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Current Opinion in Pediatrics Aug 2023Glucose metabolism alterations in cystic fibrosis range from the classic cystic fibrosis-related diabetes (CFRD) to forms of glucose intolerance and prediabetes. The aim... (Review)
Review
PURPOSE OF REVIEW
Glucose metabolism alterations in cystic fibrosis range from the classic cystic fibrosis-related diabetes (CFRD) to forms of glucose intolerance and prediabetes. The aim of the present work is to review the most up-to-date novelties in terms of CFRD diagnosis and therapy. This review is timely and relevant because it allows an update for the early and correct classification of glucose abnormalities in cystic fibrosis and because it favours an appropriate therapeutic approach.
RECENT FINDINGS
Confirm that Oral Glucose Tolerance Test is still the diagnostic gold standard despite the advent of continuous glucose monitoring (CGM) systems; this latter is spreading very rapidly, however, to date, there is still no strong evidence to hypothesize the use of CGM for diagnostic purposes. CGM has indeed proven to be very useful in managing and guiding CFRD therapy.
SUMMARY
Tailored and personalized insulin therapy is still the recommended therapy for children and adolescents with CFRD, although nutritional intervention and oral hypoglycaemic treatment are equally important and efficacious. Finally CFTR modulators have allowed the increase of the life expectancy of cystic fibrosis patients and have proven effective not only in improving the pulmonary function and the nutritional status but also the glucose control.
Topics: Adolescent; Humans; Child; Prediabetic State; Cystic Fibrosis; Blood Glucose Self-Monitoring; Blood Glucose; Diabetes Mellitus; Insulin
PubMed: 37211992
DOI: 10.1097/MOP.0000000000001259 -
Frontiers in Endocrinology 2023The purpose of this study is to investigate the independent influencing factors of the transition from normal population to prediabetes, and from prediabetes to...
OBJECTIVE
The purpose of this study is to investigate the independent influencing factors of the transition from normal population to prediabetes, and from prediabetes to diabetes, and to further construct clinical prediction models to provide a basis for the prevention and management of prediabetes and diabetes.
MATERIALS AND METHODS
The data for this study were based on clinical information of participants from the Health Management Center of Peking University Shenzhen Hospital. Participants were classified into normal group, prediabetes group, and diabetes group according to their functional status of glucose metabolism. Spearman's correlation coefficients were calculated for the variables, and a matrix diagram was plotted. Further, univariate and multivariate logistic regression analysis were conducted to explore the independent influencing factors. The independent influencing factors were used as predictors to construct the full-variable prediction model (Full.model) and simplified prediction model (Simplified.model).
RESULTS
This study included a total of 5310 subjects and 22 variables, among which there were 1593(30%) in the normal group, 3150(59.3%) in the prediabetes group, and 567(10.7%) in the diabetes group. The results of the multivariable logistic regression analysis showed that there were significant differences in 9 variables between the normal group and the prediabetes group, including age(Age), body mass index(BMI), systolic blood pressure(SBP), urinary glucose(U.GLU), urinary protein(PRO), total protein(TP), globulin(GLB), alanine aminotransferase(ALT), and high-density lipoprotein cholesterol(HDL-C). There were significant differences in 7 variables between the prediabetes group and the diabetes group, including Age, BMI, SBP, U.GLU, PRO, triglycerides(TG), and HDL.C. The Full.model and Simplified.model constructed based on the above influencing factors had moderate discriminative power in both the training set and the test set.
CONCLUSION
Age, BMI, SBP, U.GLU, PRO, TP, and ALT are independent risk factors, while GLB and HDL.C are independent protective factors for the development of prediabetes in the normal population. Age, BMI, SBP, U.GLU, PRO, and TG are independent risk factors, while HDL.C is an independent protective factor for the progression from prediabetes to diabetes. The Full.model and Simplified.model developed based on these influencing factors have moderate discriminative power.
Topics: Humans; Prediabetic State; Blood Glucose; Diabetes Mellitus; Triglycerides; Risk Factors
PubMed: 37964953
DOI: 10.3389/fendo.2023.1225696 -
Journal of Endocrinological... Sep 2023To explore the specific association between sarcopenia and prediabetes based on large population samples.
