Predictors of glycemic control in insulin-using adults with type 2 diabetes

The Japanese version of Problem Areas in Diabetes Scale: a clinical and research tool to assess emotional functioning among people with diabetes

Introduction

The purpose of this study was to develop the Japanese version of the Problem Areas in Diabetes (PAID) scale, a measure of emotional adjustment to diabetes that has been translated into Japanese by our group.

Materials and methods

A total of 418 Japanese people with diabetes attending our outpatient clinic participated (n = 65 type 1 and n = 353 type 2). We assessed the internal reliability of the PAID, examined correlations of the PAID with conceptually related psychosocial constructs, evaluated mean differences in the PAID between diabetes treatment groups, and examined correlations of the PAID with diabetes self-care behaviours and selected treatment outcomes.

Results

Results showed that the PAID had excellent reliability (Cronbach alpha = 0.934). The PAID correlated significantly with the Diabetes Treatment Satisfaction Questionnaire (r = -0.593, p < 0.0001) and the positive wellbeing (r = -0.396, p < 0.0001), negative wellbeing (r = -0.640, p < 0.0001) and energy (r = -0.444, p < 0.0001) subscales of the Wellbeing Questionnaire. Adherence to diet was negatively correlated with PAID score (r = -0.263, p < 0.0001). The frequency of recent hypoglycemia and number of chronic complications (retinopathy, nephropathy and neuropathy) were positively correlated with PAID scores. PAID was weakly correlated with HbA1c (r = 0.13, p = 0.01).

Conclusions

In conclusion, the Japanese version of the PAID demonstrated good internal reliability and evidence of concurrent and discriminant validity. The PAID measures the impact of diabetes, diabetes treatment and treatment outcomes on the emotions of people with diabetes. The results provide encouraging evidence for the clinical utility of the PAID in Japanese people with diabetes.

Predicting Response to Bolus Insulin Therapy in Patients With Type 2 Diabetes

BACKGROUND

The aim of this study was to develop a predictive model to classify people with type 2 diabetes (T2D) into expected levels of success upon bolus insulin initiation.

METHODS

Machine learning methods were applied to a large nationally representative insurance claims database from the United States (dNHI database; data from 2007 to 2017). We trained boosted decision tree ensembles (XGBoost) to assign people into Class 0 (never meeting HbA1c goal), Class 1 (meeting but not maintaining HbA1c goal), or Class 2 (meeting and maintaining HbA1c goal) based on the demographic and clinical data available prior to initiating bolus insulin. The primary objective of the study was to develop a model capable of determining at an individual level, whether people with T2D are likely to achieve and maintain HbA1c goals. HbA1c goal was defined at <8.0% or reduction of baseline HbA1c by >1.0%.

RESULTS

Of 15 331 people with T2D (mean age, 53.0 years; SD, 8.7), 7800 (50.9%) people met HbA1c goal but failed to maintain that goal (Class 1), 4510 (29.4%) never attained this goal (Class 0), and 3021 (19.7%) people met and maintained this goal (Class 2). Overall, the model's receiver operating characteristic (ROC) was 0.79 with greater performance on predicting those in Class 2 (ROC = 0.92) than those in Classes 0 and 1 (ROC = 0.71 and 0.62, respectively). The model achieved high area under the precision-recall curves for the individual classes (Class 0, 0.46; Class 1, 0.58; Class 2, 0.71).

CONCLUSIONS

Predictive modeling using routine health care data reasonably accurately classified patients initiating bolus insulin who would achieve and maintain HbA1c goals, but less so for differentiation between patients who never met and who did not maintain goals. Prior HbA1c was a major contributing parameter for the predictions.

Does Gender Influence the Effectiveness and Safety of Insulin Glargine 300 U/ml in Patients with Uncontrolled Type 2 Diabetes? Results from the REALI European Pooled Analysis

INTRODUCTION

Gender differences in risk factors and treatment outcomes for type 2 diabetes mellitus (T2DM) may exist. We used the REALI European database to investigate whether there were gender-specific differences in baseline characteristics and clinical outcomes among patients with inadequately controlled T2DM initiated on insulin glargine 300 U/ml (Gla-300).

METHODS

Data were pooled from 14 multicentre, prospective, interventional and non-interventional studies. Impact of gender on glycaemic control, insulin dose, body weight and hypoglycaemia was evaluated after 12 and 24 weeks of Gla-300 treatment.

RESULTS

Women (N = 3857) were older than men (N = 4376) (median age, 65.0 versus 63.0 years), with greater mean body mass index (32.5 versus 31.6 kg/m²) and lower median estimated glomerular filtration rate (77.5 versus 84.0 ml/min/1.73 m²). Peripheral arterial disease and a history of myocardial infarction were more frequent in men (20.1% versus 11.7% and 12.0% versus 5.8%, respectively). At baseline, mean haemoglobin A1c (HbA1c) was 8.74% in men and 8.79% in women. Least square (LS) mean (95% CI) reduction in HbA1c from baseline to week 24 was - 1.17% (- 1.21 to - 1.13) in men and - 1.07% (- 1.11 to - 1.02) in women, resulting in a LS mean difference of - 0.10% (- 0.15 to - 0.05; p < 0.0001). At 24 weeks, 21.6% of women and 27.2% of men achieved target HbA1c of < 7.0% (p < 0.001; chi-square). Reported incidence for symptomatic (8.5% versus 8.7%) and severe (0.3% versus 0.5%) any-time-of-the-day or symptomatic (2.4% versus 1.8%) and severe (0.1% versus 0.2%) nocturnal hypoglycaemia was overall low and comparable between men and women. Changes in daily Gla-300 dose and body weight were also similar.

