Diabetes risk factors checklist for screening [67].

Diabetes risk factors checklist for screening [67].

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Even though the new thresholds for defining prediabetes have been around for more than ten years, there is still controversy surrounding the precise characterization of this intermediate glucose metabolism status. The risk of developing diabetes and macro and microvascular disease linked to prediabetes is well known. Still, the prediabetic populati...

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... current ADA recommendations for prediabetes screening place obesity and age above 45 in the center of attention. Therefore, overweight or obese adults with one or more risk factors for diabetes should be tested for prediabetes (see Table 2). If there are no additional risk factors, consider screening individuals no later than when they are 45 years old. ...

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... 1 Prediabetes status is defined as intermediate hyperglycemia that is characterized by the main pathophysiological changes of DM: β-cell dysfunction with impaired insulin secretion and decreased insulin tissue cell sensitivity that co-evolve in varying proportions simultaneously rather than sequentially. 2 Individuals with prediabetes are a heterogeneous group as regards the pathophysiology and prognosis. Impaired fasting plasma glucose (IFG) and impaired glucose tolerance (IGT), both of which can appear in isolation or combination (IFG plus IGT), sometimes also associated with high HbA1c, define the subcategories of prediabetes in healthy individuals. ...
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Background Prediabetes and diabetes mellitus (DM) are complications in adult patients with transfusion-dependent β-thalassemia (β-TDT), with their incidence increasing with age. Objective This retrospective observational study describes the glycemic trajectories and evaluates predictive indices of β-cell function and insulin sensitivity/resistance in β-TDT patients with prediabetes, both in a steady state and during 3-h oral glucose tolerance test (OGTT), in order to identify patients at high risk for incipient diabetes. Setting The study was mainly conducted at the Pediatric and Adolescent Outpatient Clinic, Quisisana Hospital, Ferrara (Italy), in collaboration with thalassemia referring centers across Italy. Patients The study included 11 β-TDT (aged 15.11–31.10 years) with prediabetes. Methods: The ADA criteria for the diagnosis of glucose dysregulation were adopted. Investigations included evaluating plasma glucose levels and insulin secretion, analyzing glycemic trajectories and indices of β-cell function, and insulin sensitivity/resistance assessed in steady state and during OGTT. Results The duration of progression from prediabetes to DM, expressed in years, showed a positive direct correlation with corrected insulin response (CIR-30 = r: 0.7606, P: 0.0065), insulinogenic index (IGI 0–120 = r: 0.6121, P:0.045), oral disposition index (oDI = r: 0.7119, P:0.013), insulin growth factor-1 (IGF-1= r: 0.6246, P: 0.039) and an inverse linear correlation with serum ferritin (SF = r: −0.7197, P: 0.012). The number of patients with 1-hour post-load PG value ≥ 155 mg/dL ( ≥ 8.6 mmol/L) was at −4 years: 4/9 (44.4%); −3 years: 8/9 (88.8%); − 2 years: 7/10 (70 %) and at −1 year: 11/11 (100%) (PG range:162–217 mg/dL). Conclusions A progressive increase in 1-hour PG in response to OGTT is associated with progressive β-cell failure, peripheral resistance to insulin action, and reduced oDI and may be considered a relevant marker for incipient DM in β-TDT patients with prediabetes.
... These definitions are based on a variety of hyperglycemia-related parameters such as FBG, 2hBG, and HbA1C (6,7). Nevertheless, there is still no consistent definition of prediabetes, and different definitions correspond to different groups of individuals in epidemiologic studies (8). For example, large surveys of Chinese adults using all three glycemic tests (HbA1C, FBG, or 2hBG) revealed the prevalence of prediabetes, ranging from 36% in one study to as high as 50.1% in another (9). ...
