Fasting Plasma Glucose Measurements Research Articles

Independent and joint associations between the triglyceride-glucose index and NT-proBNP with the risk of adverse cardiovascular events in patients with diabetes and acute coronary syndrome: a prospective cohort study

BackgroundElevated triglyceride-glucose (TyG) index and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are independently associated with increased risk of major adverse cardio-cerebral events (MACCEs) in diabetic patients with the acute coronary syndrome (ACS), but have not been evaluated jointly. We sought to investigate the independent and joint association of the TyG index and NT-proBNP with MACCEs risk.MethodsData from 5046 patients with diabetes and ACS were recorded in the Cardiovascular Center Beijing Friendship Hospital Database Bank between 2013 and 2021, including measurements of fasting triglycerides, plasma glucose, and NT-proBNP. The TyG index was calculated as Ln (fasting triglycerides [mg/dL] × fasting plasma glucose [mg/dL]/2). Associations of the TyG index and NT-proBNP with MACCEs risk were assessed using flexible parametric survival models.ResultsDuring 13589.9 person-years of follow-up, 985 incident MACCEs of the 5046 patients (65.6 years of age and 62.0% men) were observed. Elevated TyG index (HR: 1.18; 95% CI 1.05‒1.32 per 1 unit increase) and NT-proBNP categories (HR: 1.95; 95% CI: 1.50‒2.54 for > 729 pg/ml compared to < 129 pg/ml) were independently associated with MACCEs risk in the fully adjusted model. According to the joint categories of the TyG index and NT-proBNP, patients with the TyG index > 9.336 and NT-proBNP > 729 pg/ml were at the highest risk of MACCEs (HR: 2.45; 95% CI 1.64‒3.65) than the ones with TyG index < 8.746 and NT-proBNP < 129 pg/ml. The test for interaction was not significant (Pinteraction = 0.49). Incorporating these two biomarkers into the established clinical model, the Global Registry of Acute Coronary Events (GRACE) risk score, resulted in a significant improvement in risk stratification.ConclusionsThe TyG index and NT-proBNP were independently and jointly associated with the risk of MACCEs in patients with diabetes and ACS, suggesting that patients with both markers elevated should be aware of the higher risk in the future.

Relationship between thyroid function tests and bioelectrical impedance measurement parameters according to degree of obesity

Aims: This study aimed to investigate the relationship between thyroid function tests and bioelectrical impedance measurement parameters showing body composition in groups of patients with varying degrees of obesity as determined by body mass index (BMI). Methods: A total of 120 people between the ages of 18 and 65 years were enrolled in the study, including 20 individuals with stage 1 obesity, 20 with Stage 2 obesity, 20 with Stage 3 obesity, and 40 with normal body weights. In the collection of data, a case report form prepared by the researcher for gathering information about the participants and the results of blood tests and bioelectrical impedance measurements made with a Tanita device were used. Blood samples were taken from the antecubital vein between 09:00 and 10:00 in the morning after at least 8 hours of fasting. HOMA-IR values were calculated by measuring fasting plasma glucose and insulin. Results: No significant correlation was found between median BMI and TSH, fT3 and fT4 levels in the whole population. While a negative correlation was found between median TSH and BMI in the group with normal body weight (r=-0.430, p=0.006), a positive correlation was found in the Stage 1 obese group (r=0.553, p=0.011). This relationship was not significant in the Stage 2 and morbidly obese groups. There was no significant correlation between BMI and fT4 and fT3 in all groups. A positive correlation was found between fat percentage and TSH (r=0.391, p=0.014) and fT3 (r=0.333, p=0.038) levels in the group with normal body weight, while no correlation was found with T4 levels. Conclusion: No statistically significant differenceswere found in terms of thyroid functions in different obesity classes as determined by BMI. Elevations of thyroid-stimulating hormone in obese patients are thought to be a result of obesity, not the cause.

Associations of obesity-related indices with prediabetes regression to normoglycemia among Chinese middle-aged and older adults: a prospective study.

Prediabetes is associated with increased cardiovascular risk and all-cause mortality, while its regression will decrease the risks. This study investigated the associations of six obesity-related indices (waist-to-height ratio (WHtR), body roundness index (BRI), conicity index (CI), body shape index (ABSI), Chinese visceral adiposity index (CVAI), and triglyceride glucose (TyG) index) with prediabetes regression based on the China Health and Retirement Longitudinal Study (CHARLS), enrolling middle-aged and older adults. We included 2,601 participants with prediabetes from CHARLS, who were followed up from 2011-2012 to 2015-2016, with blood samples collected for measuring fasting plasma glucose and hemoglobin A1c. All the obesity-related indices at baseline and their dynamic changes were calculated and categorized into tertiles. Logistic regression analysis was applied to obtain the odds ratio (OR) and 95% confidence intervals (CIs). Attributable fractions (AFs) and 95% CIs of these indices and the dynamic changes were calculated with the AF package in R software, and the cutoff values of initial obesity-related indices were obtained by the receiver operating characteristic (ROC) analysis. During the 4-year follow-up period, 562 (21.61%) participants regressed from prediabetes to normoglycemia. They had lower initial BRI, WHtR, CI, ABSI, CVAI, and TyG than those who did not (P < 0.05). After multivariable adjustment, participants in the first tertile of initial BRI (OR, 1.45, 95%CIs, 1.09-1.93), WHtR (OR, 1.46, 95%CIs, 1.10-1.95), and CVAI (OR, 1.47, 95%CIs, 1.11-1.93) had increased odds of prediabetes regression compared with those in the highest tertile. Participants with decreased TyG (OR, 2.08; 95%CIs, 1.61-2.70) also had increased odds of prediabetes regression compared with those with increased TyG. The cutoff values of initial obesity-related indices were 4.374 for BRI, 0.568 for WHtR, 8.621 for TyG, 1.320 for CI, 0.083 for ABSI, and 106.152 for CVAI, respectively. The AFs were 21.10% for BRI < 4.374, 20.85% for WHtR < 0.568, 17.48% for CVAI < 107.794, and 17.55% for ΔTyG < 0, respectively. Low initial BRI, WHtR, and CVAI, as well as TyG reduction, were significantly related to prediabetes regression to normoglycemia, and the AFs were around 20%. Less abdominal fat and insulin resistance reduction would benefit future health outcomes among people with prediabetes.

