Factors that Correlate with Poor Glycemic Control in Type 2 Diabetes Mellitus Patients with Complications

"Hyperglycemic Memory": Observational Evidence to Experimental Inference

Several epidemiological studies have appreciated the impact of "duration" and "level" of hyperglycemia on the initiation and development of chronic complications of diabetes. However, glycemic profiles could not fully explain the presence/absence and severity of diabetic complications. Genetic issues and concepts of "hyperglycemic memory" have been introduced as additional influential factors involved in the pathobiology of late complications of diabetes. In the extended phase of significant diabetes randomized, controlled clinical trials, including DCCT/EDIC and UKPDS, studies have concluded that the quality of glycemic or metabolic control at the early time around the diabetes onset could maintain its protective or detrimental impact throughout the following diabetes course. There is no reliable indication of the mechanism by which the transient exposure to a given glucose concentration level could evoke a consistent cellular response at target tissues at the molecular levels. Some biological phenomena, such as the production and the concentration of advanced glycation end products (AGEs), reactive oxygen species (ROS) and protein kinase C (PKC) pathway activations, epigenetic changes, and finally, the miRNAs-mediated pathways, may be accountable for the development of hyperglycemic memory. This work summarizes evidence from previous experiments that may substantiate the hyperglycemic memory soundness by its justification in molecular terms.

Tailoring nursing interventions to empower patients: personal coping strategies and self-management in type 2 diabetes care

BACKGROUND

Diabetes is one of the most common chronic diseases that severely reduce a patient's quality of life. Effective self-care and management are critical for maintaining blood glucose levels and preventing complications.

AIM

This study evaluates the effectiveness of a structured diabetes self-management education program on patients' self-management behaviors, empowerment, and activation levels.

METHODS

This study employed a quasi-experimental design involving 100 participants aged 30-65 to improve diabetes self-management and empowerment. Over 16 weeks, the program included three phases: a two-week pre-test phase for recruitment and baseline assessments using the Diabetes Self-Management Questionnaire (DSMQ), Diabetes Empowerment Scale (DES), and Patient Activation Measure (PAM); a 12-week intervention phase featuring weekly 90-minute educational sessions on topics such as diet, exercise, medication adherence, stress management, and self-empowerment; and a two-week post-test phase for follow-up assessments using the same tools. Data were analyzed using descriptive statistics, chi-square tests for PAM levels, and paired t-tests for DSMQ and DES scores, with statistical significance set at p < 0.05.

RESULTS

The study demonstrated significant improvements in participants' self-management, empowerment, and activation levels after the intervention. DSMQ scores increased from 64.5 to 68.6 (p < 0.001), DES scores rose from 65.4 to 70.0 (p = 0.001), and the number of participants at the highest PAM activation level (Level 4) grew from 30 to 50 (p = 0.016). Positive correlations among DSMQ, DES, and PAM scores suggest these improvements are interrelated.

CONCLUSION

The structured diabetes self-management education programme significantly impacted participants' self-management behaviors, empowerment, and activation levels. The findings underscore healthcare professionals' need to implement targeted interventions that facilitate patient engagement in diabetes care.

RECOMMENDATION

Future interventions should be designed to address the specific needs of diverse populations, paying attention to those facing socio-economic challenges. It is vital to facilitate greater access to diabetes self-management education to enhance health outcomes for these demographic groups.

Effects of concurrent training on glycemic and vascular parameters among patients with T2DM-associated Peripheral Artery Disease

Objective

To evaluate the effects of CT to improve HbA1C and ABI among the T2DM-associated PAD population.

Methods

A randomized, single-blinded, two-arm trial was conducted at the Department of Rehabilitation Sciences of Dr. Ziauddin Hospital in Karachi between July to September 2023. A total of 80 T2DM-associated PAD patients were included and randomly divided into Experimental Group (n=40) and Control Group (n=40), using the sealed envelope method. Experimental group patients received Concurrent Training (CT), whereas Control Group patients underwent Aerobic Training (AT) for 12 weeks. Both groups received thirty-minute sessions three times a week that was progressed to 60 minutes over 12 weeks. HbA1C and ABI were measured at baseline and after 12 weeks.

Results

Analysis revealed an average age of 46.75±3.59 and the duration of T2DM for developing PAD is 14.82±2.23 on average. Findings revealed that both training groups were significantly effective (p<0.000) at 95% CI in improving glycemic and vascular parameters after 12 weeks. Subsequently, findings showed that the CT group showed more significant improvement than AT group in improving HbA1C for glycemic control (p=0.002, CT: pre: 9.53±1.406, post: 7.81±0.81, AT: pre: 8.74±0.908, post: 8.15±0.83) and ABI for systemic blood flow (p=0.0001, CT: pre: 0.84±0.03, post: 0.94±0.03, AT: pre: 0.82±0.02, post: 0.86±0.02).

Conclusion

CT showed a two-fold improvement in glycemic control and arterial blood flow than AT group, which represents that CT is an effective therapeutic approach for T2DM-associated Fontain's stage IIa PAD rehabilitation.

Dietary glycemic index and glycemic load predict longitudinal change in glycemic and cardio-metabolic biomarkers among old diabetic adults living in a resource-poor country

This study aims to investigate longitudinal associations between the dietary glycemic index (GI) and glycemic load (GL) and changes in glycemic and cardio-metabolic outcomes. A 28-month retrospective cohort study included 110 Vietnamese diabetic patients, collecting their dietary GI and GL values along with blood biochemical data from baseline 24-h dietary recall and medical records. Latent class growth modelling identified three distinct HbA1c trajectories during the follow-up period, with 51% of patients achieving good glycemic control. The adjusted linear mixed-effect model showed that 1 unit increase in logarithms in dietary GL was associated with a 0.14% increase in the log-HbA1c. Among poorly controlled diabetic patients, baseline GL values were positively correlated with increases in HbA1c; GI showed effects on changes in fasting plasma glucose and the triglyceride-glucose (TyG) index. No significant association was observed in patients with good glycemic control.

Prevalence and predictors of hypoglycemia in older outpatients with type 2 diabetes mellitus

BACKGROUND

The prevalence of type 2 diabetes (DM) has been increasing globally, particularly among older adults who are more susceptible to DM-related complications. Elderly individuals with diabetes are at higher risk of developing hypoglycemia compared with younger diabetes patients. Hypoglycemia in elderly patients can result in serious consequences such as cognitive changes, increased risk of falls, heart and other vascular problems, and even high mortality rate.

OBJECTIVE

To assess prevalence, and factors associated with hypoglycemia events among geriatric outpatients with type 2 diabetes mellitus.

METHODS

The study was conducted at King Abdullah University Hospital (KAUH) at the outpatient diabetes clinic from October 1st, 2022 to August 1st, 2023. Variables such as socio-demographics, medication history, and comorbidities were obtained using electronic medical records. The prevalence of hypoglycemia was determined through patient interviews during their clinic visit. Patients were prospectively monitored for hospital admissions, emergency department visits, and mortality using electronic medical records over a three-month follow-up period. Logistic regression models were conducted to identify factors associated with hypoglycemia and hospital admissions/ emergency visits. Ethical Approval (Reference # 53/151/2022) was obtained on 19/9/2022.

RESULTS

Electronic medical charts of 640 patients who have type 2 diabetes mellitus and age ≥ 60 years were evaluated. The mean age ± SD was 67.19 (± 5.69) years. Hypoglycemia incidents with different severity levels were prevalent in 21.7% (n = 139) of the patients. Insulin administration was significantly associated with more hypoglycemic events compared to other antidiabetic medication. Patients with liver diseases had a significantly higher risk of hypoglycemia, with odds 7.43 times higher than patients without liver diseases. Patients with dyslipidemia also had a higher risk of hypoglycemia (odd ratio = 1.87). Regression analysis revealed that hypoglycemia and educational level were significant predictors for hospital admission and emergency department (ER) visits. Hypoglycemia was a positive predictor, meaning it increased the odds of these outcomes, while having a college degree or higher was associated with reduced odds of hospital admission and ER visits.

CONCLUSION

Current study identified a considerable prevalence of hypoglycemia among older patients with type 2 diabetes, particularly, among those with concurrent liver diseases and dyslipidemia. Furthermore, hypoglycemia was associated with an increased rate of emergency department visits and hospital admissions by 2 folds in this population.

Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning Model Development

BACKGROUND

Type 2 diabetes (T2D) is a significant global health challenge. Physicians need to assess whether future glycemic control will be poor on the current trajectory of usual care and usual-care treatment intensifications so that they can consider taking extra treatment measures to prevent poor outcomes. Predicting poor glycemic control from trends in hemoglobin A1c (HbA1c) levels is difficult due to the influence of seasonal fluctuations and other factors.

OBJECTIVE

We sought to develop a model that accurately predicts poor glycemic control among patients with T2D receiving usual care.

METHODS

Our machine learning model predicts poor glycemic control (HbA1c≥8%) using the transformer architecture, incorporating an attention mechanism to process irregularly spaced HbA1c time series and quantify temporal relationships of past HbA1c levels at each time point. We assessed the model using HbA1c levels from 7787 patients with T2D seeing specialist physicians at the University of Tokyo Hospital. The training data include instances of poor glycemic control occurring during usual care with usual-care treatment intensifications. We compared prediction accuracy, assessed with the area under the receiver operating characteristic curve, the area under the precision-recall curve, and the accuracy rate, to that of LightGBM.

RESULTS

The area under the receiver operating characteristic curve, the area under the precision-recall curve, and the accuracy rate (95% confidence limits) of the proposed model were 0.925 (95% CI 0.923-0.928), 0.864 (95% CI 0.852-0.875), and 0.864 (95% CI 0.86-0.869), respectively. The proposed model achieved high prediction accuracy comparable to or surpassing LightGBM's performance. The model prioritized the most recent HbA1c levels for predictions. Older HbA1c levels in patients with poor glycemic control were slightly more influential in predictions compared to patients with good glycemic control.

