Elevated Blood Glucose Levels Research Articles

Perbandingan Klasifikasi antara Naives Bayes dan Decision Tree dalam Prediksi Penyakit Diabetes Tahap Awal

Diabetes is a health condition characterized by an elevated blood glucose level. There are two types, namely diabetes type 1 and diabetes type 2. Diabetes type 1 is caused by a lack of insulin production by the pancreas. Symptoms of diabetes include excessive thirst, frequent urination, and constant hunger. Classification is a process that helps us group data or information into categories based on similar characteristics. In the context of diabetes, classification methods can be used to group individuals based on their risk levels of developing diabetes. By using classification methods, doctors can determine an individual's risk of diabetes and design an appropriate treatment plan. This study involves a comparison between the Naïve Bayes and Decision Tree methods. The results of this research indicate that the algorithm generated is the best among the two algorithms in identifying diabetes patients. An accuracy of 66.67% was obtained for Naïve Bayes, while an accuracy of 91.67% was obtained for Decision Tree. In this study, it was found that the Decision Tree method has a higher accuracy rate than the Naïve Bayes method in the case study and data testing.

Comparatively tested potential risk factors across survivors and non-survivors critically patients

Background: The risk factors associated with mortality in critically ill patients have been the subject of numerous studies. However, a considerable amount of variation is evident when one considers the dispersion of patients, the geographical spread, and the classification of healthcare establishments. Aim: The purpose of this study was to compare potential risk factors between Survivors and Non-Survivors, including demographics, anthropometrics, kidney and liver indices, complete blood counts, and biochemical assays. Patients whose condition is critical. Methods: An ICU retrospective investigation was conducted in Jordan, where critically ill patients with surgical and medical conditions were examined. Using the Electronic Medical Record System (Hakeem), the study analysed data and classified patients into two cohorts according to their survival status. Demographic information, clinical characteristics, insulin administration rate, blood glucose levels, dosing schedules for vasopressors, and the burden of comorbidities were all included in the data. The research was granted approval by the Institutional Review Board committee of the Royal Medical Services, Jordan. Results: The research examined the male-to-female ratios among COVID-19 patients and classified them into six distinct age groups. A significant proportion of critical patients, ranging in age from 50 to 60, exhibited elevated corrected sodium levels and a diminished normontraemia status. Higher albumin levels and mean arterial pressures were associated with survivors, whereas a greater proportion of non-survivors were underweight and had a low BMI. A normal temperature was observed in the majority of critically ill patients, whereas non-survivors exhibited elevated fractional blood glucose levels and estimated creatinine clearances. The research emphasises the significance of treatment outcomes and patient demographics. Conclusion: SI may be a more accurate prognostic indicator than non-septic patients due to the effect of norepinephrine, a vasopressor, on heart rate and systolic blood pressure, which may account for the difference in SI values between the two groups.

In Vitro Test of Leilem Leaf Ethanol Activity on β-Glucosidase Enzyme Inhibition

Diabetes is a chronic metabolic disease with signs of elevated blood glucose levels. One of the targets of antidiabetic drugs is to inhibit the enzyme α-/β-glucosidase which works in the process of glucose absorption. Leilem plant (Clerodendrum minahassae Teisjm. & Binn.) is well known and used as a dish and medicine for several diseases in Minahasa and has potential as an antidiabetic agent. This study aimed to determine the activity of ethanolic extract of leilem leaves in inhibiting β-glucosidase enzyme. The extract was prepared with 96% ethanol. Antidiabetic properties were measured by β-glucosidase enzyme inhibitory activity. The inhibitory concentration (IC50) values of the extract compared tp acarbose were 28,229 and 13,716. Ethanol extract of leilem leaves inhibits β-glucosidase enzyme. Keywords : β-glucosidase; ethanol extract; in vitro; leilem leaf

Knowledge and Attitude Towards Insulin Therapy in Type 2 Diabetes Mellitus Patients and Associated Factors at an Adult Endocrine Clinic of SPHMMC Addis Ababa Ethiopia