The Association Between Serum 25-hydroxyvitamin D and Glycemic Control in Patients With Diabetes Mellitus: A Single-Center Retrospective Study.

To determine the association between serum 25-hydroxyvitamin D (25(OH)D) and measures of glycemic control, hemoglobin A1c (HbA1c) and fasting plasma glucose (FPG), in adult patients with diabetes mellitus. This is an analytical cross-sectional study of 270 patients with diabetes admitted to a tertiary hospital. Serum 25(OH)D levels were categorized as follows: sufficient (>30 ng/mL), insufficient (20 to 30 ng/mL), and deficient (<20 ng/mL). The correlation of HbA1c and FPG with serum 25(OH)D and other variables was determined using Spearman's rho (ρ) coefficient. The risk factors associated with HbA1c ≥7% and FPG ≥126 mg/dL were determined using logistic regression analysis to generate crude and adjusted odds ratios. The null hypothesis was rejected at 0.05 α-level of significance. The median serum 25(OH)D was 18.92 (range 3.56-56.3) ng/mL. Ninety percent (245 patients) had vitamin D levels below 30 ng/mL. This study showed that vitamin D level is significantly but weakly correlated with patient's age (ρ=0.339) and duration of diabetes (ρ=0.147), whereas it had inverse correlations with BMI (ρ=-0.134), HbA1c (ρ=-0.261), and FPG (ρ=-0.198). In this study, we found a possible association between vitamin D levels and measures of glycemic control among this group of adult Filipino patients with diabetes mellitus, but further investigations in other cohorts of individuals with diabetes are needed.

Prediabetes, Non-Dipping Profile and Hypertension—A Recipe for Increased Arterial Stiffness

Pulse wave velocity (PWV) is a known predictor of target organ damage, cardiovascular disease and overall mortality. The aim of this study was to compare the PWV values in subjects with prediabetes, a non-dipper profile and arterial hypertension with their values in healthy subjects. A total of 301 subjects, aged 40-70 years, without diabetes mellitus were included in this cross-sectional study (150 with prediabetes). They underwent a 24 h ambulatory blood pressure monitoring (ABPM). Subjects were divided into three hypertension groups (A = healthy, B = controlled hypertension, C = uncontrolled hypertension). Dipping status was determined according to ABPM results, and PWV was measured by an oscillometric device. Prediabetes was defined as having 2 separate fasting plasma glucose (FPG) measurements between 5.6 and 6.9 mmol/L. The highest PWV values were found in group C (9.60 ± 1.34 vs. 8.46 ± 1.01 in group B vs. 7.79 ± 1.10 in group A; p < 0.001), in subjects with prediabetes (8.98 ± 1.31 m/s vs. 8.26 ± 1.22 m/s; p < 0.001) and in prediabetic non-dippers among age groups (p = 0.05). In the multivariate regression model age, blood pressure, nocturnal indices and FPG were shown as independent predictors of PWV values. Significantly higher PWV values were found in subjects with prediabetes and non-dipping profiles in all three examined hypertension groups.

Non-altered incretin secretion in women with impaired fasting plasma glucose in the early stage of pregnancy: a case control study

BackgroundsGlucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) may be involved in pathogenesis of gestational diabetes mellitus (GDM). The aim was to compare GLP-1 and GIP production in fasting state and during 3 h mixed meal tolerance test (MMTT) measured by mean area under the curve (AUC) between pregnant women with normal and impaired fasting glucose in an early phase of pregnancy, and healthy non-pregnant controls.MethodsThis study was undertaken as a case–control study. Repeated measurement of fasting plasma glucose ≥ 5.1 mmol/L and < 7.0 mmol/L during the first trimester of pregnancy and exclusion of overt diabetes according to IADSPG criteria was used to find women with impaired fasting glucose (n = 22). Age-matched controls consisted of healthy pregnant (n = 25) and non-pregnant (n = 24) women. In addition to incretins, anthropometric parameters and markers of insulin resistance and beta-cell function were assessed. Variables were summarized as median (interquartile range).ResultsFasting GLP-1 and GIP concentration or their AUC during MMTT did not significantly differ between pregnant women with impaired fasting plasma glucose [GLP-1AUC 19.0 (53.1) and GIPAUC 302 (100) pg/mL/min] and healthy pregnant women [GLP-1AUC 16.7 (22.3) and GIPAUC 297 (142) pg/mL/min] or non-pregnant controls [GLP-1AUC 16.8 (9.8) and for GIPAUC 313 (98) pg/mL/min]. Although women with impaired fasting glucose were more obese and showed decreased beta-cell function, there were not significant correlations between incretin production and parameters of insulin secretion, insulin resistance, or obesity.ConclusionsWomen with impaired fasting plasma glucose did not show altered incretin production in the first trimester of pregnancy. In contrast to type 2 diabetes, impaired incretin secretion does not seem to play a major role in the early development of GDM.

Correlation of Serum Adiponectin Level with Insulin Resistance in Healthy Obese Individuals: A Case-control Study

Introduction: Obesity, emerging as a worldwide health burden having potential risk for development of atherosclerosis, diabetes, coagulopathy, arthritis and metabolic syndrome. Obesity is classified in terms of various anthropometric modalities like Body Mass Index (BMI), Waist Circumference (WC) and Waist Hip Ratio (WHR) etc. Adipocyte secretes adiponectin that has an important role in energy homeostasis and lipid metabolism. Adiponectin level reduces in obesity and its deficiency results in higher incidence of insulin resistance. Adiponectin has insulin sensitising, antiatherogenic and anti inflammatory properties. Aim: To compare the level of serum adiponectin, fasting plasma insulin and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) in healthy obese individuals with healthy non obese controls and also to find out the correlation of serum adiponectin with fasting plasma insulin level and HOMA-IR in healthy obese cases. Materials and Methods: This case-control study was conducted in Department of Biochemistry, MKCG MCH, Berhampur, Odisha, India, during the period of October 2019 to October 2020 which included 86 subjects. Of which 43 were healthy obese individuals and 43 were age and sex matched healthy non obese volunteers, in the age group of 20-45 years were taken as controls. About 4 mL of whole blood was collected to measure fasting plasma glucose, fasting plasma insulin and serum adiponectin. Statistical Package for the Social Sciences (SPSS) version 16.0 was used to do the statistical analysis and for correlation Pearson correlation test was done. Results: In present study, maximum cases and controls were within the range of 20-35 years. Out of 43 cases, 25 were males and 18 were females and out of 43 controls, 27 were males and 16 were females. Insulin resistance and Fasting Plasma Glucose were significantly higher in healthy obese cases as compared to controls. Serum adiponectin in cases (2.35±0.77) was found to be significantly lower than controls (8.10±2.98). Present study found statistically significant negative correlation of serum adiponectin with fasting plasma insulin (r=-0.918, p&lt;0.001) and HOMA-IR (r=-0.934, p&lt;0.001). Conclusion: Negative correlation of adiponectin and positive correlation of insulin resistance in obesity suggest inflammation which may lead to development of metabolic syndrome. So adiponectin is a target for future research to reduce morbidity and mortality in relation to obesity.

Viscoelastic or Viscoplastic Glucose Theory (VGT #47): Using Viscoplasticity/Viscoplasticity to Explore the Inter-Relationships on Cancer Risk % Versus Sensor Measured Fasting Plasma Glucose and Body Weight Based on Eleven Collected Annual Data Over A 10+ Year Period From 1/1/2012 to 3/20/2022 using the GHMethod: Math-Physical Medicine (No. 632)

The purpose of this research article is to explore a possible link between cancer risk probability percentage (Cancer %) and body weight (BW) in the early morning. Body weight is very easy to measure by standing on a weight scale. Weight in the early morning is highly correlated with fasting plasma glucose (FPG) measured in the early morning or averaged glucose during sleeping hours. FPG also serves as the baseline of postprandial plasma glucose (PPG) and contributes around 25% to 29% of daily average glucose (eAG). Daily average glucose levels or quarterly HbA1C values (average eAG during the past 90-115 days) determine the severity of diabetes disease. Finally, diabetes is one of the major influential chronic diseases for developing many kinds of diseases and complications, including cancers. From the author’s mathematical view, in this biomedical field, an output biomarker sometimes turns into an input biomarker of a third biomarker. Therefore, many biomedical problems can be described as a scenario of the matrix with “m by n by p” dimensions.

Association of fasting plasma glucose trajectory with lifetime risk of cardiovascular disease.

