Evaluation of Glycemic Control, Lifestyle and Clinical Characteristics in Patients with Type 2 Diabetes Treated at King Abdullah University Hospital in Jordan

The Influence of OCT3 and MATE2 Genetic Polymorphisms in Poor Response to Metformin in Type 2 Diabetes Mellitus

BACKGROUND

The response of patients with Type 2 diabetes mellitus (T2DM) to metformin may be a variation because of genetic differences in solute carrier (SLC) transporter proteins and other effect factors, which have an important effect on how metformin is processed in the body and its efficiency for glycaemic control.

AIM

This study was conducted to investigate the impact of certain genetic variants of the organic cation transporter genes OCT3 (SLC22A3 rs12194182 and rs8187722) and MATE2 (SLC47A2 rs12943590) and their association with glycaemic parameters in patients with T2DM who respond poorly to metformin.

PATIENTS AND METHODS

This cross-sectional study involved 150 Iraqi cases with T2DM who were prescribed a daily dose of (1000 mg/day) metformin for a minimum of 3 months. Various parameters included are as follows: demographic data, glycaemic parameters and three SNPs: rs12943590 variant of SLC47A2, rs12194182 and rs8187722 variant of SLC22A3 using the standard PCR-sequencing technique.

RESULTS

Thirty-nine patients (26.17%) were responders, whereas 111 patients (73.82%) could not respond to metformin treatment. Upon analysing the genotypes of the rs12943590 variants of SLC47A2, rs12194182 and rs8187722 SNPs of SLC22A3, the present findings revealed a nonsignificant association of genetic variations in all SNPs with metformin response. SLC47A2 (rs12943590) showed nonsignificant associations of the GG, AA and AG genotyping; SLC22A3 (rs12194182) showed nonsignificant associations of the TT, TC and CC genotyping; and SLC22A3 (rs8187722) showed nonsignificant associations of the AA, CC and AC genotyping between two groups.

CONCLUSION

Variations in genes SLC22A3 and SLC47A2 did not have a significant role in the response of patients with T2DM to metformin (1000 mg/day).

Prevalence and Pattern of Dyslipidemia and Its Associated Factors Among Patients with Type 2 Diabetes Mellitus in Jordan: A Cross-Sectional Study

Background

Dyslipidemia and type 2 diabetes mellitus (T2DM) are growing health problems, particularly in developing countries. This study aimed to determine the prevalence and pattern of dyslipidemia and its associated factors among patients with T2DM.

Methods

A cross-sectional study was conducted among patients with T2DM attending Family Medicine Clinics in Jordan between August 2017 and March 2019. The socio-demographics, clinical features, medications, and laboratory findings were collected. These laboratory findings included high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs).

Results

A total of 870 patients with T2DM were included. The prevalence of dyslipidemia among patients with T2DM was 91.4%. The most common patterns of dyslipidemia were low HDL-C (66.2%), high LDL-C (62.1%), and hypertriglyceridemia (58.2%). Female gender, obesity, and hypertension were associated with diabetic dyslipidemia patterns. T2DM duration and poor glycemic control were associated with high LDL-C and hypercholesterolemia. Hypertriglyceridemia was associated with poor glycemic control and smoking.

Conclusion

Dyslipidemia is highly prevalent among patients with T2DM. Evidence -based interventions are needed to prevent and control dyslipidemia among patients with T2DM in Jordan.

Self-care practice and glycemic Control among type 2 diabetes patients on follow up in a developing country: a prospective observational study

Purpose

The main goal of managing diabetes is to achieve glycemic control. However, the glycemic level of most diabetic patients is shown to be poorly controlled mainly due to poor adherence to self-care practices. This study aims to assess the level of self-care practice and glycemic control among type 2 diabetes patients on follow up in a resource limited country.

Methods

A four-month prospective observational study was conducted among type 2 diabetes patients from February 1 to May 30, 2021. Data was collected using a data abstraction checklist and structured questionnaire. The data was entered into Epidata version 4.4.6 and analyzed with SPSS version 26. Glycemic control and its predictors were determined using binary logistic regression. P-value less than 0.05 was considered as statistically significant.

