUCTION
The association between diabetes and depressive symptoms is well recognized. However, the impact of depressive symptoms on prediabetes remains unclear. This study aims to explore the specific correlation between depressive symptoms and prediabetes.
METHODS
A total of 7467 participants from the National Health and Nutrition Examination Survey (NHANES) were included in this study, spanning five rounds of surveys conducted between 2007 and 2016. Weighted logistic regression was utilized to assess the relationship between depressive symptoms and prediabetes.
RESULTS
Compared with the normoglycemic population, individuals with prediabetes had a significantly higher probability of experiencing trouble sleeping (P = 0.020). After adjusting for non-glucose factors, there was no significant correlation between PHQ-9 and prediabetes; however, severe depressive symptoms were positively associated with abnormal fasting plasma glucose (FPG) levels (OR = 1.093 [95 % CI 1.002, 1.192]). There was a positive correlation between trouble concentrating and FPG abnormalities (OR = 1.065 [95 % CI 1.004, 1.129]).
LIMITATIONS
The cross-sectional design limits causal inference.
CONCLUSION
Individuals with depressive symptoms, especially severe cases, should be targeted for prediabetes prevention and management efforts. The diverse symptom presentations may have distinct impacts on glucose, necessitating personalized prevention and management strategies.
Topics: Humans; Prediabetic State; Nutrition Surveys; Blood Glucose; Glycated Hemoglobin; Cross-Sectional Studies; Depression; Glucose
PubMed: 38537755
DOI: 10.1016/j.jad.2024.03.122 -
European Journal of Preventive... Oct 2023To quantify the trajectories from normoglycaemia to pre-diabetes, subsequently to type 2 diabetes mellitus (T2DM), cardiovascular diseases (CVD), and cardiovascular...
AIMS
To quantify the trajectories from normoglycaemia to pre-diabetes, subsequently to type 2 diabetes mellitus (T2DM), cardiovascular diseases (CVD), and cardiovascular death, and the effects of risk factors on the rates of transition.
METHODS AND RESULTS
We used data from the Jinchang Cohort of 42 585 adults aged 20-88 free of coronary heart disease (CHD) and stroke at baseline. A multistate model was applied for analysing the progression of CVD and its relation to various risk factors. During a median follow-up of 7 years, 7498 participants developed pre-diabetes, 2307 developed T2DM, 2499 developed CVD, and 324 died from CVD. Among 15 postulated transitions, transition from comorbid CHD and stroke to cardiovascular death had the highest rate (157.21/1000 person-years), followed by transition from stroke alone to cardiovascular death (69.31/1000 person-years) and transition from pre-diabetes to normoglycaemia (46.51/1000 person-years). Pre-diabetes had a sojourn time of 6.77 years, and controlling weight, blood lipids, blood pressure, and uric acid within normal limits may promote reversion to normoglycaemia. Among transitions to CHD alone and stroke alone, transition from T2DM had the highest rate (12.21/1000 and 12.16/1000 person-years), followed by transition from pre-diabetes (6.81/1000 and 4.93/1000 person-years) and normoglycaemia (3.28/1000 and 2.39/1000 person-years). Age and hypertension were associated with an accelerated rate for most transitions. Overweight/obesity, smoking, dyslipidaemia, and hyperuricaemia played crucial but different roles in transitions.
CONCLUSION
Pre-diabetes was the optimal intervention stage in the disease trajectory. The derived transition rates, sojourn time, and influence factors could provide scientific support for the primary prevention of both T2DM and CVD.
Topics: Adult; Humans; Cardiovascular Diseases; Blood Glucose; Diabetes Mellitus, Type 2; Prospective Studies; Prediabetic State; Risk Factors; Stroke
PubMed: 37315161
DOI: 10.1093/eurjpc/zwad196 -
Annual Review of Public Health May 2024The term prediabetes describes blood glucose levels above the normal range but below the threshold to diagnose type 2 diabetes. Several population health initiatives... (Review)
Review
The term prediabetes describes blood glucose levels above the normal range but below the threshold to diagnose type 2 diabetes. Several population health initiatives encourage a test and treat approach for prediabetes. In this approach, screening and identification of individuals with prediabetes should be followed by prompt referral to structured lifestyle modification programs or pharmacologic interventions that have been shown to prevent or delay the progression to type 2 diabetes in clinical trials. Here we provide a critical review of evidence for this test and treat approach by examining health outcomes associated with prediabetes and the availability and effectiveness of lifestyle modification approaches that target prediabetes. We also describe current limitations to the reach and uptake of evidence-based treatment options for prediabetes. Finally, we highlight lessons learned from identifying and labeling other preconditions to consider challenges and opportunities that may arise with increasing awareness of prediabetes as part of routine preventive care.