CONCLUSIONS

The proposed model accurately predicts poor glycemic control for patients with T2D receiving usual care, including patients receiving usual-care treatment intensifications, allowing physicians to identify cases warranting extraordinary treatment intensifications. If used by a nonspecialist, the model's indication of likely future poor glycemic control may warrant a referral to a specialist. Future efforts could incorporate diverse and large-scale clinical data for improved accuracy.

Exploring the self-efficacy of patients with diabetes: its role as a predictor of diabetes management and well-being

Background

Self-efficacy is a popular psychological concept that refers to an individual's perception or belief in his ability to perform specific actions. This study aimed to assess the predictive value of self-efficacy, measured using the Self-Efficacy for Managing Chronic Disease 6-Item Scale (SEM6S) questionnaire, for diabetes management and overall well-being in patients with diabetes.

Subject and methods

An anonymous online cross-sectional study was conducted to evaluate the self-efficacy of diabetic patients in the Asser region of Saudi Arabia. The participants were requested to upload their most recent glycated hemoglobin A1C (HbA1C) measurements taken in the last three months, which helped in the accurate categorization of their diabetes as either controlled or uncontrolled. We used the valid Arabic version of the SEM6S and WHO-5 well-being questionnaires to assess patient self-efficacy and well-being.

Results

A cohort of 342 patients was enrolled in the study, 67.25% were married, their mean age was 43.17 ± 17.61 years, and 52.69% had university-level or higher education. Among the participants, 46.0% exhibited well-being, while 24.9% reported poor well-being, including 9.4% who were identified as experiencing depression. The mean scores of self-efficacy and well-being were significantly higher among those with controlled diabetes versus uncontrolled diabetes (40.86 ± 13.26 vs. 36.48 ± 13.26) and (67.35 ± 21.22 vs. 60.93 ± 25.05), respectively. The predictors of glycemic control were self-efficacy [Odds ratio (OR)=1.03 (95%CI, 1.01-1.06, P=0.002], having other chronic diseases [OR=3.25 (95%CI), P<0.001], having type 1 diabetes [OR=7.16, 95%CI, P=0.005], being Saudi [OR=7.67, (95%CI, P=0.027], working in a public sector [OR=0.15, (95%CI, 0.05-0.44), P=0.005], being unemployed [OR=0.19, (95%CI, 0.06-0.59), P=0.005], being a smoker [OR=0.44, 95%CI, 0.19-0.98, P=0.048], and duration of diabetes between 6-10 years [OR= 0.33, 95%CI, 0.11-0.95), P=0.043] or more than 10 years OR=0.32, 95%CI, 0.12-0.86), P=0.026]. The main determinants of well-being were having self-efficacy [OR=1.07 (95%CI, 1.04-1.09), P = 0.0001], having public health insurance [OR=4.36 (95%CI, P=0.015], and education level (read and write) [OR=0.13 (95%CI,.02-.70), P=0.021].

Conclusions

The study reveals that non-modifiable and modifiable factors, including self-efficacy, play a crucial role in diabetes control. The study recommends providing targeted educational interventions, using different social media platforms, psychosocial support programs, and inclusive healthcare policies to improve diabetes control and mental well-being among diabetic patients.

Prevalence of and factors associated with suboptimal glycemic control among patients with type 2 diabetes mellitus attending public hospitals in the Greater Male' Region, Maldives: a hospital-based cross-sectional study

BACKGROUND

Suboptimal glycemic control of type 2 diabetes mellitus (T2DM) which is defined as having HbA1c greater than 7% is a major public health problem in several countries, including the Maldives. The study aimed to estimate the prevalence and determine factors associated with suboptimal glycemic control among T2DM patients.

METHODS

A hospital-based cross-sectional was applied to collect data from T2DM patients who attended public hospitals in the Greater Male' Region, Maldives where were one of the highest reports of T2DM and suboptimal glycemic control cases in the country between January to March 2023 by a validated questionnaire and anthropometric measurements. Five (5) ml blood specimens were collected to measure the glycated hemoglobin (HbA1c) level. Univariable and multivariable logistic regressions were employed to determine factors associated with suboptimal glycemic control of T2DM at a significant level of α = 0.05.

RESULTS

A total of 341 participants were recruited for the study: 65.7% were female, 42.5% were aged 40-60 years, and 42.2% were married. The overall prevalence of suboptimal glycemic control was 50.7%. Ten variables were found to be associated with suboptimal glycemic control in multivariable logistic regression. Those aged 40-60 years (AOR = 3.35, 95% CI = 1.78-6.30), being single (AOR = 2.53, 95% CI = 1.21-5.30), preparation of food using more than three tablespoons of cooking oil (AOR = 2.78, 95% CI = 1.46-5.28), preparation of food with more than three tablespoons of sugar (AOR = 2.55, 95% CI = 1.31-4.93), no exercise (AOR = 2.04, 95% CI = 1.15-3.61), DM diagnosed with more than twenty years prior (AOR = 2.59, 95% CI = 1.34-4.99), obese body mass index (BMI) (AOR = 3.82, 95% CI = 1.75-8.32), high total cholesterol (AOR = 2.43, 95% CI = 1.36-4.35), high triglycerides (AOR = 3.43, 95% CI = 1.93-6.11), and high-level stress (AOR = 2.97, 95% CI = 1.48-5.93) were having a greater odds of having suboptimal glycemic control than those who did not have these characteristics.

CONCLUSION

A large proportion of T2DM patients in the Greater Male' Region fail to control their blood glucose. Effective public health interventions should be introduced, especially interventions focused on reducing cooking oil and sugar in daily cooking practices, encouraging regular exercise, and maintaining cholesterol levels, particularly for those diagnosed with diabetes mellitus for more than 20 years prior.

Effectiveness of Family-Based Diabetes Management Intervention on Glycated Haemoglobin Among Adults With Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Glycated hemoglobin (HbA1c) control is a crucial goal in the management of type 2 diabetes mellitus (T2DM), requiring lifelong commitment and family support. This study aimed to assess the effectiveness of family-based diabetes management intervention on HbA1c among adults with T2DM.

METHODS

From inception up to 2022, a comprehensive literature search was conducted across PubMed, ProQuest, Scopus, CORE, and the Cochrane Library. The quality of studies was evaluated using the Joanna Briggs Institute (JBI) Critical Appraisal tools. Effect sizes were calculated using standard deviations (SD), while the degree of heterogeneity was evaluated using the Higgins I2 test. Subgroup analyses were performed to explore factors contributing to sources of heterogeneity among trials. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were followed, and the protocol was registered with PROSPERO CRD42022384034.

RESULTS

A total of 18 randomized controlled trials (RCTs) involving 2815 participants indicated that family-based diabetes management intervention had a statistically significant impact on improving HbA1c (Mean Difference [MD] = -.47; 95% Confidence Interval [CI]: -.64 to -.30, p < .001) with a moderate level of heterogeneity (I2 = 59%). Subgroup analysis indicated that family-based diabetes management intervention among adults with T2DM in developing regions was more effective in improving HbA1c levels compared to developed countries.

CONCLUSION

Family-based diabetes management interventions improved HbA1c. Further research is required to develop diabetes management strategies with a family focus that clearly defines the family's involvement.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population

INTRODUCTION

Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants.

RESEARCH DESIGN AND METHODS

We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test.

RESULTS

Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs).

CONCLUSIONS

Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Exploring the Interplay of Socioeconomic and Behavioral Factors: Unraveling Gender Disparities in Glycemic Control Among Adult Type 2 Diabetic Patients in Outpatient Care

Background Diabetes mellitus (DM) presents global challenges, with optimal glycemic control being pivotal in managing complications, notably in type 2 diabetes mellitus (T2DM). Yet, achieving sustained control faces barriers stemming from socioeconomic and gender-specific disparities. This study addresses these gaps by examining socioeconomic determinants and gender disparities in diabetes management, particularly in Maharashtra, India. Methodology This cross-sectional study involved 302 T2DM patients aged 20 to 79 years. Data on sociodemographic, behavioral, and clinical factors were collected through interviews, and records were analyzed via logistic regression to identify predictors of glycemic control. Results Significant associations emerged between gender and education, occupation, and religion. Glycemic control, with a mean HbA1c of 8.45%, remained suboptimal. Logistic regression identified gender, average family income, diabetes duration, treatment nature, comorbidities, complications, and medication adherence as glycemic control predictors. Conclusions Addressing socioeconomic and gender-specific factors is paramount in diabetes management, especially in rural areas where sociocultural influences shape health behaviors. Tailored interventions, including gender-sensitive health education, are vital for improving diabetes care and outcomes. This study provides crucial insights into gender-specific influences on glycemic control among T2DM patients in Maharashtra, advocating for personalized interventions to enhance overall diabetes management.

Metabolic Biomarkers in Adults with Type 2 Diabetes: The Role of PPAR-γ2 and PPAR-β/δ Polymorphisms

Glucose and lipid metabolism regulation by the peroxisome proliferator-activated receptors (PPARs) has been extensively reported. However, the role of their polymorphisms remains unclear.

OBJECTIVE

To determine the relation between PPAR-γ2 rs1801282 (Pro12Ala) and PPAR-β/δ rs2016520 (+294T/C) polymorphisms and metabolic biomarkers in adults with type 2 diabetes (T2D).

MATERIALS AND METHODS

We included 314 patients with T2D. Information on anthropometric, fasting plasma glucose (FPG), HbA1c and lipid profile measurements was taken from clinical records. Genomic DNA was obtained from peripheral blood. End-point PCR was used for PPAR-γ2 rs1801282, while for PPAR-β/δ rs2016520 the PCR product was digested with Bsl-I enzyme. Data were compared with parametric or non-parametric tests. Multivariate models were used to adjust for covariates and interaction effects.