Few studies have used multiple measurements of fasting plasma glucose (FPG) to examine the impact of long-term FPG trajectory patterns on lifetime risk of cardiovascular disease (CVD). We aimed to identify the long-term patterns in FPG trajectories and to estimate the lifetime risk of CVD according to FPG trajectories. Individuals free of CVD at index ages 35 (n = 72,324), 45 (n = 62,049), and 55 (n = 38,113) years were included. FPG concentrations were measured in 2006, 2008, and 2010. The FPG trajectories were identified by latent mixture modeling. The modified Kaplan-Meier method was used to calculate lifetime risk of CVD. We identified five distinct FPG trajectories and named them according to FPG range and changing pattern over time: low-stable, moderate-stable, moderate-increasing, elevated-decreasing, and elevated-stable. At index age 35 years, we documented 3110 CVD events in men during 371,219 person-years of follow-up and 357 CVD events in women during 107,447 person-years of follow-up. Among all participants, the elevated-stable FPG pattern experienced the highest lifetime risk of CVD (44.8%, 95% CI: 37.8-51.9%), low-stable pattern was lowest (24.3%, 95% CI: 23.3-25.2%). At index age 55 years, although the elevated-stable and elevated-decreasing FPG patterns had similar original FPG concentrations, individuals with elevated-decreasing pattern (30.0%, 95% CI: 23.9-36.1%) had approximately one-third less lifetime risk of CVD than those with elevated-stable pattern (43.6%, 95% CI: 31.8-55.3%). FPG trajectories were significantly associated with the lifetime risk of CVD. Both decrease in FPG over time and consistently lower FPG over 4 years were associated with lower lifetime risk of CVD.

Increased Fasting Plasma Glucose and Breast Cancer Risk in Sudanese Women: Association with Premenopausal Status and High Body Mass Index

Background: Female breast cancer is the most common cancer in Sudan, however little data is available about breast cancer in Sudanese. We aimed to assess whether fasting glucose and insulin levels are associated with the risk of having breast cancer in Sudanese women.Methods: This study was conducted at the National Cancer Institute – University of Gezira (NCI-UG), Sudan. A total of 174 females were enrolled, the patient group included 77 newly diagnosed untreated breast cancer women and a control group of 97 healthy women. Overnight fasting blood samples were collected to measure fasting plasma glucose and serum insulin levels. Results: The fasting plasma glucose level was significantly increased in the breast cancer patients (101.94±2.94 mg/dL) than the controls (90.75±2.02 mg/dL), p=0.002. Overweight-obese and premenopausal breast cancer patient’s subgroups revealed significant elevation of fasting glucose levels (105.35±4.06 mg/dL); (99.64±4.06 mg/dL) compared to controls (89.44±2.62 mg/dL), p=0.001; and (86.38±2.44 mg/dL), p=0.007 respectively. Only in the non-obese patients the insulin level was significantly lower (3.76±0.40 µU/ml) than in the control (6.11±1.00 µU/ml) p=0.034. The patient group was more likely to have 2.5 times higher fasting glucose level than the control (p=0.005). Moreover, the overweight-obese and premenopausal breast cancer patients subgroups were more likely to have 4.4 times and 4.5 times respectively elevated fasting blood glucose level, both with p=0.002. The non-obese breast cancer patients were tended to have 4.3 times decreased insulin level (p=0.019). Conclusion: The elevated fasting plasma glucose levels are associated with high risk of breast cancer in Sudanese women especially in the premenopausal individuals and those having BMI more than or equal to 25 kg/m2. Consequently, adjusting blood glucose level and controlling body weight by changing the lifestyle are suggested to reduce the risk of breast cancer in Sudanese women.

Fasting plasma glucose and HbA1c levels predict the risk of type 2 diabetes and diabetic retinopathy in a Thai high-risk population with prediabetes

Introduction: The incidences of diabetes and diabetic retinopathy (DR) in Thai high-risk individuals with prediabetes have not been identified. This study compared diabetes and DR incidences among people at risk with different glycemic levels, using fasting plasma glucose (FPG) and hemoglobin A1C (HbA1c). Materials and methods: A historical cohort study estimating risk of type 2 diabetes and DR was conducted among outpatients, using FPG and HbA1c measurements at recruitment and monitored for ≥5 years. High-risk participants (defined as having metabolic syndrome or atherosclerotic cardiovascular disease) were categorized by glycemic level into 4 groups: 1) impaired fasting glucose (IFG)-/HbA1c- (FPG <110 mg/dl; HbA1c < 6.0%); 2) IFG+/HbA1c- (FPG 110–125 mg/dl; HbA1c < 6.0%); 3) IFG-/HbA1c+ (FPG <110 mg/dl; HbA1c 6.0%–6.4%); and 4) IFG+/HbA1c+ (FPG 110–125 mg/dl; HbA1c 6.0%–6.4%). The incidences of type 2 diabetes mellitus (T2DM) and DR were obtained and estimated using Kaplan-Meier analysis. Cox regression models explored hazard ratios (HRs). Results: We recruited 8,977 people at risk (metabolic syndrome, 89.9%; atherosclerotic cardiovascular disease, 16.9%). The baseline cohort consisted of 1) IFG-/HbA1c- (n = 4,221; 47.0%); 2) IFG+/HbA1c- (n = 1,274; 14.2%); 3) IFG-/HbA1c+ (n = 2,151; 24.0%); and 4) IFG+/HbA1c+ (n = 1,331; 14.8%). Their 5-year T2DM incidences were 16.0%, 26.4%, 30.8%, and 48.5% (p < 0.001). The median DR follow-up was 7.8 years (interquartile range, 7.0–8.4 years). The DR incidences were 0.50, 0.63, 1.44, and 2.68/1,000 person-years (p < 0.001) for IFG-/HbA1c-, IFG+/HbA1c-, IFG-/HbA1c+, and IFG+/HbA1c+, respectively. Compared with IFG-/HbA1c-, the multivariable-adjusted HRs (95% CI) for incident diabetes were 1.94 (1.34–2.80), 2.45 (1.83–3.29), and 4.56 (3.39–6.15) for IFG+/HbA1c-, IFG-/HbA1c+, and IFG+/HbA1c+, respectively. As for incident DR, the corresponding HRs were 0.67 (0.08–5.76), 4.74 (1.69–13.31), and 5.46 (1.82–16.39), respectively. Conclusion: The 5-year incidence of T2DM in Thai high-risk participants with prediabetes was very high. The incidences of diabetes and DR significantly increased with higher degrees of dysglycemia. High-risk people with FPG 110–125 mg/dl and HbA1c 6.0%–6.4% were more likely to develop T2DM and DR. Such individuals should receive priority lifestyle and pharmacological management.