CONCLUSION

Despite some gender differences in baseline characteristics, Gla-300 treatment improved glycaemic control, with overall low hypoglycaemia incidences in both men and women. However, women had statistically significantly lower HbA1c reductions than men, although these differences were clinically modest.

Real-world clinical outcomes and costs in type 2 diabetes mellitus patients after initiation of insulin therapy: A German claims data analysis

BACKGROUND

This study describes real-world treatment-related outcomes and healthcare costs of German type 2 diabetes mellitus (T2D) patients who initiated insulin therapy.

METHODS

This retrospective analysis includes German claims data from 01/01/2012 until 31/12/2016. Identification of eligible patients took place between 01/01/2013 and 31/12/2015, allowing for at least 1 year of follow-up. Clinical outcomes, such as HbA1c values and body mass index, were observed in a subpopulation participating in a Disease Management Program. Healthcare expenditures were evaluated for the first year of therapy.

RESULTS

Overall, 27,340 insulin starters with T2D were observed (mean age: 72.2 years, female: 51.4%). Treatment-related outcomes were evaluated in a subsample of 12,034 patients. Patients who started insulin combined with other antidiabetic drugs (ADs) achieved their HbA1c goals more frequently than patients on insulin monotherapy (+10.7 percentage points [pp] vs. +21.1 pp for insulin plus metformin). All-cause costs were by far highest among patients with insulin monotherapy (€ 12,283 per patient-year) compared with patients receiving a combined AD regimen (€ 9,947-10,509 per patient-year).

CONCLUSIONS

Changes in HbA1c values were not in favor of insulin monotherapy, compared to regimens including other ADs. It was also associated with higher costs, suggesting that insulin alone is a suboptimal treatment.

Factors affecting achievement of glycemic targets among type 2 diabetes patients in South Asia: Analysis of the CARRS trial

OBJECTIVE

To assess the predictors of achieving and maintaining guideline-recommended glycemic control in people with poorly controlled type 2 diabetes.

METHODS

We analyzed data from the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) Trial (n = 1146), to identify groups that achieved guideline-recommended glycemic control (HbA1c < 7%) and those that remained persistently poorly controlled (HbA1c > 9%) over a median of 28 months of follow-up. We used generalized estimation equations (GEE) analysis for each outcome i.e. achieving guideline-recommended control and persistently poorly controlled and constructed four regression models (demographics, disease-related, self-care, and other risk factors) separately to identify predictors of HbA1c < 7% and HbA1c > 9% at the end of the trial, adjusting for trial group assignment and site.

RESULTS

In the final multivariate model, adherence to prescribed medications (RR: 1.46, 95%CI: 1.09, 1.95), adherence to diet plans (RR: 1.79, 95% CI: 1.43, 2.23) and middle-aged: 50-64 years (RR: 1.32; 95% CI: 1.02-1.71) were associated with achieving guideline-recommended control (HbA1c < 7%). Presence of microvascular complications (RR: 0.70; 95%CI: 0.53-0.92) reduced the probability of achieving guideline-recommended glycemic control (HbA1c 7%). Further, longer duration of diabetes (>15 years), RR: 1.41; 95% CI: 1.15, 1.72, hyperlipidemia, RR: 1.19; 95% CI: 1.06, 1.34 and younger age group (35-49 years vs. >64 years: RR: 0.61; 95% CI: 0.47-0.79) were associated with persistently poor glycemic control (HbA1c > 9%).

CONCLUSION

To achieve and maintain guideline-recommended glycemic control, care delivery models must put additional emphasis and effort on patients with longer disease duration, younger people and those having microvascular complications and hyperlipidemia.

Relationship between a single measurement at baseline of body mass index, glycated hemoglobin, and the risk of mortality and cardiovascular morbidity in type 2 diabetes mellitus

Objective

This study aims to evaluate the relationship between a single measurement at baseline of body mass index (BMI), glycated hemoglobin (HbA1c) and subsequent clinical outcomes in patients with type 2 diabetes mellitus (T2DM).

Method

Patients with T2DM were recruited from an outpatient diabetes clinic in a single large teaching hospital in Kingston upon Hull, UK. At baseline, demographics and HbA1c were recorded. Patients were categorized by BMI: normal weight (18.5-24.9 kg/m²), overweight (25-29.9 kg/m²), and obese (>30 kg/m²). Multivariable Cox regression models that included demographic, risk factors, and comorbidities were separately constructed for all-cause, cardiovascular, cancer and sepsis-related mortality, using four groups of HbA1c (<6%, 6.0-6.9%, 7.0-7.9%, and >8%).

