Supervised Machine Learning-Based Models for Predicting Raised Blood Sugar.

Raised blood sugar (hyperglycemia) is considered a strong indicator of prediabetes or diabetes mellitus. Diabetes mellitus is one of the most common non-communicable diseases (NCDs) affecting the adult population. Recently, the prevalence of diabetes has been increasing at a faster rate, especially in developing countries. The primary concern associated with diabetes is the potential for serious health complications to occur if it is not diagnosed early. Therefore, timely detection and screening of diabetes is considered a crucial factor in treating and controlling the disease. Population screening for raised blood sugar aims to identify individuals at risk before symptoms appear, enabling timely intervention and potentially improved health outcomes. However, implementing large-scale screening programs can be expensive, requiring testing, follow-up, and management resources, potentially straining healthcare systems. Given the above facts, this paper presents supervised machine-learning models to detect and predict raised blood sugar. The proposed raised blood sugar models utilize diabetes-related risk factors including age, body mass index (BMI), eating habits, physical activity, prevalence of other diseases, and fasting blood sugar obtained from the dataset of the STEPwise approach to NCD risk factor study collected from adults in the Palestinian community. The diabetes risk factor obtained from the STEPS dataset was used as input for building the prediction model that was trained using various types of supervised learning classification algorithms including random forest, decision tree, Adaboost, XGBoost, bagging decision trees, and multi-layer perceptron (MLP). Based on the experimental results, the raised blood sugar models demonstrated optimal performance when implemented with a random forest classifier, yielding an accuracy of 98.4%. Followed by the bagging decision trees, XGBoost, MLP, AdaBoost, and decision tree with an accuracy of 97.4%, 96.4%, 96.3%, 95.2%, and 94.8%, respectively.

Examining the Impact of a Behavior Modification Program on Disease Prevention Behaviors among Individuals at Risk of Diabetes: A Quasi-Experimental Investigation.

This study aimed to develop and test a behavior modification intervention to prevent type 2 diabetes (T2DM) among at-risk individuals. The primary goal was to compare diabetes prevention behaviors and fasting blood sugar levels between the intervention and comparison groups. This study utilizes a quasi-experimental design to develop a behavior modification intervention for preventing diabetes. It involves two groups, each with pre- and post-intervention assessments, comprising 60 at-risk individuals equally divided into intervention and comparison groups. The 8-week intervention includes components like risk assessment, dietary skill enhancement, exercise, stress management, and social media platforms (data recording training, follow-up visits, reminders, and visual aids). Data collection includes self-administered questionnaires and blood sugar level measurements. Statistical analysis involved paired t-tests for within-group comparisons and independent t-tests for between-group differences. The findings showed that the intervention group achieved significantly higher average scores in nutrition, exercise, and stress management, and had significantly lower average blood sugar levels compared to the comparison group. These results suggest that healthcare providers and policymakers should develop community health programs and public health policies that incorporate integrative care, leverage social media platforms, and foster collaboration with other health professionals to improve outcomes for individuals at risk of T2DM.

Association between hematological indices and blood glucose level among patients with type 2 diabetes.

BACKGROUND: Diabetes mellitus is a major health problem with a variety of implications: cellular, metabolic, and hematological. Hematological alterations observed in type 2 diabetes are related to hyperglycemia and have a vital role in vascular-associated diabetes complications which could be used as a marker for these complications. The aim of this study is to assess the association between hematological indices and blood glucose levels in patients with type 2 diabetes attending outpatient clinics in Mosul. PATIENTS AND METHODS: A case-control study was done on 100 patients with type 2 diabetes and 100 healthy controls attending Alwafa Center for Diabetes and Endocrinology and four family medicine health centers in Mosul for the period 1st of January 2024-30th of March 2024. Data collection was done by a direct interview with participants. Hematological indices were tested by using an automatic hematology analyzer. RESULTS: Statistically significant differences in Hb were found between diabetic patients and controls (P = 0.007). The total WBC count, neutrophils, and lymphocytes were significantly higher in diabetic patients compared to controls (P = 0.001 for all). Moreover, platelet indices (platelets count and PDW) showed a significant difference between diabetic patients and controls (P = 0.004 and 0.000) respectively. In addition, total WBC count, neutrophil count, and lymphocytes show a statistically significant positive correlation with FBS (P = 0.026, 0.050, and 0.019) respectively. CONCLUSION: This study revealed statistically significant differences in various hematological parameters between patients with type 2 diabetes and healthy controls. Regular testing of hematological indices helps in early detection and proper management of diabetic complications.