RESULTS

minor allele frequency was 12.42% for PPAR-γ2 rs1801282-G and 13.85% for PPAR-β/δ rs2016520-C. Both polymorphisms were related to waist circumference; they showed independent effects on HbA1c, while they interacted for FPG; carriers of both PPAR minor alleles had the highest values. Interactions between FPG and polymorphisms were identified in their relation to triglyceride level.

CONCLUSIONS

PPAR-γ2 rs1801282 and PPAR-β/δ rs2016520 polymorphisms are associated with anthropometric, glucose, and lipid metabolism biomarkers in T2D patients. Further research is required on the molecular mechanisms involved.

Glycemic control and associated factors among type 2 diabetes mellitus patients: a cross-sectional study of Azar cohort population

BACKGROUND

Despite the growing prevalence of diabetes and its complications, there is a dearth of data regarding factors associated with glycemic control. Therefore, in this cross-sectional study, we aimed to identify factors influencing glycemic control in patients with type 2 diabetes mellitus (T2DM) in the Iranian population.

METHODS

This cross-sectional study was conducted among the Azar cohort population and the glycemic control status of patients with T2DM was investigated. Possible risk factors including age, sex, marital status, educational level, smoking status, sleep duration, family history of diabetes and hypertension, socioeconomic status, physical activity level, and co-existence of other chronic diseases and their relationship with glycemic control status were also assessed. Multivariate logistic regression analysis was used to identify determinants of glycemic control.

RESULTS

Among 1,710 T2DM patients (60.2% female), the overall prevalence of poor glycemic control was 56.8%. In the unadjusted logistic regression analysis model, a low wealth score index significantly increased the risk of poor glycemic control (OR: 1.49;1.10-2.02). Variables significantly associated with poor glycemic control even after adjusting for confounding factors were first-degree family history of diabetes (OR: 1.34; 1.08-1.65), and sleep duration (OR: 1.29 ;1.02-1.62 for 6.6-8 h/d; OR:1.42;1.10-1.88 for > 8 h/d). Interestingly, we found that the co-existence of ≥ 3 chronic diseases with diabetes decreased the risk of poor glycemic control.

CONCLUSIONS

In the current study, most of the patients with T2DM had uncontrolled glycemic control. Due to the individual and social costs of diabetes complications, it is necessary to suggest tailored and effective interventions for controlling blood glucose levels in people with diabetes.

Estimation of the onset time of diabetic complications in type 2 diabetes patients in Thailand: a survival analysis

BACKGROUND

This study aimed to identify factors associated with the onset time of diabetic complications in patients with type 2 diabetes mellitus (T2DM) and determine the best-fitted survival model.

METHODS

A retrospective cohort study was conducted among T2DM patients enrolled from October 1, 2016 to July 15, 2020 at the National Health Security Office (NHSO). In total, 388 T2DM patients were included. Cox proportional-hazard and parametric models were used to identify factors related to the onset time of diabetic complications. The Akaike information criterion, Bayesian information criterion, and Cox-Snell residual were compared to determine the best-fitted survival model.

RESULTS

Thirty diabetic complication events were detected among the 388 patients (7.7%). A 90% survival rate for the onset time of diabetic complications was found at 33 months after the first T2DM diagnosis. According to multivariate analysis, a duration of T2DM ≥42 months (time ratio [TR], 0.56; 95% confidence interval [CI], 0.33-0.96; p=0.034), comorbid hypertension (TR, 0.30; 95% CI, 0.15-0.60; p=0.001), mildly to moderately reduced levels of the estimated glomerular filtration rate (eGFR) (TR, 0.43; 95% CI, 0.24-0.75; p=0.003) and an eGFR that was severely reduced or indicative of kidney failure (TR, 0.38; 95% CI, 0.16-0.88; p=0.025) were significantly associated with the onset time of diabetic complications (p<0.05).

CONCLUSION

Patients with T2DM durations of more than 42 months, comorbid hypertension, and decreased eGFR were at risk of developing diabetic complications. The NHSO should be aware of these factors to establish a policy to prevent diabetic complications after the diagnosis of T2DM.

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

Background

This study aimed to assess medication adherence, glycemic control, and their influencing factors among outpatients at an Indonesian clinic with type 2 diabetes.

Methods

A 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.

Results

Of 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).

Conclusions

The 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.

Identifying Profiles of Patients With Uncontrolled Type 2 Diabetes Who Would Benefit From Referral to an Endocrinologist

OBJECTIVE

To compare the outcomes of glycemic uncontrolled diabetes mellitus type 2 patients receiving treatment from endocrinologists with those treated by primary care physicians. Additionally, this research aims to identify patient profiles that would benefit from personalized referral-a novel medical approach that aims to match the most suitable specialist for effectively managing patient while considering the patient's profile.

METHODS

This retrospective cohort study uses the Maccabi Healthcare Services diabetes registry to match 508 pairs of glycemic uncontrolled diabetes mellitus type 2 patients treated by endocrinologists (EndoG) and primary care physicians (PcPG). Using a generalized additive model, we analyzed the hemoglobin A1c (HbA1c) trend over 1 year for each group. We employed the odds ratio (OR) from conditional logistic regression to determine the likelihood of favorable outcomes in the EndoG compared to the PcPG, using the entire cohort and subcohort profiles.

RESULTS

The generalized additive model comparison indicated an improvement in HbA1c levels in both groups, with the EndoG outperforming the PcPG. Furthermore, the EndoG group had an OR = 2.27 (95% confidence interval, 1.6 to 3.2) for reducing HbA1c by at least 1% within a year and an OR = 1.68 (95% confidence interval, 1.02 to 2.76) for achieving low-density lipoprotein levels< 100 mg/dl. We identified 96 profiles with positive outcomes, all favoring treatment by endocrinologists.

CONCLUSIONS

EndoG demonstrated superior HbA1c control over time and achieved better outcomes compared to PcPG. The identification of 96 profiles benefiting from endocrinologist referral emphasizes the potential of personalized referral.

Personalized Prediction of Change in Fasting Blood Glucose Following Basal Insulin Adjustment in People With Type 2 Diabetes: A Proof-of-Concept Study

AIMS

For people with type 2 diabetes treated with basal insulin, suboptimal glycemic control due to clinical inertia is a common issue. Determining the optimal basal insulin dose can be difficult, as it varies between individuals. Thus, insulin titration can be slow and cautious which may lead to treatment fatigue and non-adherence. A model that predicts changes in fasting blood glucose (FBG) after adjusting basal insulin dose may lead to more optimal titration, reducing some of these challenges.

OBJECTIVE

To predict the change in FBG following adjustment of basal insulin in people with type 2 diabetes using a machine learning framework.

METHODS

A multiple linear regression model was developed based on 786 adults with type 2 diabetes. Data were divided into training (80%) and testing (20%) sets using a ranking approach. Forward feature selection and fivefold cross-validation were used to select features.

RESULTS

Participants had a mean age of approximately 59 years, a mean duration of diabetes of 12 years, and a mean HbA1c at screening of 65 mmol/mol (8.1%). Chosen features were FBG at week 2, basal insulin dose adjustment from week 2 to 7, trial site, hemoglobin level, and alkaline phosphatase level. The model achieved a relative absolute error of 0.67, a Pearson correlation coefficient of 0.74, and a coefficient of determination of 0.55.

CONCLUSIONS

A model using FBG, insulin doses, and blood samples can predict a five-week change in FBG after adjusting the basal insulin dose in people with type 2 diabetes. Implementation of such a model can potentially help optimize titration and improve glycemic control.

The impact of pharmacist interventions, follow-up frequency and default on glycemic control in Diabetes Medication Therapy Adherence Clinic program: a multicenter study in Malaysia

BACKGROUND

Pharmacist's involvement in optimizing medication adherence among diabetic patients has been implemented for over a decade. Diabetes Medication Therapy Adherence Clinic (DMTAC) was set up to educate diabetic patients, monitor treatment outcomes, and manage drug-related problems. While evidence shows that pharmacist-led DMTAC was effective in reducing HbA1c, there was limited data regarding the impact of different intervention types and default to follow-up on glycemic control.

AIM

To assess the impact DMTAC on glycemic control and the difference in glycemic control between hospital and health clinic settings as well as defaulter and non-defaulter. In addition, the impact of pharmacist's interventions, DMTAC follow-up frequencies, and duration of diabetes on glycemic control were also determined.

METHODS

A retrospective study was conducted among diabetes patients under DMTAC care between January 2019 and June 2020 in five hospitals and 23 primary health clinics. Patients' demographics data, treatment regimens, frequencies of DMTAC visits, defaulter (absent from DMTAC visits) and types of pharmacists' intervention were retrieved from patients' medical records and electronic database. HbA1c was collected at baseline, 4-6 months (post-1), and 8-12 months (post-2).

RESULTS

We included 956 patients, of which 60% were females with a median age of 58.0 (IQR: 5.0) years. Overall, the HbA1c reduced significantly from baseline (median: 10.2, IQR: 3.0) to post-1 (median: 8.8, IQR: 2.7) and post-2 (median: 8.3, IQR: 2.6%) (p < 0.001). There were 4317 pharmacists' interventions performed, with the majority being dosage adjustment (n = 2407, 55.8%), followed by lab investigations (849, 19.7%), drugs addition (653, 15.1%), drugs discontinuation (408, 9.5%). Patients treated in hospitals received significantly more interventions than those treated in primary health clinics (p < 0.001). We observed significantly less reduction in HbA1c in DMTAC follow-up defaulters than non-defaulters after 1 year (- 1.02% vs. - 2.14%, p = 0.001). Frequencies of DMTAC visits (b: 0.19, CI: 0.079-0.302, p = 0.001), number of dosage adjustments (b: 0.83, CI: 0.015-0.151, p = 0.018) and number of additional drugs recommended (b: 0.37, CI: 0.049-0.691, p = 0.024) had positive impact on glycemic control whereas duration of diabetes (b: - 0.0302, CI: - 0.0507, - 0.007, p = 0.011) had negative impact.