<i>Background:</i> Diabetes Mellitus (DM), a chronic disease characterized by elevated blood glucose levels, is associated with severe complications. Type 2 DM (T2DM), the most prevalent form of DM in adults, is characterized by varying degrees of insulin deficiency or resistance. The prevention or delay of macrovascular and microvascular problems associated with DM depends on achieving appropriate glycemic control. The percentage of T2DM patients failing to reach glycemic targets keeps rising even with the expanded availability of numerous anti-hyperglycemic drugs and evidence-based treatment guidelines. The delay in treatment intensification despite inadequate glucose control—often referred to as clinical or therapeutic inertia-contributes significantly to this trend.<i> Objective:</i> This study aims to evaluate the understanding and perceptions of insulin therapy among patients with T2DM. The study focuses on patients under follow-up care at the Adult Endocrine Clinic of St. Paul Hospital Millennium Medical College.<i> Method and Material:</i> An institutional-based, cross-sectional study was carried out from January to March 2021 to evaluate knowledge and attitudes regarding insulin therapy and related factors. A structured questionnaire was used for interviews with a representative sample of 271 T2DM patients who are receiving follow-up care at the endocrine clinic at SPHMMC. The SPSS, version 25, was the software utilized. The statistical significance of the relationship between the dependent and independent variables was assessed using a 95% confidence interval and a p-value less than 0.05.<i> Results:</i> The majority of the respondents were between the ages of 56 and 65, with a mean age of 57.35 years. More than half of the participants, accounting for 231 (85.2%) of the total, were from urban areas. Out of the 271 respondents, approximately 85.6% demonstrated poor knowledge of insulin therapy, and around 37.6% exhibited negative attitudes towards it. Factors such as age, occupation, and a history of long-term Oral Antidiabetic Drug use were found to be associated with the level of knowledge about insulin. In addition to these factors, marital status and a family history of insulin use were found to be associated with patients’ attitudes towards insulin. <i>Conclusions:</i> Our study identified a significant knowledge gap about insulin usage among T2DM patients in the designated study area. We recommend the implementation of regular, structured health education programs, delivered by trained health professionals. This approach is expected to enhance both the knowledge and attitudes toward insulin usage among patients attending follow-up sessions at the SPHMMC diabetic clinic.

Blood glucose fluctuation and in-hospital mortality among patients with acute myocardial infarction: eICU collaborative research database.

To assess the relationship between glycemic variability, glucose fluctuation trajectory and the risk of in-hospital mortality in patients with acute myocardial infarction (AMI). This retrospective cohort study included AMI patients from eICU Collaborative Research Database. In-hospital mortality of AMI patients was primary endpoint. Blood glucose levels at admission, glycemic variability, and glucose fluctuation trajectory were three main study variables. Blood glucose levels at admission were stratified into: normal, intermediate, and high. Glycemic variability was evaluated using the coefficient of variation (CV), divided into four groups based on quartiles: quartile 1: CV≤10; quartile 2: 10<CV≤20; quartile 3: 20<CV≤30; quartile 4: CV>30. Univariate and multivariate Cox regression models to assess the relationship between blood glucose levels at admission, glycemic variability, glucose fluctuation trajectory, and in-hospital mortality in patients with AMI. 2590 participants were eventually included in this study. There was a positive relationship between high blood glucose level at admission and in-hospital mortality [hazard ratio (HR) = 1.42, 95%confidence interval (CI): 1.06-1.89]. The fourth quartile (CV>30) of CV was associated with increased in-hospital mortality (HR = 2.06, 95% CI: 1.25-3.40). The findings indicated that only AMI individuals in the fourth quartile of glycemic variability, exhibited an elevated in-hospital mortality among those with normal blood glucose levels at admission (HR = 2.33, 95% CI: 1.11-4.87). Additionally, elevated blood glucose level was a risk factor for in-hospital mortality in AMI patients. Glycemic variability was correlated with in-hospital mortality, particularly among AMI patients who had normal blood glucose levels at admission. Our study findings also suggest early intervention should be implemented to normalize high blood glucose levels at admission of AMI.

