Predictors Of Poor Glycemic Control Research Articles

Association between self-care activities and glycemic control among patients with type 2 diabetes mellitus in Northwest Ethiopia general hospitals : a multicenter cross-sectional study

Diabetes self-care activities are essential for achieving optimal glycemic control. However, little investigation has been conducted in Ethiopia to evaluate the relationship between the rate glycemic controland self-care activities among patients with type 2 diabetes mellitus (T2DM). Therefore, this study was conducted to assess self -care activities and their association with glycemic control among patients with T2DM in Northwest Ethiopia general hospitals. This multicenter cross-sectional study was conducted in Northwest Ethiopia general hospitals diabetic clinics. Diabetes self-care activities were measured using the Amharic version of the Summary of Diabetes Self-Care Activities (SDSCA-Amharic). Glycated hemoglobin (HbA1c) were used to assess the rate of glycemic control. A linear regression model was used to identify predictors of self-care activities and glycemic control. P-value of < 0.05 at 95% confidence interval (CI) was considerd as statistically significant. Of 413 participants included in the final analysis, two-thirds (66.3%) had poor glycemic control, with a mean HbA1c of 7.94% (SD = 1.75). Blood glucose testing was the most important self-care activity domain for predicting better glycemic control [β=-0.36, 95% CI (-0.48, -0.24); P = 0.0001] followed by diet [β=-0.29, 95% CI (-0.39, -0.083); P = 0.0001], foot-care [β=-0.28, 95% CI (-0.3, -0.061); P = 0.003], and physical activity [β=-0.27, 95% CI (-0.29, -0.056); P = 0.004], respectively. Moreover, unable to read and write [β = 0.72, 95% CI (0.57, 3.8); P = 0.037], overweight [β = 0.32, 95% CI (0.011, 0.62); P = 0.042], obesity [β = 0.67, 95% CI (0.39, 0.94); P = 0.0001], and low level of medication adherence [β = 0.7, 95% CI (0.39, 1.1); P = 0.0001] were significant predictors of poor glycemic control. Previous diabetes education [β=-0.88, 95% CI (-1.2, -0.57); P=0.0001] was a significant predictor of good glycemic control. The prevalence of poor glycemic control and poor self-care activities were high among patients with T2DM. Self-care activities were independent predictors of glycemic control among patients with T2DM. Therefore, management interventions for patients with T2DM should focus on improving self-care activities and other predictor variables.

Platelet indices as predictors of poor glucoregulation in type 2 diabetes mellitus adults at Bishoftu General Hospital, Ethiopia.

Diabetes is a chronic metabolic syndrome that has become a global public health problem with significant morbidity and mortality. It is a pro-inflammatory and pro-thrombotic condition characterized by increased platelet activation and alterations in platelet indices. However, the use of platelet indices as predictors of poor glucoregulation has not been fully evaluated in this context, and evidence for their role as predictors of poor glycemic status in diabetic patients is limited. To evaluate platelet indices and determine their prognostic significance in relation to inadequate glucoregulation among individuals diagnosed with type 2 diabetes at Bishoftu General Hospital in Ethiopia, from June 15 to August 12, 2022. A comparative cross-sectional study was conducted in 261 participants including 174 individuals with type 2 diabetes mellitus (T2DM) and 87 non-diabetic controls. The systematic random sampling technique was used to select par-ticipants. Data were collected using structured questionnaires, physical measurements, checklists, and laboratory tests. Platelet parameters and fasting blood glucose levels were determined from blood samples using Sysmex-XN550 and CobasC311 analyzers, respectively. The hematology analyzer output was checked and participants were also screened for malaria parasites using a prepared blood smear. Collected data were entered into Epi-data version 3.1 and exported to SPSS version 25 for analysis. The χ 2 test, Mann-Whitney U test, Kruskal-Wallis test, post hoc test, Spearman correlation, and receiver operating characteristic curve were used for analysis. A P value < 0.05 was considered statistically significant. The results of our study indicate that diabetic patients have significantly higher levels of platelet distribution width (PDW), mean platelet volume (MPV), platelet large cell ratio (PLCR), and plateletcrit (PCT) compared to healthy individuals (P < 0.001). Furthermore, these indices were found to be significantly elevated in individuals with poor glycemic control in T2DM compared to those with good glycemic control and healthy controls. We also observed significant correlations between these indices and various anthropometric and clinical variables. Our findings suggest that PDW, with a cut-off value of 15.75 fL and an area under the curve (AUC) of 0.803, MPV, with a cut-off value of 12.25 fL and an AUC of 0.774, PLCR, with a cut-off value of 36.3% and an AUC of 0.775, and PCT, with a cut-off value of 0.24% and an AUC of 0.761, can serve as predictors of poor glycemic control in patients with diabetes mellitus. The observed correlation between diabetic patients and a significant increase in platelet indices has highlighted their potential as predictors of poor glycemic control in diabetes. Therefore, regular screening and profiling of platelet indices is recommended as part of the follow-up process for individuals with diabetes mellitus.