CONCLUSION

Glycemic control improved significantly and sustained up to one year among patients in pharmacists-led DMTAC. However, DMTAC defaulters experienced poorer glycemic control. Considering more frequent visits and targeted interventions by pharmacists at DMTAC resulted in improved HbA1c control, these strategies should be taken into account for future program planning.

Early detection system of risk factors for diabetes mellitus type 2 utilization of machine learning-random forest

BACKGROUND

The prevalence of morbidity and mortality for type 2 diabetes mellitus (DM) is still increasing because of changing lifestyles. There needs to be a means of controlling the rise in the incidence of the disease. Many researchers have utilized technological advances such as machine learning for disease prevention and control, especially in noncommunicable conditions. Researchers are, therefore, interested in creating an early detection system for risk factors of type 2 diabetes.

MATERIALS AND METHODS

The study was conducted in February 2022, utilizing secondary surveillance data from Puskesmas Johar Baru, Jakarta, in 2019, 2020, and 2021. Data was analyzed utilizing various bivariate and multivariate statistical methods at 5% significance level and machine learning methods (random forest algorithm) with an accuracy rate of >80%. The data for the three years was cleaned, normalized, and merged.

RESULTS

The final population was 65,533 visits out of the initial data of 196,949, and the final number of DM 2 population was 2766 out of the initial data of 9903. Age, gender, family history of DM, family history of hypertension, hypertension, high blood sugar levels, obesity, and central obesity were significantly associated with type 2 DM. Family history was the strongest risk factor of all independent variables, odds ratio of 15.101. The classification results of feature importance, with an accuracy rate of 84%, obtained in order were age, blood sugar level, and body mass index.

CONCLUSION

Blood sugar level is the most influential factor in the incidence of DM in Puskesmas Johar Baru. In other words, a person with a family history of type 2 diabetes, at unproductive age, of female gender, and of excessive weight can avoid type 2 diabetes if they can regularly maintain their blood sugar levels.

Management goal achievements of diabetes care in Iran: study profile and main findings of DiaCare survey

Aim

This paper presented the methodology and main findings of a population-based survey to determine diabetes care status among type 2 diabetic subjects in Iran. The current study assessed treatment goal achievements in type 2 diabetics, diabetes care service utilization, prevalence of diabetes complications, and psychological effects of diabetes in a representative sample of Iranian population in urban and rural areas.

Materials and Methods

This nationwide study was conducted between 2018 and 2020 as the observational survey entitled "Diabetes Care (DiaCare)". We studied a representative sample of participants with type 2 diabetes, aged 35-75 years, living in urban and rural areas in all thirty- one provinces of Iran. Data were collected by an interviewer in a form of a questionnaire that includes demographic and socioeconomic status, family and drug history, lifestyle, and self-reported psychological status according to a Patient's Health Questionnaire (PHQ). Management goal achievements, diabetes care service utilization, diabetes complications and psychological effects of diabetes were also assessed. Physical measurements were measured based on standard protocol. Fasting blood glucose (FBG), HbA1c, lipid profile, and also urine albumin to creatinine ratio were obtained from all participants of the study.

Results

Overall, 13,334 people with type 2 diabetes in 31 provinces of Iran completed the survey (response rate: 99.6%). In total 13,321 participants, 6683(50.17%) women and 6638(49.83%) men were included in our analysis. Thirteen recruited patients refused after the consenting process and did not respond. The mean age (SD) of total participants was 54.86 ± 9.44 years and 71.50% were from the urban areas. 13.66% of diabetic patients had achieved the triple target of management [controlled HbA1c, blood pressure, and Low-Density Lipoprotein-Cholesterol (LDL-C)] in the whole country. While 28.74% of people had controlled HbA1c and 33.40% of them had controlled FBG. Diabetic subjects living in rural areas had less controlled HbA1c (23.93 vs. 29.48), controlled FBG (29.50 vs. 34.20) and controlled triple targets (10.45 vs. 14.32) than those living in urban areas. Diabetic neuropathy and diabetic foot were more common in women than men, while end-stage of renal disease (ESRD) was more common in men than women.

Conclusions

This population-based study provided representative information about diabetes care in Iran. The high prevalence of diabetes and low proportion of diabetes control in Iran implies that it is necessary to identify factors associated with poor treatment goal achievements. Besides, general improvements in management and care of diabetes are mandatory.

Cost of screening, out-of-pocket expenditure & quality of life for diabetes & hypertension in India

Background & objectives

The Government of India has initiated a population based screening (PBS) for noncommunicable diseases (NCDs). A health technology assessment agency in India commissioned a study to assess the cost-effectiveness of screening diabetes and hypertension. The present study was undertaken to estimate the cost of PBS for Type II diabetes and hypertension. Second, out-of-pocket expenditure (OOPE) for outpatient care and health-related quality of life (HRQoL) among diabetes and hypertension patients were estimated.

Methods

Economic cost of PBS of diabetes and hypertension was assessed using micro-costing methodology from a health system perspective in two States. A total of 165 outpatients with diabetes, 300 with hypertension and 497 with both were recruited to collect data on OOPE and HRQoL.

Results

On coverage of 50 per cent, the PBS of diabetes and hypertension incurred a cost of ₹ 45.2 per person screened. The mean OOPE on outpatient consultation for a patient with diabetes, hypertension and both diabetes and hypertension was ₹ 4381 (95% confidence interval [CI]: 3786-4976), ₹ 1427 (95% CI: 1278-1576) and ₹ 3932 (95% CI: 3614-4250), respectively. Catastrophic health expenditure was incurred by 20, 1.3 and 14.8 per cent of patients with diabetes, hypertension and both diabetes and hypertension, respectively. The mean HRQoL score of patients with diabetes, hypertension and both was 0.76 (95% CI: 0.72-0.8), 0.89 (95% CI: 0.87-0.91) and 0.68 (95% CI: 0.66-0.7), respectively.

Interpretations & conclusions

The findings of our study are useful for assessing cost-effectiveness of screening strategies for diabetes and hypertension.

Using Machine Learning for the Risk Factors Classification of Glycemic Control in Type 2 Diabetes Mellitus

Several risk factors are related to glycemic control in patients with type 2 diabetes mellitus (T2DM), including demographics, medical conditions, negative emotions, lipid profiles, and heart rate variability (HRV; to present cardiac autonomic activity). The interactions between these risk factors remain unclear. This study aimed to use machine learning methods of artificial intelligence to explore the relationships between various risk factors and glycemic control in T2DM patients. The study utilized a database from Lin et al. (2022) that included 647 T2DM patients. Regression tree analysis was conducted to identify the interactions among risk factors that contribute to glycated hemoglobin (HbA1c) values, and various machine learning methods were compared for their accuracy in classifying T2DM patients. The results of the regression tree analysis revealed that high depression scores may be a risk factor in one subgroup but not in others. When comparing different machine learning classification methods, the random forest algorithm emerged as the best-performing method with a small set of features. Specifically, the random forest algorithm achieved 84% accuracy, 95% area under the curve (AUC), 77% sensitivity, and 91% specificity. Using machine learning methods can provide significant value in accurately classifying patients with T2DM when considering depression as a risk factor.

Knowledge and Awareness About Diabetes Mellitus Among Urban and Rural Population Attending a Tertiary Care Hospital in Haryana

BACKGROUND

Diabetes mellitus (DM) is one of the fastest-growing public health problems in the twenty-first century. The ignorance among people about their disease may be related to their low socioeconomic status and lack of quality education available to them about the disease. It is a serious condition leading to several complications if the individual does not follow up regularly for check-ups and blood sugar monitoring. Lifestyle modifications such as a healthy diet, regular exercise, reducing weight, stress management, and smoking cessation can play a critical role in managing diabetes and improving the health and well-being of diabetic patients. Thus, through this study, we want to assess and create awareness among diabetic patients.

METHODOLOGY

It is a hospital-based cross-sectional study conducted at a tertiary care hospital on diagnosed cases of DM. The patients aged 18 years or above of either gender who had already been diagnosed with DM type 1 and type 2 were included, and patients with gestational DM were excluded from the study. Informed consent was taken from the patients, and all the required details were obtained using a well-structured questionnaire. After obtaining all the answers, the level of knowledge and awareness was analyzed, and the data was entered into an MS Excel sheet (Microsoft, Redmond, Washington) and analyzed by Statistical Package for the Social Sciences (SPSS) version 22.0 (IBM Corp., Armonk, NY).

RESULTS

In our study, the maximum prevalence of diabetes was seen in males (55.5%) than females (44.5%), and the mean age of our study population was 53.3 ± 16.4 years. In our study, participants from rural areas made up the majority (59%) compared to those from urban areas (41%), and the majority of participants had a high school education. Among 211 diabetics, about 84%, 79%, and 41% of the patients knew about diabetes, symptoms of diabetes, and complication of diabetes. Only 18% of the patients were aware of the symptoms of hypoglycemia, and 38% of the patients possess their own glucometers and monitor their blood sugar levels on a regular basis. Merely 38% of the diabetics were aware of the various DM treatment choices. About 52% of patients had some awareness of insulin therapy. Out of 211 patients, about half skipped their antidiabetic prescriptions, and of those, 22% took a double dose the next day. A total of 121 patients (57%) combined the use of alternative and allopathic medications, and among these, 22% of patients had replaced the allopathic with alternative medicines. Almost 53% of patients had a positive family history of diabetes; 54% of patients believe that obesity is unrelated to diabetes, and 79% of diabetics are aware of the lifestyle changes that must be done for diabetes. Almost 67% of the patients believed that diabetes could be permanently treated, and 84% of patients believed that eating too much sugar caused their diabetes.