Therapeutic potentials of Hibiscus trionum: Antioxidant, anti-lipid peroxidative, hypoglycemic, and hepatoprotective effects in type 1 diabetic rats

Recent advances in diabetes treatment have primarily focused on insulin and hypoglycemic agents; however, there is growing interest in exploring herbal and synthetic alternatives. Numerous studies have highlighted the preventive effectiveness of regular plant consumption in managing chronic conditions, particularly diabetes. Hibiscus, a medicinal plant recognized in various cultures, is known for its diverse health benefits. This study investigated the impact of Hibiscus trionum on glycemic control and assessed its influence on glucose and insulin levels in diabetes-induced rats. The concentrations of antioxidant enzymes, particularly superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px), were scrutinized across multiple body tissues (plasma, heart, muscle, liver, and kidney). The malondialdehyde (MDA) concentration, an indicator of lipid peroxidation, was examined in both plasma and tissue samples. Serum total cholesterol (TC), triglyceride (TG), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels were evaluated. Diabetic Group (D) exhibited a significant decrease in body weight, increased fluid and food consumption, elevated blood glucose levels, and increased antioxidant enzyme activity. Moreover, the diabetic group also showed increased levels of MDA, TC, TG, AST, and ALT, along with reduced insulin levels, compared to the control group. A substantial improvement in all parameters impaired by diabetes was observed following the application of Hibiscus trionum (HTT) in the Diabetes+HTT group. The antioxidative stress-reducing, lipid peroxidation-improving, and hepatoprotective potential of Hibiscus trionum in mitigating diabetes-induced oxidative stress is noteworthy. These findings indicate that HTT supplementation has valuable beneficial effects in protecting against the harmful impacts of diabetes.

Elucidation of inhibitory effects of bioactive anthraquinones towards formation of DNA advanced glycation end products (DNA-AGEs)

DNA is essential in biological processes as it directs transcription and translation assisting in RNA and protein synthesis. Extended periods of elevated blood glucose levels cause non-enzymatic DNA glycation, which results in the formation of DNA-AGEs and the production of free radicals, causing structural perturbation of DNA. In this work, we have investigated the glycation of calf thymus (ct-DNA) DNA and examined its inhibition by two anthraquinone derivatives, purpurin and aloin. Ribose sugar served as the glycating agent inducing non-enzymatic glycation of DNA and subsequent DNA-AGEs formation. UV–vis and fluorescence spectroscopic methods were utilized to characterize DNA-AGE formation in vitro. Circular dichroism (CD) spectroscopy was used to observe the structural disruption of DNA caused by glycation. The changes in AGEs fluorescence intensity and melting temperature (Tm) were measured to assess the inhibition of glycation process by aloin and purpurin. These derivatives demonstrated inhibitory effects via binding to glycating sites of ct-DNA or by scavenging free radicals generated during glycation. The current study elucidates the inhibitory actions of aloin and purpurin on DNA glycation, suggesting their possible applications in mitigating the adverse consequences linked to increased ribose concentrations.

Factors Affecting the Awareness of Diabetic Retinopathy: An Observational Cross-Sectional Study.

Diabetes mellitus (DM) is a chronic metabolic disease characterized by elevated blood glucose levels. Over time, it can lead to serious complications in the eyes, heart, blood vessels, kidneys, and nerves, being the leading cause of blindness among working-age patients. This descriptive observational cross-sectional study aims to evaluate the factors affecting the awareness of the general adult diabetic population about their chronic disease and its complications. A survey was distributed anonymously among diabetic patients in different parts of Jordan over four months (January 2023-April 2023), targeting diabetic patients (DMT2 or adults DMT1). The link was sent via WhatsApp to willing candidates. Data collected included age, sex, region, education, home blood sugar (BS) testing, knowledge about cumulative blood sugar test (HbA1c), eye affection by DM, optician role, and doctor and nutritionist follow-up visits. A chi-squared test or Fisher's exact test explored the association between categorical data; a z-test was applied for column proportion differences. An alpha level of 0.05 was deemed statistically significant. IBM SPSS Statistics for Windows, Version 28 (Released 2021; IBM Corp., Armonk, New York) was used for data analysis. The sample comprised 447 diabetic adults aged 18-80 years. The majority were school-educated or school leavers (278; 62.2%); 20 (4.5%) held a master's or PhD degree. The largest group had DM for one to five years. Insulin was the sole treatment for 188 patients (42.1%), while oral hypoglycemic agents (OHA) were used by 170 patients (38%) as the only anti-DM medication. A total of 174 patients (38.9%) had never been seen by an ophthalmologist, and 153 (34.2%) believed an optometrist checkup suffices. Although 381 (85.2%) reported knowing DM affects the eyes, 272 (60.9%) believed they needed to see an ophthalmologist only when experiencing eye symptoms. Less than half (186; 41.6%) had an HbA1c reading of 7% or less. There was a significant correlation between education level and awareness of DM and diabetic retinopathy (DR): HbA1c, regular home BS checkups, early DR symptoms, and optometrist visits. Significant variations in awareness were noted across Jordan's major areas. Diabetics with abnormal HbA1c who visited a nutritionist were almost triple those who did not. The main information source about DM and DR was the treating physician for 298 (66.7%) respondents. Awareness of DM and DR in Jordan is not satisfactory for assisting patients in their long journey with minimal complications. A national awareness campaign utilizing social media and a sustainable screening program prioritizing the north, south, and middle regions of Jordan are needed.