Correlation between cerebral neurotransmitters levels by proton magnetic resonance spectroscopy and HbA1c in patients with type 2 diabetes

BACKGROUND Cognitive dysfunction is the main manifestation of central neuropathy. Although cognitive impairments tend to be overlooked in patients with diabetes mellitus (DM), there is a growing body of evidence linking DM to cognitive dysfunction. Hyperglycemia is closely related to neurological abnormalities, while often disregarded in clinical practice. Changes in cerebral neurotransmitter levels are associated with a variety of neurological abnormalities and may be closely related to blood glucose control in patients with type 2 DM (T2DM). AIM To evaluate the concentrations of cerebral neurotransmitters in T2DM patients exhibiting different hemoglobin A1c (HbA1c) levels. METHODS A total of 130 T2DM patients were enrolled at the Department of Endocrinology of Shanghai East Hospital. The participants were divided into four groups according to their HbA1c levels using the interquartile method, namely Q1 (&lt; 7.875%), Q2 (7.875%-9.050%), Q3 (9.050%-11.200%) and Q4 (≥ 11.200%). Clinical data were collected and measured, including age, height, weight, neck/waist/hip circumferences, blood pressure, comorbidities, duration of DM, and biochemical indicators. Meanwhile, neurotransmitters in the left hippocampus and left brainstem area were detected by proton magnetic resonance spectroscopy. RESULTS The HbA1c level was significantly associated with urinary microalbumin (mALB), triglyceride, low-density lipoprotein cholesterol (LDL-C), homeostasis model assessment of insulin resistance (HOMA-IR), and beta cell function (HOMA-β), N-acetylaspartate/creatine (NAA/Cr), and NAA/choline (NAA/Cho). Spearman correlation analysis showed that mALB, LDL-C, HOMA-IR and NAA/Cr in the left brainstem area were positively correlated with the level of HbA1c (P &lt; 0.05), whereas HOMA-β was negatively correlated with the HbA1c level (P &lt; 0.05). Ordered multiple logistic regression analysis showed that NAA/Cho [Odds ratio (OR): 1.608, 95% confidence interval (95%CI): 1.004-2.578, P &lt; 0.05], LDL-C (OR: 1.627, 95%CI: 1.119-2.370, P &lt; 0.05), and HOMA-IR (OR: 1.107, 95%CI: 1.031-1.188, P &lt; 0.01) were independent predictors of poor glycemic control. CONCLUSION The cerebral neurotransmitter concentrations in the left brainstem area in patients with T2DM are closely related to glycemic control, which may be the basis for the changes in cognitive function in diabetic patients.

1430-P: Demographic and Socioeconomic Predictors of Poor Glycemic Control among Rural Americans without a Prior Diagnosis of Diabetes

1430-P: Demographic and Socioeconomic Predictors of Poor Glycemic Control among Rural Americans without a Prior Diagnosis of Diabetes

Glycemic Control and Self-Monitoring of Blood Glucose in Type 2 Diabetic Patients on Insulin and Prevalence of Candidiasis in these Patients at Dschang District Hospital, Cameroon: A Cross-Sectional Study

Background: The number of deaths attributed to diabetes was estimated at nearly 1.5 million worldwide in 2012, making this disease one of the 15 most deadly pathologies in the world. Self-monitoring of blood glucose is not widely used in type 2 diabetics on insulin. Objective: To evaluate the level of glycemic control and identified some factors that may influence it as well as determining the prevalence of candidiasis in these patients. Methodology: A descriptive cross-sectional study was conducted on a population of type 2 diabetic patients on insulin followed at Dschang District Hospital with an average age of 58 years treated with insulin for at least 2 months and the predictors of poor glycemic control were measured (HbA1c higher than 7%) and the search for three species of Candida carried out in 3 different types of samples (urine, blood and oral cavity). Furthermore, a questionnaire was used to collect information on self-monitoring of blood glucose. Results: This study included 66 diabetic patients with a mean age of 58 years and a male predominance (51.5%). The majority of patients had been diabetic for at least 6 years with a mean duration of insulin therapy of 6 months. 90.1% of the participants reported having a glucometer and 54.5% reported performing self-monitoring of blood glucose twice a day as recommended by the physician. This study found that 78.8% of these patients had inadequate glycemic control. Factors such as Body mass index, duration of diabetes and coexistence with hypertension influenced this glycemic control. Similarly, a prevalence of 15.2%, 12.1% and 00% were recorded for urinary, oral and systemic candidiasis respectively with Candida albicans being the species most involved in these infections. Conclusion: Poor glycemic control is common among type 2 diabetic patients on insulin at Dschang District Hospital and is due to poor use and lack of training of patients on the practice of self-monitoring of blood glucose. This poor glycemic control favours the development of candida infections, especially urinary and oral.