CONCLUSION

In our study, a significant number of patients suffering from diabetes had less knowledge and awareness about it. The prevalence of myths about the onset of diabetes was noticeably higher among diabetic patients. It was observed that a greater number of patients were shifting to alternative medications instead of allopathic ones, and in the long run, it can lead to various complications. Therefore, there is an immediate need to promote awareness about diabetes among the general population.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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%).

CONCLUSION

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.

Determinants of poor glycemic control among type 2 diabetes mellitus patients at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia: Unmatched case-control study

BACKGROUND

Poor glycemic control is one of the most determinant factors for type 2 diabetes-related morbidity and mortality. The proportion of type 2 diabetes mellitus patients with poor glycemic control remains high. Yet evidence on factors contributing to poor glycemic control remains scarce. The aim of this study is to identify determinants of poor glycemic control among type 2 diabetes mellitus patients at a diabetes mellitus clinic in University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia Determinants of Poor Glycemic Control among Type 2 Diabetes mellitus Patients at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia: Unmatched Case-Control Study.

METHODS

A hospital-based case-control study was conducted from June to September 2020. Using convenience sampling techniques, a total of 90 cases and 90 controls with type 2 diabetes were recruited. The data were entered into Epidata version 4.6.0.2 and analyzed by Stata version 14. A multivariable logistic regression analysis was performed to assess the association between independent variables and glycemic control. Both 95% CI and p-value<0.05 were used to determine the level and significance, respectively.

RESULTS

The mean age ( ± standard deviations) for the cases and controls were 57.55± 10.42 and 61.03± 8.93% respectively. The determinants of poor glycemic control were age (Adjusted odd ratio (AOR)= 0.08; 95% CI= 0.02-0.33), inadequate physical exercise (AOR = 5.05; 95% CI = 1.99-11.98), presence of comorbidities (AOR = 5.50; 95% CI = 2.06-14.66), non-adherence to anti-diabetes medications (AOR= 2.76; 95% CI= 1.19-6.40), persistent proteinuria (AOR=4.95; 95% CI=1.83-13.36) and high-density lipoprotein less than 40 mg/dl (AOR=3.08; 95% CI= 1.30-7.31).

CONCLUSIONS

Age less than 65 years, inadequate physical exercise, presence of comorbidities, non-adherence to anti-diabetes medications, persistent proteinuria, and high-density lipoprotein less than 40 mg/dl were the determinants of poor glycemic control. Therefore, targeted educational and behavioral modification programs on adequate exercise and medication adherence should be routinely practiced. Furthermore, early guideline-based screening and treatment of comorbidities and complications is required to effectively manage diabetes mellitus.

Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis

The primary method for preventing health and health-related problems in diabetic people is glycemic control. Numerous studies have documented the importance of glycemic control and the factors that influence it. However, the results are dispersed. This study sought to identify the prevalence of poor glycemic control and associated factors in Ethiopia. Findings will be crucial to reduce the burden of poor glycemic control. Comprehensive search was performed from databases: PubMed, Global Health, CINAHL, IRIS, and FSTA. Gray literature sources were also explored. This document was prepared based on the PRISMA flowchart. The protocol is registered in PROSPERO (ID: CRD42022296583). STATA software was used for data analyses and I2 test with Cochrane Q statistics, and forest plot were used to verify heterogeneity. When the I2 value was higher than 50% and the p-value was 0.05, heterogeneity was deemed significant. To confirm publication bias, a funnel plot with an Egger's regression test was performed. The factors related to poor glycemic control were reported using pooled odds ratios (POR) and a 95% confidence interval. In this study, 46 papers totaling 15 457 people were used to calculate the pooled estimates. It was determined that 32.6% (95% CI: 28.3, 36.9) and 61.92% (95% CI: 57.92, 65.92) of the subjects, respectively, had good and poor glycemic control. Being male protected against poor glycemic control, while poor diet adherence, lack of exercise, poor adherence to anti-diabetic medications, and smoking increased the likelihood of poor glycemic control. Lack of formal education, no family history of diabetes, lack of glucometer for blood glucose monitoring, comorbidity, being overweight and prolonged length of stay with diabetes all contributed to poor glycemic control. Ethiopia had a fairly high rate of poor glycemic control. The main determinants are lifestyle factors. Therefore, it is important to focus on behavioral interventions.

Sex Differences in the Effects of CDKAL1 Variants on Glycemic Control in Diabetic Patients: Findings from the Korean Genome and Epidemiology Study

BACKGROUND

Using long-term data from the Korean Genome and Epidemiology Study, we defined poor glycemic control and investigated possible risk factors, including variants related to type 2 diabetes mellitus (T2DM). In addition, we evaluated interaction effects among risk factors for poor glycemic control.

METHODS

Among 436 subjects with newly diagnosed diabetes, poor glycemic control was defined based on glycosylated hemoglobin trajectory patterns by group-based trajectory modeling. For the variants related to T2DM, genetic risk scores (GRSs) were calculated and divided into quartiles. Risk factors for poor glycemic control were assessed using a logistic regression model.

RESULTS

Of the subjects, 43% were in the poor-glycemic-control group. Body mass index (BMI) and triglyceride (TG) were associated with poor glycemic control. The risk for poor glycemic control increased by 11.0% per 1 kg/m2 increase in BMI and by 3.0% per 10 mg/dL increase in TG. The risk for GRS with poor glycemic control was sex-dependent (Pinteraction=0.07), and a relationship by GRS quartiles was found in females but not in males. Moreover, the interaction effect was found to be significant on both additive and multiplicative scales. The interaction effect was evident in the variants of cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like (CDKAL1).

CONCLUSION

Females with risk alleles of variants in CDKAL1 associated with T2DM had a higher risk for poor glycemic control than males.

A Comparative analysis of type 2 diabetes management quality indicators in cancer survivors

Objective

This study aimed to assess indicators of type 2 diabetes mellitus (DM) management, including adequate DM control, and treatment rates, in cancer survivors according to the time of DM diagnosis and to compare them with the DM management indicators of a non-cancer control group.

Methods

We used the 2013-2019 data of the Korea National Health and Nutrition Examination Survey for this study. To compare their adequate DM control, and treatment rates, we identified 4918 patients with type 2 DM aged ≥ 30 years and classified them into pre-existing diabetes, pre-existing cancer, and diabetes without cancer groups. Predictors of adequate glycemic control and diabetes treatment were analyzed using binary logistic regression.

Results

Diabetes without cancer group had higher fasting blood glucose and glycosylated hemoglobin A1c levels and lower adequate glycemic control than did the other two groups. The preexisting cancer group had low treatment rates. After adjusting for age, gender, employment status, and duration of diabetes, the preexisting cancer group had 0.51-fold lower odds of receiving treatment, such as insulin injection or oral diabetes medications, than the other two groups (adjusted odds ratio, 0.50; 95% confidence interval, 0.38-0.66).

Conclusions

Cancer survivors had lower fasting glucose and HbA1c than those with diabetes without cancer. However, as a result of the sub-analysis, the treatment rate of the pre-existing cancer group was significantly lower than that of diabetes without cancer. Based on these results, cancer survivors' care-related healthcare workers should be aware of the need for monitoring blood sugar even in cancer survivors without underlying diabetes mellitus and pay more attention to early detection and active treatment of diabetes.

Analysis of the Association between Metabolic Syndrome and Renal Function in Middle-Aged Patients with Diabetes

This study investigated the effects of metabolic syndrome on the estimated glomerular filtration rate in middle-aged participants with diabetes to provide basic data to enable the development of education programs for middle-aged people to prevent diabetic kidney disease. This cross-sectional descriptive study analyzed data obtained in the 2nd year of the 8th Korea National Health and Nutrition Examination Survey in 2020 and enrolled 279 participants aged 40-65 years who were diagnosed with diabetes. Multilevel stratified cluster sampling was used to improve the representativeness of the samples and the accuracy of parameter estimation. The risk factors of metabolic syndrome and the risk of elevated eGFR were analyzed using regression analysis and the correlation between the variables was determined using Pearson's correlation analysis. Middle-aged participants with diabetes whose eGFR was <90 showed a significant difference in their risk for metabolic syndrome based on sex, age, disease duration, and total cholesterol concentrations. Systolic blood pressure and waist circumference in men, and waist circumference and HDL cholesterol level in women were identified as risk factors that contribute to the increasing prevalence of metabolic syndrome.

Association between depression and HbA1c levels in the elderly population with type 2 diabetes mellitus during COVID-19 pandemic

Diabetes mellitus is a chronic progressive disease affecting the metabolic hormonal system and its prevalence in the elderly population is high. Depression is one of the psychiatric disorders in diabetic patients in particular during the coronavirus disease 2019 (COVID-19) pandemic. People with depression are more susceptible to leading an unhealthy lifestyle; therefore, depression and diabetes have a negative influence on life quality and aggravate complications and symptoms. The aim of this study was to determine the association between depression and hemoglobin A1c (HbA1c) levels in elderly with type 2 diabetes mellitus patients. A cross-sectional study was conducted where a total of 42 diabetic patients from the Puskesmas Belakang Padang, Batam of Indonesia was recruited. The HbA1c level, the main determinant of optimum glycemic control, was measured using ion-exchange high-performance liquid chromatography while the level of depression was assessed using Geriatric Depression Scale-15 (GDS-15). The association between depression and HbA1c levels was analyzed using the chi-squared test. Our study found that that 69% of the elderly with diabetes experienced a depression, classified as mild (40.5%), moderate (21.4%) and severe (7.1%). There were 61.9% of the subjects had poor HbA1c control. Our data suggested that the depression level was associated with HbA1c (p = 0.002). In conclusion, there is a significant association between depression and HbA1c levels in the elderly with type 2 diabetes mellitus.