Synthesis and molecular docking studies of new aryl imeglimin derivatives as a potent antidiabetic agent in a diabetic zebrafish model

Diabetes mellitus (DM) is a persistent, progressive, and multifaceted disease characterized by elevated blood glucose levels. Type 2 diabetes mellitus is associated with a relative deficit in insulin mainly due to beta cell dysfunction and peripheral insulin resistance. Metformin has been widely prescribed as a primary treatment option to address this condition. On the other hand, an emerging glucose-reducing agent known as imeglimin has garnered attention due to its similarity to metformin in terms of chemical structure. In this study, an innovative series of imeglimin derivatives, labeled 3(a–j), were synthesized through a one-step reaction involving an aldehyde and metformin. The chemical structures of these derivatives were thoroughly characterized using ESI–MS, 1H, and 13C NMR spectroscopy. In vivo tests on a zebrafish diabetic model were used to evaluate the efficacy of the synthesized compounds. All compounds 3(a–j) showed significant antidiabetic effects. It is worth mentioning that compounds 3b (FBS = 72.3 ± 7.2 mg/dL) and 3g (FBS = 72.7 ± 4.3 mg/dL) have antidiabetic effects comparable to those of the standard drugs metformin (FBS = 74.0 ± 5.1 mg/dL) and imeglimin (82.3 ± 5.2 mg/dL). In addition, a docking study was performed to predict the possible interactions between the synthesized compounds and both SIRT1 and GSK-3β targets. The docking results were in good agreement with the experimental assay results.

Practical method in the diagnosis of diabetic ketoacidosis: end-tidal carbon dioxide

Objectives: Diabetic ketoacidosis (DKA) poses a life-threatening risk in uncontrolled diabetes. Current diagnostic criteria rely on invasive measures, leading to potential delays in treatment initiation. This study aimed to assess the diagnostic utility of noninvasive end-tidal carbon dioxide (EtCO2) measurements in DKA patients. Methods: A prospective, cross-sectional study was conducted in a tertiary-level Emergency Medicine Clinic from January 2021 to January 2023. Participants included adults with DKA symptoms and those with stable vital signs as controls. EtCO2 levels were measured using a capnograph device. Diagnostic criteria for DKA were blood glucose ≥250 mg/dL, ketonuria, ketonemia, and metabolic acidosis (pH&amp;lt;7.3 or bicarbonate &amp;lt;15 mEq/dL). Statistical analysis was performed using SPSS Statistics. Results: Of 730 participants, 120 had DKA, 410 did not, and 200 served as controls. EtCO2 levels significantly differed between DKA, non-DKA, and control groups (P&amp;lt;0.05). EtCO2 correlated with pH, lactate, base deficit, and bicarbonate (P&amp;lt;0.05). ROC analysis showed an AUC of 0.86 for EtCO2 in diagnosing DKA (P&amp;lt;0.01), with 91.67% sensitivity and 74.39% specificity at a cut-off value 23.7. Conclusion: This study suggests that EtCO2 measurement is a valuable noninvasive tool for diagnosing and assessing the severity of DKA in the emergency department. An EtCO2 threshold of &amp;lt;23.7 could prompt consideration of DKA in patients with elevated blood glucose levels. More extensive multicenter studies are warranted to validate these findings further. EtCO2 measurement could facilitate early DKA diagnosis and improve patient outcomes.

Exploring the link between obesity and hypothyroidism in autoimmune thyroid diseases: a metabolic perspective.