Diabetic retinopathy incidence, predictors and its association with longitudinal fasting blood sugar level changes among diabetes mellitus patients in Ethiopia: joint model.

Background: Diabetes mellitus (DM) is a global public health problem characterized by an elevated blood glucose level. Monitoring blood sugar levels is vital for effective diabetes management and preventing complications. However, the association between longitudinal biomarkers and the incidence of diabetic complications is often overlooked. Therefore, this study aimed to assess the incidence of diabetic retinopathy, predictors, and association with longitudinal fasting blood sugar level changes among diabetes mellitus patients in Ethiopia. Methods: A multicenter retrospective follow-up study was carried out in referral hospitals in Amhara region, Ethiopia. A random sample of 462 newly diagnosed DM patients was selected. The proportional hazard assumption was checked for the survival sub-model, and for the longitudinal sub-model, the normality assumption was checked. Then the joint modeling with time-dependent lagged parameterizations was fitted. Model assumptions and comparisons were checked. Finally, the hazard ratio with a 95% confidence interval (CI) with a corresponding P-value<0.05 was used to identify predictors. Results: In this study, Overall, 54 patients developed DR, and the incidence rate was 2.33 per 1000 person-months over the follow-up period, with a 95% CI of [1.78, 3.05]. Rural residence (AHR = 2.21, 95% CI: [1.21, 4.05]), hypertension co-morbidity (AHR = 3.01, 95% CI: [1.85, 6.53]), and longer duration of DM (>5 years) (AHR = 2.28, 95% CI: [1.91, 5.15]) were important predictors for the incidence of DR. In addition, the incidence of DR was substantially correlated with the time-dependent lagged value of FBS change (AHR = 4.20, 95% CI [1.62, 10.85]). Conclusions: In this study, the incidence of diabetic retinopathy was somewhat high when compared to prior similar studies in Ethiopia. A joint model of longitudinal fasting blood sugar level changes was significantly associated with an increased risk of DR. Besides, being rural residence, hypertension co-morbidity, and a longer duration of DM were significant predictors for the incidence of DR. Therefore, public awareness, an integrated care approach, and prioritizing glycemic control are highly recommended.

The association between dietary meal intake habits and coronary artery stenosis and cardio-metabolic risk factors.

BACKGROUND AND OBJECTIVE: We are not aware of studies examining the association between dietary meal intake habits (DMIH) and severity of coronary artery stenosis (CAS). This study was conducted to investigate the relationship between DMIH and the severity of CAS as well as cardiometabolic risk factors in adults undergoing coronary angiography. METHODS: This cross-sectional study was done on 720 patients undergoing coronary angiography (aged 35-75 years) who were admitted to Afshar Hospital, a referral hospital for cardiovascular diseases in Yazd, Iran. Data on DMIH were gathered by interview. Blood samples were taken for biochemical analysis. Blood pressure, anthropometric indices, and body composition were also evaluated. The relationship between DMIH and the severity of CAS [examined by angiography based on Gensini Score (GS) and Syntax Score (SS)] and cardiometabolic risk factors were assessed using logistic regression and the analysis of covariance (ANCOVA), respectively, in crude and multivariable adjusted models. RESULTS: After adjustment for all possible confounding variables, the study revealed that people who ate 3 meals/day had a lower risk of severe CAS compared to people who ate 2 or fewer meals (OR = 0.48, 95% CI: 0.26, 0.88, P-trend = 0.02). There was an inverse association between the number of snacks /day and the severity of CAS (OR = 0.43, 95% CI: 0.22, 0.87, P-trend = 0.02). There was also an inverse relationship between breakfast frequency/week and the severity of CAS based on both GS and SS (P < 0.05). Breakfast consumption, meal frequency, lunch consumption, snack frequency, and more food consumption on holidays were also associated with different cardiometabolic markers and anthropometric measures (P < 0.05). CONCLUSION: According to the results of the present study, meal frequency and breakfast consumption might be inversely associated with CAS and cardiometabolic risk factors.

How Age, Sex and Transfusion Affects the Incidence of Endocrine and Bone Density Disorders in Major Thalassemic Patients.