Alternate day add on therapy with dapagliflozin in patients with type 2 diabetes mellitus: potential benefits and concerns

INTRODUCTION

Factors like compliance, cost and safety play a major role in achieving the long-term goal in the management of type 2 diabetes mellitus (T2DM). Dapagliflozin carries great potential of becoming an alternate day therapy because of its favorable pharmacokinetic profile and other properties.

AREAS COVERED

In this review, we have discussed and hypothesized the potential of dapagliflozin as an alternate day add-on drug in T2DM patients. We have discussed the properties by virtue of which it carries a potential to become an alternate day therapy. We have also explained the potential benefits and concerns of using this approach.

EXPERT OPINION

Alternate day add-on therapy with dapagliflozin could be a promising approach in reducing the cost, improving the treatment satisfaction and reducing the adverse effects. It may be a cost-effective option for T2DM patients and demands an in-depth investigation among T2DM subjects who are not able to achieve glycemic control with initial therapy with standard monotherapy or combination therapy. Pilot studies or some small-scale investigator initiated trial or academic clinical trials may be carried out to explore this concept. At the same time large industry sponsored multicenter RCTs including pharmacoeconomic analyses may be planned to have a more detailed investigation.

Visual impairment and its predictors among people living with type 2 diabetes mellitus at Dessie town hospitals, Northeast Ethiopia: institution-based cross-sectional study

BACKGROUND

Visual impairment is a functional limitation of the eye(s) that results in reduced visual acuity, visual field loss, visual distortion, perceptual difficulties, or any combination of the above. Type 2 diabetes mellitus is one of the common causes of visual impairment. Since there is no study conducted in Ethiopia so far in this regard, the current study aimed to determine the prevalence and predictors of visual impairment among people living with diabetes at Dessie town Hospitals, Northeast Ethiopia.

METHODS

Institution based cross-sectional study was carried out from 15 February to 15 March 2020 using simple random sampling to recruit study participants among type 2 diabetes. Visual impairment was measured using visual acuity test. We used Epi Data 3.1 and SPSS version 22 for data entry and statistical analysis, respectively. Bi-variable binary logistic regression was performed to check independent association of each factor with visual impairment. After selecting candidate variables at p < 0.25, we computed multivariable binary logistic regression to identify statistically associated factors of visual impairment. The degree of association was determined using adjusted odds ratio with 95%CI. In the final model, statistical significance was declared at p < 0.05.

RESULTS

Three hundred and twenty-two people living with T2DM participated in this study with 97% response rate. The prevalence of visual impairment was 37.58% (95% CI: 32.3, 42.9). Age (AOR: 1.06, 95% CI: 1.02, 1.09, p < or = 0.001), poor regular exercise (AOR = 2.91, 95%CI: 1.47-5.76, p < or = 0.001), duration of DM above 5 years (AOR = 2.42, 95% CI: 1.25-4.73, p < or = 0.01), insulin treatment (AOR = 14.05, 95% CI: 2.72, 72.35, p < or = 0.01), and poor glycemic control (AOR = 2.17, 95% CI: 1.13-4.14, p < 0.05) were statistically associated with visual impairment.

CONCLUSION

The prevalence of visual impairment in Dessie town hospitals accounted for more than a third of patients living with T2DM. Visual impairment is associated with increased age, poor regular exercise, longer duration of DM, and insulin treatment. Thus, early detection of VI through screening and regular follow-up is recommended to reduce the risk of VI and vision loss.

Exploring of Determinants Factors of Anti-Diabetic Medication Adherence in Several Regions of Asia - A Systematic Review

BACKGROUND

The determinants of medication adherence in people with diabetes may differ between populations of an area due to social environment, cultural beliefs, socioeconomic conditions, education, and many other factors differences.

OBJECTIVE

Therefore, this study aims to explore, identify and classify the determinants of medication adherence in several Asian regions.

METHODS

A systematic literature review was conducted to gain insight into the determinants of medication adherence. Seven relevant databases (EBSCO, ProQuest, PubMed, ScienceDirect, Scopus, Wiley, dan Taylor and Francis) and hand searching methods were conducted from January 2011 to December 2020. Keywords were compiled based on the PICO method. The selection process used the PRISMA guidelines based on inclusion, and the quality was assessed using Crowe's critical assessment tool. Textual summaries and a conceptual framework model of medication adherence were proposed to aid in the understanding of the factors influencing medication adherence.

RESULTS

Twenty-six articles from countries in several Asian regions were further analyzed. Most studies on type 2 diabetes patients in India used the MMAS-8 scale, and cross-sectional study is the most frequently used research design. The medication adherence rate among diabetic patients was low to moderate. Fifty-one specific factors identified were further categorized into twenty-three subdomains and six domains. Furthermore, the determinants were classified into four categories: inconsistent factors, positively related factors, negatively related factors, and non-associated factors. In most studies, patient-related factors dominate the association with medication adherence. This domain relates to patient-specific demographics, physiological feelings, knowledge, perceptions and beliefs, comorbidities, and other factors related to the patient. Several limitations in this review need to be considered for further research.

CONCLUSION

Medication adherence to diabetic therapy is a complex phenomenon. Most determinants produced disparate findings in terms of statistical significance. The identified factors can serve various goals related to medication adherence. Policymakers and health care providers should consider patient-related factors.

Prevalence and predictors of suboptimal glycemic control among patients with type 2 diabetes mellitus in northern Thailand: A hospital-based cross-sectional control study

Background

Suboptimal glycemic control among patients with type 2 diabetes mellitus (DM) is a significant public health problem, particularly among people living with poor education and economic statuses, including those with a unique dietary culture. This study aimed to estimate the prevalence and identify the factors associated with suboptimal glycemic control among patients with type 2 DM during the coronavirus disease-2019 (COVID-19) pandemic.

Methods

A hospital-based cross-sectional study was used to elicit information from DM patients attending six hospitals located in Chiang Rai Province, northern Thailand, between February and May 2021. A validated questionnaire and 5 mL blood specimens were used as the research tools. Glycated hemoglobin (HbA1c) greater than 7.0% among DM patients at least two years after diagnosis was defined as suboptimal glycemic control. Chi-square tests and logistic regression were used to identify the associations between variables at the significance level α = 0.05.

Results

A total of 967 patients were recruited for this study; 54.8% 530 had suboptimal glycemic control, 58.8% were female, 66.5% were aged 50-69 years, and 78.5% were married (78.5%). Six variables were found to be associated with suboptimal glycemic control in multivariable logistic regression. Participants aged <49, 50-59, and 60-69 years had 3.32 times (95% CI = 1.99-5.53), 2.61 times (95% CI = 1.67-4.08), and 1.93 times (95% CI = 1.26-2.95) greater odds of having suboptimal glycemic control, respectively, than those aged ≥70 years. Married individuals had 1.64 times (95% CI = 1.11-2.41) greater odds of having suboptimal glycemic control than those ever married. Participants who consumed sticky rice had 1.61 times (95% CI = 1.19-2.61) greater odds of having suboptimal glycemic control than those who did not consume sticky rice in daily life. Participants who had been diagnosed with DM for 11-20 years and ≥21 years had 1.98 times (95% CI = 1.37-2.86) and 2.46 times (1.50-4.04) greater odds of having suboptimal glycemic control, respectively, than those who had been diagnosed ≤ 10 years. Participants who had experienced forgetting to take their medication had 2.10 times (95% CI = 1.43-3.09) greater odds of having suboptimal glycemic control than those who did not, and those who had their medical expenses covered by the national scheme had 2.67 times (95% CI = 1.00-7.08) greater odds of suboptimal glycemic control than those who self-paid.

Conclusion

Effective health interventions to control blood glucose among DM patients during ongoing treatment are urgently required. The interventions should focus on patients aged less than 69 years, marital status, forgetting to take their medication, and a longer time since diagnosis, including reducing their sticky rice consumption. The effects of copayments should also be considered.

Relations of Well-Being, Coping Styles, Perception of Self-Influence on the Diabetes Course and Sociodemographic Characteristics with HbA1c and BMI Among People with Advanced Type 2 Diabetes Mellitus

PURPOSE

Assessment of the relationship between psychological and sociodemographic factors with the levels of glycated hemoglobin (HbA1c) and Body Mass Index (BMI) among people with advanced type 2 diabetes mellitus (T2DM).

PATIENTS AND METHODS

A total of 2574 persons, among them 1381 (53.7%) women, with type 2 diabetes, during the period of switching from biphasic mixtures of human insulin to insulin analogues. The age of participants ranged from 22 to 94 years (M = 63.5; SD = 9.58), and their treatment period was in the time frame from 2 years to 43 years (M = 10.2; SD = 6.1). Participants filled out a Scale for Perception of Self-Influence on the Diabetes Course, Well-Being Index WHO-5, two questions from the Brief Method of Evaluating Coping with a Disease.

RESULTS

Statistically significant correlations were found between the HbA1c levels and (1) disease duration (r_s=0.067; p < 0.001); (2) number of complications (r_s = 0.191, p < 0.001) (3) the perception of self-influence on the diabetes course (r_s=- 0.16; p < 0.001); (4) well-being (risk of depression) (r_s=- 0.10; p < 0.001). The regression analysis showed that 7% of HbA1c variability is explained by age, a perception of self-influence on the diabetes course, the number of complications, place of residence, education, BMI. The most important findings concerning BMI were found in regression analysis, which indicated a week relationship between BMI and a number of complications, perception of self-influence on the diabetes course and coping styles (3% of the resultes' variability). The group at high risk of depression had the highest levels of HbA1c.