Topics: Humans; Prediabetic State; Diabetes Mellitus, Type 2; Mass Screening; Life Style; Risk Reduction Behavior; Blood Glucose
PubMed: 38109519
DOI: 10.1146/annurev-publhealth-060222-023417 -
Circulation. Cardiovascular Imaging Oct 2023The contemporary burden and characteristics of coronary atherosclerosis, assessed using coronary computed tomography angiography (CCTA), is unknown among asymptomatic...
BACKGROUND
The contemporary burden and characteristics of coronary atherosclerosis, assessed using coronary computed tomography angiography (CCTA), is unknown among asymptomatic adults with diabetes and prediabetes in the United States. The pooled cohort equations and coronary artery calcium (CAC) score stratify atherosclerotic cardiovascular disease risk, but their association with CCTA findings across glycemic categories is not well established.
METHODS
Asymptomatic adults without atherosclerotic cardiovascular disease enrolled in the Miami Heart Study were included. Participants underwent CAC and CCTA testing and were classified into glycemic categories. Prevalence of coronary atherosclerosis (any plaque, noncalcified plaque, plaque with ≥1 high-risk feature, maximal stenosis ≥50%) assessed by CCTA was described across glycemic categories and further stratified by pooled cohort equations-estimated atherosclerotic cardiovascular disease risk and CAC score. Adjusted logistic regression was used to evaluate the associations between glycemic categories and coronary outcomes.
RESULTS
Among 2352 participants (49.5% women), the prevalence of euglycemia, prediabetes, and diabetes was 63%, 30%, and 7%, respectively. Coronary plaque was more commonly present across worsening glycemic categories (euglycemia, 43%; prediabetes, 58%; diabetes, 69%), and similar pattern was observed for other coronary outcomes. In adjusted analyses, compared with euglycemia, prediabetes and diabetes were each associated with higher odds of any coronary plaque (OR, 1.30 [95% CI, 1.05-1.60] and 1.75 [1.17-2.61], respectively), noncalcified plaque (OR, 1.47 [1.19-1.81] and 1.99 [1.38-2.87], respectively), and plaque with ≥1 high-risk feature (OR, 1.65 [1.14-2.39] and 2.53 [1.48-4.33], respectively). Diabetes was associated with stenosis ≥50% (OR, 3.01 [1.79-5.08]; reference=euglycemia). Among participants with diabetes and estimated atherosclerotic cardiovascular disease risk <5%, 46% had coronary plaque and 10% had stenosis ≥50%. Among participants with diabetes and CAC=0, 30% had coronary plaque and 3% had stenosis ≥50%.
CONCLUSIONS
Among asymptomatic adults, worse glycemic status is associated with higher prevalence and extent of coronary atherosclerosis, high-risk plaque, and stenosis. In diabetes, CAC was more closely associated with CCTA findings and informative in a larger population than the pooled cohort equations.
Topics: Adult; Humans; Female; Male; Coronary Artery Disease; Prediabetic State; Cardiovascular Diseases; Florida; Constriction, Pathologic; Protestantism; Coronary Angiography; Prospective Studies; Plaque, Atherosclerotic; Atherosclerosis; Diabetes Mellitus; Risk Factors
PubMed: 37772409
DOI: 10.1161/CIRCIMAGING.123.015314 -
Scientific Reports Feb 2024We aimed to examine the concordance of type-2 diabetes, prediabetes and the metabolic syndrome in couples. In cross-sectional analyses, we used data from 1173 couples...
We aimed to examine the concordance of type-2 diabetes, prediabetes and the metabolic syndrome in couples. In cross-sectional analyses, we used data from 1173 couples with index persons from the Heinz Nixdorf Recall Study (2011-2015), a population-based cohort study in Western Germany, and partners from the associated Heinz Nixdorf Multigeneration Study (2013-2016). Mean age (standard deviation) was 67.2 (6.6) years in index persons, and 67.8 (7.7) years in partners. The exposure was the presence of diabetes, prediabetes or metabolic syndrome in index persons, the outcome was the presence of the same health status in partners. Diabetes was defined by either self-reported diagnosis, intake of antidiabetic drugs or insulin, or HbA1c ≥ 6.5%. If the index person had prediabetes or diabetes, the partner was 1.46 (95% CI 1.07-2.00) times more likely to have diabetes than partners of index persons without the condition in the crude model (adjusted model: 1.33 (0.97-1.83)). For self-reported diabetes and for the metabolic syndrome, the corresponding prevalence ratios were 1.33 (0.90-1.97) and 1.17 (1.03-1.32), respectively (adjusted models: 1.23 (0.77-1.94), 1.04 (0.91-1.18)). In German couples, there was weak to moderate concordance of type-2 diabetes, prediabetes and the metabolic syndrome in crude, but poor concordance in adjusted models.