Background: Beta-thalassemia major patients frequently have endocrinopathies. We tried to determine relation between demographic and transfusion factor and endocrinopathies. Methods: Major beta-thalassemia patients (n=114 cases), 3-38 yr of age, entered this study. Female to male ratio was 51/63. Children (less than 20 yr) formed 57% of participants. Information about bone mineral density (BMD) and hormonal and biochemistry blood evaluation including fasting blood sugar (FBS), ferritin, triiodothyronine (T3), thyroxine (T4) and thyroid-stimulating hormone (TSH), luteinizing hormone (LH) and follicle-stimulating hormone (FSH), testosterone (males), and estradiol (females) entered data sheet. Results: Sex and ferritin level showed no significant correlation with above disorders. Age significantly correlated to short stature, diabetes, low BMD at femur and neck (P, 0.031, 0.008, 0.009 and <0.001, respectively) . The risk of short stature had increased in 12 yr and older patients 7.71 times than younger patients (P= 0.008). The risk of diabetes had increased in 35 yr and older patients 26.25 times than younger patients (P= 0.03). The risk of Z-score ≤ -2 in femoral region has increased in 19 yr and older patients 5.84 times than younger patients (P= 0.002). The risk of Z-score ≤ -2 in spinal region has increased in 14 yr and older patients 17 times than younger patients (P= 0.007). Conclusion: The main factor related with endocrinopathies was age. The correlation between age and short stature, diabetes and low BMD was positive. Therefore, we recommend early monitoring of thalassemia patients (in their late childhood and early teenage) for these complications.

Point prevalence of metabolic syndrome in HIV positive patients.

Introduction: Human immunodeficiency virus (HIV)-related morbidity and mortality have declined over time, but this increased longevity may lead to the development of other diseases, which may further manifest as the metabolic syndrome (MS). Method: To find out the point prevalence of MS in HIV positive patients, a cross-sectional prospective observational study was conducted on 200 patients who approached ART plus Centre of Government Medical College and Hospital Jammu, including 50 symptomatic patients HIV negative as controls. Results: The mean age group in MS was 37.85 ± 6.61. Males consisted of 55% (110) and females consisted of 45% (90). The overall prevalence of MS was 13.5%, with prevalence in males being 16.3% and in females 10%. Patients receiving first line highly active antiretroviral therapy (HAART) showed a 24% prevalence, while that of second line HAART showed a 14% prevalence. Central obesity (47.3%) was the most common component of MS followed by hyperglycemia (43.3%), hypertriglyceridemia (38.6%), and low high density cholesterol (HDL-C) level (38.6%). Out of 84 males with MS, 94% (79) males were having hypertriglyceridemia, 88% (74) were hypertensive, and 72% (60) were having FBS >=100. Out of 66 females with MS, 100% (66) females had central obesity and 88% (58) had hypertriglyceridemia and low HDL-C levels. Conclusion: The metabolic complications as a result of treatment with HAART leave HIV patients at a risk of developing cardiovascular disease and diabetes in spite of improvements in morbidity and mortality. Risk factors like central obesity, hypertension, hyperglycemia, and hypertriglyceridemia should be taken into consideration well before to prevent the add-on effect of developing MS.

Relationship between blood lead (Pb) concentration with risk of diabetes mellitus in women living in mining area.

Diabetes is a global health concern with significant implications for individuals and societies. Diabetes results from a complex interaction between genes and environmental factors, including metal exposure. Lead or plumbum (Pb) is a heavy metal pollutant and is predicted to be associated with the morbidity of diabetes. The aim of this study was to assess the relationship between blood Pb level and possible risk factors (body mass index insulin resistance, carbohydrate intake, sugar intake, and physical activity) with fasting blood sugar (FBS) level in women living in the mining area. A cross-sectional study was conducted in a mining area of Indonesia located in Pemali District, Bangka Belitung Regency, involving women aged 30-49, selected through purposive sampling. Logistic regression was used to assess the relationship between the risk factors and FBS level, while the Spearman correlation was used to analyze the correlations between the risk factors and FBS level. Our data indicated that blood Pb concentration and other risk factors (carbohydrate intake, sugar intake and physical activity) were neither associated nor correlated with FBS level. However, as predicted, insulin resistance was associated with FBS level with OR: 9.66; 95%CI: 1.13-82.29; p=0.038. In addition, the Homeostatic Model Assessment Insulin Resistance (HOMA-IR) score was also correlated with FBS level (r=0.316, p=0.002). This study highlights the level of Pb is not associated with the risk of diabetes in women living in mining area.

The relationship between health literacy and blood sugar control in rural areas among diabetes patients.