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Background Prediabetes is a widespread condition that represents the state between normal serum glucose and diabetes. Older individuals and individuals with obesity experience a higher rate of prediabetes. Prediabetes is not only a risk factor for type 2 diabetes mellitus (t2dm) but is also closely related to microvascular and macrovascular complications. Despite its importance, a bibliometric analysis of prediabetes is missing. The purpose of this study is to provide a comprehensive and visually appealing overview of prediabetes research. Methods First, the Web of Science (WOS) database was searched to collect all articles related to prediabetes that were published from 1985 to 2022. Second, R language was used to analyze the year of publication, author, country/region, institution, keywords, and citations. Finally, network analysis was conducted using the R package bibliometrix to evaluate the hotspots and development trends of prediabetes. Results A total of 9,714 research articles published from 1985 to 2022 were retrieved from WOS. The number of articles showed sustained growth. Rathmann W was the most prolific author with 71 articles. Diabetes Care was the journal that published the highest number of articles on prediabetes (234 articles), and Harvard University (290 articles) was the most active institution in this field. The United States contributed the most articles (2,962 articles), followed by China (893 articles). The top five clusters of the keyword co-appearance network were “prediabetes”, “diabetes mellitus”, “glucose”, “insulin exercise”, and “oxidative stress”. The top three clusters of the reference co-citation network were “Knowler. WC 2002”, “Tabak AG 2012”, and “Matthews DR1985”. Conclusions The combined use of WOS and the R package bibliometrix enabled a robust bibliometric analysis of prediabetes papers, including evaluation of emerging trends, hotspots, and collaboration. This study also allowed us to validate our methodology, which can be used to better understand the field of prediabetes and promote international collaboration.
... To halt the epidemic of diabetes, we need to target those at risk of developing prediabetes and steer effective strategies, which premises from understanding the characteristics of individuals at "high-risk" systematically. Even though the new thresholds for defining prediabetes have been around for more than 10 years, there is still controversy surrounding the precise characterization of prediabetic population (15). To date, little is known about the prediabetic conditions, and some knowledge of prediabetes gaps still remains in China (16), especially with regard to the potentially different characteristics of prediabetic subgroups classified by impaired fasting glucose (IFG), impaired glucose tolerance (IGT), or elevated glycosylated hemoglobin (HbA1c), in which more tailored and adjusted advices for interventions could be needed. ...
... There was no doubt that prevention approaches in Chinese individuals should differ from those advocated in other populations currently (4). The precise knowledge of prediabetes was not only helpful to distinguish people who might develop prediabetes from those who might not (15) but also contribute to self-identification and self-management. Thus, targeted and regular screening for people at high risk of prediabetes could be cost saving than universal screening (13,14). ...
... Thus, personalized interventions targeting these factors and measures were needed among Chinese adults. Obviously, the prediabetic population was far from being homogeneous, and phenotyping it into less heterogeneous groups might prove useful for long-term risk assessment, follow-up, and primary prevention (15). Several merits of our study deserve to be pointed. ...
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Background There is still controversy surrounding the precise characterization of prediabetic population. We aim to identify and examine factors of demographic, behavioral, clinical, and biochemical characteristics, and obesity indicators (anthropometric characteristics and anthropometric prediction equation) for prediabetes according to different definition criteria of the American Diabetes Association (ADA) in the Chinese population. Methods A longitudinal study consisted of baseline survey and two follow-ups was conducted, and a pooled data were analyzed. Prediabetes was defined as either impaired fasting glucose (IFG), impaired glucose tolerance (IGT), or elevated glycosylated hemoglobin (HbA1c) according to the ADA criteria. Robust generalized estimating equation models were used. Results A total of 5,713 (58.42%) observations were prediabetes (IGT, 38.07%; IGT, 26.51%; elevated HbA1c, 23.45%); 9.66% prediabetes fulfilled all the three ADA criteria. Among demographic characteristics, higher age was more evident in elevated HbA1c [adjusted OR (aOR)=2.85]. Female individuals were less likely to have IFG (aOR=0.70) and more likely to suffer from IGT than male individuals (aOR=1.41). Several inconsistency correlations of biochemical characteristics and obesity indicators were detected by prediabetes criteria. Body adiposity estimator exhibited strong association with prediabetes (D10: aOR=4.05). For IFG and elevated HbA1c, the odds of predicted lean body mass exceed other indicators (D10: aOR=3.34; aOR=3.64). For IGT, predicted percent fat presented the highest odds (D10: aOR=6.58). Conclusion Some correlated factors of prediabetes under different criteria differed, and obesity indicators were easily measured for target identification. Our findings could be used for targeted intervention to optimize preventions to mitigate the obviously increased prevalence of diabetes.