AIM
To explore the specific association between sarcopenia and prediabetes based on large population samples.
METHODS
A total of 16,116 U.S. adults aged 20-59 with dual energy X-ray absorptiometry (DXA) was identified from the National Health and Nutrition Examination Surveys (NHANES). Sarcopenia was defined according to appendicular skeletal muscle mass (ASM) adjusted for body mass index (BMI). Multivariable binary logistic regression models were used to ascertain odds ratios (ORs) for developing prediabetes. Stratified analyses were also performed.
RESULTS
Prevalence of prediabetes was higher in the sarcopenia group (n = 1055) compared with the non-sarcopenia group (n = 15,061) (45.50% vs 28.74%, P < 0.001). Sarcopenia was strongly associated with an increased risk of prediabetes after full adjustment (OR = 1.21, 95CI%: 1.05, 1.39, P = 0.009). In the stratified analysis, this association remained significant independent of obesity, triglycerides, and low-density lipoprotein cholesterol levels. When sarcopenia subjects combined with obesity especially central obesity, the risk of prediabetes was the highest (OR = 2.63, 95CI%: 2.22, 3.11, P < 0.001). Furthermore, a greater proportion of any of impaired glucose tolerance (IGT) individuals was observed in the sarcopenia group compared to the non-sarcopenia group among prediabetes population (41.72% vs 24.06%, P < 0.001).
CONCLUSIONS
Sarcopenia was positively associated with prevalent prediabetes especially IGT in the non-elderly. Moreover, synergistic interactions between the sarcopenia and obesity could greatly increase the risk of prediabetes.
Topics: Adult; Humans; Middle Aged; Prediabetic State; Nutrition Surveys; Sarcopenia; Obesity; Absorptiometry, Photon; Glucose Intolerance; Body Mass Index; Prevalence; Muscle, Skeletal
PubMed: 36856982
DOI: 10.1007/s40618-023-02038-y -
Journal of Diabetes Investigation Oct 2023There has been conflicting evidence regarding the role of prediabetes as a risk factor of lung cancer. A systemic review and meta-analysis was conducted to determine the... (Meta-Analysis)
Meta-Analysis
AIMS/INTRODUCTION
There has been conflicting evidence regarding the role of prediabetes as a risk factor of lung cancer. A systemic review and meta-analysis was conducted to determine the relationship between prediabetes and lung cancer incidence and mortality in general adult populations.
MATERIALS AND METHODS
Observational studies relevant to the objective were found in Medline, Embase, Cochrane Library, and Web of Science. By incorporating potential heterogeneity into the model, a randomized-effects model was selected.
RESULTS
Ten cohort studies were included. People with prediabetes were associated with a mildly increased risk of lung cancer incidence compared with controls with normoglycemia (risk ratio [RR]: 1.09, 95% confidence interval [CI]: 1.01-1.18, P = 0.03; I = 79%), which was mainly observed in men rather than in women (RR: 1.07 vs 0.99, P for subgroup difference < 0.001). Prediabetes was related to a higher risk of lung cancer mortality (RR: 1.19, 95% CI: 1.02-1.39, P = 0.03; I = 52%), and the results were consistent in both men and women (P for subgroup difference = 0.67). The association between prediabetes and lung cancer incidence or mortality did not appear to be significantly affected by different definitions of prediabetes (P for subgroup difference = 0.27 and 0.37).
CONCLUSIONS
Prediabetes might be associated with a mildly increased risk of lung cancer incidence in men, but not in women. In addition, prediabetes may be related to a higher risk of lung cancer mortality in the adult population.
Topics: Male; Adult; Humans; Female; Incidence; Prediabetic State; Lung Neoplasms; Risk Factors
PubMed: 37517054
DOI: 10.1111/jdi.14057 -
The American Journal of Clinical... Dec 2023Evidence on associations between dairy consumption and incident prediabetes is inconsistent. One potential explanation for heterogeneity is that health behavior and food...
BACKGROUND
Evidence on associations between dairy consumption and incident prediabetes is inconsistent. One potential explanation for heterogeneity is that health behavior and food intake covary with the consumption of various high-fat and low-fat dairy types.