Correlation of Neutrophil–Lymphocyte Ratio with Glycemic Control: An Analytical Cross-sectional Study

Abstract Background: Poorly controlled diabetes is one of the most common risk factors for cardiovascular disease. Neutrophil–Lymphocyte ratio (NLR) is a potential marker to predict inflammation. Many studies have shown it to be a predictor of adverse cardiovascular events in Type 2 diabetic patients. Our study was done to examine and establish a relationship between NLR and poor glycemic control and to examine whether a correlation exists between NLR and HbA1c. Materials and Methods: An analytical cross-sectional study was conducted with 104 randomly selected Type 2 diabetic patients (39 females and 65 males). They were randomly divided into three groups based on glycemic control according to the American Diabetes Association criteria. Patients with HbA1c &lt;7% as excellent control, HbA1c 7%–9% as poor control, and HbA1c &gt;9% as worst control were considered. Total leukocyte count, fasting blood sugar (FBS), low-density lipoprotein (LDL), and NLR were assessed. Results: Our study showed that the mean neutrophil count was significantly higher and the mean lymphocyte count was significantly lower in patients with the worst diabetic control. NLR was also significantly higher in patients with worse diabetic control. However, our study did not find any statistically significant correlation between total leukocyte count and glycemic control. Mean LDL and mean FBS were also significantly higher in patients with the worst diabetic control. Conclusions: Increased NLR was associated with high HbA1c and poor glycemic control. Thus, NLR can be used as a tool in follow-up of Type 2 diabetic patients and as a predictor of poor glycemic control and adverse cardiovascular events.

Poor Glycaemic Control and It’s Risk Factors Among Diabetes Patients in An Urban Area of Western India

Introduction: Diabetes is a major public health problem worldwide including India. Poor glycaemic control is a major risk factor for the development of diabetes-related complications. Hence, monitoring and achieving good glycaemic control is critical to reducing the risk of complications and improving outcomes in people with diabetes. This study conducted to determine the prevalence of poor glycaemic control and to identify the factors associated with poor glycaemic control. Methodology: This cross-sectional descriptive study conducted in an urban area among those patients having diabetes since more than five years. All participants were interviewed and tested for HbA1c. Cases with good glycaemic control (HbA1c &lt;7%) were compared with those with poor glycaemic control (HbA1c ≥7%). Multivariate analysis was conducted to find out independent determinants. Results: Out of 632 cases, poor glycaemic control was found in 81.3% cases. Multivariate logistic regression indicated that living without a spouse (p 0.036), Female gender (p 0.032), MBI &gt;23(kg/m2) (p &lt;0.001), poor medication adherence (p 0.022), and high perceived stress level (p 0.011) were independent predictors of poor glycaemic control. More than 10 years duration of diabetes was found to be associated with good glycaemic control (p 0.016) Conclusion: There are a high proportion of patients with poor glycaemic control. Higher BMI, poor drug adherence and higher stress level are independently associated with poor glycaemic control.

Correlation of Neutrophil Lymphocyte ratio with HbA1c in patients of type 2 Diabetes Mellitus attending Medical Department of a Tertiary Care Centre