Results

A total of 138 patients were included in the study. Nearly three-fourths (74.6%) of patients had poor glycemic control and the majority of patients had poor self-care practice. 78.3%, 98.6%, 96.4%, and 55.8% of patients had poor adherence to diet, exercise, self-monitoring of blood glucose, and medications respectively. Importantly, 85(79%), 102(75%), 99(74.4%), and 65(84.4%) patients with poor adherence to diet, physical activity, self-monitoring of blood glucose, and antidiabetic medications had poor glycemic control. On multivariate logistic regression, BMI (AOR 4.1, CI:1.20-14.11, p = 0.024) and drug adherence (AOR 3.08, CI:1.22-7.08, p = 0.017) were factors associated with poor glycemic control.

Conclusions

A higher proportion of patients had low-level of self-care practice and poor glycemic control. This highlights the need to improve patients' awareness about the importance of self-care practice to maintain good glycemic control and prevent adverse outcomes associated with the disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-022-00995-4.

Glycaemic control and its associated factors in patients with type 2 diabetes in the Middle East and North Africa: An updated systematic review and meta-analysis

Aims

To examine the patient‐related factors that have been linked to glycaemic control in people living with type 2 diabetes mellitus in Middle Eastern countries.

Design

A systematic review and meta‐analysis.

Data Sources

A computerized search was conducted using the databases MEDLINE (via PubMed and Ovid), EMBASE, Scopus and CINAHL to identify peer‐reviewed articles published in English between 1 January 2010 and 21 May 2020. On 28 June 2021, the search was updated with the same keywords and databases; however, no further relevant studies were identified.

Review Methods

Extracted data were analysed using Review Manager 5.4.

Results

The final sample consisted of 54 articles with a total of 41,079 participants. Pooled data showed an increased risk of inadequate glycaemic control in smokers [OR = 1.26, 95% confidence interval (CI): 1.05, 1.52; p = .010], obese patients (OR = 1.30, 95% CI: 1.10, 1.54; p = .002), patients with elevated waist to hip ratio (OR = 1.62, 95% CI: 1.16, 2.26; p = .004) and longer disease duration (OR = 2.01, 95% CI: 1.64, 2.48; p < .001). A lower risk of inadequate control was associated with physical activity (OR = 0.40, 95% CI: 0.24, 0.67; p < .001) and self‐management (OR = 0.49, 95% CI: 0.29, 0.82; p = .006).

Conclusion

These findings highlight the opportunity to address factors to improve glycaemic control. Further longitudinal studies are required to better understand these variations, to assess all predictors of glycaemic control in participants with type 2 diabetes, and to provide a strong basis for future measures to optimize glycaemic control.

Do Weight trajectories influence diabetes control? A prospective study in Switzerland (CoLaus study)

OBJECTIVE

Identify anthropometric trajectories among subjects with type 2 diabetes mellitus (T2DM), and associate them with glycaemic control.

METHODS

Prospective study including 268 community-dwelling participants with T2DM (34% women, mean age 68.7 ± 8.9 years) followed for 10.7 years (range: 8.8-13.6 years). T2DM control was considered for 1) fasting plasma glucose (FPG) < 7.0 mmol/L, or 2) HbA1c < 7.0% (53 nmol/mol). Changes in weight or waist and weight variability were considered.

RESULTS

One half (FPG) and one third (HbA1c) of participants presented with uncontrolled T2DM. Half of the participants presented with obesity and 75% with abdominal obesity. During follow-up, half of the participants maintained their weight, 25% gained > 5 kg, and 25% lost < 5 kg; almost half increased their waist by > 5 cm. Using FPG as criterion, participants who lost > 5 cm waist were more likely to be controlled: multivariable-adjusted odds ratio (OR) and 95% confidence interval (CI): 3.10 (1.23-7.78). Participants with controlled T2DM also presented with a higher weight variability: multivariable adjusted mean ± standard error 4.8 ± 0.3 vs. 3.9 ± 0.3 kg, p = 0.028. Using HbA1c as criterion, participants who lost > 5 kg were less likely to be controlled: OR and (95% CI): 0.35 (0.18-0.66). Similar findings were obtained when restricting the analysis to participants who were diabetic throughout the whole study period.