OBJECTIVE
The objective was to investigate the associations of total dairy and dairy types with incident prediabetes and to assess how dairy intake is linked with metabolic risk factors, lifestyle behaviors, and foods, as potential explanations for these associations.
METHODS
Overall, 74,132 participants from the prospective population-based Lifelines study were included (mean age, 45.5 ± 12.3 y; 59.7% female). Baseline dairy intake was measured using a validated food frequency questionnaire. Prediabetes at follow-up was defined based on the World Health Organization/International Expert Committee criteria as fasting plasma glucose of 110-125 mg/dL or glycated hemoglobin concentrations of 6.0%-6.5%. Associations were analyzed using Poisson regression models adjusted for social demographics, lifestyle behaviors, family history of diabetes, and food group intake. Interconnections were assessed with mixed graphical model networks.
RESULTS
At a mean follow-up of 4.1 ± 1.1 y, 2746 participants developed prediabetes (3.7%). In regression analyses, neutral associations were found for most dairy types. Intake of plain milk and low-fat milk were associated with a higher risk of prediabetes in the top compared with bottom quartiles (relative risk [RR]: 1.17; 95% confidence interval [CI]: 1.05, 1.30; P-trend = 0.04 and RR: 1.18; 95% CI: 1.06, 1.31; P-trend =0.01). Strong but nonsignificant effect estimates for high-fat yogurt in relation to prediabetes were found (RR: 0.80; 95% CI: 0.64, 1.01). The network analysis showed that low-fat milk clustered with energy-dense foods, including bread, meat, and high-fat cheese, whereas high-fat yogurt had no clear link with lifestyle risk factors and food intake.
CONCLUSIONS
In this large cohort of Dutch adults, low-fat milk intake was associated with higher prediabetes risk. Heterogeneous associations by dairy type and fat content might partly be attributed to confounding caused by behaviors and food intake related to dairy intake.
Topics: Adult; Humans; Female; Middle Aged; Male; Animals; Prediabetic State; Dairy Products; Dietary Fats; Milk; Risk Factors; Cheese; Diet
PubMed: 37813340
DOI: 10.1016/j.ajcnut.2023.10.002 -
JAMA Aug 2023
Topics: Humans; Diabetes Mellitus, Type 2; Prediabetic State
PubMed: 37552499
DOI: 10.1001/jama.2023.9964 -
JAMA Aug 2023
Topics: Humans; Diabetes Mellitus, Type 2; Prediabetic State
PubMed: 37552502
DOI: 10.1001/jama.2023.9959 -
JAMA Aug 2023
Topics: Humans; Diabetes Mellitus, Type 2; Prediabetic State
PubMed: 37552503
DOI: 10.1001/jama.2023.9956 -
Cardiovascular Diabetology Dec 2023Prediabetes, an intermediate stage between normal blood sugar levels and a diabetes mellitus diagnosis, is increasing in prevalence. Severe prediabetes is associated...
BACKGROUND
Prediabetes, an intermediate stage between normal blood sugar levels and a diabetes mellitus diagnosis, is increasing in prevalence. Severe prediabetes is associated with a similar risk of complications as diabetes, but its relationship with peripheral arterial disease remains underexplored.
METHODS
We conducted a retrospective cohort study involving 36,950 adult patients, utilizing electronic medical records from the National Taiwan University Hospital between 2014 and 2019. We employed multivariable Cox regression and Kaplan-Meier analysis with the log-rank test to analyze major adverse limb events (MALE) and major adverse cardiovascular events (MACE) in relation to normal glucose regulation (NGR) and prediabetes.