Results

In total, 6220 patients with T2DM (median age 62 years, 54% male) were followed for a median of 10.6 years. HbA1c levels >8.0% were associated with increased risk of all-cause mortality and cardiovascular death. However, this increased risk was not consistent across the weight categories and reached statistical significance only in overweight patients (BMI 25-29.9 kg/m²).

Conclusions

In a large cohort of patients with T2DM elevated HbA1c levels at baseline did not consistently predict increased risk of all-cause and cardiovascular mortality across the different BMI categories.

Glycated Hemoglobin and Blood Pressure Levels in Adults With Type 2 Diabetes: How Many Patients Are on Target?

OBJECTIVES

Achieving glycated hemoglobin (A1C) and blood pressure targets is an important strategy for preventing chronic vascular complications in diabetes. Our aim in this study was to determine the proportion of type 2 diabetes patients who meet the recommended A1C and arterial blood pressure targets and to identify the determinants of failure to do so.

METHODS

A cross-sectional study was conducted in an outpatient endocrine clinic at a university hospital. The A1C goal was 7% in general and 8% for patients with advanced chronic complications. Regarding blood pressure, the overall expected target was 140/90 mmHg.

RESULTS

A total of 602 type 2 diabetes patients were analyzed: 62% were female, 14% self-reported as black, mean age was 63±11 years, mean diabetes duration was 17±9 years and median A1C was 8.0% (interquartile range, 7.0% to 9.5%). Macrovascular disease was present in 33% of the patients, diabetic retinopathy in 47%, peripheral neuropathy in 43% and diabetic kidney disease in 56%. Regarding metabolic control, 403 (67%) patients were not at the adjusted target A1C level, and being female, black, young and an insulin user were the main determinants of poor glycemic control. Regarding blood pressure, 348 (58%) patients were not at the recommended targets, and a more advanced age was the main associated factor.

CONCLUSIONS

Because more than half of type 2 diabetes outpatients do not meet the recommended A1C and blood pressure target values, there is a major call to overcome the therapeutic inertia and target treatment of patients on an individual basis.

Diabetes mellitus control in a large cohort of people with HIV in care-Washington, D.C

With more effective antiretroviral therapy (ART), people with HIV (PWH) are living longer and have more chronic diseases, including diabetes mellitus (DM). The prevalence of DM has been estimated in PWH previously, however there is less research regarding DM control. Our objectives were to determine the prevalence of DM and DM control and determine factors associated with DM control in a large urban cohort of PWH in care. We examined DC Cohort participants aged ≥18 years old to determine DM prevalence and to assess DM control (HbA1c measurement <7.0%). Demographic, clinical, and HIV-related factors associated with DM control were identified using multivariate logistic regression. The cohort of 5876 participants was predominantly male (71.3%), Non-Hispanic Black (78.1%) and had a median age of 52.0 years. DM prevalence was 17.4% (1023/5876). Among participants with recent HbA1c data available (39.9%) the proportion with DM control was 60.0% (245/408). In multivariate analysis, higher BMI (aOR: 0.47; 95% CI 0.28, 0.79) and use of non-insulin DM medication (aOR 0.43, 95% CI 0.25, 0.73) or insulin (aOR 0.010, 95% CI 0.04,0.24) compared to no medication use. Our findings suggest that individuals on medication for their DM likely need enhanced support to reach their treatment goals.

Determinants of glycemic control: Phase 2 analysis from nationwide diabetes report of National Program for Prevention and Control of Diabetes (NPPCD-2018)

BACKGROUND

Diabetes is one of the leading causes of morbidity and mortality worldwide, especially among middle and low income nations. Many diabetic complications and comorbidities are attributable to poor glycemic control. The aim of this study was to update and extend the national diabetes reports on the status of comorbidities, diabetes care and complications in Iran. Moreover, we investigated the risk factors of poor glycemic control in the Iranian population.

METHODS

National database of 99,651 patients with diabetes who attended university-affiliated clinics between April 1, 2017 and February 30, 2018 was used to carry out a cross-sectional study. Stepwise backward selection logistic regression model was used to examine the associated factors of glycemic control.

RESULTS

In this study 73.0% and 56.5% of the enrolled population with diabetes, had hypertension and hyperlipidemia, respectively. The prevalence of patients who received education for nutrition therapy or diabetes self-management was 16.3% and 23.3% respectively. Poor glycemic control was associated with male gender (OR=1.06, p=0.001), obesity (OR=1.03, p=0.05), duration of diabetes (OR=1.018, p<0.001), smoking (OR=1.08, p=0.041), hypertension (OR=1.53, p<0.001), hyperlipidemia (OR=1.15, p<0.001), insulin therapy (OR=1.26, p<0.001) and combination of insulin and oral anti-diabetic agents compared to oral anti-diabetic agents alone (OR=2.36, p<0.001).

CONCLUSION

We demonstrated that the prevalence of diabetes comorbidities is high in Iranian population and that a great proportion of Iranian patients with diabetes had not reached the goal of glycemic control. Our findings provide a starting point from which to investigate the obstacles that prevent patients with diabetes from reaching metabolic targets.