CONCLUSION

In a Swiss community-based sample of participants with T2DM, T2DM control rates could be implemented. Neither weight nor waist variability was significantly and consistently associated with T2DM control.

Fear of hypoglycaemia among patients with type 2 diabetes mellitus: a cross-sectional study

To investigate the fear of hypoglycaemia in patients with type 2 diabetes mellitus (T2DM), to identify factors related to this fear, and thus to provide evidence for clinical assessment. A total of 385 patients with T2DM who were admitted to the departments of endocrinology in five tertiary grade-A hospitals in Chongqing, China were included in this study. A questionnaire for general information and a Chinese version of Hypoglycemia Fear Survey (HFS) were used to collect the data. The average total score on the HFS was 71.67 ± 17.06 (HFS-W was 38.15 ± 10.57; HFS-B was 33.52 ± 9.54).The three items with the highest average score for HFS-W were not recognising low blood glucose (BG), not having food available, experiencing a hypoglycaemic episode alone, and for HFS-B were eating large amount of snacks, measuring BG six or more times per day, and keeping BG > 150 mmol/L. Regressions showed that number of hospitalisations for T2DM, receiving health education on diabetes, age and hypoglycaemia history because of T2DM were associated with fear of hypoglycaemia (all p < 0.05). Fear of hypoglycaemia in hospitalised patients with T2DM was strongly associated with diabetes health education, hospitalisation for diabetes, age, and hypoglycaemia history. Medical professionals should attach importance to the specific psychological interventions, health education on diabetes and the early prevention of hypoglycaemia or diabetic complications for patients with T2DM to reduce the fear of hypoglycaemia and improve their health status.

Prevalence, Patterns and Predictors of Chronic Complications of Diabetes Mellitus at a Large Referral Hospital in Ethiopia: A Prospective Observational Study

PURPOSE

Diabetes mellitus complications are responsible for increased disability, morbidity, and mortality. This study aimed to assess prevalence, patterns, and predictors of chronic complications of diabetes among people with diabetes.

PATIENTS AND METHODS

The study was conducted using a prospective observational study design which was done on people with diabetes attending the ambulatory clinic of Mettu Karl Referral Hospital. The data were collected using a consecutive type of sampling technique from April 15 to August 9, 2019. The data were entered into Epidata manager version 4.4.2. Logistic regression analysis was done to identify predictors of chronic complications of diabetes.

RESULTS

A total of 330 participants were included in this study. The mean age of participants was 49.9±14.2, and 156 (47.3%) were 41 to 60 years old. About 127 (38.5%) had one or more chronic complications. The predictors of chronic diabetes complications were resident in urban areas [AOR: 1.94; 95% CI: (1.17, 3.20); p = 0.010], duration of diabetes 10 years [AOR: 2.05, 95% CI: (1.21, 3.47); p = 0.007], hypertension [AOR: 4.19; 95% CI: (2.54, 6.91); p < 0.001] and poor glycemic control [AOR: 2.82; 95% CI: (1.53, 5.21); p = 0.001].

CONCLUSION

Almost two-fifth of the study participants had chronic complications of diabetes. Residents in urban areas, longer duration of diabetes, hypertension and poor glycemic control were predictors of chronic diabetes complications. It is important to achieve good glycemic control and manage comorbid diseases like hypertension to minimize the risk of chronic diabetes complications.

Glycemic Control and its Predictors among Adult Diabetic Patients attending Mettu Karl Referral Hospital, Southwest Ethiopia: A Prospective Observational Study

INTRODUCTION

The current estimate is that 463 million people worldwide have diabetes. In 2017, an estimated 5 million (9.9%) deaths worldwide among adults were caused by diabetes. The burden of disease associated with uncontrolled diabetes is substantial in terms of mortality and cardiovascular disease. The aim of this study was to assess glycemic control level and its predictors among adult patients with diabetes.

METHODS

A prospective observational study was conducted among patients with diabetes during follow-up at an ambulatory clinic of Mettu Karl referral hospital from 15 April to 09 August 2019. The consecutive sampling method was used to collect data, following which the data were entered into Epidata manager version 4.4.2 and exported to the SPSS version 24.0 statistical software package for analysis. Logistic regression analysis was performed to identify predictors of poor glycemic control. Variables whose significance level was < 0.05 (p value) were considered to be predictors of poor glycemic control.

