Predictors of glycemic control among patients with Type 2 diabetes: a longitudinal study

Magnitude of glycemic control and its associated factors among patients with type 2 diabetes at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia

Back ground

Diabetes is increasing at an alarming rate throughout the world and about 80% of diabetic cases live in low and middle income countries. Glycemic control is the most important predictor for diabetic related complications and deaths. Identifying factors associated with glycemic control help health care providers and patients to work in the areas that reduce risks of diabetic related complications and deaths.

Objectives

The aim of this study is to assess the magnitude and factors associated with glycemic control among type 2 diabetic patients at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia.

Methods

Hospital-based cross sectional study was conducted on 412 type 2 diabetic patients who were attending in diabetic clinics at Tikur Anbessa Specialized Hospital. Data were collected through structured interview questionnaire, and data abstraction format to collect information from each patient’s medical records from March to April, 2015. Data were entered and analyzed using SPSS version 20 statistical software. Both descriptive and inferential statistics were used to determine magnitude of glycemic control and factors associated with poor glycemic control.

Result

Median age of participants was 52 years old (IQR = 40–60 years old). From the study participants,51.7% were females. Median duration of living with diabetes since diagnosis was 10 years (IQR: 5–16 years). About 80% of the respondents had uncontrolled fasting blood glucose level. The factors which are significantly associated with poor glycemic control were longer duration of diabetes (AOR = 2.72 95%CI:1.16–6.32), and being on insulin therapy (AOR = 3.01 95% CI: 1.5–5.9).

Conclusion

A high proportion of patients had poor glycemic control. Longer duration of the disease, and being on drug regimen of insulin were associated with poor glycemic control. Appropriate attention should be given to patients with longer duration of disease and those who are on insulin therapy.

Metformin, other antidiabetic drugs, and endometrial cancer risk: a nested case-control study within Italian healthcare utilization databases

Metformin may reduce the risk of endometrial cancer whereas other drugs for the treatment of type 2 diabetes mellitus appear to increase it, although the evidence is still limited. We investigated this issue using data from a nested case-control study within the healthcare utilization databases of the Lombardy Region, Italy. This study included 376 diabetic women with endometrial cancer and 7485 diabetic controls matched for cases on age, date at cohort entry, and duration of follow-up. We used conditional logistic regression models to estimate the odds ratio (OR) of endometrial cancer in relation to use of antidiabetic drugs, adjusted for the Charlson's comorbidity index, selected medical conditions, prescription of selected drugs, and concomitant use of other antidiabetic drugs. At cohort entry, no significant associations were observed for metformin [OR=0.99, 95% confidence interval (CI) 0.80-1.23], sulfonylureas (OR=1.14, 95% CI 0.91-1.42), insulin (OR=0.72, 95% CI 0.34-1.56), and other antidiabetic drugs (OR=1.21, 95% CI 0.75-1.95). When we considered use during follow-up, a borderline significant excess risk was found for metformin (OR=1.30, 95% CI 1.00-1.70). However, this estimate decreased to 1.07 (95% CI 0.82-1.41) when taking into account BMI using a Monte Carlo sensitivity analysis. No significant associations were found for sulfonylureas (OR=1.16, 95% CI 0.91-1.47), thiazolidinediones (OR=0.77, 95% CI 0.48-1.24), repaglinide (OR=1.32, 95% CI 0.94-1.87), incretins (OR=1.21, 95% CI 0.63-2.32), and insulin (OR=1.19, 95% CI 0.82-1.71). Our data indicate that metformin, insulin, and other antidiabetic drugs did not meaningfully affect the risk of endometrial cancer.

The relationship between context, structure, and processes with outcomes of 6 regional diabetes networks in Europe

Background

While health service provisioning for the chronic condition Type 2 Diabetes (T2D) often involves a network of organisations and professionals, most evidence on the relationships between the structures and processes of service provisioning and the outcomes considers single organisations or solo practitioners. Extending Donabedian’s Structure-Process-Outcome (SPO) model, we investigate how differences in quality of life, effective coverage of diabetes, and service satisfaction are associated with differences in the structures, processes, and context of T2D services in six regions in Finland, Germany, Greece, Netherlands, Spain, and UK.

Methods

Data collection consisted of: a) systematic modelling of provider network’s structures and processes, and b) a cross-sectional survey of patient reported outcomes and other information. The survey resulted in data from 1459 T2D patients, during 2011–2012. Stepwise linear regression models were used to identify how independent cumulative proportion of variance in quality of life and service satisfaction are related to differences in context, structure and process. The selected context, structure and process variables are based on Donabedian’s SPO model, a service quality research instrument (SERVQUAL), and previous organization and professional level evidence. Additional analysis deepens the possible bidirectional relation between outcomes and processes.

Results

The regression models explain 44% of variance in service satisfaction, mostly by structure and process variables (such as human resource use and the SERVQUAL dimensions). The models explained 23% of variance in quality of life between the networks, much of which is related to contextual variables. Our results suggest that effectiveness of A1c control is negatively correlated with process variables such as total hours of care provided per year and cost of services per year.

Conclusions

While the selected structure and process variables explain much of the variance in service satisfaction, this is less the case for quality of life. Moreover, it appears that the effect of the clinical outcome A1c control on processes is stronger than the other way around, as poorer control seems to relate to more service use, and higher cost. The standardized operational models used in this research prove to form a basis for expanding the network level evidence base for effective T2D service provisioning.

Relevant patient characteristics for guiding tailored integrated diabetes primary care: a systematic review

Aim

To identify which patient-related effect modifiers influence the outcomes of integrated care programs for type 2 diabetes in primary care.

Background

Integrated care is a widespread management strategy for the treatment of type 2 diabetes. However, most integrated care programs are not tailored to patients’ needs, preferences and abilities. There is increasing consensus that such a patient-centered approach could improve the management of type 2 diabetes. Thus far, it remains unclear which patient-related effect modifiers should guide such an approach.

Methods

PubMed, CINAHL and EMBASE were searched for empirical studies published after 1998. A systematic literature review was conducted according to the PRISMA guidelines.

Findings

In total, 23 out of 1015 studies were included. A total of 21 studies measured the effects of integrated diabetes care programs on hemoglobin A1c (HbA1c) and three on low-density lipoprotein cholesterol, systolic blood pressure and health-care utilization. In total, 49 patient characteristics were assessed as potential effect modifiers with HbA1c as an outcome, of which 46 were person or health-related and only three were context-related. Younger age, insulin therapy and longer disease duration were associated with higher HbA1c levels in cross-sectional and longitudinal studies. Higher baseline HbA1c was associated with higher HbA1c at follow-up in longitudinal studies. Information on context- and person-related characteristics was limited, but is necessary to help identify the care needs of individual patients and implement an effective integrated type 2 diabetes tailored care program.

Glycemic control and associated factors among type 2 diabetic patients at Shanan Gibe Hospital, Southwest Ethiopia

OBJECTIVE

The aim of this study was to assess the rate of glycemic control and factors affecting glycemic control in type 2 diabetic patients.

RESULTS

A total of 174 type 2 diabetic patients were interviewed and were studied. Mean age of the patients was 48.98 ± 14.96 years (range 18-80 years). More than half (51.7%) of the patients were males. About a third of patients, 53 (30.5%), were on antidiabetic medications for less than 5 years. The most common prescribed antidiabetic medications were insulin, 48 (27.6%), and metformin 15 (8.6%). One hundred seven (61.5%) patients were on combination therapy (two drug treatment) and the remaining patients were on monotherapy. The majority, 103 (59.2%), of patients had uncontrolled blood glucose. A larger proportion of female patients, 54 (52.4%), had uncontrolled blood glucose than males. Level of education (p < 0.001) and duration of diabetes treatment (p < 0.001) were significantly associated with glycemic control. Adherence of patients to regular follow up (Adjusted Odds Ratio (AOR) = 2.42, 95% CI 1.08-5.44, p = 0.03) and diabetes treatment for 5-10 years (AOR = 4.64, 95% CI 1.79-12.06, p = 0.002) are found to be independent predictors of glycemic control among type 2 diabetes patients.

Trajectories of Glycemic Change in a National Cohort of Adults With Previously Controlled Type 2 Diabetes

BACKGROUND

Individualized diabetes management would benefit from prospectively identifying well-controlled patients at risk of losing glycemic control.

OBJECTIVES

To identify patterns of hemoglobin A1c (HbA1c) change among patients with stable controlled diabetes.