CONCLUSION

Sociodemographic and psychological factors show weak but statistically significant relationships with the current levels of HbA1c and BMI.

Persistent Cardiometabolic Health Gaps: Can Therapeutic Care Gaps Be Precisely Identified from Electronic Health Records

The objective of this study was to determine the strengths and limitations of using structured electronic health records (EHR) to identify and manage cardiometabolic (CM) health gaps. We used medication adherence measures derived from dispense data to attribute related therapeutic care gaps (i.e., no action to close health gaps) to patient- (i.e., failure to retrieve medication or low adherence) or clinician-related (i.e., failure to initiate/titrate medication) behavior. We illustrated how such data can be used to manage health and care gaps for blood pressure (BP), low-density lipoprotein cholesterol (LDL-C), and HbA1c for 240,582 Sutter Health primary care patients. Prevalence of health gaps was 44% for patients with hypertension, 33% with hyperlipidemia, and 57% with diabetes. Failure to retrieve medication was common; this patient-related care gap was highly associated with health gaps (odds ratios (OR): 1.23-1.76). Clinician-related therapeutic care gaps were common (16% for hypertension, and 40% and 27% for hyperlipidemia and diabetes, respectively), and strongly related to health gaps for hyperlipidemia (OR = 5.8; 95% CI: 5.6-6.0) and diabetes (OR = 5.7; 95% CI: 5.4-6.0). Additionally, a substantial minority of care gaps (9% to 21%) were uncertain, meaning we lacked evidence to attribute the gap to either patients or clinicians, hindering efforts to close the gaps.

Effect of educational interventions on knowledge of the disease and glycaemic control in patients with type 2 diabetes mellitus: a systematic review and meta-analysis of randomised controlled trials

BACKGROUND

Globally, type 2 diabetes has continued to increase, now accounting for over 90% of all diabetes cases. Though the magnitude of uncontrolled glycaemic levels in patients with type 2 diabetes is steadily rising, evidence showed that effectively controlled glycaemic levels can prevent complications and improve the quality of life of these patients. As little is known about the effect of educational interventions on this population, this systematic review and meta-analysis evaluated the effectiveness of educational interventions versus standard care on glycaemic control and disease knowledge among patients with type 2 diabetes.

METHODS

PubMed, Google Scholar, Cochrane Library, Scopus, African Journals Online and Wiley Online Library were searched. Two authors independently assessed within-trial risk of bias in each included study using revised Cochrane risk-of-bias tool for randomised trials. A random-effects model was employed to estimate combined effect sizes. Subgroup analyses were employed to investigate possible sources of heterogeneity between studies. The overall certainty of the evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation approach.

RESULTS

A total of 19 trials with 2708 study participants were included in the review. Primary outcomes (glycaemic control) were reported in 18 trials. The pooled estimated impact of educational intervention on glycaemic levels using the random-effects model was -0.83 (95% CI: -1.17 to -0.49, p<0.001). Subgroup analyses revealed greater A1c reductions in those studies with intervention duration of up to 3 months and with empirical intervention designs. Educational interventions led to significant increases in participants' knowledge of type 2 diabetes (standardised mean difference: 1.16; 95% CI: 0.71 to 1.60; I2=93%).

CONCLUSION

In the current review overall, educational interventions can potentially lead to improved glycaemic control levels in patients with type 2 diabetes despite heterogeneity across the studies. Besides, the findings showed that educational interventions could increase disease knowledge among patients with type 2 diabetes.

PROSPERO REGISTRATION NUMBER

CRD42020205838.

Factors impacting on diabetes knowledge, medication adherence and glycemic control among adult diabetics visiting a county teaching and referral hospital in Kenya: a cross-sectional study

Introduction

optimal management of diabetes involves interplay between patients’ understanding of their disease and medication adherence, which would eventually influence glycemic control. However, there is scant published literature on the interconnection of patient related factors that impact on optimal management of diabetes in resource-limited settings such as Kenya.

Methods

a hospital based cross-sectional survey involving 270 freely consenting adult diabetics investigated the interconnection between diabetes knowledge, medication adherence and glycemic control. Data on the patient´s knowledge and medication adherence was collected using validated tools whilst glycemic control was evaluated using the patients' glycated haemoglobin values. Data analysis was carried out using STATA version 13 statistical software, employing the chi square test for association and simple linear regression for prediction, with p ≤0.05 considered significant.

Results

participants´ level of knowledge on diabetes was significantly associated with the academic achievement (p=0.001), while their medication adherence was significantly associated with family support (p=0.001) and duration of disease since diagnosis (p=0.019). On linear regression, family support occasioned by the nature of participants’ household setup, had a strong positive correlation [r=0.99 (CI 0.60-1.00)] with optimal glycemic control.

Conclusion

family support is an important determinant of medication adherence and optimal glycemic control among diabetic patients. Clinicians should team up with family members of diabetic patients for optimal glycemic control.

Association of glycemic control and anthropometric measurement among type 2 diabetes mellitus: a cross-sectional study

Introduction

Maintaining good glycemic control is the main therapeutic target for diabetes mellitus (DM) patients. Nevertheless, due to complex factors, the majority of patients worldwide persist poorly controlled. Hence the study was conducted to determine the association of anthropometric measurement and other factors with glycemic control among type 2 DM patients.

Methods

An institutional-based cross-sectional study was conducted among 366 type 2 DM patients from October-1 to November 30/2019. Data were collected by a pre-tested structured questionnaire and data abstraction format. The collected data were edited in Epi-data-4.4.1.0 and exported to SPSS-25 for analysis. The degree of association was assessed using logistic regression analysis and expressed in terms of p value and odds ratio with a 95%CI. p value < 0.05 was considered statistically significant.

Results

Of the total 366 participants, (66.1%) had poor glycemic control. Increased waist circumference (AOR 2.37, 95% CI 1.28-4.40 for overweight and AOR 3.31, 95% CI 1.28-8.58 for obesity), long duration of DM (AOR 2.12, 95% CI 1.14-3.95 for 5-10 years and AOR 5.67, 95% CI 1.76-11.30 for > 10 years), occupation (AOR 3.74, 95% CI 1.94-7.23 for government employee and AOR 4.90, 95% CI 2.19-10.94 for private employee), and family history of DM (AOR 1.93, 95% CI 1.08-3.43), were significantly associated with poor glycemic control.

Conclusion

Nearly two-thirds of study participants had poor glycemic control. Increased waist circumference, long duration of DM, occupational status, and family history of DM were independently associated with poor glycemic control. Therefore, type 2 DM patients with these identified factors should be strictly monitored to maintain good glycemic control.

Probucol Pharmacological and Bio-Nanotechnological Effects on Surgically Transplanted Graft Due to Powerful Anti-Inflammatory, Anti-Fibrotic and Potential Bile Acid Modulatory Actions

INTRODUCTION

A major obstacle in islet transplantation and graft survival pre and post transplantation is islet apoptosis due to mainly inflammatory bio molecules released during islet harvesting and post graft transplantation and hence, subsequent graft fibrosis and failure. This study aimed to investigate if incorporation of the anti-inflammatory anti-hyperlipidaemic drug probucol (PB) would improve islet-graft survival and function, post transplantation in Type 1 diabetes (T1D).

METHODS

T1D was induced in mice, and biological profiles of the diabetic mice transplanted PB-microencapsulated islets harvested from healthy syngeneic mice were measured.

RESULTS AND CONCLUSION

Compared with sham (no PB), the treated group showed significant reduction in serum levels of interleukin-1β, interleukin-6, interleukin-12, interleukin-17, and tumour necrosis factor-α, accompanied by a 3-fold increase in survival duration, which suggests PB islet-protective effects, post transplantation.

Oral health and longitudinal changes in fasting glucose levels: A nationwide cohort study

We investigated the association between oral hygiene indicators of periodontitis, tooth loss, and tooth brushing on the longitudinal fasting glucose level in non-diabetic subjects. Using a nationwide health screening database in Korea, we included non-diabetic individuals who received a health screening program with oral health check in 2009-2010. We constructed a linear mixed model for the longitudinal data of fasting glucose from the baseline to 2015. During the 4.84-year of median follow-up, 91,963 individuals (mean age 56.2 at baseline) underwent 392,780 health examinations with fasting glucose level (mmol/L). The presence of periodontitis was 39.3%. In the multivariate linear mixed analysis, periodontitis was related with increased fasting glucose levels (β = 0.0084, standard error = 0.0035, p = 0.018). Similarly, tooth loss was associated with increased level of fasting glucose (β = 0.0246, standard error = 0.0038, p < 0.001). Compared with tooth brushing ≤2 times/day, tooth brushing ≥3 times/day was associated with decreased fasting glucose levels (β = -0.0207, standard error = 0.0033, p < 0.001). Our data showed that periodontitis and tooth loss were associated with increased fasting glucose levels in non-diabetic individuals. The study findings imply that frequent tooth brushing may reduce fasting glucose levels. Further research is needed to determine the effect of periodontal intervention on glycemic control.