Profile and factors associated with glycaemic control of patients with type 2 diabetes in Greece: results from the diabetes registry

BACKGROUND

Strict glycaemic control early in the treatment process has been shown to reduce the occurrence of micro- and macro- vascular complications of diabetes in the long-term. Thus, treatment guidelines advise early intensification of treatment to achieve glycaemic control goals. However, evidence in Greece suggests that, despite guideline recommendations, glycaemic control among patients with T2DM remains challenging. This study presents the demographic and clinical characteristics of patients with T2DM in Greece using data from an electronic registry designed specifically for this treatment category and investigates the factors that are independently associated with glycaemic control.

METHODS

This is a multi-center, observational, cross-sectional study to investigate epidemiological and clinical factors affecting glycaemic control among patients with T2DM in Greece. Data was collected via a web-based disease registry, the Diabetes Registry, which operated from January 1st to December 31st, 2017. Five large specialized diabetes centers operating in Greek hospitals participated in the study.

RESULTS

Data for 1141 patients were retrieved (aged 63.02 ± 12.65 years, 56.9% male). Glycaemic control (Hb1Ac < 7%) was not achieved in 57.1% of patients. Factors independently associated with poor glycaemic control were: family history of diabetes [OR: 1.53, 95% CI: 1.06-2.23], BMI score between 25 to 30 [OR: 2.08, 95% CI: 1.05-4.13] or over 30 [OR: 2.12, 95% CI 1.12-4.07], elevated LDL levels [OR: 1.53, 95% 1.06-2.21] and low HDL levels [OR: 2.12, 95% CI: 1.44-3.12]. Lastly, use of injectable antidiabetic agents (in monotherapy or in combination) was less likely to be associated with poor glycaemic control versus treatment with combination of oral and injectable agents [OR: 0.50, 95% CI: 0.24-1.01]. This association was found to be marginally statistically significant.

CONCLUSION

Inadequate lipid control, family history of diabetes and presence of obesity (ΒΜΙ ≥ 30 kg/m²) were associated with poor glycaemic control among study sample, whereas use of injectable antidiabetic agents was less likely to be associated with poor glycaemic control. These findings indicate how complex optimal glycaemic control is, highlighting the need for tailored interventions in high-risk subpopulations with T2DM.

Predictors of poor glycemic control in adult with type 2 diabetes in South-Eastern Nigeria

BACKGROUND

The study investigated predictors of poor glycemic control in type 2 diabetes (T2DM).

METHODS

Data on demographics, anthropometric and clinical parameters were collected in a cross-section survey from 140 adults with T2DM, using standard tools/instruments. Glycated hemoglobin (A1C) was assessed as a measure of glycemic control.

RESULTS

Majority (83.3%) had poor glycemic control status of which about 95% constitute the elderly. The elderly (OR= 5.90, 95% Cl: 1.66-20.96) were more likely associated with poor glycemic control than the non-elderly (p = 0.006). Adjustment for significant predictor variables: Age, waist-hip ratio (WHR), Fasting plasma glucose (FPG) and Systolic blood pressure (SBP), although attenuated the odds (OR= 5.00, 95% CI: 1.19-20.96) of poor glycemic control, it still remained significantly (p = 0.028) higher in the elderly. Patients outside tight FPG control significantly (p = 0.001) showed poor glycemic cotrol than those within tight FPG (OR= 17.39, 95%Cl: 5.83-51.90), even with attenuated OR (OR= 10.85, 95%Cl: 3.10-37.96) and (OR=12.08, 95%Cl: 3.64-40.09) when non-significant and significant predictor variables were accounted for, respectively.

CONCLUSION

Age, WHR, FPG, and SBP were significantly associated with differences in glycemic control. The elderly and FPG outside tight control showed significantly increased odds of poor glycemic control status.

Determinants of poor glycemic control among adult patients with type 2 diabetes mellitus in Jimma University Medical Center, Jimma zone, south west Ethiopia: a case control study

OBJECTIVE AND BACKGROUND

In 2015 approximately 5.0 million people were estimated to have died from diabetes. Poor glycemic control is the most determinant of diabetes-related complication and death. The percentage of patients whose blood glucose level are not well controlled remains high yet. The aim of this study is to identify the determinants of poor glycemic control at the diabetes clinic of the Jimma University Medical Center from April 01 to June 30/2017.

METHODS

Facility-based case-control study design was conducted on patients with type 2 diabetes mellitus on follow-up at the diabetes clinic of Jimma University medical center. The consecutive sampling technique was employed and data were collected from April to June 2017. The data were entered using Epidata manager version 4.0.2 and exported to SPSS Version 21 for analysis. Logistic regression analysis was performed and variables with the p-value of less than 0.05 were considered as statistically significant determinants of poor glycemic control.