RESEARCH DESIGN

Cohort study using OptumLabs Data Warehouse, 2001-2013. We develop and apply a machine learning framework that uses a Bayesian estimation of the mixture of generalized linear mixed effect models to discover glycemic trajectories, and a random forest feature contribution method to identify patient characteristics predictive of their future glycemic trajectories.

SUBJECTS

The study cohort consisted of 27,005 US adults with type 2 diabetes, age 18 years and older, and stable index HbA1c <7.0%.

MEASURES

HbA1c values during 24 months of observation.

RESULTS

We compared models with k=1, 2, 3, 4, 5 trajectories and baseline variables including patient age, sex, race/ethnicity, comorbidities, medications, and HbA1c. The k=3 model had the best fit, reflecting 3 distinct trajectories of glycemic change: (T1) rapidly deteriorating HbA1c among 302 (1.1%) youngest (mean, 55.2 y) patients with lowest mean baseline HbA1c, 6.05%; (T2) gradually deteriorating HbA1c among 902 (3.3%) patients (mean, 56.5 y) with highest mean baseline HbA1c, 6.53%; and (T3) stable glycemic control among 25,800 (95.5%) oldest (mean, 58.5 y) patients with mean baseline HbA1c 6.21%. After 24 months, HbA1c rose to 8.75% in T1 and 8.40% in T2, but remained stable at 6.56% in T3.

CONCLUSIONS

Patients with controlled type 2 diabetes follow 3 distinct trajectories of glycemic control. This novel application of advanced analytic methods can facilitate individualized and population diabetes care by proactively identifying high risk patients.

Knowledge of type 2 diabetic patients about their condition in Kimpese Hospital diabetic clinic, Democratic Republic of the Congo

Background

Diabetes mellitus is a worldwide increasing health problem of which type 2 diabetes is the most prevalent. Previously considered as a problem of industrialised countries, diabetes is currently a huge concern in developing countries and the Democratic Republic of the Congo (DRC) is one of the sub-Saharan countries with a high prevalence rate of diabetes. Deficit of knowledge has already been shown to be one of the barriers preventing diabetic patients from controlling their disease.

Objectives

This study aimed to assess the knowledge of type 2 diabetic patients seen at the Institut Médical Evangélique (IME) Kimpese Hospital diabetic clinic, DRC, and the factors associated with their knowledge.

Methods

A cross-sectional study involving 184 respondents was conducted at the diabetic clinic of the IME Kimpese Hospital, DRC. We administered a pre-tested questionnaire. Out of a total of 10, scores of < 5, 5 to < 7, and ≥ 7 were classified as ‘poor knowledge’, ‘moderate knowledge’ and ‘good knowledge’, respectively, according to expert consensus. All statistical tests were performed using p < 0.05 as the level of statistical significance.

Results

The mean age of respondents was 57.5 years (s.d. ± 1.4, ranging from 40 to 83 years), with 56% being male. The mean diabetes knowledge score was poor: 3.2 out of a total of 10 (s.d. ± 1.7), with the range between 0.2 and 7.7. The majority of respondents (72.3%) had poor general knowledge about diabetes mellitus. Respondents also scored poorly in areas of the causes (35.6%), risk factors (39.3%), clinical features (34.9%), complications (20.5%) and management (42.4%) of diabetes mellitus. Using the student t-test analysis, it was found that age (p = 0.001), gender (p = 0.002), educational level (p = 0.007) and duration of disease (p = 0.032) were significantly associated with poor knowledge of diabetes mellitus.

Conclusions

Knowledge of diabetes mellitus among type 2 diabetic patients seen at our setting was poor. Areas of deficiency and factors associated with knowledge of diabetes were identified. Our findings suggest the need for a health education intervention programme for our diabetic patients.

Age differences in diabetes-related complications and glycemic control

BACKGROUND

This study aimed to examine the associations of age with the presence of complications and glycemic control in the Northwest of Iran.

METHODS

A total of 649 people with diabetes who were >25 years old and had a caring record in diabetes clinics in two Northwestern provinces of Iran during 2014-15, were recruited in this cross-sectional study. General information including demographic, socioeconomic status and lifestyle factors were collected by trained interviewers. Clinical information was retrieved from clinic's record. Univariate and multivariate logistic regression were performed to assess the predictors of diabetes outcome of interest as well as to clarify the role of age in relation to these outcomes.

RESULTS

Compared to the age group of ≤49, the middle age group (50-59) and the older age group (60 years of age and older) were less likely to report poor glycemic control (OR fully adjusted = 0.49 95% CI: 0.28-0.86 and (OR = 0.44 95% CI: 0.24-0.80), respectively. Additionally, poor glycemic control was associated with income level, disease duration, hypercholesterolemia, high level of LDL and hypertension. In contrast, age was associated with the highest percentage of complications. People with duration of >7 years of disease record were 6 times more likely to have complications (OR_adj = 5.98 95% CI: 2.35-15.22).

CONCLUSION

Although the prevalence of complications was higher among the older diabetic patients, they had a better glycemic control. The influential factors were variably associated with the two diabetes-related outcomes; therefore, a more comprehensive risk profiles assessment is needed for glycemic control.

Using Routine Data to Categorize Poor Control Diabetic Patients: An Application of Cluster Analysis Technique

BACKGROUND

Diabetes mellitus is one of the most important causes of morbidity and mortality all over the world. Chronic high blood glucose is the root cause of developing future micro and macro vascular complications. In current study, we analyzed poorly controlled patients' information by clustering method in order to find more homogenous sub-groups of patients for planning for further interventions.

METHODS

This study was conducted based on medical records of diabetic patients admitted to 23 health care centers in four cities of Iran from 2010 to 2014. Demographic data and physical and biochemical measurements were extracted and analyzed using two-steps cluster analysis method.

RESULTS

Three distinct clusters were derived from 2087 eligible cases. Cluster 1 totally consisted of men without any apparent risk factors. Members of clusters 2 and 3 were illiterate women with obesity. Dyslipidemia was a prominent characteristic in members of cluster 2.

CONCLUSION

Masculinity would play the main role in diabetes control. Meanwhile, aggregation of obesity, illiteracy and/or dyslipidemia in diabetic women predispose them to poor control condition. Based on these findings, we will be able to plan interventions that are more appropriate for identified groups.

Diabetes awareness, treatment, control rates and associated risk factors among Beijing residents in 2011: A cross-sectional survey

Objective

To examine the awareness, treatment and control rates of diabetes and identify their associated risk factors among Beijing residents.

Methods

A cross-sectional survey was conducted in 2011, using a stratified multistage cluster random sampling method to select a representative sample of 20,242 residents in Beijing aged 18–79 years. Diabetes was defined as fasting blood glucose (FBG) ≥7.0 mmol/L and/or history of diabetes and/or using insulin or hypoglycemic agents. All estimates of awareness, treatment and control rates were weighted by the 2010 Beijing Population Census data and the sampling scheme. Multivariate Logistic regression was used to identify factors associated with awareness, treatment and control rates.

Results

A total of 2061 (10.3%) participants were diagnosed as diabetes. The overall awareness, treatment and control rate among patients were 60.9%, 51.3% and 22.4%, respectively, while overall control rate among treated patients was 33.8%. These rates differed across subgroups. Women were more likely to be aware of diabetes status, receive treatment and have better glucose controlled than men (69.5% vs. 54.7% for awareness, 61.0% vs. 44.3% for treatment, and 27.6% vs. 18.6% for control, respectively). In addition, only 22.2% of treated patients had both FBG and hemoglobin A1c (HbA1c) controlled well. Multivariate Logistic regression suggested that old age, women, higher education and family history of diabetes were associated with higher awareness, treatment and control rates (All P < 0.05). Treated individuals living in rural (OR = 0.67(95%CI: 0.47–0.96)) or with dyslipidemia (OR = 0.63 (95%CI: 0.44–0.91)) had a lower diabetic control rate.

Conclusions

Awareness, treatment and control rates of diabetes in Beijing were still low. A comprehensive intervention strategy on diabetes management and control is warranted.

The association between sociodemographic and clinical characteristics and poor glycaemic control: a longitudinal cohort study

AIMS

People with diabetes and poor glycaemic control are at higher risk of diabetes-related complications and incur higher healthcare costs. An understanding of the sociodemographic and clinical characteristics associated with poor glycaemic control is needed to overcome the barriers to achieving care goals in this population.

METHODS

We used linked administrative and laboratory data to create a provincial cohort of adults with prevalent diabetes, and a measure of HbA_1c that occurred at least 1 year following the date of diagnosis. The primary outcome was poor glycaemic control, defined as at least two consecutive HbA_1c measurements ≥ 86 mmol/mol (10%), not including the index measurement, spanning a minimum of 90 days. We used multivariable Cox proportional hazards models to evaluate the association between baseline sociodemographic and clinical factors and poor glycaemic control.