Background: Although the relationship between health literacy and glycemic control has been explored in patients with diabetes, little is known about the relationship between different categories of diabetes health literacy and glycemic control in rural areas. Therefore, this study focused on the relationship between different categories of health literacy and glycemic control among diabetic patients in rural areas of Guangxi, China. Objective: To explore the potential profiles of health literacy among rural diabetes patients in Guangxi and investigate their relationship with blood sugar control. Methods: A health literacy questionnaire was administered to 2280 rural diabetes patients in five cities in the Guangxi Zhuang Autonomous Region. Latent profile analysis was conducted to identify potential health literacy profiles. Results: Health literacy among rural diabetes patients in Guangxi could be categorized into high literacy-high functionality and low literacy-low criticality groups. The latent categories of health literacy were associated with blood sugar control, with diabetes patients in the high literacy-high functionality group demonstrating better blood sugar control than those in the low literacy-low criticality group (P < 0.05). Conclusion: Health literacy among rural diabetes patients in Guangxi exhibits heterogeneity. Healthcare professionals should pay attention to patients with low literacy and low criticality in rural areas and develop interventions to enhance their health literacy, thereby improving their blood sugar control.

Generalization of a Deep Learning Model for Continuous Glucose Monitoring-Based Hypoglycemia Prediction: Algorithm Development and Validation Study.

Background: Predicting hypoglycemia while maintaining a low false alarm rate is a challenge for the wide adoption of continuous glucose monitoring (CGM) devices in diabetes management. One small study suggested that a deep learning model based on the long short-term memory (LSTM) network had better performance in hypoglycemia prediction than traditional machine learning algorithms in European patients with type 1 diabetes. However, given that many well-recognized deep learning models perform poorly outside the training setting, it remains unclear whether the LSTM model could be generalized to different populations or patients with other diabetes subtypes. Objective: The aim of this study was to validate LSTM hypoglycemia prediction models in more diverse populations and across a wide spectrum of patients with different subtypes of diabetes. Methods: We assembled two large data sets of patients with type 1 and type 2 diabetes. The primary data set including CGM data from 192 Chinese patients with diabetes was used to develop the LSTM, support vector machine (SVM), and random forest (RF) models for hypoglycemia prediction with a prediction horizon of 30 minutes. Hypoglycemia was categorized into mild (glucose=54-70 mg/dL) and severe (glucose<54 mg/dL) levels. The validation data set of 427 patients of European-American ancestry in the United States was used to validate the models and examine their generalizations. The predictive performance of the models was evaluated according to the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: For the difficult-to-predict mild hypoglycemia events, the LSTM model consistently achieved AUC values greater than 97% in the primary data set, with a less than 3% AUC reduction in the validation data set, indicating that the model was robust and generalizable across populations. AUC values above 93% were also achieved when the LSTM model was applied to both type 1 and type 2 diabetes in the validation data set, further strengthening the generalizability of the model. Under different satisfactory levels of sensitivity for mild and severe hypoglycemia prediction, the LSTM model achieved higher specificity than the SVM and RF models, thereby reducing false alarms. Conclusions: Our results demonstrate that the LSTM model is robust for hypoglycemia prediction and is generalizable across populations or diabetes subtypes. Given its additional advantage of false-alarm reduction, the LSTM model is a strong candidate to be widely implemented in future CGM devices for hypoglycemia prediction.

Association of Glycated Hemoglobin With Acute Ischemic Stroke in a Tertiary Care Center in a Tribal Region of Jharkhand.