Background: The management of primary hypothyroidism demands a comprehensive approach that encompasses both the implications of autoimmune thyroid disease and the distinct effects posed by obesity and metabolic irregularities. Despite its clinical importance, the interplay between obesity and hypothyroidism, especially in the context of metabolic perspectives, is insufficiently explored in existing research. This study endeavors to classify hypothyroidism by considering the presence of autoimmune thyroid disease and to examine its correlation with various metabolic obesity phenotypes. Method: This research was conducted by analyzing data from 1,170 individuals enrolled in the Thyroid Disease Database of Shandong Provincial Hospital. We assessed four distinct metabolic health statuses among the participants: Metabolically Healthy No Obese Metabolically Healthy Obese Metabolically Unhealthy No Obese and Metabolically Unhealthy Obese Utilizing logistic regression, we investigated the association between various metabolic obesity phenotypes and hypothyroidism. Results: The study revealed a significant correlation between the Metabolically Unhealthy Obese (MUO) phenotype and hypothyroidism, particularly among women who do not have thyroid autoimmunity. Notably, the Metabolically Unhealthy No Obese (MUNO) phenotype showed a significant association with hypothyroidism in individuals with thyroid autoimmunity, with a pronounced prevalence in women. Furthermore, elevated levels of triglycerides and blood glucose were found to be significantly associated with hypothyroidism in men with thyroid autoimmunity and in women without thyroid autoimmunity. Conclusion: Effective treatment of hypothyroidism requires a thorough understanding of the process of thyroid autoimmune development. In patients without concurrent thyroid autoimmunity, there is a notable correlation between obesity and metabolic issues with reduced thyroid function. Conversely, for patients with thyroid autoimmunity, a focused approach on managing metabolic abnormalities, especially triglyceride levels, is crucial.

Controlling autoimmune diabetes onset by targeting Protease-Activated Receptor 2

BackgroundType 1 diabetes (T1D) is a challenging autoimmune disease, characterized by an immune system assault on insulin-producing β-cells. As insulin facilitates glucose absorption into cells and tissues, β-cell deficiency leads to elevated blood glucose levels on one hand and target-tissues starvation on the other. Despite efforts to halt β-cell destruction and stimulate recovery, success has been limited. Our recent investigations identified Protease-Activated Receptor 2 (Par2) as a promising target in the battle against autoimmunity. We discovered that Par2 activation’s effects depend on its initial activation site: exacerbating the disease within the immune system but fostering regeneration in affected tissue. MethodsWe utilized tissue-specific Par2 knockout mice strains with targeted Par2 mutations in β-cells, lymphocytes, and the eye retina (as a control) in the NOD autoimmune diabetes model, examining T1D onset and β-cell survival. ResultsWe discovered that Par2 expression within the immune system accelerates autoimmune processes, while its presence in β-cells offers protection against β-cell destruction and T1D onset. This suggests a dual-strategy treatment for T1D: inhibiting Par2 in the immune system while activating it in β-cells, offering a promising strategy for T1D. ConclusionsThis study highlights Par2's potential as a drug target for autoimmune diseases, particularly T1D. Our results pave the way for precision medicine approaches in treating autoimmune conditions through targeted Par2 modulation.

Metabolic and Skeletal Characterization of the KK/Ay Mouse Model-A Polygenic Mutation Model of Obese Type 2 Diabetes.

Type 2 diabetes (T2D) increases fracture incidence and fracture-related mortality rates (KK.Cg-Ay/J. The Jackson Laboratory; Available from: https://www.jax.org/strain/002468 ). While numerous mouse models for T2D exist, few effectively stimulate persistent hyperglycemia in both sexes, and even fewer are suitable for bone studies. Commonly used models like db/db and ob/ob have altered leptin pathways, confounding bone-related findings since leptin regulates bone properties (Fajardo et al. in Journal of Bone and Mineral Research 29(5): 1025-1040, 2014). The Yellow Kuo Kondo (KK/Ay) mouse, a polygenic mutation model of T2D, is able to produce a consistent diabetic state in both sexes and addresses the lack of a suitable model of T2D for bone studies. The diabetic state of KK/Ay stems from a mutation in the agouti gene, responsible for coat color in mice. This mutation induces ectopic gene expression across various tissue types, resulting in diabetic mice with yellow fur coats (Moussa and Claycombe in Obesity Research 7(5): 506-514, 1999). Male and female KK/Ay mice exhibited persistent hyperglycemia, defining them as diabetic with blood glucose (BG) levels consistently exceeding 300mg/dL. Notably, male control mice in this study were also diabetic, presenting a significant limitation. Nevertheless, male and female KK/Ay mice showed significantly elevated BG levels, HbA1c, and serum insulin concentration when compared to the non-diabetic female control mice. Early stages of T2D are characterized by hyperglycemia and hyperinsulinemia resulting from cellular insulin resistance, whereas later stages may feature hypoinsulinemia due to β-cell apoptosis (Banday et al. Avicenna Journal of Medicine 10(04): 174-188, 2020 and Klein et al. Cell Metabolism 34(1): 11-20, 2022). The observed hyperglycemia, hyperinsulinemia, and the absence of differences in β-cell mass suggest that KK/Ay mice in this studyare modeling the earlier stages of T2D. While compromised bone microarchitecture was observed in this study, older KK/Ay mice, representing more advanced stages of T2D, might exhibit more pronounced skeletal manifestations. Compared to the control group, the femora of KK/Ay mice had higher cortical area and cortical thickness, and improved trabecular properties which would typically be indicative of greater bone strength. However, KK/Ay mice displayed lower cortical tissue mineral density in both sexes and increased cortical porosity in females. Fracture instability toughness of the femora was lower in KK/Ay mice overall compared to controls. These findings indicate that decreased mechanical integrity noted in the femora of KK/Ay mice was likely due to overall bone quality being compromised.