RESULTS

In this population-based cohort of 169 890 people, younger age was significantly associated with sustained poor glycaemic control, with a hazard ratio (HR) of 3.08, 95% CI (2.79-3.39) for age 18-39 years compared with age ≥ 75 years. Longer duration of diabetes, First Nations status, lower neighbourhood income quintile, history of substance abuse, mood disorder, cardiovascular disease, albuminuria and high LDL cholesterol were also associated with poor glycaemic control.

CONCLUSIONS

Although our results may be limited by the observational nature of the study, the large geographically defined sample size, longitudinal design and robust definition of poor glycaemic control are important strengths. These findings demonstrate the complexity associated with poor glycaemic control and indicate a need for tailored interventions.

Patient-level predictors of achieving early glycaemic control in Type 2 diabetes mellitus: a population-based study

AIMS

To identify individual predictors of early glycaemic control in people with Type 2 diabetes mellitus after initiation of first glucose-lowering drug treatment in everyday clinical practice.

METHODS

Using medical registries, we identified a population-based cohort of people with a first-time glucose-lowering drug prescription in Northern Denmark in the period 2000-2012. We used Poisson regression analysis to examine patient-level predictors of success in reaching early glycaemic control [HbA_1c target of < 53 mmol/mol (7%)] < 6 months after treatment start.

RESULTS

Among the 38 418 people (median age 63 years), 27 545 (72%) achieved early glycaemic control. The strongest predictor of achieving early control was pre-treatment HbA_1c level; compared with a pre-treatment HbA_1c level of ≤ 58 mmol/mol (7.5%), the adjusted relative risks of attaining early control were 0.63 (95% CI 0.61-0.64) for baseline HbA_1c levels of > 58 and ≤ 75 mmol/mol (> 7.5 and ≤ 9%), and 0.58 (95% CI 0.57-0.59) for a baseline HbA_1c level of > 9% (> 75 mmol/mol). All other examined predictors were only weakly associated with the chance of achieving early control. After adjustment, the only characteristics that remained independently associated with early control (in addition to high baseline HbA_1c ) were being widowed (adjusted relative risk 0.95; 95% CI 0.93-0.97) and having a high Charlson comorbidity index score (score ≥ 3; adjusted relative risk 0.94; 95% CI 0.90-0.97).

CONCLUSIONS

In a real-world clinical setting, people with Type 2 diabetes mellitus initiating glucose-lowering medication had a similar likelihood of achieving glycaemic control, regardless of sex, age, comorbidities and other individual factors; the only strong and potentially modifiable predictor was HbA_1c before therapy start.

Living with sub-optimal glycaemic control: the experiences of Type 2 diabetes diagnosis and education

AIM

The aim of this study was to explore the experiences of diagnosis and education for people living with Type 2 diabetes who have sub-optimal glycaemic control.

BACKGROUND

The increasing prevalence of Type 2 diabetes is a global concern. Many people have difficulty maintaining optimal glycaemic control with up to 50% having HbA1c levels higher than recommended. A range of factors that have been suggested as possibly contributing to this, however, little is known about how their experience of diagnosis, education and support to attempt to understand the context of their self-management practices.

DESIGN

A qualitative thematic analysis of interviews conducted with people with sub-optimal glycaemic control prior to their participation in an intervention study.

METHOD

Thirty participants taking part in a psychosocial/educational intervention for people with sub-optimal glycaemic control were interviewed in 2012 before the intervention commenced. These interviews explored each participant's experience of the diagnosis and associated education. The interviews were transcribed and a thematic analysis was conducted.

FINDINGS

Almost all the participants had been shocked at receiving the diagnosis and felt it had been a moral indictment on their lifestyle. Many had been given the impression that they had a mild form of diabetes and most had been given very little information on self-management that they had found useful.

CONCLUSION

The findings suggest that for the participants there was a considerable gap between the rhetoric of person-centred services and the reality of the experiences of diagnosis and education for the self-management of Type 2 diabetes.

Financial Incentives and Diabetes Disease Control in Employees: A Retrospective Cohort Analysis

BACKGROUND

Many employers offer worksite wellness programs, including financial incentives to achieve goals. Evidence supporting such programs is sparse.

OBJECTIVE

To assess whether diabetes and cardiovascular risk factor control in employees improved with financial incentives for participation in disease management and for attaining goals.

DESIGN

Retrospective cohort study using insurance claims linked with electronic medical record data from January 2008-December 2012.

PARTICIPANTS

Employee patients with diabetes covered by the organization's self-funded insurance and propensity-matched non-employee patient comparison group with diabetes and commercial insurance.

INTERVENTION

Financial incentives for employer-sponsored disease management program participation and achieving goals.

MAIN MEASURES

Change in glycosylated hemoglobin (HbA1c), low-density lipoprotein (LDL), systolic blood pressure (SBP), and weight.

RESULTS

A total of 1092 employees with diabetes were matched to non-employee patients. With increasing incentives, employee program participation increased (7 % in 2009 to 50 % in 2012, p < 0.001). Longitudinal mixed modeling demonstrated improved diabetes and cardiovascular risk factor control in employees vs. non-employees [HbA1c yearly change -0.05 employees vs. 0.00 non-employees, difference in change (DIC) p <0.001]. In their first participation year, employees had larger declines in HbA1c and weight vs. non-employees (0.33 vs. 0.14, DIC p = 0.04) and (2.3 kg vs. 0.1 kg, DIC p < 0.001), respectively. Analysis of employee cohorts corresponding with incentive offerings showed that fixed incentives (years 1 and 2) or incentives tied to goals (years 3 and 4) were not significantly associated with HbA1c reductions compared to non-employees. For each employee cohort offered incentives, SBP and LDL also did not significantly differ in employees compared with non-employees (DIC p > 0.05).

CONCLUSIONS

Financial incentives were associated with employee participation in disease management and improved cardiovascular risk factors over 5 years. Improvements occurred primarily in the first year of participation. The relative impact of specific incentives could not be discerned.

Health inequalities in hypertension and diabetes management among the poor in urban areas: a population survey analysis in south Korea

BACKGROUND

This study investigated whether the prevalence, awareness, treatment, and control of hypertension and diabetes differed by residential areas. In addition, the rate of good hypertension or diabetes control was examined separately in men and women, and in urban and rural areas.

METHODS

This study used Korea National Health and Nutrition Examination V (2010-2012) data, a nationwide cross-sectional survey of general South Korean population. Residential areas were categorized into urban and rural areas. To examine differences between the residential areas in terms of prevalence, awareness, treatment, and control of hypertension and diabetes we performed a multivariate logistic regression adjusting for age, body mass index, physical activity, alcohol use, smoking, marital status, monthly income, and educational level. To investigate control of hypertension or diabetes within each residential area, we performed a subgroup analysis in both urban and rural areas.

RESULTS

The prevalence of hypertension is higher among men in urban areas than among those in rural areas (OR = 0.80; 95 % CI = 0.67-0.96, reference group = urban areas). However, the subgroups did not differ in terms of diabetes prevalence, awareness, treatment, and control. Regardless of both sex and residential area, participants in good control of their hypertension and diabetes were younger. Inequality in good control of hypertension was observed in men who lived in urban (≤Elementary school, OR 0.74, 95 % CI 0.60-0.92) and rural areas (≤Elementary school, OR 0.67, 95 % CI 0.46-0.99). Inequality in health status was found in women who resided in urban areas (≤Elementary school, OR 0.53, 95 % CI 0.37-0.75). Good control of diabetes also showed inequalities in health status for both men (≤Elementary school, OR 0.61, 95 % CI 0.40-0.94; Middle/High school, OR 0.69, 95 % CI 0.49-0.96) and women in urban areas (≤1 million won, OR 0.56, 95 % CI 0.33-0.93) (Reference group = '≥College' for education and '>3 million' Korean won for income).

CONCLUSIONS

After correction for individual socioeconomic status, differences by residential area were not observed. However, when the participants with good disease control were divided by region, inequality was confirmed in urban residents. Therefore, differentiated health policies to resolve individual and regional health inequalities are necessary.

Evaluation of empowerment model on indicators of metabolic control in patients with type 2 diabetes, a randomized clinical trial study

AIMS

Diabetes education is a major subject in achieving optimal glycemic control. Effective empowerment approach can be beneficial for improving patients' health. The aim of this study was to evaluate the effect of empowerment model on indicators of metabolic control in patients with type 2 diabetes.