BACKGROUND: Increased glycated hemoglobin (HbA1c) levels have shown an association with an increased risk of stroke in patients admitted to a tertiary care center in Jharkhand. OBJECTIVES: To find out and estimate the risk of acute ischemic stroke in patients with increased HbA1c levels compared with controls. METHODS: This observational case-control study was conducted on patients admitted to the department of general medicine at a tertiary care center in Ranchi from June 2021 to November 2022. The patients included in this study were those aged 18 years or older and who were clinically and radiologically diagnosed with acute ischemic stroke. Only patients with a first episode of stroke were included, and patients with hemorrhagic stroke or transient ischemic attack were excluded from this study. An equal number of control participants were also included. Ion exchange high-performance liquid chromatography was used to perform the HbA1c tests. The same method was used to measure HbA1c levels in the controls. All findings were recorded in a Microsoft Excel sheet (Microsoft Corporation, Redmond, WA), and the data were analyzed using SPSS version 22.0 software (IBM Corp., Armonk, NY). After performing a descriptive statistical analysis, the findings were classified over a range of values and described accordingly. For each variable, an independent t-test was performed to compare the cases with the controls. A multivariable logistic regression analysis was used to choose the appropriate potential factors to determine the association in the multivariable analysis. RESULTS: A total of 185 cases and 185 controls were included. The mean age of the cases with ischemic stroke was 63.77 ± 10.312, and that of the controls was 53.18 ± 11.35 (p < 0.01). The mean HbA1c level in the patients of acute ischemic stroke was 6.97 ± 1.84, and that of the controls was 5.99 ± 1.69 (p < 0.01). The mean random blood sugar (RBS) value in the ischemic stroke cases was 170.21 ± 84.16, and that of the controls was 150.03 ± 82.25 (p = 0.02). To compare the factors that were determined to be statistically significant between ischemic stroke cases and controls, a multivariable logistic regression analysis was performed. The HbA1c p-value was 0.01, the odds ratio (OR) was 1.280, and the 95% CI was 1.11-1.48. The other variables apart from HbA1c that were statistically significant between the ischemic stroke cases and the controls were age (p < 0.01, OR: 1.280, 95% CI: 1.06-1.11), hypertension (p = 0.618, OR: 1.130, 95% CI: 0.70-1.83), and high-density lipoprotein (p = 0.055, OR: 0.975, 95% CI: 0.95-1.00). When other cofounders were considered, it was concluded that with a 1% increase in HbA1c, the risk of stroke increases by 28% (OR: 1.28, 95% CI: 1.11-1.48). To compare the variables that were determined to be statistically significant between the control and ischemic stroke case groups, a multivariable logistic regression was used. The area under the receiver operating characteristic curve for HbA1c was 0.773 and RBS was 0.600. CONCLUSION: This study shows that higher HbA1c levels in patients increase the risk of ischemic stroke. This study brings to light the need to screen the population periodically for diabetes by routinely testing for Hba1c in those who are at high risk of diabetes. Stroke risk can be reduced with early management and intervention. This study also concludes that HbA1c is a better predictor for assessing the risk of ischemic stroke than RBS levels.

Implementation of an Electronic Clinical Decision Support System for the Early Recognition and Management of Dysglycemia in an Inpatient Mental Health Setting Using CogStack: Protocol for a Pilot Hybrid Type 3 Effectiveness-Implementation Randomized Controlled Cluster Trial.

BACKGROUND: Severe mental illnesses (SMIs), including schizophrenia, bipolar affective disorder, and major depressive disorder, are associated with an increased risk of physical health comorbidities and premature mortality from conditions including cardiovascular disease and diabetes. Digital technologies such as electronic clinical decision support systems (eCDSSs) could play a crucial role in improving the clinician-led management of conditions such as dysglycemia (deranged blood sugar levels) and associated conditions such as diabetes in people with a diagnosis of SMI in mental health settings. OBJECTIVE: We have developed a real-time eCDSS using CogStack, an information retrieval and extraction platform, to automatically alert clinicians with National Health Service Trust-approved, guideline-based recommendations for dysglycemia monitoring and management in secondary mental health care. This novel system aims to improve the management of dysglycemia and associated conditions, such as diabetes, in SMI. This protocol describes a pilot study to explore the acceptability, feasibility, and evaluation of its implementation in a mental health inpatient setting. METHODS: This will be a pilot hybrid type 3 effectiveness-implementation randomized controlled cluster trial in inpatient mental health wards. A ward will be the unit of recruitment, where it will be randomly allocated to receive either access to the eCDSS plus usual care or usual care alone over a 4-month period. We will measure implementation outcomes, including the feasibility and acceptability of the eCDSS to clinicians, as primary outcomes, alongside secondary outcomes relating to the process of care measures such as dysglycemia screening rates. An evaluation of other implementation outcomes relating to the eCDSS will be conducted, identifying facilitators and barriers based on established implementation science frameworks. RESULTS: Enrollment of wards began in April 2022, after which clinical staff were recruited to take part in surveys and interviews. The intervention period of the trial began in February 2023, and subsequent data collection was completed in August 2023. Data are currently being analyzed, and results are expected to be available in June 2024. CONCLUSIONS: An eCDSS can have the potential to improve clinician-led management of dysglycemia in inpatient mental health settings. If found to be feasible and acceptable, then, in combination with the results of the implementation evaluation, the system can be refined and improved to support future successful implementation. A larger and more definitive effectiveness trial should then be conducted to assess its impact on clinical outcomes and to inform scalability and application to other conditions in wider mental health care settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT04792268; https://clinicaltrials.gov/study/NCT04792268. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49548.