RESULT

The study was conducted on 410 patients, of which 228 males and 182 females. The determinants of poor glycemic control were comorbidities [Adjusted odd ratio(AOR) = 2.56, 95%CI = 1.10-5.96], lack of self-monitoring blood glucose [AOR = 3.44,95%CI = 1.33-8.94], total cholesterol level of 200 mg/dl or more [AOR = 3.62, 95%CI = 1.46-8.97], diabetes duration of greater than 7 years [AOR = 3.08, 95%CI = 1.33-7.16], physical activity of three or less than three days [AOR = 4.79, 95%CI = 1.70-13.53], waist to hip ratio of 0.9 or greater for male and 0.85 or greater for female [AOR = 3.52, 95%CI = 1.23-10.11], being on metformin plus insulin [AOR = 9.22, 95%CI = 2.90-29.35] and being on insulin [AOR = 4.48, 95%CI = 1.52-13.16].

CONCLUSION

Lack of Self-monitoring blood glucose, presence of comorbidities, duration of diabetes mellitus, physical activity of three or less than three days, total cholesterol of 200 mg/dl or more, waist to hip ratio of 0.9 or greater for male and 0.85 or greater for female, and types of antidiabetic medication were the independent predictors of poor glycemic control. Effort should be made towards reducing these factors by the concerned body.

Health Literacy, Self-management Activities, and Glycemic Control Among Adults With Type 2 Diabetes: A Path Analysis

PURPOSE

This study evaluated a novel composite measure of health literacy and numeracy by assessing its predictive validity for diabetes self-care activities and glycemic control.

METHODS

Patients (N = 102) with type 2 diabetes were recruited from a family medicine clinic at an academic medical center. Combined health literacy was assessed by combining the results of the Health Literacy Scale and the Subjective Numeracy Scale. Self-management activities were assessed by the Summary of Diabetes Self-Care Activities scale. Hemoglobin A1c (A1c) values were extracted from patients' medical records to assess glycemic control. Path models were used to test the predicted pathways linking health literacy and numeracy, independently and together, to self-management activities and glycemic control.

RESULTS

The mean combined literacy score was 72.0 (range, 33-104); the mean health literacy score alone was 43.9 (range, 14-56); and the mean numeracy score alone was 28.1 (range, 8-48). The direct effects results showed that the combined health literacy score (B = 0.107, P < .05) and the health literacy score alone (B = 0.234, P < .05) were significantly associated with self-care activities. The health literacy score alone also had a significant direct effect on A1c (B = -0.081, P < .05). The indirect effects of the combined health literacy on glycemic control through self-care activities were not statistically significant.

CONCLUSIONS

Findings from this study suggest that the combined health literacy has predictive validity for self-care activities whereas the health literacy alone has predictive validity for glycemic control. More research is needed to validate these findings. Higher patient health literacy skills were not consistently associated with higher perceived numeracy skills. Additional attention and efforts should be made to make sure patients understand medical instructions involving numerical calculations.

Clinical factors associated with persistently poor diabetes control in the Veterans Health Administration: A nationwide cohort study

OBJECTIVE

Patients with persistent poorly-controlled diabetes mellitus (PPDM) despite engagement in clinic-based care are at particularly high risk for diabetes complications and costs. Understanding this population's demographics, comorbidities and care utilization could guide strategies to address PPDM. We characterized factors associated with PPDM in a large sample of Veterans with type 2 diabetes.

METHODS

We identified a cohort of Veterans with medically treated type 2 diabetes, who received Veterans Health Administration primary care during fiscal years 2012 and 2013. PPDM was defined by hemoglobin A1c levels uniformly >8.5% during fiscal year (FY) 2012, despite engagement with care during this period. We used FY 2012 demographic, comorbidity and medication data to describe PPDM in relation to better-controlled diabetes patients and created multivariable models to examine associations between clinical factors and PPDM. We also constructed multivariable models to explore the association between PPDM and FY 2013 care utilization.

RESULTS

In our cohort of diabetes patients (n = 435,820), 12% met criteria for PPDM. Patients with PPDM were younger than better-controlled patients, less often married, and more often Black/African-American and Hispanic or Latino/Latina. Of included comorbidities, only retinopathy (OR 1.68, 95% confidence interval (CI): 1.63,1.73) and nephropathy (OR 1.26, 95% CI: 1.19,1.34) demonstrated clinically significant associations with PPDM. Complex insulin regimens such as premixed (OR 10.80, 95% CI: 10.11,11.54) and prandial-containing regimens (OR 18.74, 95% CI: 17.73,19.81) were strongly associated with PPDM. Patients with PPDM had higher care utilization, particularly endocrinology care (RR 3.56, 95% CI: 3.47,3.66); although only 26.4% of patients saw endocrinology overall.

CONCLUSION

PPDM is strongly associated with complex diabetes regimens, although heterogeneity in care utilization exists. While there is evidence of underutilization, inadequacy of available care may also contribute to PPDM. Our findings should inform tailored approaches to meet the needs of PPDM, who are among the highest-risk, highest-cost patients with diabetes.

Treatment Costs and Factors Associated with Glycemic Control among Patients with Diabetes in the United Arab Emirates

Background

We aimed to estimate the proportion of patients with diabetes who achieved target glycemic control, to estimate diabetes-related costs attributable to poor control, and to identify factors associated with them in the United Arab Emirates.