Phenotypes of streptozotocin-induced gestational diabetes mellitus in mice.

Gestational diabetes mellitus (GDM) in human patients disrupts glucose metabolism post-pregnancy, affecting fetal development. Although obesity and genetic factors increase GDM risk, a lack of suitable models impedes a comprehensive understanding of its pathology. To address this, we administered streptozotocin (STZ, 75 mg/kg) to C57BL/6N mice for two days before pregnancy, establishing a convenient GDM model. Pregnant mice exposed to STZ (STZ-pregnant) were compared with STZ-injected virgin mice (STZ-virgin), citrate buffer-injected virgin mice (CB-virgin), and pregnant mice injected with citrate buffer (CB-pregnant). STZ-pregnant non-obese mice exhibited elevated blood glucose levels on gestational day 15.5 and impaired glucose tolerance. They also showed fewer normal fetuses compared to CB-pregnant mice. Additionally, STZ-pregnant mice had the highest plasma C-peptide levels, with decreased pancreatic islets or increased alpha cells compared to CB-pregnant mice. Kidneys isolated from STZ-pregnant mice did not display histological alterations or changes in gene expression for the principal glucose transporters (GLUT2 and SGLT2) and renal injury-associated markers. Notably, STZ-pregnant mice displayed decreased gene expression of insulin-receiving molecules (ISNR and IGFR1), indicating heightened insulin resistance. Liver histology in STZ-pregnant mice remained unchanged except for a pregnancy-related increase in lipid droplets within hepatocytes. Furthermore, the duodenum of STZ-pregnant mice exhibited increased gene expression of ligand-degradable IGFR2 and decreased expression of GLUT5 and GLUT12 (fructose and glucose transporters, respectively) compared to STZ-virgin mice. Thus, STZ-pregnant mice displayed GDM-like symptoms, including fetal abnormalities, while organs adapted to impaired glucose metabolism by altering glucose transport and insulin reception without histopathological changes. STZ-pregnant mice offer a novel model for studying mild onset non-obese GDM and species-specific differences in GDM features between humans and animals.

Research on the Influencing Factors that affecting Female Diabetes

This paper provides an in-depth look at diabetes as a growing public health problem among women in light of globalization and lifestyle changes. Diabetes mellitus encompasses a collection of metabolic conditions marked by elevated blood glucose levels following a fasting period, typically resulting from inadequate insulin function or reduced sensitivity to insulin within the body. As per the International Diabetes Federation (IDF), the projected global population living with diabetes in 2011 was approximately 366 million. The IDF's projections indicate a potential increase to 522 million by 2030. This substantial escalation not only signifies the persistent rise in diabetes prevalence on a global scale, but also emphasizes the critical need for efficacious preventive interventions and diabetes management strategies. The prevalence of diabetes among women is not only high but rising, and there are significant gender differences in disease management and the probability of complications. The unique risks of diabetes in women include an increased risk of heart disease, stroke, kidney disease, and polycystic ovary syndrome. These complications further affect women's health and quality of life. In order to better understand the factors affecting diabetes in women, we conducted an in-depth analysis of relevant data using R language, focusing on Pima Indian women aged 21 to 81 years. The data set used in the study, the Diabetes Dataset, contained 768 observations and nine variables, all of which were Pima Indian women. This paper uses the logistic regression method to analyze these variables. The findings suggest that diabetes spectrum function is the most significant factor affecting diabetes risk in this population. This study is of great value to academic research and has far-reaching implications for formulating public health policies and optimizing clinical treatment guidelines.