Background: Type 2 diabetes mellitus is associated with chronic low-grade inflammation. Neutrophil lymphocyte is an indicator of subclinical inflammation. One of the novel inflammatory markers is neutrophil to lymphocyte ratio. We find only less studies that are directly accessing the relation between NLR and HbA1c, in the present study we aim to correlate neutrophil lymphocyte ratio with glycemic control in patients having type 2 diabetes.&#x0D; Methods: Hospital based observational cross section study was carried out at department of medicine at Bharatpur Period August 2023 to December 2023. 176 patients with type 2 diabetes mellitus as per ADA criteria aged more than 18 years were included in the study. Microsoft excel and SPSS version 20.0 were used for collection and analysis of the data, p&lt;0.05 was considered as significant.&#x0D; Results: Out of 176 cases having mean age 55.78±9.111, Mean BMI of all participant was 28.37±4.061, mean absolute Neutrophil count was 7.36±7.123 10³/μl and Mean neutrophil lymphocyte ratio count was 4.03±1.545, in which 147 patients (83.5%) had NLR within normal limit, and remaining 29 patients (16.5%) had NLR within more than 3.53. In our study 123 patients (69.9%) had HbA1C more than 9.0. The association of NLR with HbA1c which was significant association (p=0.047) noted between two parameters indicating higher frequency of NLR had a positive correlation with HbA1c and was found to be an independent predictor of poor glycemic control in patients with type 2 diabetes mellitus.&#x0D; Conclusions: Our study concluded that the association of NLR with HbA1c which was significant association. The Association of HbA1c with absolute neutrophil count was which significant and association of HbA1c with absolute lymphocyte count was which significant. Type 2 DM patients with raised NLR should be evaluated for cardiovascular, renal and ocular complications of diabetes. NLR may be useful as an easily measurable, noninvasive, widely available and cost-effective parameter for the disease monitoring tool during follow up of diabetic patients.

Predictors of Poor Glycemic Control and Increased Glucose Variability Among Admitted Moderate to Critical COVID-19 Patients with Type 2 Diabetes Mellitus: A Single Center Cross-sectional Study.

COVID-19 exacerbates the long-standing, low-grade chronic inflammation observed in diabetes leading to heightened insulin resistance and hyperglycemia. Mortality increases with hyperglycemia and poor glycemic variability, hence, this study aims to identify the predictors associated with poor glycemic control and increased glucose variability among patients with COVID-19 and Type 2 Diabetes Mellitus (T2DM). A retrospective chart review of 109 patients with moderate to severe COVID-19 and T2DM admitted from March 2020 to June 2021 was done. Logistic regression was done to determine predictors for hyperglycemia and poor variability. Of the 109 patients, 78% had hyperglycemia and poor variability and 22% had no poor outcomes. Chronic kidney disease (eOR 2.83, CI [1.07-7.46], p = 0.035) was associated with increased glycemic variability. In contrast, increasing eGFR level (eOR 0.97, CI [0.96-0.99], p = 0.004) was associated with less likelihood of increased variability. Hs-CRP (eOR 1.01, CI [1.00-1.01], p = 0.011), HbA1c (eOR 1.86, CI [1.23-2.82], p = 0.003), severe COVID-19 (eOR 8.91, CI [1.77-44.94], p = 0.008) and critical COVID-19 (eOR 4.42, CI [1.65-11.75], p = 0.003) were associated with hyperglycemia. Steroid use (eOR 71.17, CI [8.53-593.54], p<0.001) showed the strongest association with hyperglycemia. Potential clinical, laboratory and inflammatory profiles were identified as predictors for poor glycemic control and variability outcomes. HbA1c, hs-CRP, and COVID-19 severity are predictors of hyperglycemia. Likewise, chronic kidney disease is a predictor of increased glycemic variability.

Magnitude and predictors of poor glycemic control in patients with diabetes at Jimma Medical Center, Ethiopia

Despite the development of new medications over the past decade to aid in the control of blood glucose, most diabetic patients often do not reach recommended glycemic targets of glycated hemoglobin (HbA1C) < 7% in daily clinical practice because of many contributing factors. This study was designed to assess the magnitude and predictors of poor glycemic control among adult diabetic patients on ambulatory chronic care follow-up at Jimma Medical Center. A cross sectional study was conducted on 307 adult diabetic patients between January 2 and April 30, 2022. Representative samples were selected using a systematic random sampling technique. Predictors of poor glycemic control were assessed using a binary and multi variable logistic regression. Data analysis was performed using Statistical Package for Social Science version 25 and R in the R studio environment. A total of 307 adult diabetic patients were included in the study making a response rate of 93%. Out of 307 adult diabetic patients, majority (62.5%) were males. Mean age of the patients was 48.91 ± 15.68 years. The majority, 221 (72%), of patients had poor glycemic control. Non-adherence of patients to medications (AOR = 3.36, 95% CI 1.16–9.72, p = 0.04), no formal education (AOR = 3.84, 95% CI (1.06–13.93, p = 0.04), therapeutic inertia (AOR = 3.16, 95% CI 1.61–6.20, p = 0.001) and poor diabetic knowledge (AOR = 4.79, 95% CI 1.56–14.68, p = 0.006) were found to be independent predictors of poor glycemic control. Nearly three fourth of diabetic patients in the present study had poor glycemic control and were at higher risk of developing diabetic complications or already developed it. These results highlight the need for appropriate management of patients focusing on adherence to medications, education, therapeutic inertia and diabetic knowledge to maintain good glycemic control and improve adverse outcomes of the disease in this study setting.