Methods

This retrospective cohort study used administrative claims data handled by Abu Dhabi Health Authority (January 2010 to June 2012) to determine glycemic control and diabetes-related treatment costs. A total of 4,058 patients were matched using propensity scores to eliminate selection bias between patients with glycosylated hemoglobin (HbA1c) <7% and HbA1c ≥7%. Diabetes-related costs attributable to poor control were estimated using a recycled prediction method. Factors associated with glycemic control were investigated using logistic regression and factors associated with these costs were identified using a generalized linear model.

Results

During the 1-year follow-up period, 46.6% of the patients achieved HbA1c <7%. Older age, female sex, better insurance coverage, non-use of insulin in the index diagnosis month, and non-use of antidiabetic medications during the follow-up period were significantly associated with improved glycemic control. The mean diabetes-related annual costs were $2,282 and $2,667 for patients with and without glycemic control, respectively, and the cost attributable to poor glycemic control was $172 (95% confidence interval [CI], $164–180). The diabetes-related costs were lower with mean HbA1c levels <7% (cost ratio, 0.94; 95% CI, 0.88–0.99). The costs were significantly higher in patients aged ≥65 years than those aged ≤44 years (cost ratio, 1.45; 95% CI, 1.25–1.70).

Conclusion

More than 50% of patients with diabetes had poorly controlled HbA1c. Poor glycemic control may increase diabetes-related costs.

Factors related to sense of coherence in adult patients with Type 2 diabetes

The influence of a diabetic person's sense of burden and blood sugar control through sense of coherence (SOC) on self-management has yet to be sufficiently clarified. The purpose of this study was to examine the utility of salutogenesis, which has sense of coherence at its core, for the self-management of patients with type 2 diabetes. A total of 258 questionnaires were distributed to patients who were seen at one of three hospitals in an urban area in Japan, after obtaining consent from the patient. They were between 20 and 75 years old and regularly received care. Of the 185 responses, 177 were valid. The responses were analyzed by referring to the framework of salutogenesis, and the relationship between patient characteristics, SOC, the Problem Areas In Diabetes survey (PAID), and glycosylated hemoglobin (HbA1c) were studied with structural equation modeling (SEM). SOC had a main effect on PAID scores and an indirect effect on HbA1c. Moreover, age influenced SOC positively. The SOC of patients with type 2 diabetes in the present study was comparatively high. These observations suggest a direct effect of SOC on reducing the sense of burden from having diabetes and an indirect effect on decreasing HbA1c. This research suggested the possibility that diabetes can be controlled by improving SOC.

The prevalence and determinants of poor glycemic control among adults with type 2 diabetes mellitus in Saudi Arabia

BACKGROUND

Although the prevalence of type 2 diabetes mellitus (T2DM) is rising sharply in Saudi Arabia, data on glycemic control, crucial to reducing diabetes mellitus complications, remain scarce. This study therefore investigated glycemic control status and the factors influencing poor glycemic control among adult T2DM patients in Saudi Arabia.

METHODS

This cross-sectional study examined 423 T2DM patients at a diabetic center in Tabuk, Saudi Arabia between September 2016 and July 2017. Glycemic levels were measured via fasting blood glucose (FBG) levels, and "poor glycemic control" was defined as FBG >130 mg/dL. Poor glycemic control's risk factors were identified using a logistic regression.

RESULTS

In the sample, 74.9% of the patients had poor blood glycemic control. Logistic regression revealed that T2DM patients had an increased chance of poorly controlled diabetes if they had family histories of diabetes (adjusted odds ratio [AOR] =7.38, 95% CI 4.09-13.31), longer diabetic durations (AOR =2.33, 95% CI 1.14-4.78 for 5-10 years and AOR =5.19, 95% CI 2.50-10.69 for >10 years), insufficient physical exercise (AOR =19.02, 95% CI 6.23-58.06), or were overweight (AOR =3.79, 95% CI 2.00-7.18), or obese (AOR =5.35, 95% CI 2.72-12.59).

CONCLUSION

A high proportion of the sampled patients had poor glycemic control, therefore, health care professionals should manage the associated risk factors to limit disease complications and improve the health of patients with diabetes.

Factors associated to adherence to blood glucose self-monitoring in patients with diabetes treated with insulin. The dapa study

OBJECTIVE

To assess adherence to self-monitoring of blood glucose and the main factors associated with it, particularly those related to self-perception of glycemia, in patients with diabetes on insulin therapy.

PATIENTS AND METHODS

An epidemiological, observational, prospective, multicenter study conducted in standard clinical practice in primary care, outpatient centers, and hospitals from different Spanish regions. Sociodemographic, clinical and treatment data were collected. Patients were considered adherent to self-monitoring if they performed the minimum number of controls recommended by the Spanish Society of Diabetes (SED).

RESULTS

Adherence was shown in 61.6% of patients. Factors associated to adherence included treatment with less than three insulin injections daily (OR 2.678; 95% CI 2.048- 3.5029; p <0.001), presence of peripheral vascular disease (OR 1.529; 95% CI 1.077 - 2.171; p=0.018), alcohol abstinence (OR 1.442; 95% CI 1.118 - 1.858; p=0.005), and collection of the glucose test strips from the pharmacy (OR 1.275; 95% CI 1.026 - 1.584; p=0.028). Adequate self-perception of glycemia was found in 21.4% of patients.