Topics: Humans; Aged; Prediabetic State; Metabolic Syndrome; Cohort Studies; Cross-Sectional Studies; Risk Factors; Diabetes Mellitus, Type 2; Prevalence
PubMed: 38316913
DOI: 10.1038/s41598-024-53417-1 -
BMC Endocrine Disorders Sep 2023Prediabetes and diabetes involve alterations in glucose homeostasis, including increased fasting blood glucose and impaired glucose tolerance. Berberine has been... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
Prediabetes and diabetes involve alterations in glucose homeostasis, including increased fasting blood glucose and impaired glucose tolerance. Berberine has been identified as a potential regulator of glucose homeostasis with implications on the management of type 2 diabetes mellitus (DM). Given a paucity of data on berberine in prediabetes, evaluation of its effect in individuals with prediabetes may prove clinically valuable.
OBJECTIVE
The present pilot study aimed to investigate the effect of daily oral berberine on markers of glycemic control and insulin resistance among individuals with prediabetes.
METHODS
A randomized, double-blinded, placebo-controlled trial was conducted for 12 weeks among 34 individuals with prediabetes as defined by the American Diabetes Association (fasting plasma glucose (FPG) between 5.6 and 6.9 mmol/L, glycosylated hemoglobin (HbA) between 5.7% and 6.4%, or 2-hour 75-gram oral glucose tolerance test (2 h-OGTT) between 7.8 and 11.1 mmol/L). HIMABERB® 500 mg was given three times daily to the treatment group, and placebo was administered three times daily to the control group. Glycemic control markers and physical parameters were evaluated for both groups on days 0, 28, 56, and 84. The glycemic control markers assessed included FPG, fasting insulin (FI), 2 h-OGTT, HbA, and homeostatic model assessment-insulin resistance (HOMA-IR). The observed outcomes were analyzed using independent t-test statistics to determine the significance of differences over time after treatment initiation and between treatment and control groups.
RESULTS
Significant decreases in all markers of glycemic control were observed in the treatment group at intermediate time points and the endpoint of the study compared to baseline levels and to the control group. For the treatment group, FPG decreased from 6.75 ± 0.23 mmol/L to 5.33 ± 0.28 mmol/L, FI from 9.81 ± 0.36 to 7.88 ± 0.52 mmol/L, 2 h-OGTT from 10.44 ± 0.52 to 8.12 ± 0.40 mmol/L, HbA from 6.40% ± 0.20-5.43% ± 0.21%, and HOMA-IR from 3.61 ± 0.31 to 2.41 ± 0.14. The decreases in glycemic control markers compared to the control group were clinically and statistically significant (p<10). No severe adverse effects, kidney or liver toxicity were detected.
CONCLUSION
After 12 weeks, berberine (HIMABERB®) intervention in individuals with prediabetes significantly reduced glycemic control markers, with mean FPG and 2 h-OTGG being reduced to below prediabetic thresholds, supporting the investigation of the use of HIMABERB® for delaying progression to diabetes mellitus.
TRIAL REGISTRATION
http://ctri.nic.in (CTRI/2021/12/038751) (20/12/2021).
Topics: Humans; Prediabetic State; Glycemic Control; Pilot Projects; Berberine; Diabetes Mellitus, Type 2; Insulin Resistance; Double-Blind Method; Insulin; Glucose
PubMed: 37679692
DOI: 10.1186/s12902-023-01442-y -
Nutrients Dec 2023Diets with a low glycemic index (GI) and a low glycemic load (GL) can improve glycemic control, blood lipids, blood pressure and BMI in prediabetes and type 2 diabetes... (Review)
Review
Diets with a low glycemic index (GI) and a low glycemic load (GL) can improve glycemic control, blood lipids, blood pressure and BMI in prediabetes and type 2 diabetes (T2DM), but evidence regarding other aspects of cardiometabolic health is limited. We searched the literature for RCTs published from 2013 to 2023 and reviewed the evidence on low-GI/GL diets and their effects on different aspects of health in prediabetes and T2DM, aiming to build a report on all relevant outcomes included in the studies. We included 14 RCTs with 1055 participants, who were mostly middle-aged individuals with T2DM. Interventions were mostly low GI and lasted 1-36 months. Low-GI/GL foods and diets showed benefits in terms of short-term glycemic control, weight and adiposity. Longer-term trials would be necessary to determine whether these benefits persist over time and/or lead to lower CVD risk and mortality. Effects on lipid profile were inconsistent. Some studies also reported positive effects of low-GI/GL interventions on blood pressure, inflammatory biomarkers, renal function and gut microbiota composition. Future trials should focus on some of these novel outcome measures, which may provide important insights into the metabolic effects of low-GI diets on individuals with diabetes.
Topics: Middle Aged; Humans; Glycemic Index; Diabetes Mellitus, Type 2; Blood Glucose; Glycemic Load; Prediabetic State; Diet
PubMed: 38140319
DOI: 10.3390/nu15245060