The Impact of Resistance Exercise Training on Glycemic Control Among Adults with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background: The prevalence of type 2 diabetes mellitus (T2DM) presents a challenge for health organizations because of its high likelihood of morbidity and mortality. There is an increasing body of evidence exploring the efficacy of resistance training (RT) alone on glycemic control. Objective: To update the effectiveness of RT on glycosylated hemoglobin (HbA1c) and fasting glucose in adults diagnosed with T2DM. Methods: CINAHL (EBSDCO), PubMed, MEDLINE (Ovid), and EMBASE (Ovid) databases were searched from inception to 30 January 2024. Published randomized controlled trials (RCTs) of adult humans with T2DM assessing the impact of RT on HbA1c and fasting glucose compared with control condition were included. Data were pooled by the inverse-variance method and reported as mean differences (MDs) with 95% confidence intervals (CIs). Results: Forty-six RCTs totaling 2130 participants met the inclusion criteria. Meta-analysis demonstrated RT significantly reduced HbA1c (MD -0.50% [95% CI, -0.67, -0.34 %], p < .00,001) and fasting glucose (MD -12.03 mg/dl [95% CI, -19.36, -4.69 mg/dl], p = .001). Subgroup analyses found that exercise training durations, gender, and risk of bias had statistically significant effects on HbA1c levels and fasting glucose concentrations after resistance training. However, meta-regression analyses revealed that variables including year of publication, number of sessions per week, mean sample age, sample size, and study quality scores did not significantly affect the change in either HbA1c or glucose. Conclusion: Our meta-analysis with meta-regression delivers further evidence that RT programs are effective approach in attenuation of HbA1c and fasting glucose in individuals with T2DM.

Enzymatic Hydrolysis Optimization of Yak Whey Protein Concentrates and Bioactivity Evaluation of the Ultrafiltered Peptide Fractions.

Yak whey protein concentrates (YWPCs) have good functional properties, but there is still a gap in the study of their peptides. In this study, peptides were obtained by enzymatic hydrolysis, and the bioactivity of each ultrafiltration fraction was evaluated using an optimal process. YWPCs were isolated and purified from yak milk as the raw material. Alkaline protease, trypsin, and papain were used to hydrolyze YWPCs. The protease with the highest degree of hydrolysis (DH) and peptide concentration was selected as the most suitable enzyme. The effects of pH, temperature, time, and the enzyme-to-substrate ratio (E/S) on the DH and peptide concentration were investigated, and response surface methodology was utilized to optimize the hydrolysis process. The hydrolysate was separated using ultrafiltration membranes with molecular weight cut-offs of 10 kDa, 5 kDa, 3 kDa, and 1 kDa. The bioactivity of each ultrafiltration component was analyzed, including the inhibition rates of α-amylase and xanthine oxidase (XOD) activities and the scavenging rates of 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) cation radicals. The results indicated that alkaline protease was the best enzyme for hydrolyzing YWPCs. The peptide concentration in the YWPC hydrolysate was the highest (17.21 mg/mL) at a pH of 8 and a concentration of 7500 U/g, after 2.5 h at 62 °C. The enzymatic hydrolysate was ultrafiltered to yield four peptide fractions, of which the <1 kDa peptides exhibited the highest α-amylase inhibitory activity (22.06%), XOD inhibitory activity (17.15%), and ABTS cationic free radical scavenging rate (69.55%). This demonstrates the potential of YWPC hydrolyzed peptides for hypoglycemic, uric acid-lowering, and antioxidant applications, providing a theoretical basis for the high-value utilization of YWPCs.

Plant-Based Diet and Glycemic Control in Type 2 Diabetes: Evidence from a Thai Health-Promoting Hospital.

The prevalence of type 2 diabetes (T2DM) is associated with diet. While consumption of plant-based foods may reduce blood sugar levels, the impact of consuming plant-based foods on fasting blood sugar levels has not been well defined. This cross-sectional study was conducted at the Health-Promoting Hospital in Pak Phun Municipality, Thailand. It included 61 patients with T2DM and 74 controls matched for age and gender. Dietary intake levels among T2DM and controls were assessed by a validated food-frequency questionnaire from which plant-based-food scores were calculated. This study found significant differences between specific plant foods and fasting blood sugar levels in patients with T2DM. Adherence to a plant-based diet appeared to influence fasting blood sugar levels. Patients who consumed higher amounts of certain vegetables and fruits showed lower fasting blood sugar levels. Diabetic patients consumed more legumes than controls, but the consumption of cereals and nuts/seeds in the two groups were similar. Consumption of nuts and seeds was also associated with a 76.3% reduction in the risk of a T2DM diagnosis. These findings suggest the potential efficacy of glycemic control in T2DM patients. More work is required to explore strategies for preventing and treating metabolic disorders through dietary modification.