Long-term glycemic variability and risk of adverse health outcomes in patients with diabetes: A systematic review and meta-analysis of cohort studies

AimsTo quantify associations of different metrics of long-term glycemic variability (GV) with multiple adverse diabetes-related outcomes. MethodsWe searched PubMed and Embase from database inception to 23 August 2021. GV was based on measurements of HbA1c or fasting plasma glucose (FPG) and calculated by standard deviation (SD), coefficient of variance (CV) or other metrics. Outcomes included mortality, cardiovascular disease (CVD), renal disease, peripheral neuropathy, retinopathy, dementia and cancer. Random-effects meta-analyses were adopted to pool the relative risks (RRs). ResultsSeventy-five articles with 2,051,701 participants were included. When comparing top with bottom quartiles, HbA1c variabilities were associated with all-cause mortality (RRCV = 1.63, 95 % CI 1.37–1.92; RRSD = 1.87, 1.55–2.26), CVD (RRCV = 1.38, 1.07–1.78; RRSD = 1.34, 1.12–1.59), renal disease (RRCV = 1.43, 1.18–1.74; RRSD = 1.44, 1.24–1.67), and peripheral neuropathy (RRCV = 1.84, 1.40–2.43; RRSD = 1.98, 1.51–2.61), but not retinopathy. FPG variabilities were associated with all-cause mortality (RRCV = 1.59, 1.43–1.78; RRSD = 1.67, 1.26–2.20), renal disease (RRCV = 1.77, 1.32–2.38), and retinopathy (RRCV = 1.92, 1.10–3.35), but not CVD and peripheral neuropathy. Associations of GV with Alzheimer’s disease (RRHbA1c-CV = 1.38, 1.13–1.70; RRFPG-CV = 1.32, 1.07–1.63) and cancer (RRHbA1c-SD = 2.19, 1.52–3.17; RRFPG-CV = 3.64, 2.21–5.98) were each found significant in one study. ConclusionsLong-term GV was associated with multiple adverse diabetes-related outcomes, while the strength of associations varied. The findings support the use of long-term GV for diabetes management in clinical practice.

Day-to-day fasting plasma glucose variability on the short-term prognosis of ST-segment elevation myocardial infarction: A retrospective cohort study.

Glycemic variability in one fact that explain the differences in cardiovascular outcomes. The short-term fasting plasma glucose (FPG) variability may have an on major adverse cardiovascular events (MACE) in type 2 diabetes mellitus (T2DM) patients with ST-segment elevation myocardial infarction (STEMI). This study retrospectively analyzed T2DM patients who underwent emergent percutaneous coronary intervention (PCI) due to STEMI in Fuwai Hospital, Chinese Academy of Medical Sciences, Shenzhen, between January 2016 and March 2020. All patients underwent at least 5 FPG measurements during the perioperative period. FPG variability score (FPG-VS) was defined as the percentage of the number of FPG variations > 1 mmol/L between two adjacent FPG measurements. The Cox proportional-hazards model was used to estimate the relationship between FPG-VS and MACE. A validation set was utilized to further evaluate the prognostic value of FPG-VS in a standardized STEMI diabetic diet cohort following PCI intervention. A total of 612 patients were included in the retrospective cohort study. In comparison to the minimum quintile, FPG-VS > 60% was associated with an increased risk of 30-day MACE. Moreover, compared to FPG-VS ≤ 20%, the FPG-VS > 80% group had a higher risk of MACE (odd ratio [OR] = 4.87, 95% confidence interval [CI]: 2.55-5.28), recurrent angina pectoris (OR = 5.43, 95%CI: 2.27-8.27), nonfatal myocardial infarction (OR = 5.00, 95%CI: 2.47-7.69), heart failure (OR = 3.70, 95%CI: 1.92-5.54), malignant arrhythmia (OR = 4.63, 95%CI: 1.12-6.25) and cardiac death (OR = 1.41, 95%CI: 0.17-1.97). Consistent results were obtained after adjustment for HbA1c, demonstrating the robustness of FPGFPG-VS. Moreover, the standard diet intervention group had a lower FPG-VS index as well as a lower incidence of MACE. Higher FPG variability is associated with an increased risk of MACE within 30 days in diabetes patients receiving PCI for STEMI. A standardized diet may improve the prognosis of STEMI patients by reducing the FPG-VS.