METHODS

a randomized controlled trial of 103 patients with type 2 diabetes were randomly assigned to either the intervention (empowerment approach training) or the control group (conventional training) 2014. Empowerment approach training were performed for the experimental group for eight weeks. Data collection tool included demographic information form and indicators of metabolic control checklist. Analysis was performed by one-way analysis of variance, chi-square test, paired t-test, independent t-test and multiple linear regression.

RESULTS

Before the intervention, two groups were homogeneous in terms of demographic variables, glycosylated hemoglobin (HbA1C), and other indicators of metabolic control. After the intervention, average HbA1C and other metabolic indicators except for LDL showed significant differences in the experimental group compared to the control group.

CONCLUSION

study results indicated the positive effects of applying the empowerment model on the metabolic control indicators. Therefore, applying this model is recommended to nurses and the relevant authorities in order to improve clinical outcomes in diabetic patients.

Association of Comorbid and Metabolic Factors with Optimal Control of Type 2 Diabetes Mellitus

Background:

Type 2 diabetes mellitus (T2DM) is a poorly controlled epidemic worldwide that demands active research into mitigation of the factors that are associated with poor control.

Aims:

The study was to determine the factors associated with suboptimal glycemic control.

Materials and Methods:

Electronic medical records of 263 adult patients with T2DM in our suburban internal medicine office were reviewed. Patients were divided into two groups: Group 1 [optimal diabetes control with glycosylated hemoglobin (HbA1c) of 7% or less] and Group 2 (suboptimal diabetes control with HbA1c greater than 7%). The influence of factors such as age, gender, race, social history, comorbid conditions, gestational diabetes, family history of diabetes, diabetes management, statin use, aspirin use, angiotensin convertase enzyme inhibitor (ACE-I) or angiotensin receptor blocker (ARB) use, body mass index (BMI), blood pressures, lipid profile, and urine microalbumin level were analyzed in the two groups.

Results:

In the suboptimal diabetes control group (N = 119), the majority (86.6%) of the patients were 41-80 years old. Factors associated with the suboptimal control were male gender [odds ratio (OR) 2.6, 95% confidence interval (CI), 1.579-4.321], Asian ethnicity (OR 1.4, 95% CI, 0.683-3.008), history of peripheral arterial disease (PAD; OR 3.9, 95% CI, 1.017-14.543), history of congestive heart failure (CHF; OR 3.9, 95% CI, 1.017-14.543), elevated triglycerides (OR 1.004, 95% CI, 1.000-1.007), and elevated urine microalbumin level of 30 mg/24 h or above (OR 4.5, 95% CI, 2.446-8.380). Patients with suboptimal diabetes control had a 3.8 times greater odds (95% CI, 1.493-6.885) of receiving the insulin and oral hypoglycemic agent together.

Conclusions:

In adult patients with T2DM, male gender, Asian ethnicity, CHF, PAD, management with insulin along with oral hypoglycemic agents, hypertriglyceridemia, and microalbuminuria were associated with suboptimal control.

Incretin based drugs and the risk of pancreatic cancer: international multicentre cohort study

OBJECTIVE

To determine whether the use of incretin based drugs compared with sulfonylureas is associated with an increased risk of incident pancreatic cancer in people with type 2 diabetes.

DESIGN

Population based cohort.

SETTING

Large, international, multicentre study combining the health records from six participating sites in Canada, the United States, and the United Kingdom.

PARTICIPANTS

A cohort of 972,384 patients initiating antidiabetic drugs between 1 January 2007 and 30 June 2013, with follow-up until 30 June 2014.

MAIN OUTCOME MEASURES

Within each cohort we conducted nested case-control analyses, where incident cases of pancreatic cancer were matched with up to 20 controls on sex, age, cohort entry date, duration of treated diabetes, and duration of follow-up. Hazard ratios and 95% confidence intervals for incident pancreatic cancer were estimated, comparing use of incretin based drugs with use of sulfonylureas, with drug use lagged by one year for latency purposes. Secondary analyses assessed whether the risk varied by class (dipeptidyl peptidase-4 inhibitors and glucagon-like peptide-1 receptor agonists) or by duration of use (cumulative duration of use and time since treatment initiation). Site specific hazard ratios were pooled using random effects models.

RESULTS

During 2,024,441 person years of follow-up (median follow-up ranging from 1.3 to 2.8 years; maximum 8 years), 1221 patients were newly diagnosed as having pancreatic cancer (incidence rate 0.60 per 1000 person years). Compared with sulfonylureas, incretin based drugs were not associated with an increased risk of pancreatic cancer (pooled adjusted hazard ratio 1.02, 95% confidence interval 0.84 to 1.23). Similarly, the risk did not vary by class and evidence of a duration-response relation was lacking.

CONCLUSIONS

In this large, population based study the use of incretin based drugs was not associated with an increased risk of pancreatic cancer compared with sulfonylureas. Although this potential adverse drug reaction will need to be monitored long term owing to the latency of the cancer, these findings provide some reassurance on the safety of incretin based drugs.

Investigation of the relationship between patient empowerment and glycaemic control in patients with type 2 diabetes: a cross-sectional analysis

OBJECTIVE

To determine whether there is an association between patient empowerment and diabetes management in terms of the primary outcomes of metabolic control as measured by glycaemic control (glycated haemoglobin, HbA1c), high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC) and triglycerides.

DESIGN

Retrospective cross-sectional analysis conducted in 2012.

SETTING

Data from Diabetes Federation of Ireland from participants enrolled in the Community Orientated Diabetes Education (CODE) Programme.

PARTICIPANTS

569 patients diagnosed with type 2 diabetes.

EXPOSURES

Patient empowerment levels, as measured by the Diabetes Empowerment Scale-Short Form. Additional information collected included patients' gender, age, body mass index (BMI), smoking status and number of years with diabetes.

OUTCOME MEASURES

HbA1c, HDL, LDL, TC and triglycerides values.

RESULTS

Partial correlation analyses failed to show any statistically significant relationship between patient empowerment and glycaemic control or other diabetes management variables (HbA1c, p=0.32; HDL, p=0.95; LDL, p=0.77; TC, p=0.49; triglycerides, p=0.77). Logistic regression analysis confirmed that patient empowerment score was not a significant predictor of level of glycaemic control. Time since diagnosis of diabetes was associated with increased HbA1c levels. Age and gender were significant predictors of HDL and LDL levels, while gender and age were associated with changes in TC and triglycerides levels, respectively.

CONCLUSIONS

No significant association was found between patient empowerment levels and other measures of diabetes control in this study. Further research into the short-term and long-term outcomes of the empowerment model, at different levels of disease management, and across different settings, is required to evaluate its value in the management of patients with diabetes.

Metformin association with lower prostate cancer recurrence in type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Accumulating evidence suggests that metformin possesses anticarcinogenic properties, and its use is associated with favorable outcomes in several cancers. However, it remains unclear whether metformin influences prognosis in prostate cancer (PCa) with concurrent type 2 diabetes (T2D).

MATERIALS AND METHODS

We searched PubMed, EMBASE, and the Cochrane Library from database inception to April 16, 2014 without language restrictions to identify studies investigating the effect of metformin treatment on outcomes of PCa with concurrent T2D. We conducted a meta-analysis to quantify the risk of recurrence, progression, cancer-specific mortality, and all-cause mortality. Summary relative risks (RRs) with corresponding 95% confidence intervals (CIs) were calculated. Publication bias was assessed by Begg's rank correlation test.

RESULTS

A total of eight studies fulfilled the eligibility criteria. We found that diabetic PCa patients who did not use metformin were at increased risk of cancer recurrence (RR, 1.20; 95%CI, 1.00-1.44), compared with those who used metformin. A similar trend was observed for other outcomes, but their relationships did not reach statistical significance. Funnel plot asymmetry was not observed among studies reporting recurrence (p=0.086).

CONCLUSIONS

Our results suggest that metformin may improve outcomes in PCa patients with concurrent T2D. Well-designed large studies and collaborative basic research are warranted.

Association between depression and glycemic control among type 2 diabetes patients in Lima, Peru

INTRODUCTION

There is limited and controversial information regarding the potential impact of depression on glycemic control. This study aims to evaluate the association between depression and poor glycemic control. In addition, the prevalence of depression and rates of poor glycemic control were determined.