CONCLUSIONS

Our results show a suboptimal adherence to the recommended protocol for blood glucose self-monitoring in patients with diabetes on insulin therapy. Independent variables associated to good adherence were treatment with less than three insulin injections dailyu, presence of peripheral vascular disease, alcohol abstinence, and collection of glucose test strips from the pharmacy.

Effects of age, gender, and body mass index on efficacy and hypoglycaemia outcomes across treat-to-target trials with insulin glargine 100 U/mL added to oral antidiabetes agents in type 2 diabetes

AIMS

To analyse the effects of patient characteristics and different oral antidiabetes drug (OAD) use on standardised clinical outcomes in type 2 diabetes patients initiating insulin glargine 100 U/mL (Gla-100).

MATERIALS AND METHODS

Patient-level data from 16 randomized, treat-to-target clinical trials that added Gla-100 to existing metformin (MET), sulfonylurea (SU) or metformin plus sulfonylurea (MET+SU) treatment in insulin-naïve patients inadequately controlled by oral therapy were analysed and patients were followed for ≥24 weeks. Change in glycated haemoglobin A1c (HbA1c) from baseline to week 24, other glycaemic endpoints and incidence of hypoglycaemia (overall, nocturnal, and severe) were analysed by age (<65 vs ≥65 years), gender (male vs female), body mass index (BMI; <25 vs ≥25 to <30 vs >30 kg/m² ) and concomitant OAD (MET vs SU vs MET+SU).

RESULTS

At baseline, the overall population (N = 3188) had a mean age of 57.7 years, BMI of 30.5 kg/m² , HbA1c of 8.7%, fasting plasma glucose of 192 mg/dL, and 52.7% were male. Younger and older patients had similar HbA1c reductions with Gla-100 and a similar risk of hypoglycaemia. Females and patients with BMI <25 kg/m² were less likely to achieve HbA1c targets and more likely to experience hypoglycaemia, regardless of concomitant OAD. Adding Gla-100 to SU therapy (alone or in combination with MET) increased hypoglycaemia risk across all analyses.

CONCLUSIONS

Our data suggest that female patients with type 2 diabetes and normal-weight patients treated with Gla-100 and MET ± SU are less likely to achieve glycaemic targets and, therefore, may require more clinical attention. Addition of Gla-100 to SU regimens may increase hypoglycaemia risk irrespective of age, gender, or BMI.

Efficacy of an education course delivered to community health workers in diabetes control: A randomized clinical trial

BACKGROUND

Community health workers are community members who provide education and care for patients for a broad range of health issues, including diabetes mellitus. However, few community health workers are trained for diabetes education and little is known about the effectiveness of their interventions. The aim of this study is to evaluate the effect of a diabetes education program delivered to community health workers in improving the metabolic control of patients with type 2 diabetes mellitus.

METHODS

Eight community health workers, providing care for 118 patients, were randomized in two groups to receive a 1-month diabetes education program (intervention, patients n = 62) or an education course in other health issues (control, patients n = 56). Each community health worker was responsible for transmitting the acquired knowledge to patients. Primary outcome was changed in HbA1C 3 months after the intervention.

RESULTS

PARTICIPANTS: Mean age was 61 ± 11 years, 35% were men and 62% were whites. HbA1c levels reduced in both groups (intervention: 9.1 ± 2.2 vs. 7.9 ± 1.9%; control: 9.1 ± 2.1 vs. 8.4 ± 2.5%, p < 0.001), but no statistically significant differences were observed between groups (p between groups = 0.13). Total cholesterol (intervention: 192 ± 43 vs. 182 ± 39 mg/dl; control: 197 ± 44 vs. 191 ± 45 mg/dl, p between groups = 0.035) and triglycerides (intervention: 158 [106-218] vs. 135 [106-215]; control: 128 [100-215] mg/dl vs. 146 [102-203] mg/dl, p between groups = 0.03) reduced overtime only in intervention group.

CONCLUSIONS

In this study, a significant decrease in HbA1c was observed during patients' follow-up, but it was similar in intervention and control groups. The diabetes mellitus education course delivered to community health workers was able to improve patients' lipid profile.

Distress and psychopathology among Sudanese patients with type 2 diabetes mellitus and its relation to glycaemic control

Objectives

Methods

Results

Conclusion

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.

Flash Glucose-Sensing Technology as a Replacement for Blood Glucose Monitoring for the Management of Insulin-Treated Type 2 Diabetes: a Multicenter, Open-Label Randomized Controlled Trial

INTRODUCTION

Glycemic control in participants with insulin-treated diabetes remains challenging. We assessed safety and efficacy of new flash glucose-sensing technology to replace self-monitoring of blood glucose (SMBG).

METHODS

This open-label randomized controlled study (ClinicalTrials.gov, NCT02082184) enrolled adults with type 2 diabetes on intensive insulin therapy from 26 European diabetes centers. Following 2 weeks of blinded sensor wear, 2:1 (intervention/control) randomization (centrally, using biased-coin minimization dependant on study center and insulin administration) was to control (SMBG) or intervention (glucose-sensing technology). Participants and investigators were not masked to group allocation. Primary outcome was difference in HbA1c at 6 months in the full analysis set. Prespecified secondary outcomes included time in hypoglycemia, effect of age, and patient satisfaction.