... Preventive methods for the development of type 2 diabetes after gestational diabetes have been studied, and metformin is effective in preventing the occurrence of a metabolic syndrome and may have benefits in early treatment before weight gain or insulin resistance development. The American Diabetes Association recommends metformin use for women with prior gestational diabetes [79,80]. ...
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During gestation, the maternal body should increase its activity to fulfil the demands of the developing fetus as pregnancy progresses. Each maternal organ adapts in a unique manner and at a different time during pregnancy. In an organ or system that was already vulnerable before pregnancy, the burden of pregnancy can trigger overt clinical manifestations. After delivery, symptoms usually reside; however, in time, because of the age-related metabolic and pro-atherogenic changes, they reappear. Therefore, it is believed that pregnancy acts as a medical stress test for mothers. Pregnancy complications such as gestational hypertension, preeclampsia and gestational diabetes mellitus foreshadow cardiovascular disease and/or diabetes later in life. Affected women are encouraged to modify their lifestyle after birth by adjusting their diet and exercise habits. Blood pressure and plasmatic glucose level checking are recommended so that early therapeutic intervention can reduce long-term morbidity. Currently, the knowledge of the long-term consequences in women who have had pregnancy-related syndromes is still incomplete. A past obstetric history may, however, be useful in determining the risk of diseases later in life and allow timely intervention.
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Type 2 diabetes mellitus (T2DM) is one of the most prevalent diseases in modern society, governed by both genetic and environmental factors, such as nutritional habits. This metabolic disorder is characterized by insulin resistance, which is related to high blood glucose levels, implying negative health effects in humans, hindering the healthy ageing of people. The relationship between food and health is clear, and the ingestion of specific nutrients modulates some physiological processes, potentially implying biologically relevant changes, which can translate into a health benefit. This review aims to summarize human studies published in which the purpose was to investigate the effect of protein ingestion (in native state or as hydrolysates) on human metabolism. Overall, several studies showed how protein ingestion might induce a decrease of glucose concentration in the postprandial state (area under the curve), although it is highly dependent on the source and the dose. Other studies showed no biological effects upon protein consumption, mostly with fish-derived products. In addition, the major challenges and perspectives in this research field are highlighted, suggesting the future directions, towards which scientists should focus on. The dietary intake of proteins has been proven to likely exert a beneficial effect on diabetes-related parameters, which can have a biological relevance in the prevention and pre-treatment of diabetes. However, the number of well-designed human studies carried out to date to demonstrate the effects of specific proteins or protein hydrolysates in vivo is still scarce.
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BACKGROUND: The main condition of pre-diabetes is insulin resistance that can lead to a prothrombotic state. AIM: This study aims to correlate insulin resistance with soluble CD40 ligand (sCD40L) and plasminogen activator inhibitor-1 (PAI-1) plasma in pre-diabetic patients. METHODS: This study is an analytic observational study with a cross-sectional approach. HOMA-IR assessed insulin resistance, and prothrombotic factors were assessed by PAI-1 and soluble CD40L. PAI-1 and sCD40L were examined by ELISA. These indicators were assessed on 30 pre-diabetic patients. RESULTS: Thirty subjects included in this study with a mean age of 31.47 (5.03) years old, consist of 19 (63%) men and 11 (37%) women. The mean HOMA-IR was 3.69 (1.12), PAI-1 was 10.25 (3.72) ng/mL, and the PAI-1 levels were increased (>8.4 ng/mL) in 70% of the subjects. The mean of sCD40L levels was 4495.7 (1136.3) pg/ml, and sCD40L levels were increased (>4000 pg/ml) in 63% of subject. There was a significant correlation between HOMA-IR levels and sCD40L (r = 0.636, p < 0.05) and between of HOMA-IR and PAI-1 (r = 0.742, p < 0.05). Moderate correlation was found between sCD40L levels and plasma PAI-1 (r = 0.592, p < 0.05) in pre-diabetic patient. The correlation between three variables was HOMA-IR had a significant effect on PAI-1 levels through sCD40L (t = 2.010, p < 0.05, structure loading factor = 0.286). CONCLUSION: Insulin resistance has a strong and significant correlation with sCD40L and PAI-1 levels in pre-diabetic patients.