METHODS

Cross-sectional study performed in the endocrinology unit of two hospitals of ESSALUD in Peru. The outcome of interest was poor glycemic control, evaluated by glycated hemoglobin (HbA1c: <7% versus ≥7%), whereas the exposure of interest was depression defined as 15 or more points in the Patient Health Questionnaire-9 tool. The association of interest was evaluated using Poisson regression models with robust standard errors reporting prevalence ratios (PR) and 95% confidence intervals (95% CI) adjusting for potential confounders.

RESULTS

A total of 277 participants, 184 (66.4%) males, mean age 59.0 (SD: 4.8), and 7.1 (SD: 6.8) years of disease were analyzed. Only 31 participants (11.2%; 95% CI: 7.5%-14.9%) had moderately severe or severe depression, whereas 70 (25.3%; 95% CI 20.3%-30.8%) had good glycemic control. Depression increased the probability of having poor glycemic control (PR=1.32; 95% CI 1.15-1.51) after adjusting for several potential confounders.

CONCLUSIONS

There is an association between depression and poor glycemic control among type 2 diabetes patients. Our results suggest that early detection of depression might be important to facilitate appropriate glycemic control and avoid further metabolic complications.

Achievement of partial combined control of major diabetes targets in primary care correlates with development of chronic complications in T2DM patients--A real life data

AIMS

Strict long term glucose, cholesterol and blood pressure control is advocated in type 2 Diabetes Mellitus (T2DM) patients. It is not known whether combined partial goals' achievement affects development of chronic complications.

METHODS

We evaluated the relative ability or failure of 5369 T2DM ambulatory patients to achieve and maintain control of blood pressure, glycaemia and cholesterol for 3 consecutive years. Correlation between the extent of combined goal achievement, and development of chronic complications was determined.

RESULTS

Only 9 patients (0.17%) fully achieved and none completely failed to achieve all strict goals. Therefore, patients were characterized as either partial achievers (PA) (n=699) or partial non achievers (PNA) (n=322). As compared to PA patients, PNA patients were significantly younger, single, and demonstrated a higher female and Arab ethnicity dominance. PNA patients had higher BMI, received more insulin treatment and consumed more hospital services. The incidence of microvascular complications during 3 years was significantly increased in PNA patients.

CONCLUSIONS

A negligible number of primary care patients completely and persistently achieve or fail to achieve combined control of major diabetes targets. Partial achievement of these targets correlates with specific patients' characteristics and incidence of chronic micro-vascular complications.

Diabetes Quality of Care Before and After Implementation of a Resident Clinic Practice Partnership System

Deficiencies in resident diabetes care quality may relate to continuity clinic design. This retrospective analysis compared diabetes care processes and outcomes within a traditional resident continuity clinic structure (2005) and after the implementation of a practice partnership system (PPS; 2009). Under PPS, patients were more likely to receive annual foot examinations (odds ratio [OR] = 11.6; 95% confidence interval [CI] = 7.2, 18.5), microalbumin screening (OR = 2.4; 95% CI = 1.6, 3.4), and aspirin use counseling (OR = 3.8; 95% CI = 2.5, 6.0) and were less likely to receive eye examinations (OR = 0.54; 95% CI = 0.36, 0.82). Hemoglobin A1c and lipid testing were similar between periods, and there was no difference in achievement of diabetes and blood pressure goals. Patients were less likely to achieve cholesterol goals under PPS (OR = 0.62; 95% CI = 0.39, 0.98). Resident practice partnerships may improve processes of diabetes care but may not affect intermediate outcomes.

Glycemic control and antidiabetic drugs in type 2 diabetes mellitus patients with renal complications

BACKGROUND

Good glycemic control can delay the progression of kidney diseases in type 2 diabetes mellitus (T2DM) patients with renal complications. To date, the association between antidiabetic agents and glycemic control in this specific patient population is not well established.

PURPOSE

This study aimed to identify antidiabetic regimens as well as other factors that associated with glycemic control in T2DM patients with different stages of chronic kidney disease (CKD).

PATIENTS AND METHODS

This retrospective, cross-sectional study involved 242 T2DM inpatients and outpatients with renal complications from January 2009 to March 2014 and was conducted in a tertiary teaching hospital in Malaysia. Glycated hemoglobin (A1C) was used as main parameter to assess patients' glycemic status. Patients were classified to have good (A1C <7%) or poor glycemic control (A1C ≥7%) based on the recommendations of the American Diabetes Association.

RESULTS

Majority of the patients presented with CKD stage 4 (43.4%). Approximately 55.4% of patients were categorized to have poor glycemic control. Insulin (57.9%) was the most commonly prescribed antidiabetic medication, followed by sulfonylureas (43%). Of all antidiabetic regimens, sulfonylureas monotherapy (P<0.001), insulin therapy (P=0.005), and combination of biguanides with insulin (P=0.038) were found to be significantly associated with glycemic control. Other factors including duration of T2DM (P=0.004), comorbidities such as anemia (P=0.024) and retinopathy (P=0.033), concurrent medications such as erythropoietin therapy (P=0.047), α-blockers (P=0.033), and antigouts (P=0.003) were also correlated with A1C.

CONCLUSION

Identification of factors that are associated with glycemic control is important to help in optimization of glucose control in T2DM patients with renal complication.

Quality of Diabetes Care: The Challenges of an Increasing Epidemic in Mexico. Results from Two National Health Surveys (2006 and 2012)

Background

The quality of diabetes care remains suboptimal according to numerous studies assessing the achievement of quality indicators for diabetes care in various healthcare settings. We report about global and specific quality indicators for diabetes care and their association to glycemic control at the population level in two national health surveys in Mexico.

Methods

We conducted a cross-sectional analysis of the 2006 and 2012 National Health Surveys in Mexico. We examined quality of care for 2,965 and 4,483 adults (≥ 20 years) with diagnosed type 2 diabetes using fourteen simple and two composite indicators derived from self-reported information. In a subsample for both surveys, glycated hemoglobin (HbA1c) was measured at the time of the interview. We obtained survey weight-adjusted estimators using multiple regression models (logistic and linear) with combined data files, including survey year as covariate to assess change.

Results

Global quality of care in 2012 was 40.8%, with a relative improvement of 11.7% between 2006 and 2012. Detections of cardiovascular disease risk factors (dyslipidemia and hypertension) were the indicators with the highest improvement, while non-pharmaceutical treatment and diabetic foot exams showed minor changes. We found a significant association between the quality of the process of diabetes care and glycemic control (OR 2.53, 95% CI 1.63-3.94). Age more than 65 years old, the type of health subsystem, gender (males), and high socio-economic status were also significantly associated to glycemic control.

Conclusions

Quality diabetes care and glycemic control improved and are significantly associated. However, according to international standards, the current situation remains suboptimal. A more holistic approach is needed, with an emphasis on improving quality in outpatient care.

Quality of Diabetic Care among Patients in a Tertiary Care Hospital in Bangalore, South India: A Cross-sectional Study

BACKGROUND

Despite high prevalence of diabetes, translation of practice recommendations to care is still deficient in Asian and developed countries. The objective of this study is to assess the quality of care provided to diabetic patients and extent of knowledge transfer by the provider to these patients as a measure of the quality of service.

MATERIALS AND METHODS

A cross sectional study was done among 190 diabetic patients over a period of 6 months. All type II diabetic patients, 30 years and above, who were diagnosed at least 1 year back without any other co-morbidity satisfied the inclusion criteria. They were interviewed based on an audit checklist formulated by National Diabetes Quality Improvement Alliance.

RESULTS

The results revealed that blood pressure is the only parameter which is regularly monitored in majority (93%) of the diabetics. Hb1AC, LDL cholesterol and eye check up were less common and done only in 40%, 52.6% and 56.8% of diabetics respectively. Only 33(17.37%) had at least 5 of the 7 essential parameters monitored at least once in the last year. The knowledge questionnaire showed that more than 70% of the diabetic patients know that their condition requires lifelong management, diet modifications and exercises. There was no difference in the knowledge scores between the people who had no essential tests done and those diabetics who got 5 essential tests done. Gender, education, occupation and duration of diabetes were associated with knowledge score.

CONCLUSION

There is a need to formulate the local standards of care and clinical practice guidelines for the management of diabetes that are easily affordable and available to the health care providers and applicable to our country at the national level. Continuing audit of patients with diabetes is a feasible and a very useful method of promoting and helping to achieve the management goals of a good quality care.

Insulin and other antidiabetic drugs and hepatocellular carcinoma risk: a nested case-control study based on Italian healthcare utilization databases

PURPOSE

Insulin and other antidiabetic drugs may modulate hepatocellular carcinoma (HCC) risk in diabetics.