The efficacy and safety of perioperative glucocorticoid for total knee arthroplasty: a systematic review and meta-analysis

BackgroundAn increasing number of individuals undergo total knee arthroplasty (TKA), which can result in pain, limited motor function and adverse complications such as infection, nausea and vomiting. Glucocorticoids have been shown anti-inflammatory and antiemetic effects, but can also elevate blood glucose levels and increase the risk of wound infection. Thus, it is essential to investigate the efficacy and safety of glucocorticoid usage in TKA.MethodA comprehensive systematic search of PubMed, Medline, EMBASE, Cochrane databases, to identify relevant randomized controlled trials (RCTs) of glucocorticoid application in TKA. The primary outcomes assessed were the postoperative pain assessment. Secondary outcomes included the range of motion in knee joint, levels of inflammatory cytokines, adverse complications, and the length of hospital stay.ResultsThirty-six randomized controlled trials were included in the final analysis. The glucocorticoid group exhibited significant reduction in the resting VAS scores on postoperative days 1, 2 (POD1, 2)and postoperative 3 months (POM3), as well as decreased morphine consumption on POD1 and increased range of motion (ROM) in knee joint on POD1, 3. Additionally, the glucocorticoid group exhibited decreased levels of postoperative inflammatory cytokines and the incidence of PONV along with a shorter length of hospital stay. The blood glucose concentration was significantly increased in the glucocorticoid group on POD1 compared with the control group. While the blood glucose on POD2 and occurrence of postoperative adverse complications were similar between two groups including wound infection and venous thrombosis. The periarticular injection analgesia (PIA) group demonstrated lower VAS scores on POD2 comparing to the systemic administration (SA) group according to two studies. However, there was no significant difference of the resting VAS on POD1 and POD2 between PIA and SA group across all studies.ConclusionPerioperative glucocorticoids treatment in TKA significantly reduced short-term pain score and opioid-use which was probably not patient relevant. The application of glucocorticoids in TKA implied a beneficial trend in analgesic, anti-inflammatory, and antiemetic effects, as well as improved range of motion and shortened hospital stay. While it will not increase the risk of continued high glucose, postoperative wound infection and venous thrombosis.

Prediction and analysis of risk factors for diabetic retinopathy based on machine learning and interpretable models

ObjectiveDiabetic retinopathy is one of the major complications of diabetes. In this study, a diabetic retinopathy risk prediction model integrating machine learning models and SHAP was established to increase the accuracy of risk prediction for diabetic retinopathy, explain the rationality of the findings from model prediction and improve the reliability of prediction results. MethodsData were preprocessed for missing values and outliers, features selected through information gain, a diabetic retinopathy risk prediction model established using the CatBoost and the outputs of the mode interpreted using the SHAP model. ResultsOne thousand early warning data of diabetes complications derived from diabetes complication early warning dataset from the National Clinical Medical Sciences Data Center were used in this study. The CatBoost-based model for diabetic retinopathy prediction performed the best in the comparative model test. ALB_CR, HbA1c, UPR_24, NEPHROPATHY and SCR were positively correlated with diabetic retinopathy, while CP, HB, ALB, DBILI and CRP were negatively correlated with diabetic retinopathy. The relationships between HEIGHT, WEIGHT and ESR characteristics and diabetic retinopathy were not significant. ConclusionThe risk factors for diabetic retinopathy include poor renal function, elevated blood glucose level, liver disease, hematonosis and dysarteriotony, among others. Diabetic retinopathy can be prevented by monitoring and effectively controlling relevant indices. In this study, the influence relationships between the features were also analyzed to further explore the potential factors of diabetic retinopathy, which can provide new methods and new ideas for the early prevention and clinical diagnosis of subsequent diabetic retinopathy.