Factors Associated with Glycaemic Control among Diabetic Patients Managed at an Urban Hospital in Hanoi, Vietnam

Type 2 diabetes (T2DM) epidemic is rising in Vietnam. Identifying associated factors with glycaemic control in patients with T2DM is vital to improve treatment outcomes. This study is aimed at examining the uncontrolled glycaemic level of patients with type 2 diabetes (T2DM) at an urban hospital in Hanoi, Vietnam, and determining associated factors. An observational longitudinal cohort survey was performed among T2DM patients. Glycaemic control was evaluated by using the HbA1c level ≥ 6.5% or fasting blood glucose level ≥ 7.5 g/mmol. Information about sociodemographic, clinical, and behavioral characteristics was collected. Multivariate mixed-effects logistic regression was employed to identify associated factors with control glycaemic level conditions. Among 189 T2DM patients, 70.4% had an uncontrolled glycaemic level. A higher number of comorbidities were associated with a lower likelihood of having uncontrolled glycaemic levels (OR = 0.71, p < 0.001, 95%CI = 0.52 − 0.98). Meanwhile, a higher body mass index (OR = 1.15, p < 0.05, 95%CI = 1.02 − 1.29), higher initial HbA1C (OR = 3.75, p < 0.01, 95%CI = 2.59 − 5.44), and higher initial fasting blood glucose levels (OR = 1.57, p < 0.01, 95%CI = 1.29 − 1.90) were positively associated with a higher risk of uncontrolled glycaemic levels. This study reveals that poor glycaemic control was common among T2DM patients in the urban hospital in Vietnam. Findings underlined the need for appropriate management strategies to control glycaemic levels and weight in this population.

Glycemic Control of Diabetes Mellitus Patients in Referral Hospitals of Amhara Region, Ethiopia: A Cross-Sectional Study

Background

Glycemic control is the level of glucose in diabetes patient. Evidence regarding glycemic control is scarce in resource-limited settings, and this study was conducted to generate information regarding the prevalence and predictors of glycemic control among diabetes mellitus patients attending their care from the referral hospitals of the Amhara region, Ethiopia.

Methods

A cross-sectional study design was implemented. A simple random sampling technique was used. Data were collected from March 2018 to January 2020. The data were collected using interviews, chart review, and blood samples. Hemoglobin A1c was measured using high-performance liquid chromatography. Data were entered into Epi-info software and analyzed by SPSS software. Descriptive statistics were used to estimate the prevalence of glycemic control; linear regression was used to identify the predictors of HbA1c.

Results

A total of 2554 diabetes patients were included giving for the response rate of 95.83%. The mean age of the study participants was 54.08 years [SD (standard deviation) ± 8.38 years]. The mean HbA1c of the study participants was 7.31% [SD ± 0.94%]. Glycemic control was poor in 55.32% [95% CI: 53.4%-57.25%] of diabetes patients. The glycemic control of diabetes patients was determined by BMI (β 0.1; [95% CI: 0.09-0.1]), type 2 diabetes (β -0.14; [95% CI: -0.11-0.16]), age (β 0.22; [95% CI: 0.02-0.024]), duration of the disease (β 0.04; [95% CI: 0.037-0.042]), the presence of hypertension (β 0.12; [95% CI:0.09-0.16]), regular physical exercise (β -0.06; [95% CI: -0.03-0.09]), medication adherence (β -0.16; [95% CI: -0.14-0.18]), and male (β 0.34; [95% CI: 0.31-.037]).

Conclusion

The glycemic control of diabetes patients was poor, and it needs the attention of decision-makers.

Electronic medical records-based comparison of glycemic control efficacy between sulfonylureas and dipeptidyl peptidase-4 inhibitors added on to metformin monotherapy in patients with type 2 diabetes

Sulfonylurea (SU) and dipeptidyl peptidase-4 (DPP-4) inhibitors are most common secondary agents that are added to metformin monotherapy. Real-world studies have become increasingly important in providing evidence of treatment effectiveness in clinical practice and real-world data could help appropriate therapeutic information. Therefore, this study aims to compare the glycemic effectiveness of SU and DPP-4 inhibitors, which are added to metformin monotherapy in real clinical practice using electronic medical record (EMR) data. EMR data of type 2 diabetes patients treated at Seoul National University Hospital from December 2002 to December 2012 were retrieved and analyzed. The patients were divided into three groups: patients who maintained metformin monotherapy (M), and patients who added SU (MS) or DPP-4 inhibitors (MD) to metformin monotherapy. The mean change in HbA1c level, the proportion of patients achieving the HbA1c target < 7.0%, proportion of patients with treatment failure, and probability of treatment failure occurrence and changes in prescription were evaluated to compare glycemic control efficacy between SU and DPP-4 inhibitors. The MS showed significantly greater reduction in the Hb1Ac level than MD. The proportion of patients achieving HbA1c < 7.0% is higher in MD, whereas the proportion of patients with treatment failure was greater in MS. The probability of the treatment failure and probability of changes in the prescription were lower in MD than MS with hazard ratio of 0.499 and 0.579, respectively. In conclusion, this real-world study suggested that DPP-4 inhibitors are expected to show more durable glycemic control efficacy than SU in long-term use.

Poor Glycemic Control and Its Contributing Factors Among Type 2 Diabetes Patients at Adama Hospital Medical College in East Ethiopia

BACKGROUND

Poor glycemic control is a major public health issue among patients with type 2 diabetes mellitus and a significant risk factor for the progression of diabetic complications. This study aimed to assess the magnitude and contributing factors of poor glycemic control among type 2 diabetes patients on follow-up at Adama Hospital Medical College (AHMC) in East Ethiopia.

METHODS

A cross-sectional study was conducted among 245 type 2 diabetes patients on follow-up at AHMC from March 1 to 30, 2020. All type 2 diabetes patients on follow-up at AHMC and fulfilling the inclusion criteria were included in the study. The data were collected through face-to-face interviews using structured questionnaires and reviewing the patient chart. The data were entered and analyzed using SPSS version 21. The level of significance was declared at a p-value of <0.05.

RESULTS

Of the 245 type 2 diabetes patients included in the study, 157 (64.1%) had poor glycemic control. The factors associated with poor glycemic control were being male (AOR = 2.28, 95% CI [1.24-4.21]), not attending formal education (AOR = 3.12, 95% CI [1.53-6.35]), monthly income of <136 USD (AOR = 2.14, 95% CI [1.17-3.91]), overweight (AOR = 2.60, 95% CI [1.32-5.10]) and obesity (AOR = 3.44, 95% CI [1.44-8.21]), and chewing khat (AOR = 2.77, 95% CI [1.04-7.33]).

CONCLUSION

The proportion of poor glycemic control among type 2 diabetes patients at AHMC was remarkably high. Therefore, more effort should be taken to strengthening and disseminating health education programs for diabetes patients at each follow-up visit on the importance of achieving optimal body weight, avoiding khat chewing, and maintaining regular physical exercise to prevent and mitigate the complications resulting from poor glycemic control.

Predictors of Poor Plasma Glucose Maintenance in Type II Diabetic People with Ophthalmic Complication: The Case of Dessie Hospitals in Ethiopia

BACKGROUND

Diabetes mellitus, the commonest metabolic disorder, leads to cardiovascular diseases, neurological problems, kidney injury, and visual disturbances. Such complications can be prevented by maintaining plasma glucose level in the normal range, including ophthalmic complications. Hence, this study intended to pinpoint predictors of poor plasma glucose maintenance in type II DM people with ophthalmic complication.

METHODS

We conducted a cross-sectional survey using simple random sampling approach to recruit participants. An interviewer-based questionnaire was used and ophthalmic complication was determined by visual acuity test. We used statistical package for social sciences version 23 to analyze the data and descriptive statistics were calculated. Predictors were ascertained using multivariable logistic regression at p≤0.05. Besides, AOR with 95% CI was also estimated to show extent of association.

RESULTS

The prevalence of poor plasma glucose maintenance was 65.1% (56.6-73.6). Poor plasma maintenance was predicted by the absence of formal education (OR: 0.67; 0.20-2.23), DM history of family members (OR=4.29; 1.33-13.83), longer duration of diabetes (OR: 3.02; 1.09-8.63), insulin use (OR=10.05; 2.72-52.35), and less physical exercise (OR=2.91; 1.47-5.76).

CONCLUSION

Study subjects with no education, DM history of family members, prolonged DM, insulin medication, and inadequate exercise had higher rate of poor plasma glucose maintenance. Health professionals should educate patients on the importance of self-adherence to plasma glucose monitoring, and encourage them to practice recommended physical activity.

Impact of Pharmacist-led Educational Intervention on Predictors of Diabetic Foot at Two Different Hospitals of Malaysia

Objective:

Diabetes mellitus (DM) is a chronic metabolic disorder that can initiate organ damage inside the body if not treated appropriately. Apart from tight glycemic control, a suitable educational intervention is also needed from health-care providers to stop or decrease the progression of organ damage in diabetic patients. This study intended to measure the impact of pharmacist-led educational intervention on improvement in predictors of diabetic foot in two different hospitals in Malaysia.

Materials and Methods:

In two tertiary care selected hospitals, the included diabetic patients were randomly divided into two study arms. In the control group, 200 patients who were receiving usual treatment from hospitals were included. However, in the intervention group, those 200 patients who were receiving usual treatment along with counseling sessions from pharmacists under the Diabetes Medication Therapy Adherence Clinic (DMTAC) program were included. The study continued for 1 year, and there were four follow-up visits for both study arms. A prevalidated data collection form was used to measure the improvement in predictors of diabetic foot in included patients. Data were analyzed by using the Statistical Package for the Social Sciences (SPSS) software program, version 24.0.

Results:

With the average decrease of 1.97% of HbA1c values in the control group and 3.43% in the intervention group, the univariate and multivariate analysis showed a statistically significant difference between both of the study arms in the improvement of predictors belonging to the diabetic foot (P < 0.05). The proportion of patients without any signs and symptoms of the diabetic foot in the intervention group was 91.7%, which increased from 42.3% at baseline (P < 0.05). However, this proportion in the control group was 76.9% at the fourth follow-up, from 48.3% at baseline (P < 0.05).

Conclusion:

A statistically significant reduction in the signs and symptoms of diabetic foot was observed in the intervention group at the end of 1 year. The progression of diabetic foot was significantly decreased in the pharmacist intervention group.