METHODS

We have analyzed the role of various antidiabetic drugs on HCC in a nested case-control study using the healthcare utilization databases of the Lombardy Region in Italy. This included 190 diabetic subjects with a hospital discharge reporting a diagnosis of malignant HCC and 3772 diabetic control subjects matched to each case on sex, age, date at cohort entry, and duration of follow-up.

RESULTS

Increased risks of HCC were found for use of insulin (odds ratio [OR] = 3.73, 95% confidence interval [CI] 2.52-5.51), sulfonylureas (OR = 1.39, 95%CI 0.98-1.99), and repaglinide (OR = 2.12, 95%CI 1.38-3.26), while a reduced risk was found for use of metformin (OR = 0.57, 95%CI 0.41-0.79). The risk of HCC increased with increasing duration of insulin use (OR = 2.52 for <1 year, 5.41 for 1-2 years, and 6.01 for ≥2 years; p for trend < 0.001), while no clear pattern with duration was observed for sulfonylureas, repaglinide, and metformin.

CONCLUSION

Our study supports the evidence that patients with diabetes using metformin, and possibly other antidiabetic drugs that increase insulin sensibility, have a reduced risk of HCC, while those using insulin or drugs that increase circulating insulin, such as insulin secretagogues, have an increased risk. Whether these associations are causal, or influenced by different severity of diabetes and/or possible residual bias or misclassification, is still open to discussion.

Predictors of poor glycaemic control in older patients with type 2 diabetes mellitus

INTRODUCTION

We assessed the predictors of poor glycaemic control among older patients with type 2 diabetes mellitus (T2DM) in Malaysia.

METHODS

This cross-sectional study used the data of 21,336 patients aged ≥ 60 years with T2DM from the Adult Diabetes Control and Management Registry 2008-2009.

RESULTS

Predictors of poor glycaemic control were: age groups 60-69 years (odds ratio [OR] 1.96, 95% confidence interval [CI] 1.66-2.33) and 70-79 years (OR 1.43, 95% CI 1.20-1.71); Malay (OR 1.53, 95% CI 1.41-1.66) and Indian (OR 1.32, 95% CI 1.19-1.46) ethnicities; T2DM durations of 5-10 years (OR 1.46, 95% CI 1.35-1.58) and > 10 years (OR 1.75, 95% CI 1.59-1.91); the use of oral antidiabetic agents only (OR 5.86, 95% CI 3.32-10.34), insulin only (OR 17.93, 95% CI 9.91-32.43), and oral antidiabetic agents and insulin (OR 29.42, 95% CI 16.47-52.53); and elevated blood pressure (OR 1.10, 95% CI 1.01-1.20), low-density lipoprotein cholesterol (OR 1.48, 95% CI 1.38-1.59) and triglycerides (OR 1.61, 95% CI 1.51-1.73). Hypertension (OR 0.71, 95% CI 0.64-0.80), hypertension and dyslipidaemia (OR 0.68, 95% CI 0.61-0.75), pre-obesity (OR 0.89, 95% CI 0.82-0.98) and obesity (OR 0.76, 95% CI 0.70-0.84) were less likely to be associated with poor glycaemic control.

CONCLUSION

Young-old and middle-old age groups (i.e. < 80 years), Malay and Indian ethnicities, longer T2DM duration, the use of pharmacological agents, and elevated blood pressure and lipid levels were associated with poor glycaemic control. The presence of comorbidities, pre-obesity and obesity were less likely to be associated with poor glycaemic control.

Evaluating Primary Care Physician Performance in Diabetes Glucose Control

This study demonstrates that it is possible to identify primary care physicians (PCPs) who perform better or worse than expected in managing diabetes. Study subjects were 14 033 adult diabetics and their 133 PCPs. Logistic regression was used to predict the odds that a patient would have uncontrolled diabetes (defined as HbA1c ≥8%) based on patient-level characteristics alone. A second model predicted diabetes control from physician-level identity and characteristics alone. A third model combined the patient- and physician-level models using hierarchical logistic regression. Physician performance is calculated from the difference between the expected and observed proportions of patients with uncontrolled diabetes. After adjusting for important patient characteristics, PCPs were identified who performed better or worse than expected in managing diabetes. This strategy can be used to characterize physician performance in other chronic conditions. This approach may lead to new insights regarding effective and ineffective treatment strategies.

Poor glycemic control in type 2 diabetes in the South of the Sahara: the issue of limited access to an HbA1c test

BACKGROUND

Management of type 2 diabetes remains a challenge in Africa. The objective of this study was to evaluate the prevalence and predictors of poor glycemic control in patients with type 2 diabetes living in sub-Saharan.

PATIENTS AND METHODS

This was a cross-sectional study involving 1267 people (61% women) with type 2 diabetes (mean age 58 years) recruited across health facilities in Cameroon and Guinea. Predictors of poor glycemic control (HbA1c ≥7.0% (53 mmol/mol)) were investigated via logistic regressions.

RESULTS

The mean body mass index was 27.4 ± 5.8 kg/m(2), and 74% of patients had poor glycemic control. Predictors of poor glycemic control in multivariable regression models were recruitment in Guinea [odd ratio: 2.91 (95% confidence interval 2.07 to 4.11)], age <65 years [1.40 (1.04 to 1.88)], diabetes duration ≥3 years [2.36 (1.74 to 3.21)], treatment with: oral glucose control agents [3.46 (2.28 to 5.26)], insulin alone or with oral glucose control agents [7.74 (4.70 to 12.74)] and absence of a previous HbA1c measurement in Guinea [2.96 (1.30 to 6.75)].

CONCLUSION

Poor control of blood glucose is common in patients with type 2 diabetes in these two countries. Limited access to HbA1c appears to be a key factor associated with poor glycemic control in Guinea, and should be addressed by health policies targeting improvement in the outcomes of diabetes care.

Distinct HbA1c trajectories in a type 2 diabetes cohort

AIMS

The aim of this study was to identify subgroups of type 2 diabetes mellitus patients with distinct hemoglobin A1c (HbA1c) trajectories. Subgroup characteristics were determined and the prevalence of microvascular complications over time was investigated.

STUDY DESIGN AND SETTING

Data from a cohort of 5,423 type 2 diabetes patients from a managed primary care system were used [mean follow-up 5.7 years (range 2-9 years)]. Latent class growth modeling was used to identify subgroups of patients with distinct HbA1c trajectories. Multinomial logistic regression analyses were conducted to determine which characteristics were associated with different classes.

RESULTS

Four subgroups were identified. The first and largest subgroup (83 %) maintained good glycemic control over time (HbA1c ≤53 mmol/mol), the second subgroup (8 %) initially showed severe hyperglycemia, but reached the recommended HbA1c target within 2 years. Patients within this subgroup had significantly higher baseline HbA1c levels but were otherwise similar to the good glycemic control group. The third subgroup (5 %) showed hyperglycemia and a delayed response without reaching the recommended HbA1c target. The fourth subgroup (3.0 %) showed deteriorating hyperglycemia over time. Patients within the last two subgroups were significantly younger, had higher HbA1c levels and a longer diabetes duration at baseline. These subgroups also showed a higher prevalence of retinopathy and microalbuminuria.

CONCLUSION

Four subgroups with distinct HbA1c trajectories were identified. More than 90 % reached and maintained good glycemic control (subgroup one and two). Patients within the two subgroups that showed a more unfavorable course of glycemic control were younger, had higher HbA1c levels and a longer diabetes duration at baseline.

Nutritional status, glycemic control and its associated risk factors among a sample of type 2 diabetic individuals, a pilot study

BACKGROUND

The prevalence of type 2 diabetes is increasing in Malaysia, with most patients poorly controlled. Hence, this study aimed to determine nutritional and metabolic status as well as blood pressure of Malaysian patients with type 2 diabetes mellitus and identify associated risk factors for poor glycemic control.

MATERIALS AND METHODS

A total of 104 type 2 diabetic patients were recruited and completed a questionnaire covering socio-demographic status, 3-day diet records, and physical activity. Anthropometry and glycemic control parameters, lipid profile and blood pressure were also measured.

RESULTS

Subjects were on average 56.7±9.9 years old with a mean duration of diabetes of 6.5 ± 5.0 years. The mean hemoglobin A1c of the subjects was 7.6% ± 1.4%, with only 20.2% achieving the target goal of <6.5% with no significant differences between genders. The mean body mass index was 26.9 ± 4.7 kg/m(2), with 86.5% either were overweight or obese. Only 10.6% of the subjects exercised daily. The proportions of macronutrients relative to total energy intake were consistent with the recommendations of most diabetes associations. The adjusted odds of having poor glycemic control were 3.235 (1.043-10.397) (P < 0.05) higher among those who had high density lipoprotein cholesterol levels below the normal range. Those taking one or two types of oral anti-diabetic drugs had 19.9 (2.959-87.391) (P < 0.01) and 14.3 (2.647-77.500) (P < 0.01) higher odds of poor glycemic control respectively compared to those who were being treated by diet alone.