Daily feeding frequency affects feed intake and body weight management of growing layers

The objective of this study was to investigate the effect of feeding behavior on feed intake and body weight in growing layers and the underlying mechanisms, thereby providing a scientific foundation for optimal feeding practices in growing layers' management. A total of 144 Hy-line brown growing layers of 10 wk old and similar body weight, were divided into 3 treatment groups with different feeding frequency and equal cumulative daily feeding amount: the once-a-day feeding group (F1) was fed at 9:00 am every day, with feeding amount of 150 g/layer; the twice-a-day feeding group (F2) were fed at 9:00 am and 13:00 pm every day, with each feeding amount of 75 g/layer; the 4 times-a-day feeding group (F4) were fed at 9:00 am, 11:00 am, 13:00 pm, and 15:00 pm every day, with each feeding amount of 37.5 g/layer. Pre-experiment lasted for 1 wk and formal experiment lasted for 8 wk. The results indicated that the daily feed intake and body weight were decreased (P < 0.05) while feed conversion ratio was not affected (P > 0.05) as daily feeding times increased. The glandular stomach proportion was significantly increased in twice-a-day feeding group, while liver proportion and ileum length were significantly increased in 4 times-feeding group (P < 0.05). Additionally, 4 times-feeding daily resulted in a significant elevation of blood glucose levels, which may have suppressed feed intake (P < 0.05). In 4 times-feeding group, the plasma triglyceride levels increased as feeding times, accompanied by a notable up-regulation in the mRNA level of appetite-suppressing gene, hypothalamic pro-opiomelanocortin (POMC) and glandular stomach ghrelin. This modulation effectively suppressed the subsequent feed intake and body weight. Therefore, 4 times feeding daily is recommended in growing layers' management, because it reduced the feed cost without affecting the feed conversion efficiency.

An Improved Ensemble Machine Learning Approach for Diabetes Diagnosis

Diabetes is recognized as one of the most detrimental diseases worldwide, characterized by elevated levels of blood glucose stemming from either insulin deficiency or decreased insulin efficacy. Early diagnosis of diabetes enables patients to initiate treatment promptly, thereby minimizing or eliminating the risk of severe complications. Although years of research in computational diagnosis have demonstrated that machine learning offers a robust methodology for predicting diabetes, existing models leave considerable room for improvement in terms of accuracy. This paper proposes an improved ensemble machine learning approach using multiple classifiers for diabetes diagnosis based on the Pima Indians Diabetes Dataset (PIDD). The proposed ensemble voting classifier amalgamates five machine learning algorithms: Decision Tree (DT), Logistic Regression (LR), K-Nearest Neighbor (KNN), Random Forests (RF), and XGBoost. We obtained the individual model accuracies and used the ensemble method to improve accuracy. The proposed approach uses a pre-processing stage of standardization and imputation and applies the Local Outlier Factor (LOF) to remove data anomalies. The model was evaluated using sensitivity, specificity, and accuracy criteria. With a reported accuracy of 81%, the proposed approach shows promise compared to prior classification techniques.

Congenital anatomical variants in human fetal embryological development and its risk factors in low-resource setting: A longitudinal study

Objectives We aimed to determine the variants of congenital anomalies in human fetal development using ultrasound diagnosis, its associated risk factors, and the outcome of such pregnancies. Material and Methods This longitudinal study was conducted at a secondary health facility in north-central Nigeria. A total of 250 consenting pregnant women between 12 and 28 weeks of gestation were recruited, and each had a detailed history taken, an ultrasound scan to screen for fetal congenital anatomic variants, packed cell volume (PCV), and a 75-g oral glucose tolerance test at 24–28 weeks of gestation. All participants were followed up until delivery, and data analysis was done with SPSS version 21.0 (Chicago, IL, USA). Results Ultrasound-diagnosed congenital anatomical malformations were found in 29 participants (11.6%), and all were confirmed at birth. Of the 29 cases with congenital malformation, 15 (51.7%) were males. Maternal characteristics that were significantly associated with the risk of fetal congenital anomalies included age (p &lt; 0.001), hypertension in pregnancy (p &lt; 0.001), ingestion of herbal medication during pregnancy (p &lt; 0.001), previous history of unexplained neonatal death (p &lt; 0.001), and elevated blood glucose level (p &lt; 0.001). Conclusion The study shows a high incidence of congenital anomalies, especially among pregnant women with medical disorders in pregnancy. Also, there is a need to discourage the use of herbal medications during pregnancy.