Analysis of the influencing factors and clinical related characteristics of pulmonary tuberculosis in patients with type 2 diabetes mellitus.

BACKGROUND: In China, the prevalence of type 2 diabetes mellitus (T2DM) among diabetic patients is estimated to be between 90%-95%. Additionally, China is among the 22 countries burdened by a high number of tuberculosis cases, with approximately 4.5 million individuals affected by active tuberculosis. Notably, T2DM poses a significant risk factor for the development of tuberculosis, as evidenced by the increased incidence of T2DM coexisting with pulmonary tuberculosis (T2DM-PTB), which has risen from 19.3% to 24.1%. It is evident that these two diseases are intricately interconnected and mutually reinforcing in nature. AIM: To elucidate the clinical features of individuals diagnosed with both T2DM and tuberculosis (T2DM-PTB), as well as to investigate the potential risk factors associated with active tuberculosis in patients with T2DM. METHODS: T2DM-PTB patients who visited our hospital between January 2020 and January 2023 were selected as the observation group, Simple DM patients presenting to our hospital in the same period were the control group, Controls and case groups were matched 1:2 according to the principle of the same sex, age difference ( ± 3) years and disease duration difference ( ± 5) years, patients were investigated for general demographic characteristics, diabetes-related characteristics, body immune status, lifestyle and behavioral habits, univariate and multivariate analysis of the data using conditional logistic regression, calculate the odds ratio (OR) values and 95%CI of OR values. RESULTS: A total of 315 study subjects were included in this study, including 105 subjects in the observation group and 210 subjects in the control group. Comparison of the results of both anthropometric and biochemical measures showed that the constitution index, systolic blood pressure, diastolic blood pressure and lymphocyte count were significantly lower in the case group, while fasting blood glucose and high-density lipoprotein cholesterol levels were significantly higher than those in the control group. The results of univariate analysis showed that poor glucose control, hypoproteinemia, lymphopenia, TB contact history, high infection, smoking and alcohol consumption were positively associated with PTB in T2DM patients; married, history of hypertension, treatment of oral hypoglycemic drugs plus insulin, overweight, obesity and regular exercise were negatively associated with PTB in T2DM patients. Results of multivariate stepwise regression analysis found lymphopenia (OR = 17.75, 95%CI: 3.40-92.74), smoking (OR = 12.25, 95%CI: 2.53-59.37), history of TB contact (OR = 6.56, 95%CI: 1.23-35.03) and poor glycemic control (OR = 3.37, 95%CI: 1.11-10.25) was associated with an increased risk of developing PTB in patients with T2DM, While being overweight (OR = 0.23, 95%CI: 0.08-0.72) and obesity (OR = 0.11, 95%CI: 0.02-0.72) was associated with a reduced risk of developing PTB in patients with T2DM. CONCLUSION: T2DM-PTB patients are prone to worse glycemic control, higher infection frequency, and a higher proportion of people smoking, drinking alcohol, and lack of exercise. Lymphopenia, smoking, history of TB exposure, poor glycemic control were independent risk factors for T2DM-PTB, and overweight and obesity were associated with reduced risk of concurrent PTB in patients with T2DM.

Effect of Sevoflurane, Isoflurane, and Desflurane on the Random Blood Glucose Levels in Non-diabetic Patients Undergoing General Anesthesia: A Randomized, Single-Blind Study.

BACKGROUND: Volatile anesthetic agents like sevoflurane, isoflurane, and desflurane are widely used for maintaining general anesthesia (GA). Their effect on the autonomic system is different and can impact the blood sugar homeostasis. This study compares the intraoperative blood glucose levels in non-diabetic patients undergoing non-cardiac surgery under GA with the three volatile agents. METHODS: A randomized, single-blind, parallel-arm study recruited 105 non-diabetic patients into three groups. GA induction and maintenance were standardized except for the volatile agent. Capillary blood sugar levels were measured at different time points and compared between and within the groups. A p-value of <0.05 was considered significant. RESULTS: Entire participants completed the study, and their baseline characteristics were statistically indifferent. Intraoperative blood glucose rise and variation were the highest in the desflurane group and the lowest in the isoflurane group; the differences were statistically significant at 15, 30, and 45 minutes. The highest blood sugar level was noted at 60 minutes in all groups; after that, the level started falling. However, none of the raises were beyond 140 mg% to categorize them as hyperglycemia. CONCLUSION: Intraoperative glycemic variation was evident with isoflurane, sevoflurane, and desflurane. The maximum increase from the pre-induction level was noted at 60 minutes. However, none of the readings reached the hyperglycemia level. The rise was significantly higher in desflurane-based anesthesia than in isoflurane. This study was, however, conducted in non-diabetic patients; hence, results might not be extrapolated to diabetic patients.