Factors associated with glycemic control and diabetes complications in a group of Saudi patients with type 2 diabetes.

Poor glycemic control is a risk factor for micro and macrovascular complications of diabetes. The aim of this study was to assess the prevalence and factors related to suboptimal glycemic control and diabetes complications in a group of patients with type 2 diabetes mellitus (T2DM). This cross-sectional descriptive study conducted in Al Qassim region, Saudi Arabia. Two hundred patients with T2DM were enrolled. Demographic, social, and self-care behavior data were collected. A thorough clinical evaluation was done. Glycated hemoglobin, lipid, and kidney profile results were recorded. Mann-Whitney test was used to compare different groups. For comparing categorical data, Chi-square (χ2) test was performed. Multivariate logistic regression analyses used to detect predictors of poor glycemic control and macrovascular and microvascular complications. The median age of patients was 58 years, and 62% of them were males. Only 22.5% of patients had glycated hemoglobin <7%. Forty-four patients (22%) had evidence of macrovascular complications. Retinopathy, neuropathy, and nephropathy were found in 42.5%, 32.5%, and 12%, respectively. Longer diabetes duration was significantly associated with poor glycemic control (OR = 1.006, P < .005). The age of the patients was independently associated with macrovascular complications (OR = 1.050, P = .029). Hyperlipidemia was significantly associated with neuropathy (OR = 0.229, P = .043) and retinopathy (OR = 12.887, P = .003). Although physical activity was lower in patients with suboptimal glycemic levels (P = .024), cardiovascular disease (P = .030), neuropathy (P < .001), retinopathy (P < .001), and nephropathy (P = .019), multivariate analysis showed that it was only independently associated with neuropathy (OR = 0.614, P = .001). The prevalence of suboptimal glycemic control is high in the studied population. Effective health measures are urgently needed to stop diabetes complications, especially retinopathy and neuropathy. Elderly people with long durations of diabetes, and lower physical activity should be the focus of the interventions. Tailored exercise programs are particularly needed for better diabetes control and for the prevention of complications in patients with T2DM.

GLYCAEMIC CONTROL AMONG SAUDI PATIENTS WITH TYPE 2 DIABETES MELLITUS AT FIRST TIME REGISTRY IN RAQEB RECORDS FROM 2018-2022

Background:Diabetes Mellitus (DM) is a major risk factor for many complications and glycaemic control prevents and delays such complications. The Raqeb registry aims toimprove diabetic patientscontrol of their diabetes by giving them glucometers. Objective:This study aims to determine the prevalence of type 2 diabetes (T2DM) glycaemic control in all regions of Saudi Arabia using Raqeb data, as well as outline the factors associated with uncontrolled T2DM. Methods:This paper conducted a registry-based cross-sectional study among all patients with T2DM who registered in Raqeb from October 16, 2018, to July 17, 2022. According to the American Diabetes Association, for non-pregnant adults, HbA1c can be used to assess glycaemic control according to the HbA1c target of &lt; 7% (control DM) and ≥7 (uncontrolled DM). To identify glycaemic control determinants, the present study used multivariate logistic regression analysis, while SPSS v26 software was used for data entry and analysis. Results: In the study, the mean level of HbA1c of the patients was 8.4 (SD1.7) and approximately 86% of the patients had uncontrolled diabetes mellitus (HbA1c ≥ 7%). Multivariate analysis revealed that being over 45 years old, using hypoglycaemic agents (OHA) and insulin, being followed up in a diabetic centre and being from the Western, Southern or Northern regions were all significant predictors of poor glycaemic control. Meanwhile, the female gender and OHA treatment were linked to a lower risk of poor glycaemic control. Conclusion:Using data from Saudi Arabias Raqeb registry of T2DM patients, this different level of care database analysis over a five-year period revealed uncontrolled DM. An increased risk of uncontrolled DM in T2DM patients was seen in those over the age of 45 years and patients using OHA and insulin treatment, as well as people from the Western, Southern or Northern regions of Saudi Arabia.