Validation of salivary glucose as a screening tool of diabetes mellitus.

Background: Improved prognosis and delay of clinical complications in diabetes mellitus can be ensured by early screening and regular monitoring after diagnosis. This requires venipuncture at regular intervals of time causing anxiety and discomfort to the patient. Hence, development of a painless, non-invasive procedure is desirable for which saliva is a potential tool. Also, this would provide easy and cost-effective means for large scale screening and epidemiological intervention. Aim: To measure fasting plasma glucose (FPG) and compare and correlate with salivary glucose levels in normal and diabetic individuals. Also, the correlation between glycated hemoglobin (HbA1c) and salivary glucose is studied in the diabetics and controls. Methods: Blood and salivary glucose was estimated by GOD-POD method and glycated hemoglobin by HPLC. Statistical analysis was done on SPSS 16. Mean, Standard deviation, independent t test, ANOVA (f test), Pearson's correlation coefficient along with regression analysis was carried out and comparison was done between the control and diabetic groups and the different subgroups within the diabetic group. Results: A significant difference between the salivary glucose levels in subjects indicating that a deranged glycemic status is reflected in saliva. Also, salivary glucose increases in proportion to an increase in the FPG and HbA1C of the diabetics. The regression coefficient was calculated and a formula was derived for prediction of FPG and HbA1c using salivary glucose. Conclusion: Saliva can be used as a screening tool for diabetes. Standardization of the technique and setting up a reference range will also make it useful in diagnosing diabetes mellitus.

Correlates of Glycemic Control Among Patients With Type 2 Diabetes in Eastern Ethiopia: A Hospital-Based Cross-Sectional Study

IntroductionEven though optimal blood glucose control reduces the risk of diabetes-related complications, many patients with type 2 diabetes (T2D) fail to achieve it for a variety of reasons. In the study area, there was a paucity of evidence regarding correlates of glycemic control. Therefore, this study aimed to find out the correlates of glycemic control among patients with T2D in Eastern Ethiopia.MethodsA cross-sectional study was conducted among 879 adult patients with T2D on follow-up at two public hospitals in Harar. Data were collected through interviews, physical measurements, and record reviews. The level of glycemic control was determined from three consecutive fasting plasma glucose (FPG) measurements. A mean value of FPG measurements falling in the normal range (80–130 mg/dl) was considered as optimal glycemic control; otherwise, a mean FPG level that is below or above the normal range (<80 mg/dl or >130 mg/dl) was defined as suboptimal glycemic control. Descriptive statistics were used to summarize the data, while a linear regression model was used to find out the correlates of glycemic control. A beta coefficient and a 95% CI reported associations. The statistical significance was declared at a p-value ≤0.05.ResultsThe mean age of the patients with T2D was 52.7 ( ± 13.3) years. The mean FPG level was 172 ± 56 mg/dl. Suboptimal glycemic control was found in 76% (95% CI: 73.41, 79.04) of patients with T2D. In a multivariable linear regression, khat chewing (β = 6.12; 95% CI: 1.55, 8.69), triglycerides (β = 0.56; 95% CI: 0.41.48, 0.65), comorbidity (β = 5.29; 95% CI: 1.39, 9.13), and poor level of self-care practices (β = 5.43; 95% CI: 1.41, 6.46) showed a significant correlation with glycemic control.ConclusionsThis study found that about three-fourths of patients with T2D had suboptimal glycemic control. Khat chewing, comorbidity, and poor level of self-care practices were independently correlated with glycemic control. Thus, suppressing glycemic levels through appropriate treatment and strict diabetes self-care practices including avoidance of Khat chewing is a useful approach to attaining glycemic target that subsequently reduces cardiovascular risks.

Association of Visit-to-Visit Variability in Fasting Plasma Glucose with Digestive Cancer Risk.

Background and Aims The aim of this study is to investigate the association between visit-to-visit variability in fasting plasma glucose (FPG) and the risk of digestive cancers among individuals with and without diabetes. Methods Using data from Kailuan cohort, a prospective population-based study, individuals who had at least two measurements of FPG between 2006 and 2012 without prior cancer were included in this study. Four indexes of variability were used, including standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average successive variability (ARV). Cox regression was used to evaluate the relationship between the quartiles of FPG variability and digestive cancers. Results A total of 98,161 individuals were studied. Over a mean follow-up of 9.32 ± 0.81 years, 1103 individuals developed incident digestive cancer (1.21 per 1000 person-years). Compared to the individuals in the lowest quartile, those in the highest quartile of FPG variability by SD had 38.7% higher risk of developing overall digestive cancers after adjusting for the significant confounders (hazard ratio, 1.387; 95% confidence interval, 1.160-1.659; P = 0.0003). Higher FPG variability was associated with significantly higher risks of colorectal cancer (fully adjusted HR 1.432, 95% CI [1.073-1.912], P = 0.015) and pancreatic cancer (fully adjusted HR 2.105, 95% CI [1.024-4.329], P = 0.043), but not liver cancer (fully adjusted HR 1.427, 95% CI [0.973-2.092], P = 0.069) or esophageal and gastric cancer (fully adjusted HR 1.139, 95% CI [0.776-1.670], P = 0.506). Subgroup analyses showed that individuals who were younger (<65 years), male, and those without diabetes experienced a predominantly higher risk of developing digestive cancers. Similar results were observed when using CV, VIM, and ARV. Conclusions FPG variability was significantly associated with increasing risk of digestive cancers, especially for pancreatic and colorectal cancer. Our study suggested a potential role of FPG variability in risk stratification of digestive cancers. Approaches that reduce FPG variability may lower the risks of incident digestive cancers among the general population. This trial is registered with ChiCTR-TNRC-11001489.