RESULTS

A total of 330 diabetic patients were included in the study, among whom 240 (72.7%) had poor glycemic control. The predictors of poor glycemic control in the multivariate logistic regression analysis were overweight [adjusted odds ratio (AOR) 4.07; 95% confidence interval (CI) 1.60, 10.36; p = 0.003], obesity (AOR 4.39; 95% CI 1.59, 12.14; p = 0.004), higher estimated glomerular filtration rate (eGFR) (AOR 2.34; 95% CI 1.23, 4.44; p = 0.010), type 1 diabetes (AOR 3.22; 95% CI 1.58, 6.55; p = 0.001), poor diet adherence (AOR 6.95; 95% CI 3.63, 13.32; p < 0.001) and non-adherence to medications (AOR 5.82; 95% CI 2.77, 12.26; p < 0.001).

CONCLUSION

Almost three-quarters of the study population of diabetic patients had poorly controlled blood sugar. Overweight, obesity, higher eGFR, type 1 diabetics, poor adherence to diet recommendation and non-adherence to medications were independent predictors of poor glycemic control. Educational strategies should focus on improving adherence to the recommended diet and medication(s), achieving weight control and optimizing glycemic control.

Organisational and individual characteristics associated with glycaemic control among patients with type 2 diabetes: cross-sectional study in China

OBJECTIVE

There is a high prevalence of poor glycaemic control among patients with type 2 diabetes (T2DM) in China. This study aimed to explore both organisational and individual characteristics associated with glycaemic control among patients with T2DM.

DESIGN

Cross-sectional survey.

SETTING

Shandong Province, China.

PARTICIPANTS

The participants were 2166 patients with T2DM and 337 healthcare providers from 36 urban communities and 36 rural villages in Shandong Province.

PRIMARY AND SECONDARY OUTCOME MEASURES

Multistage stratified sampling procedures were used to measure demand-side individual demographic, clinical and self-management characteristics, and supply-side organisational characteristics, and the status of glycaemic control. Multilevel logistic regression analysis was performed to assess key determinants of glycaemic control.

RESULTS

Only 42.8% of the patients with T2DM achieved good glycaemic control. Age, income, hypertension and self-efficacy were significantly positive predictors of optimal glycaemic control, while duration of diabetes, antidiabetic drugs and monitoring of blood glucose were significantly negative predictors of that. Private VCs (OR=0.48, 95% CI 0.29 to 0.82, p<0.01) and lack of healthcare providers (OR=0.69, 95% CI 0.53 to 0.89, p<0.01; OR=0.71, 95% CI 0.52 to 0.98, p<0.05) were significantly negative predictors of optimal glycaemic control, while diabetes knowledge level of healthcare providers (OR=1.36, 95% CI 1.02 to 1.83, p<0.05; OR=1.45, 95% CI 1.00 to 2.10, p<0.05) and kinds of antidiabetic drugs (OR=1.37, 95% CI 0.97 to 1.93, p<0.1; OR=1.46, 95% CI 1.07 to 2.00, p<0.05) were significantly positive predictors of that.

CONCLUSIONS

Glycaemic control was suboptimal among patients with T2DM in China. The determinants of failing to achieve good glycaemic control included both organisational and individual characteristics. Potential interventions that target patients, providers and the healthcare organisations should be taken to improve the glycaemic control and health outcome among patients with T2DM.

Genetic Association of SH2B1 Gene Polymorphisms in Jordanian Arab Patients with Type 2 Diabetes Mellitus

OBJECTIVE

To investigate the genotypic and allelic association of Src homology 2 B adapter protein 1 (SH2B1) gene polymorphisms with type 2 diabetes mellitus (T2DM) in Jordanian patients.