Poor glycemic control and associated factors among patients with type 2 diabetes mellitus: a cross-sectional study

Glycemic control is of paramount importance in care and management for patients with type 2 diabetes mellitus (T2DM). Poor glycemic control is a major health problem that greatly contributes to the development of diabetes related complications. This study aims to assess the prevalence of poor glycemic control and associated factors among outpatients with T2DM attending diabetes clinic at Amana Regional Referral Hospital in Dar-es-salaam, Tanzania from December 2021 to September 2022. A face to face interviewer semi-structured questionnaire was administered during data collection. Binary logistic regression under multivariable analysis was used to determine the independent predictors of poor glycemic control. A total of 248 patients with T2DM were included in the analysis with mean age of 59.8 ± 12.1 years. The mean fasting blood glucose was 166.9 ± 60.8 mg/dL. The prevalence of poor glycemic control was 66.1% (fasting blood glucose > 130 mg/dL or < 70 mg/dL). Failure to adhere to regular follow-up (AOR = 7.53, 95% CI = 2.34–19.73, p < 0.001) and alcoholism (AOR = 4.71, 95% CI = 1.08–20.59, p = 0.040) were the independent predictors of poor glycemic control. The prevalence of poor glycemic control observed in this study was significantly high. Emphasis should be placed on ensuring that patients have regular follow-up for their diabetes clinics and they should also continue modifying some of lifestyle behaviors including refraining from alcoholism, this can help them to have good glycemic control.

Prevalence of medication adherence and glycemic control among patients with type 2 diabetes and influencing factors: A cross-sectional study

BackgroundThis study aimed to assess medication adherence, glycemic control, and their influencing factors among outpatients at an Indonesian clinic with type 2 diabetes. MethodsA cross-sectional study was conducted among patients with type 2 diabetes at a hospital-based clinic in Surabaya, Indonesia, from September to December 2018. A purposive sampling was used; patients aged 18 years and older, had diabetes and any comorbidity, received hypoglycemic agents, and provided written informed consent were included. The previously validated Brief Medication Questionnaire was used to measure medication adherence, while glycosylated hemoglobin (A1C) levels were used to evaluate glycemic control. Binary logistic regression was used to identify factors associated with medication adherence and glycemic control. ResultsOf 321 patients enrolled in the study, 268 (83.5%) patients were medication nonadherent. Patients who did not engage regularly in physical activity (aOR: 0.49, 95% CI: 0.26–0.93) was more likely to be medication adherent. Poor glycemic control (A1C: >7%) was observed in 106 (33.0%) of the patients. Patients who used a combination of oral hypoglycemic agents and insulin (aOR: 2.74, 95% CI: 1.09–6.86), did not take biguanide (aOR: 2.73, 95% CI: 1.16–6.43), reported hyperglycemia (aOR: 4.24, 95% CI: 1.53–11.81), and had comorbid diseases (aOR: 4.33, 95% CI: 1.08–17.34) increased the risk of having poor glycemic control. Patients who were more likely to achieve good glycemic control were male (aOR: 0.39, 95% CI: 0.20–0.74) and aged older (aOR: 0.95, 95% CI: 0.92–0.99). ConclusionsThe proportion of patients who were medication nonadherent was much higher than those with poor glycemic control. Whereas regular exercise was a predictor of nonadherence, age, sex, diabetes medication, not taking biguanide, acute complications, and comorbidity were predictors of poor glycemic control. Therefore, strategies are needed to improve medication adherence and glycemic control.

Glycemic control and its associated factors in hypertensive patients with type 2 diabetes.

Inadequate glycemic control among patients with type 2 diabetes is growing worldwide. Earlier research studies investigated the predictors of poor glycemic control among patients with diabetes, but not among hypertensive patients who have type 2 diabetes as a comorbid disease. The aim of this study was to explore the factors associated with poor glycemic control in patients with type 2 diabetes and hypertension. In the present retrospective study, the medical records of two major hospitals were used to collect sociodemographic, biomedical, disease and medication-related information about patients with hypertension and type 2 diabetes. Binary regression analysis was conducted to find the predictors of the study outcome. The data from 522 patients were collected. High physical activity (OR=2.232; 95% CI: 1.368-3.640; p<0.01), receiving insulin (OR=5.094; 95% CI: 3.213-8.076; p <0.01) or GLP1 receptor agonist (OR=2.057; 95% CI: 1.309-3.231; p<0.01) increased the odds of having controlled blood glucose. Increased age (OR=1.041; 95% CI: 1.013-1.070; p<0.01), elevated high-density lipoprotein (HDL) levels (OR=3.727; 95% CI: 1.959-7.092; p<0.01), and lower triglycerides (TGs) levels (OR=0.918; 95% CI: 0.874-0.965; p<0.01) were also associated with improved glycemic control among the study participants. Most of the current study participants showed uncontrolled type 2 diabetes. Low physical activity, not receiving insulin or GLP1 receptor agonist, younger age, low HDL and high TG levels were independently associated with poor glycemic control. Future interventions should place a strong emphasis on the value of consistent physical activity and a stable lipid profile in enhancing glycemic control, particularly in younger patients and those who are not receiving insulin or GLP1 receptor agonist therapy.