Viscoelastic and Viscoplastic Glucose Theory (VGT #29): Applying viscoelastic Glucose Theory with CGM Sensor Measured Fasting Plasma Glucose (FPG) Values as the Strain along with the FPG Change Rate Multiplied by a Viscosity Factor as the Stress, and Finally Utilizing the Viscoelastic Perturbation Model to Calculate the Predicted FPG Values to Compare Against the Measured FPG Values Based on GH-Method:

The author has studied strength of materials and theory of elasticity through his undergraduate courses at the University of Iowa. He also conducted research work to earn a master’s degree in Biomechanics under Professor James Andrews. At that time, he used the spring and dashpot models to simulate the behaviors of human joints, bones, muscles, and tendons in order to investigate the human-weapon interactions during the Vietnam war era. Later, he went to MIT to pursue his PhD study under Professor Norman Jones, who taught him theory of plasticity and dynamic plastic behaviors of various structure elements. He also took additional graduate courses in the field of fluid dynamics and thermodynamics. Since then, many advancements have been made in the biomechanics branch, especially with human body tissues that possess certain viscoelastic characteristics, such as bones, muscles, cartilages, tendons (connect bone to muscle), ligaments (connect bone to bone), fascia, and skin. For example, the author suffered plantar fasciitis for many years. He understood that the night splint dorsiflexes forefoot, at the back of the foot, increases plantar fascia tension to offer stress-relaxation for the pain. This model where muscles and tendons connect the lower leg and foot is a form of viscoelastic study for medical problem solving. When dealing with human internal organs, it is not easy to conduct live experiments to obtain accurate measurements for the biomedical material properties. Blood itself is a viscous material (time-dependent) and its viscosity factor may fall between water, honey, syrup, or gel. The author’s research focuses on “glucose” where the blood sugar amount is produced by the liver and carried by red blood cells, not the blood itself. Fasting plasma glucose (FPG) has nothing to do with either diet or exercise during sleep hours and is mainly relying on the health condition of both liver and pancreatic beta cells, which produces glucose and releases insulin, to control the glucose level in blood. Therefore, it is nearly impossible to measure the material geometry or material properties to determine the viscosity of “glucose” like in engineering research work. As a result, the best the author could do is to apply the “concept of viscoelasticity and/or viscoplasticity” to construct an analogy model of time-dependent glucose behaviors.

Viscoelastic or Viscoplastic Glucose Theory (VGT #46): Using Viscoplasticity/ Viscoplasticity to Explore the Inter-Relationships on CVD Risk % Versus Sensor Measured Fasting Plasma Glucose and Body Weight Based on Eight Collected Semi-Annual Data over an ~4-Year Period from 5/8/2018 to 3/20/2022 using the GH-Method: Math-Physical Medicine (No. 631)

The purpose of this research article is to explore a possible link between CVD risk probability percentage (CVD %) and body weight (BW) in the early morning. Body weight is very easy to measure by standing on a weight scale. Weight in the early morning is highly correlated with fasting plasma glucose (FPG) measured in the early morning or averaged glucose during sleeping hours. FPG also serves as the baseline of postprandial plasma glucose (PPG) and contributes around 25% to 29% of daily average glucose (eAG). Daily average glucose levels or quarterly HbA1C values (averaged eAG during the past 90-115 days) determine the severity of diabetes disease. Finally, diabetes is one of the major influential chronic diseases for developing many kinds of heart diseases, such as cardiovascular diseases (CVD). From the author’s mathematical view, in this biomedical field, an output biomarker sometimes turns into an input biomarker of a third biomarker. Therefore, many biomedical problems can be described as a scenario of the matrix with “m by n by p” dimensions. Since 2012, the author has been collecting his body weight (BW) and finger-piercing glucose values each day. In addition, he accumulates medical conditions data including blood pressure (BP), heart rate (HR), and blood lipids along with lifestyle details (LD). Based on the collected big data, he further organized them into two main groups. The first is the medical conditions group (MC) with 4 categories: weight, glucose, BP, and blood lipids. The second is the LD group with 6 categories: food &amp; diet, exercise, water intake, sleep, stress, and daily routines. At first, he collected his data daily since Y2012 and then calculated a unique combined daily score for each of the 10 categories within the MC and LD groups. The combined scores of the 2 groups, 10 categories, and 500+ detailed elements constitute an overall “metabolism index (MI) model”. This MI model includes the root causes from 6 major lifestyle inputs and symptoms from 4 rudimentary chronic diseases: obesity, diabetes, hypertension, and hyperlipidemia. Therefore, it can serve as the foundation and building block for his additional research work that can expand into various diseases associated with different organs, such as cardiovascular diseases (CVD), and cancers.