RESULTS
During the 131,783 person-years follow-up, 17,754 cases of prediabetes and 19,196 individuals with normal glucose regulation (NGR) were identified. Kaplan-Meier analysis revealed an increased incidence of both MALE and MACE in individuals with prediabetes. (log-rank p = 0.024 and < 0.001). Prediabetes exhibited a significant association with an elevated risk of MALE (adjusted hazard ratio (aHR) 1.26 [95% CI 1.10-1.46], p = 0.001) and MACE (aHR 1.46 [1.27-1.67], p < 0.001). Furthermore, in individuals with prediabetes, the elevation in the risk of MALE commenced before HbA1c levels surpassed 5.0% (for HbA1c 5.0-5.5%: aHR 1.78 (1.04-3.04), p = 0.036; HbA1c 5.5-6.0%: aHR 1.29 [1.06-1.58], p = 0.012; aHbA1c 6.0-6.5%: aHR 1.39 [1.14-1.70], p < 0.001). Similarly, the onset of increased MACE risk was observed when HbA1c levels exceeded 5.5% (for HbA1c 5.5-6.0%: aHR 1.67 [1.39-2.01], p < 0.001; HbA1c 6.0-6.5%: HR 2.10 [1.76-2.51], p < 0.001). Factors associated with both MALE and MACE in prediabetes include advanced age, male gender, higher body mass index, and a history of heart failure or atrial fibrillation.
CONCLUSION
We demonstrated higher susceptibility to MALE and MACE in prediabetes compared to normoglycemic counterparts, notwithstanding lower HbA1c levels. Complications may manifest at an earlier prediabetes trajectory. Intensive lifestyle modification may improve the prognosis of severe prediabetes.
Topics: Adult; Humans; Male; Prediabetic State; Glycated Hemoglobin; Retrospective Studies; Blood Glucose; Diabetes Mellitus; Atrial Fibrillation; Risk Factors
PubMed: 38115080
DOI: 10.1186/s12933-023-02085-y -
Diabetes & Metabolic Syndrome Nov 2023The association between serum cystatin C level and vascular outcomes has not been fully elucidated in diabetes and is unclear in prediabetes. We aim to evaluate whether...
BACKGROUND
The association between serum cystatin C level and vascular outcomes has not been fully elucidated in diabetes and is unclear in prediabetes. We aim to evaluate whether cystatin C level predicts future risk for mortality and vascular outcomes in prediabetes and diabetes.
METHODS
A total of 85,371 participants with prediabetes and diabetes, and available baseline cystatin C in the UK biobank were included with a 14-year follow-up. Cox hazards models were used to calculate the associations between cystatin C level, mortality (all-cause, cause-specfic mortality) and vascular outcomes (myocardial infarction [MI], stroke, end-stage renal disease [ESRD] and diabetic retinopathy [DR]). The 1136 diabetes subjects in Guangzhou Diabetic Eye Study (GDES) were included for examing the impact of cystatin C on in vivo retinal degeneration and microvascular changes by using SS-OCT and OCTA.
RESULTS
The highest cystatin C quartile had increased risks of all-cause (hazard ratio [HR], 2.02; 95% confidence interval [CI] 1.86-2.19), cardiovascular (HR, 2.29; 95% CI 1.97-2.67), cancer (HR, 1.86; 95% CI 1.65-2.10) and other-cause mortality (HR, 2.24; 95% CI 1.90-2.64), MI (HR, 1.40; 95% CI 1.26-1.55), stroke (HR, 1.88; 95% CI, 1.57-2.26), ESRD (HR, 7.33; 95% CI, 5.02-10.71), DR (HR, 1.17; 95% CI 1.03-1.32) than those in the lowest quartile. Adding cystatin C to the conventional model improved C-statistic for all-cause (0.699-0.724), cardiovascular (0.762-0.789), cancer (0.661-0.674) and other-cause mortality (0.675-0.715), MI (0.748-0.750), stroke (0.712-0.718), and ESRD (0.808-0.827). The GDES analysis identified a strong association between increased cystatin C levels and diminished retinal neural layers, as well as microvascular rarefaction in both macular and optic disc regions (all P < 0.05).
CONCLUSIONS
Serum cystatin C refines the risk stratification for mortality and vascular outcomes among patients with prediabetes or diabetes.
Topics: Humans; Cystatin C; Diabetes Mellitus; Kidney Failure, Chronic; Myocardial Infarction; Neoplasms; Prediabetic State; Risk Assessment; Risk Factors; Stroke
PubMed: 37898064
DOI: 10.1016/j.dsx.2023.102882