Quality of glycemic control in type 2 diabetes mellitus (T2DM) and its association with markers of coagulation and inhibitors of fibrinolysis: A case-control study in the Upper West Region, Ghana.

Type 2 diabetes mellitus (T2DM) individuals are at a higher risk of developing diabetes complications, with approximately 80% complication-related mortality. The increased morbidity and mortality among T2DM patients are partly due to dysregulated hemostasis. This study determined the quality of glycemic control in T2DMand its association with markers of coagulation and inhibitors of fibrinolysis. This case-control study recruited 90 participants involving: 30 T2DM patients with good glycemic control, 30 with poor glycemic control, and 30 nondiabetic subjects as controls at a Municipal Hospital in Ghana. Fasting blood glucose, glycated hemoglobin, activated partial thromboplastin time (APTT), prothrombin time (PT), calculated international normalized ratio (INR), and full blood count (FBC) were determined for each respondent. Plasma levels of plasminogen activator inhibitor-1 (PAI-1) and thrombin activatable fibrinolysis inhibitor (TAFI) were determined using the solid-phase sandwich enzyme-linked immunosorbent assaymethod. Data wereanalyzed using R language software. Plasma PAI-1 antigen levels were significantly higher in the participants with poor glycemic control as compared to participants with good glycemic control (p < 0.0001). There was no significant difference in plasma TAFI levels between the participants with poor glycemic control as compared to participants with good glycemic control (p = 0.900). T2DM patients had significantly shorter APTT, PT, and INR than controls (p < 0.05). At a cut-off of ≥161.70 pg/μL, PAI was independently associated with increasing odds (adjusted odds ratio = 13.71, 95% confidence interval:3.67-51.26, p < 0.0001) of poor glycemic control and showed the best diagnostic accuracy for poor glycemic control (area under the curve = 0.85, p < 0.0001). PAI-1 levels were significantly increased in T2DM with poor glycemic control and emerged as the best predictor for poor glycemic control. Good glycemic management to control the plasma levels of PAI-1 is required to prevent hypercoagulability and thrombotic disorders.

Glycemic control and diabetes complications among adult type 2 diabetic patients at public hospitals in Hadiya zone, Southern Ethiopia.

Diabetes is one of the biggest worldwide health emergencies of the 21st century. A major goal in the management of diabetes is to prevent diabetic complications that occur as a result of poor glycemic control. Identification of factors contributing to poor glycemic control is key to institute suitable interventions for glycemic control and prevention of chronic complications. A hospital-based cross-sectional study was conducted among 305 adult type 2 diabetic patients at public hospitals in Hadiya zone from March 1-30, 2019. The study participants were selected by systematic sampling technique. Data were collected using a pretested structured questionnaire and patient chart review; anthropometric and blood pressure measurements were taken. Multivariable logistic regression analysis was used to identify factors associated with poor glycemic control. Adjusted odds ratios (AOR) with respective 95% Confidence Interval (CI) and p < 0.05 were used to set statistically significant variables. Out of 305 diabetic patients, 222 (72.8%) were found to have poor glycemic control. Longer duration of diabetes (5-10 years) [AOR = 2.24, 95% CI: 1.17-4.27], lack of regular follow-up [AOR = 2.89, 95% CI: 1.08-7.71], low treatment adherence [AOR = 4.12, 95% CI: 1.20-8.70], use of other alternative treatments [AOR = 3.58, 95% CI: 1.24-10.36], unsatisfactory patient physician relationship [AOR = 2.27, 95% CI: 1.27-4.04], and insufficient physical activity [AOR = 4.14, 95% CI: 2.07-8.28] were found to be independent predictors of poor glycemic control. Diabetes Mellitus (DM) complications were slightly higher among participants with poor glycemic control (39.2%), duration of DM 10 and above years (41.9%), low medication adherence (48.5%), taking oral anti-diabetics (54.3%), and DM patients having unsatisfactory patient provider relationship (72.4%). A significant proportion of diabetic patients had poor glycemic control and DM complications. Therefore, appropriate interventions are required to maintain optimal glycemic control and prevent the development of life-threatening complications among DM patients.

Interplay between Myokine Profile and Glycemic Control in Type 2 Diabetes Mellitus Patients with Heart Failure.