Educational intervention based on the extended parallel process model improves adherence to diabetic diet and glycaemic control indices: a randomised, double-blind, controlled, factorial field trial.

Nutritional education is pivotal in the medical nutritional therapy of type 2 diabetes mellitus (T2DM). The extended parallel process model (EPPM) is a health education method for inducing desirable health behaviours. The present study aimed to investigate the effect of nutritional education based on the EPPM in T2DM patients on knowledge, attitude, practice, anthropometric indices, glycaemic factors, lipid profile and adherence to the diabetic diet. A randomised, double-blind, controlled, factorial field trial was designed for T2DM patients aged 30-59 years (n 88). Participants were randomly allocated into four groups to receive EPPM-based nutritional education through gain framed message (GFM), loss framed message (LFM), their combination (G\LFM) or usual diabetic education in the control group (CG). Participants were assessed before and after the study duration. After 3 months of intervention, eighty participants finished the study. The EPPM-based intervention increased participants' knowledge, behavioural intention, perceived sensitivity, severity, self-efficacy (P < 0·001 for all) and response efficacy (P = 0·029) in comparison with CG. GFM (P = 0·004) and G\FLM (P = 0·034) reduced carbohydrate intake and LFM (P = 0·034) and G\LFM (P = 0·047) decreased fat intake. Between-group analysis indicated interventions reduced weight (P = 0·046), BMI (P = 0·038), fasting blood sugar (P = 0·030), 2-hour postprandial blood glucose (P = 0·027) and TAG (P = 0·002) in comparison with the CG. Results were NS for protein intake, waist and hip circumference, waist:hip ratio, HbA1c, total cholesterol, LDL and HDL. Nutritional education based on EPPM could increase the knowledge and awareness of T2DM patients. Also, it could be beneficial for blood glucose amendment. Further investigations are recommended.

The Impact of Time-Restricted Meal Intake on Glycemic Control and Weight Management in Type 2 Diabetes Mellitus Patients: An 18-Month Longitudinal Study.

AIMS: This study aimed to investigate the impact of time-restricted meal intake (TRM) on anthropometric and biochemical parameters in patients with type 2 diabetes mellitus (T2DM). METHODS: A total of 400 patients diagnosed with T2DM were selected from the Endocrinology Department at King George's Medical University (KGMU), Lucknow, based on the American Diabetes Association (ADA) guidelines and specific criteria. A total of 127 patients were lost to follow-up, resulting in 273 patients who completed the study. The patients were randomly assigned to two groups: the TRM group (consenting to have an early dinner at 7 pm) and the control group (non-TRM/late-night eater group). Baseline data were recorded, and follow-up assessments were conducted at six months, 12 months, and 18 months. Informed consent was obtained, and a diet chart was regularly maintained and updated. RESULTS:  The TRM group experienced a significant weight loss of 3.88 kg (5.45%) and a substantial reduction in BMI by 1.5 units (5.26%). In contrast, the non-TRM/control group had smaller reductions in weight (1.36 kg, 1.77%) and BMI (0.5 units, 1.65%). TRM group showed significant reductions in fasting blood sugar levels by 33.9 mg/dl (21.17%), postprandial blood sugar levels by 94.6 mg/dl (38.88%), and glycosylated hemoglobin (HbA1c) levels by 1.37 (15.87%). These improvements were significantly greater than the reductions observed in the control group, which had decreases of 29.3 mg/dl (17.85%) in fasting blood sugar levels, 41.6 mg/dl (16.84%) in postprandial blood sugar levels, and 0.59 (6.89%) in HbA1c levels. CONCLUSION: Our findings underscore the potential of TRM as an effective strategy for weight management and glycemic control in patients with T2DM, even in a long-term context. These results support time-restricted eating as a sustainable lifestyle modification for managing chronic metabolic diseases.