Viscoelastic or Viscoplastic Glucose Theory (VGT #47): Using Viscoplasticity/ Viscoplasticity to Explore the Inter-Relationships on Cancer risk % Versus Sensor Measured Fasting Plasma Glucose and Body Weight Based on Eleven Collected Annual Data over a 10+ Year Period From 1/1/2012 to 3/20/2022 using the GH-Method: Math-Physical Medicine (No. 632)

The purpose of this research article is to explore a possible link between cancer risk probability percentage (Cancer %) and body weight (BW) in the early morning. Body weight is very easy to measure by standing on a weight scale. Weight in the early morning is highly correlated with fasting plasma glucose (FPG) measured in the early morning or averaged glucose during sleeping hours. FPG also serves as the baseline of postprandial plasma glucose (PPG) and contributes around 25% to 29% of daily average glucose (eAG). Daily average glucose levels or quarterly HbA1C values (average eAG during the past 90-115 days) determine the severity of diabetes disease. Finally, diabetes is one of the major influential chronic diseases for developing many kinds of diseases and complications, including cancers. From the author’s mathematical view, in this biomedical field, an output biomarker sometimes turns into an input biomarker of a third biomarker. Therefore, many biomedical problems can be described as a scenario of the matrix with “m by n by p” dimensions. Since 2012, the author has been collecting his body weight (BW) and finger-piercing glucose values each day. In addition, he accumulates medical conditions data including blood pressure (BP), heart rate (HR), and blood lipids along with lifestyle details (LD). Based on his collected big data, he further organized them into two main groups. The first is the medical conditions group (MC) with 4 categories: weight, glucose, BP, and blood lipids. The second is the LD group with 6 categories: food &amp; diet, exercise, water intake, sleep, stress, and daily routines. At first, he collected his data on a daily basis since Y2012 and then calculated a unique combined daily score for each of the 10 categories within the MC and LD groups. The combined scores of the 2 groups, 10 categories, and 500+ detailed elements constitute an overall “metabolism index (MI) model”. This MI model includes the root causes from 6 major lifestyle inputs and symptoms from 4 rudimentary chronic diseases: obesity, diabetes, hypertension, and hyperlipidemia. Therefore, it can serve as the foundation and building block for his additional research work that can expand into various diseases associated with different organs, such as cancers. As we know, lifestyle details cause rudimentary chronic diseases which further influence more complicated diseases, such as heart problems (CVD &amp; CHD), chronic kidney disease (CKD), stroke, diabetic retinopathy (DR), neuropathy, hypothyroidism, diabetic constipation, diabetic skin fungal infection, and others including cancers. Some genetic conditions and lifetime unhealthy habits, such as smoking, alcohol consumption, and illicit drug use would account for approximately 15% to 25% of the root cause of chronic diseases &amp; their complications, including cancers and dementia. Some external factors - environmental factors and viral infections, such as radiation, air and water pollution, food poison and pollution, toxic chemicals, and hormonal therapy can also contribute to the causes of a variety of cancers.

Gender as a Risk Factor for Cardiovascular Disease in type 2 Diabetes-Sudan

OBJECTIVES: Researchers intended to see if there was a link between gender and an increased risk of dyslipidemia and cardiovascular disease (CVD) in Sudanese people with type 2 diabetes mellitus (T2DM) by measuring fasting plasma glucose (FPG), glycated hemoglobin (HbA1C) and lipid profiles as well as blood pressure. MATERIALS AND METHOD: During the period of April 2012 and March 2013, a case-control study was conducted in Central Sudan. The study involved 300 people who met the inclusion criteria, who were divided equally into diabetes, diabetic hypertension, and non-diabetic non hypertensive (NDNH) groups to estimate FPG, HbA1C, and lipid profile levels (TC, HDL-C, LDL-C, and TG). A15, a random access auto-analyzer bio system, was used to analyze the samples. A questionnaire was completed, which included personal information, anthropometric and biochemical measurements. After each respondent gave verbal consent, venous blood was drawn after an overnight fast. The statistical analysis was done with the help of a statistical software for social sciences (SPSS version 16, Chicago, IL, USA). RESULT: In the women's group, statistically significant differences in anthropometric measurements (WC =0.017, BMI =0.004, SBP &lt;0.0001, DBP=0.029) and biochemical measurements (FPG &lt;0.0001, HbA1C =0.007, HDL-C=0.027) were discovered when the means were compared. When the mean HDL-C values of diabetic and diabetic hypertensive women were compared, there was a significant rise of 0.029. Men, on the other hand, had statistically significant disparities in anthropometric parameters, with WC=0.001, BMI &lt;0.0001, and SBP &lt;0.0001. FPG showed a significant increase of &lt;0.0001, whereas HbA1C mean in diabetes and diabetic hypertensive patients showed poor management with no significant increase (0.615). HDL-C had a modestly high mean (0.089), while DBP had a non-significant increase (0.172). CONCLUSION: Diabetic and diabetic hypertensive women were at increased risk of dyslipidemia and CVD.