Type 2 diabetes mellitus (T2DM) remains a powerful predictor of progressive heart failure (HF), but it is not clear whether altered glycemic control interferes with HF progression via an impaired profile of circulating myokines. The aim was to investigate plausible effects of glucose control on a myokine signature in T2DM patients affected by chronic HF. We selected 372 T2DM patients from the local database and finally included 314 individuals suffering from chronic HF and subdivided them into two groups according to glycosylated hemoglobin (HbA1c) levels (&lt;6.9% and ≥7.0%). Echocardiography and Doppler examinations along with biomarker measurements were performed at the baseline of the study. The results showed that irisin levels were significantly lower in patients with HbA1c ≥ 7.0% than in those with HbAc1 &lt; 6.9%, whereas concentrations of apelin, myostatin and adropin did not significantly differ between these two groups. We also identified numerous predictors of poor glycemic control, but only N-terminal brain natriuretic propeptide (odds ratio [OR] = 1.07; 95% confidence interval [CI] = 1.02-1.10, p = 0.04) and irisin (OR = 1.09; 95% CI = 1.04-1.17, p = 0.001) remained independent predictors of the dependent variable. In conclusion, we found that decreased levels of irisin were associated with poor glycemic control in T2DM patients with HF regardless of clinical conditions and other biomarkers.

Adherence as a Predictor of Glycemic Control Among Adolescents With Type 1 Diabetes: A Retrospective Study Using Real-world Evidence

PurposeMetabolic control among adolescents with type 1 diabetes mellitus (T1DM) is generally poor. Nonadherence is a contributor to this poor glycemic control, leading to adverse outcomes. The findings of studies reporting the association between adherence and glycemic control are conflicting. This study aimed to assess the level of adherence among adolescents with T1DM and its relationship with glycemic control. MethodsThis was a retrospective, cross-sectional study that was conducted at Sidra Medicine, a state-of-the-art tertiary health care facility for women and children in Qatar. Mean blood or interstitial glucose monitoring frequency (BGMF) was used to assess adherence level among adolescents with T1DM, whereas glycemic control was assessed via documented glycated hemoglobin A1c (HbA1c). Adolescents who had a mean BGMF of ≥4 checks per day were considered adherent, and those who had an HbA1c level of <7% were considered as having controlled diabetes. Correlational and logistic regression analyses were performed to assess the relationship between adherence and glycemic control, incorporating other covariates into the model. FindingsThe rate of adherence among adolescents with T1DM in Qatar was 40.9%. Adherent adolescents had significantly lower median HbA1c levels compared with nonadherent adolescents (9.0% vs. 9.7%; P = 0.002). A significant negative correlation was found between BGMF and HbA1c level (correlation coefficient rs = −0.325; P < .001). Approximately 97% of nonadherent adolescents compared with 87% of adherent adolescents had suboptimal diabetes control (HbA1c ≥7%) (P = .016). Furthermore, nonadherent adolescents were 78% less likely to have controlled diabetes compared with adherent adolescents (adjusted odds ratio = 0.221; 95% CI, 0.063−0.778; P = 0.019). The combined effect of the determinants of glycemic control among adolescents with T1DM that were included in the multiple regression model was able to explain approximately 9% of the variances in glycemic control (Cox and Snell R2 = 0.092). ImplicationsThe current findings suggest that nonadherence was highly prevalent among adolescents with T1DM and was a significant independent predictor of glycemic control, explaining 9% of the variability. This finding warrants further exploration of other possible predictors of poor glycemic control among the adolescent population. Comprehensive interventions, including educational, technological, and health service delivery aspects, aimed at improving adherence and ultimately optimizing glycemic control are warranted in adolescents with T1DM.

Predicting poor glycemic control during Ramadan among non-fasting patients with diabetes using artificial intelligence based machine learning models

AimsThis study aims to predict poor glycemic control during Ramadan among non-fasting patients with diabetes using machine learning models. MethodsFirst, we conducted three consultations, before, during, and after Ramadan to assess demographics, diabetes history, caloric intake, anthropometric and metabolic parameters. Second, machine learning techniques (Logistic Regression, Support Vector Machine, Naive Bayes, K-nearest neighbor, Decision Tree, Random Forest, Extra Trees Classifier and Catboost) were trained using the data to predict poor glycemic control among patients. Then, we conducted several simulations with the best performing machine learning model using variables that were found as main predictors of poor glycemic control. ResultsThe prevalence of poor glycemic control among patients was 52.6%. Extra tree Classifier was the best performing model for glycemic deterioration (accuracy = 0.87, AUC = 0,87). Caloric intake evolution, gender, baseline caloric intake, baseline weight, BMI variation, waist circumference evolution and Total Cholesterol serum level after Ramadan were selected as the most significant for the prediction of poor glycemic control. We determined thresholds for each predicting factor among which this risk is present. ConclusionsThe clinical use of our findings may help to improve glycemic control during Ramadan among patients who do not fast by targeting risk factors of poor glycemic control.