CONCLUSION

Poor glycemic control was prevalent among Malaysian diabetic patients, and this could be associated with low levels of HDL and being treated with oral anti-diabetes agents.

Lifestyle interventions for adults with impaired glucose tolerance: a systematic review and meta-analysis of the effects on glycemic control

OBJECTIVE

Previous meta-analyses have demonstrated that lifestyle modification can reduce the blood glucose levels in patients with type 2 diabetes, although the effects of changes in the blood glucose level on impaired glucose tolerance (IGT) remain controversial. This review therefore aimed to determine the efficacy of lifestyle interventions in adults with IGT.

METHODS

We searched the Medline, Cochrane Library, EMBASE and Science Citation Index databases and reference lists of the included articles. Two independent reviewers extracted the data and assessed the quality of the included studies; a total of nine randomized controlled trials met the inclusion criteria. In addition, we tested for trial heterogeneity and calculated the pooled effects size using the random effects model.

RESULTS

The overall interventions were associated with a decline in the 2-hour plasma glucose levels [standardized mean differences (SMD) -0.56; 95% confidence interval (CI), -1.01 to -0.10; I(2), 96.6%]. Moreover, dietary intervention (SMD -0.53; 95% CI -0.77 to -0.28) and physical intervention (SMD -0.42; 95% CI -0.63 to -0.20) were each associated with a decline in the 2-hour plasma glucose levels compared with that observed in the control participants. The overall interventions were associated with a decline in the fasting plasma glucose (FPG) levels (SMD -0.27; 95% CI -0.38 to -0.15; I(2) = 47.1%). In addition, physical intervention (SMD -0.25; 95% CI -0.44 to -0.05) and combined dietary and physical intervention were each associated with a decreased FPG level (SMD -0.28; 95% CI -0.44 to -0.12) compared with that observed in the control participants.

CONCLUSION

Lifestyle modification based on physical or dietary interventions or both is associated with improvements in the 2-hour plasma glucose and FPG levels in IGT patients.

Level of sustained glycemic control and associated factors among patients with diabetes mellitus in Ethiopia: a hospital-based cross-sectional study

BACKGROUND

The level of sustained glycemic control in patients with diabetes mellitus (DM) is a major determinant of the occurrence of both acute and chronic complications. However, information about the level of glycemic control among patients in the follow-up care at the University of Gondar Referral Hospital is scanty. The study assessed the degree of glycemic control and associated factors among diabetic patients in the study area.

METHOD

A hospital-based cross-sectional study was conducted at the University of Gondar Referral Hospital. All diabetic patients aged ≥18 years who visited the Diabetes Clinic in January and February 2013 for follow-up medical evaluation and medication participated in the study. Patients with glycosylated hemoglobin test (HbA1c) of ≥7% were classified as having a poor level of glycemic control. Propensity score was used to estimate the treatment effect. Multivariable logistic regression analysis was applied to determine the associated factors.

RESULT

Two hundred and fifty three (64.7%) of the 391 diabetic patients included in the study had a poor level of glycemic control, as evidenced by HbA1c ≥7%. Poor glycemic control was much higher among Type 1 patients (82.9%) compared with Type 2 patients (57.5%). Being on insulin treatment (AOR =2.51; 95% CI =1.25, 5.04) and reporting poor medication adherence (AOR =3.19; 95% CI =1.76, 5.80) were found to be associated with poor glycemic control among Type 2 DM patients. High waist circumference was inversely associated with a poor level of glycemic control in Type 1 DM patients (AOR =0.05; 95% CI =0.01, 0.85).

CONCLUSION

The proportion of diabetic patients with a poor level of glycemic control is high. We recommend a comprehensive intervention to improve the overall treatment adherence with special attention to DM patients receiving insulin.

Factors associated with persistent poorly controlled diabetes mellitus: clues to improving management in patients with resistant poor control

OBJECTIVES

Patients with persistent poorly controlled diabetes mellitus (PPDM), defined as an uninterrupted hemoglobin A1c >8.0% for ≥1 year despite standard care, are at high risk for complications. Additional research to define patient factors associated with PPDM could suggest barriers to improvement in this group and inform the development of targeted strategies to address these patients' resistant diabetes.

METHODS

We analyzed patients with type 2 diabetes from a multi-site randomized trial. We characterized patients with PPDM relative to other patients using detailed survey data and multivariable modeling.

RESULTS

Of 963 patients, 118 (12%) had PPDM, 265 (28%) were intermittently poorly controlled, and 580 (60%) were well-controlled. Patients with PPDM had younger age, earlier diabetes diagnosis, insulin use, higher antihypertensive burden, higher low-density lipoprotein cholesterol, and lower statin use relative to well-controlled patients. Among patients with objective adherence data (Veterans Affairs patients), a larger oral diabetes medication refill gap was associated with PPDM.

DISCUSSION

Strategies are needed to target-specific barriers to improvement among patients whose diabetes is resistant to standard diabetes care. Our data suggest that strategies for targeting PPDM should accommodate younger patients' lifestyles, include medication management for insulin titration and comorbid disease conditions, and address barriers to self-management adherence.

Age-related differences in diabetes care outcomes in Korea: a retrospective cohort study

Background

Age-related differences in diabetes outcomes are important both for clinical and policy considerations. To clarify the basis of such differences, we investigated patterns of associations for age in relation to hospitalization and glycemic control and examined the role of other factors.

Methods

4471 patients with diabetes aged 40–79 years were drawn from a retrospectively retrieved National Health Insurance Cohort. Using logistic regression, risk factors measured over the two years (2007–2008) were examined for their associations with hospitalization and poor glycemic control during the last year (2009) of follow-up.

Results

Compared to the middle-aged patients, older patients were more likely to have been hospitalized (Adjusted odds ratio (OR_adjusted) = 1.97(95% CI = 1.28, 3.04) for the oldest group (ages 70–79) vs youngest group (ages 40–49)) but less likely to have poor glycemic control (OR_adjusted = 0.45 (95% CI = 0.37, 0.56) for the oldest group vs youngest group). Older patients were also less likely to be obese but had more complications, longer duration of diabetes, lower continuity of care, and higher blood pressure and total cholesterol level. The pattern of associations for hospitalization and glycemic control was not uniform across the risk factors, sharing only a few common factors such as the duration of diabetes and blood pressure. In general, poor glycemic control was affected predominantly by metabolic management, while hospitalization was strongly related to functional status (i.e., number of complications) and care quality measures (i.e., continuity of care).

Conclusion

Hospitalization was higher among the older diabetic patients, despite better glycemic control. Factors were differently associated with the two diabetes-related outcomes, providing more comprehensive risk profiles for hospitalization. The co-existence of improved glycemic control and increased hospitalization among older diabetic patients suggests an extension of a geriatric evaluation to wider functional and comorbidity status.

The Role of Educational Level in Glycemic Control among Patients with Type II Diabetes Mellitus

OBJECTIVES

To evaluate the impact of the educational level on glycemic control among patients with type II diabetes mellitus.

METHODS

A disproportional systematic stratified sample of 384 patients, based on educational level, was selected from patients of type II diabetes attending the Primary Care Clinic of King Khalid University Hospital, over a period of 6 months in 2012-2013. A questionnaire sought information about socio-demographic factors, clinical characteristics, awareness of diabetic complications and self-care management behaviors. Weight and height were measured. Poor glycemic control was defined as HbA1c ≥7%.

RESULT

The rate of patients who had poor glycemic control is 67.7%. The educational level had no impact on glycemic control, but the patients of high educational level had better awareness of the complications and a high rate of adherence to diet. About 70.5% of patients were aware of two or more diabetic complications. The factors associated with poor control included increased duration of diabetes, use of insulin and oral hypoglycemic agents combination, being obese or overweight, poor adherence to diet, poor adherence to exercise and poor compliance with follow up. This study found a high rate of poor adherence to diet (68%) and poor adherence to exercise (79.4%).

CONCLUSION

The proportion of patients with poor glycemic control was high in this study. This study showed that educational level may not be a good predictor of better therapeutic compliance. In-spite of the significant importance of appropriate diet and exercise in the control of diabetes, there was a high rate of poor adherence to diet and to exercise, especially among females. Educational programs that emphasize adherence to treatment regimens as a whole, especially to diet, to exercise and to regular follow up are of greater benefit in glycemic control as compared to compliance of medications alone.