PATIENTS AND METHODS

Three hundred patients were screened, but only 200 adult Jordanian patients diagnosed with T2DM (53.5% male and 46.5% female) have participated in this study. Blood samples were collected from both patients and healthy individuals for DNA extraction according to well-established procedures. Exon 1 and exon 9 of the SH2B1 gene were sequenced using an efficient and sensitive DNA sequencing method in order to identify specific single nucleotide polymorphisms (SNPs) in the SH2B1 gene associated with T2DM. Genetic and haplotype correlation analysis was performed for the chosen SNPs to detect any association if existent. In addition, SNPStats Web Tool and Hardy-Weinberg equilibrium (HWE) analyses for the genotype distribution were used. The significance was determined according to the P-value, and the level of significance taken as P < 0.05. The normality of the data distribution was statically analysed by the Shapiro-Wilk test with a P-value >0.05. Also, the patient's characteristics and clinical data about all participants were mentioned.

RESULTS

Two novel variations were present in the SH2B1 gene in Jordanian patients with T2DM: c.827C>G and c.2026G>A, and previously reported five SNPs: rs146946750, rs565131715, rs370302573, rs143212778, rs200470848. Our results showed a strong genetic association of rs565131715 SNP polymorphism within the SH2B1 gene in T2DM patients (χ ² test, P < 0.001). Additionally, rs143212778 SNP presented a genetic correlation with T2DM patients (χ ² test, P = 0.035) as compared to control individuals. GTACG haplotype of SH2B1 has a highly significant association with responders (P< 0.0001).

CONCLUSION

Our findings indicated a strong association between the rs565131715 polymorphism and the risk of T2DM among the Jordanian population. Moreover, our data showed that the rs143212778 polymorphism significantly elevated the danger of T2DM among this population. This study reveals the first data regarding the SH2B1 gene polymorphisms in Jordanian patients of Arab descent with diabetes.

Predictors of poor glycemic control among patients with type 2 diabetes on follow-up care at a tertiary healthcare setting in Ethiopia

OBJECTIVE

Contemporary clinical guidelines endorsed that glycemic control is the ultimate goal in the management patients with diabetes. The aim of this study was to assess the prevalence of glycemic control and to identify predictors of poor glycemic control in patients with type 2 diabetes (T2D). A cross-sectional study was conducted among systematically selected 357 diabetic patients. Data were collected through direct patients' interviews and medical chart review. Binary logistic regression analyses were performed and analyzed using SPSS version 22.0.

RESULTS

Participants' mean age was (± SD) 56.1 ± 11.6 years. Nearly four in five (77.9%) of the participants had comorbidities, mainly of hypertension, and 60.2% had diabetic complications, mainly diabetes neuropathy. Poor glycemic control was found in 68.3% of the participants with a mean (± SD) FBG of 174.1 ± 48.9 mg/dL. Being female gender, having greater body mass index and low medication adherence was significantly associated with poor glycemic control. In conclusion, the overall aspects of glycemic control level of patients were far from the standards. Being female, greater body mass index and poor medication adherence were predictors of poor glycemic control. In response to this finding, an aggressive intervention that targets in improving the glycemic control is required.

Metformin Pharmacogenetics: Effects of SLC22A1, SLC22A2, and SLC22A3 Polymorphisms on Glycemic Control and HbA1c Levels

Type 2 diabetes mellitus (T2DM) constitutes a major portion of Jordan’s disease burden, and incidence rates are rising at a rapid rate. Due to variability in the drug’s response between ethnic groups, it is imperative that the pharmacogenetics of metformin be investigated in the Jordanian population. The objective of this study was to investigate the relationship between twenty-one single nucleotide polymorphisms (SNPs) in the SLC22A1, SLC22A2, and SLC22A3 genes and their effects on metformin pharmacogenetics in Jordanian patients diagnosed with type 2 diabetes mellitus. Blood samples were collected from 212 Jordanian diabetics who fulfilled the inclusion criteria, which were then used in SNP genotyping and determination of HbA1c levels. The rs12194182 SNP in the SLC22A3 gene was found to have a significant association (p < 0.05) with lower mean HbA1c levels, and this association more pronounced in patients with the CC genotype (i.e., p-value was significant before correcting for multiple testing). Moreover, the multinomial logistic regression analysis showed that SNP genotypes within the SLC22A1, SLC22A2, and SLC22A3 genes, body mass index (BMI) and age of diagnosis were significantly associated with glycemic control (p < 0.05). The results of this study can be used to predict response to metformin and other classes of T2DM drugs, making treatment more individualized and resulting in better clinical outcomes.