Glycemic control in patients with type 2 diabetes mellitus in Spain

OBJECTIVE

To evaluate the degree of glycemic control in patients with type 2 diabetes in Spain and identify factors associated with glycemic control.

PATIENTS AND METHODS

This was a cross-sectional, multicenter, epidemiological study that used consecutive sampling and was conducted in primary care practices in Spain. A total of 5591 patients with type 2 diabetes mellitus lasting more than 1 year and who were treated with hypoglycemic agents for more than 3 months were included in the study. At a single visit, HbA1c levels were measured (A1cNow+ system) and demographic and clinical variables related to diabetes and its treatment were recorded. During the visit, CV risk factors (CVRF), the presence of target-organ damage (TOD), the presence of hypoglycemia and body weight changes within the previous year were recorded.

RESULTS

We analyzed data from 5382 patients (mean age 66.7 [10.8] years, mean duration of the diabetes 8.8 [6.3] years). TOD was present in 43.6% of the patients and 59.1% were taking 2 or more drugs. The patients' mean HbA1c was 7.1 (1.1)%, and 48.6% had HbA1c levels <7.0%. The patients with HbA1c levels ≥7.0% had longer-standing diabetes, a higher prevalence of TOD and CVRF, used more complex therapies, experienced more hypoglycemic episodes in the previous year and had more weight gain. In the multivariate analysis, the absence of insulin treatment, the absence of abdominal obesity and atherogenic dyslipidemia, a duration of the diabetes <10 years and an age >70 years were associated with improved glycemic control.

CONCLUSIONS

Patients with poorly controlled type 2 diabetes mellitus are highly prevalent in Spain. Factors associated with poorer glycemic control include the complexity of both the disease and the hypoglycemic therapy, a history of hypoglycemia and weight gain.

Level of A1C control and its predictors among Lebanese type 2 diabetic patients

AIM

Lebanon is among the top 10 countries with the highest prevalence of diabetes in the Middle East region with estimates reaching as high as 16.6% in adults aged 20-79 years. The objective of this study was to assess the level of A1C control among a cohort of type 2 diabetic patients and factors associated with uncontrolled A1C.

METHODS

We carried out a retrospective observational study among type 2 diabetes mellitus patients attending an outpatient endocrinologist's clinic between June 2008 and July 2012 in Beirut, Lebanon. Two groups were compared, based on their diabetic control (A1C < 7% and A1C ≥ 7%).

RESULTS

A total of 551 patients were included in this study, where 31.8% attained A1C control. Crude analyses showed that some factors were significantly associated with uncontrolled A1C, and these were long-standing diabetes, diabetes-related complications, uncontrolled blood pressure, lipid profile, as well as the use of metformin, sulfonylurea, or insulin. When multivariate analysis was carried out, the chances of having uncontrolled A1C were significantly higher among patients who developed neuropathy (odds ratio [OR] 2.08, 95% confidence interval [CI] 1.11-3.90), had uncontrolled triglycerides (OR 1.98, 95% CI 1.33-2.94), used insulin (OR 4.52, 95% CI 2.32-8.83), and sulfonylureas (OR 2.88, 95% CI 1.88-4.40).

CONCLUSION

Uncontrolled diabetes is more likely to exist in patients with neuropathy, uncontrolled triglycerides and those using insulin or sulfonylurea. Further research is needed to confirm the findings.

Age of diabetes diagnosis and diabetes duration associate with glycated haemoglobin

An earlier age of diagnosis (r=-0.28, p<0.0001) and longer duration of type 2 diabetes (r=0.26, p<0.0001) were each found to correlate with higher HbA1c level, on analysis of a diabetes centre database in people under regular shared care. When combined, these biological variables strongly associate with the current HbA1c level.

The role of TNF-α G-308A promoter polymorphism in glycemic control in Type 2 diabetes patients

BACKGROUND

TNF-α polymorphisms were shown to be associated with insulin resistance and diabetes development and complications.

AIM

To investigate the association between glycemic control in Type 2 diabetes patients and TNF-α G-308A single nucleotide polymorphism (SNP).

METHODS

This was a cross-sectional observational study, where diabetes patients from both genders (170 male and 185 female) were enrolled in the study. Patients were divided into two groups: good glycemic control (n = 158) and poor glycemic control (n = 197). Genotyping of TNF-α G-308A SNP was carried out using restriction fragment length polymorphisms-polymerase chain reaction.

RESULTS

The results showed that TNF-α G-308A SNP is strongly associated with glycemic control in type 2 diabetes patients. Patients with the AA and AG genotypes had better glycemic control than those with GG genotype (P < 0.01). Other parameters that impacted glycemic control include duration of the disease (P < 0.01) and response to insulin therapy (P < 0.01). However, no contribution for gender or statins use to glycemic control was observed (P > 0.05).

CONCLUSION

TNF-α G-308A SNP might modulate glycemic control among type 2 diabetes patients.

Current level of glycaemic control and its associated factors in patients with type 2 diabetes across Europe: data from the PANORAMA study

OBJECTIVE

To provide an update on glycaemic control in European patients with type 2 diabetes based on data from the nine-country, cross-sectional PANORAMA study (NCT00916513).

DESIGN

Post-hoc analysis to report the number of patients achieving/not achieving glycaemic goal (HbA(1c) <7%).

PATIENTS

Patients were randomly or consecutively selected from physician practices in nine countries. Eligible patients were aged ≥40 years, diagnosed with type 2 diabetes >1 year prior to study entry, and had an available medical record of >1 year.

MEASUREMENTS

All data were collected at a single visit, including HbA1c measurement using a common device (A1CNow). Bivariate and multivariate analyses were used to investigate factors associated with not reaching glycaemic goal.

RESULTS

Of 5817 patients enrolled (aged 65·9 ± 10·4 years, 53·7% male), 37·4% had an HbA(1c) ≥7%; (range 25·9% in The Netherlands to 52·0% in Turkey). In adjusted multivariate analyses, higher individual glycaemic target, younger age, poor physician-reported patient adherence to lifestyle/medication, longer diabetes duration, increasing treatment regimen complexity and physician-reported patient's unwillingness to intensify treatment were associated with not achieving goal. However, bivariate analyses also found gender, socioeconomic factors, body mass index, rate of complications and hypoglycaemia to be associated with not achieving goal.

CONCLUSIONS

In PANORAMA, 37·4% of patients enrolled were not at glycaemic goal. Factors relating to patient characteristics, physician selection of individualized HbA1c target and diabetes itself (longer duration, more complex treatment) were strongly associated with not achieving goal. Further studies are warranted to explore these associations and evaluate strategies for improving glycaemic control.

Predictive and explanatory factors of change in HbA1c in a 24-week observational study of 66,726 people with type 2 diabetes starting insulin analogs

OBJECTIVE

Individualization of therapy choices requires the prediction of likely response. Predictor and explanatory factors of change in HbA1c were studied using data from a large observational study of starting insulin analog therapy (the A1chieve study).

RESEARCH DESIGN AND METHODS

Univariate analyses were performed for insulin-naive people and prior insulin users in the A1chieve study. Statistically significant factors were carried forward to baseline factor-only multivariate analyses ("predictor" analysis), and separately using all significant factors ("explanatory" analysis). Power was considered in terms of the variance explained.

RESULTS

Geographical region, baseline HbA1c level, lipid levels, and baseline insulin dose were the most powerful predictors of HbA1c change (mean change -2.1% [-23 mmol/mol]) observed in the univariate analysis (r2 > 0.010, P < 0.001). However, although the predictor and explanatory multivariate models explained 62-82% of the variance in HbA1c change, this was mainly associated with baseline HbA1c (r2 = 0.544-0.701) and region (r2 = 0.014-0.037). Other factors were statistically significant but had low predictive power (r2 < 0.010); in the explanatory analysis, this included end-of-study hypoglycemia (insulin-naive group), insulin dose, and health-related quality of life (r(2) < 0.001-0.006, P ≤ 0.007).

CONCLUSIONS

Many factors can guide clinicians in predicting the response to starting therapy with insulin analogs, but many are interdependent and thus of poor utility. The factor explaining most of the variance in HbA1c change is baseline HbA1c level, with each increase of 1.0%-units (11 mmol/mol) providing a 0.7-0.8%-units (8-9 mmol/mol) greater fall. Other factors do not explain much of the remaining variance, even when including all end-of-trial measures.