RESULTS

Participants (n = 224) were randomized (149 intervention, 75 controls). At 6 months, there was no difference in the change in HbA1c between intervention and controls: -3.1 ± 0.75 mmol/mol, [-0.29 ± 0.07% (mean ± SE)] and -3.4 ± 1.04 mmol/mol (-0.31 ± 0.09%) respectively; p = 0.8222. A difference was detected in participants aged <65 years [-5.7 ± 0.96 mmol/mol (-0.53 ± 0.09%) and -2.2 ± 1.31 mmol/mol (-0.20 ± 0.12%), respectively; p = 0.0301]. Time in hypoglycemia <3.9 mmol/L (70 mg/dL) reduced by 0.47 ± 0.13 h/day [mean ± SE (p = 0.0006)], and <3.1 mmol/L (55 mg/dL) reduced by 0.22 ± 0.07 h/day (p = 0.0014) for intervention participants compared with controls; reductions of 43% and 53%, respectively. SMBG frequency, similar at baseline, decreased in intervention participants from 3.8 ± 1.4 tests/day (mean ± SD) to 0.3 ± 0.7, remaining unchanged in controls. Treatment satisfaction was higher in intervention compared with controls (DTSQ 13.1 ± 0.50 (mean ± SE) and 9.0 ± 0.72, respectively; p < 0.0001). No serious adverse events or severe hypoglycemic events were reported related to sensor data use. Forty-two serious events [16 (10.7%) intervention participants, 12 (16.0%) controls] were not device-related. Six intervention participants reported nine adverse events for sensor-wear reactions (two severe, six moderate, one mild).

CONCLUSION

Flash glucose-sensing technology use in type 2 diabetes with intensive insulin therapy results in no difference in HbA1c change and reduced hypoglycemia, thus offering a safe, effective replacement for SMBG.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02082184.

FUNDING

Abbott Diabetes Care.

Clinical characteristics of type 2 diabetic patients on basal insulin therapy with adequate fasting glucose control who do not achieve HbA1c targets

BACKGROUND

The aim of the present study was to determine the clinical characteristics of patients with type 2 diabetes mellitus (T2DM) treated with basal insulin who achieved an adequate fasting plasma glucose (FPG) level (<130 mg/dL), but were unable to achieve the HbA1c target (<7%; <53 mmol/mol).

METHODS

A cross-sectional study was performed on T2DM patients aged 31-90 years treated with basal insulin registered in the SIDIAP^Q primary healthcare electronic database during 2010.

RESULTS

In 2010, of a population of 126 811 T2DM subjects, 9899 were treated with basal insulin (neutral protamine Hagedorn [NPH], detemir, or glargine). Of these, 23.5% (n = 2322) achieved optimal FPG control levels (<130 mg/dL) but an inadequate HbA1c target (>7%). Mean HbA1c values in the contolled and uncontrolled groups were 8.15% (65.6 mmol/mol) and 6.31% (45.5 mmol/mol), respectively. Patients with controlled FPG but uncontrolled HbA1c had longer T2DM duration (11.6 vs 9.9 years), higher systolic blood pressure (138.2 vs 136.3 mmHg) and low-density lipoprotein cholesterol (104 vs 99 mg /dL), and a higher prevalence of retinopathy (24.8% vs 18.2%) than patients (17.8%) with optimal control of both glycemic targets (P < 0.05). Multivariate analysis showed that inadequate glycemic control was positively related only to younger age.

CONCLUSION

One-quarter of T2DM patients treated with basal insulin have difficulties attaining the recommended HbA1c goal despite adequate FPG levels. As some guidelines state, healthcare professionals should focus on PPG to identify and intensify treatment to control prandial glucose excursions in these patients.

Factors Associated with Long-Term Control of Type 2 Diabetes Mellitus

Aims. This study assessed factors associated with glycemic control among Saudi patients with Type 2 diabetes mellitus (T2DM). Methods. We conducted an analytical cross-sectional study, which included a random sample of 288 patients with T2DM proportional to the diabetes population of each primary health care center in Jazan city, Kingdom of Saudi Arabia. Results. More than two-thirds (74%) of patients had poor glycemic control. Lack of education, polypharmacy, and duration of diabetes ≥ 7 years were significantly associated with higher glycated hemoglobin (HbA1c). Moreover, patients who were smoker or divorced were significantly more likely to have higher HbA1c. The patients who did not comply with diet or take their medications as prescribed had poor glycemic control. The study found lower HbA1c levels among patients who received family support or had close relationship with their physicians. Similarly, knowledgeable patients towards diabetes or those with greater confidence in ability to manage self-care behaviors had a lower HbA1c. In contrast, risk factors such as depression or stress were significantly correlated with poorer glycemic control. Conclusion. The majority of T2DM patients had poor glycemic control. The study identified several factors associated with glycemic control. Effective and tailored interventions are needed to mitigate exposure to these risk factors. This would improve glycemic control and reduce the risks inherent to diabetes complications.

Factors associated with glycemic control in people with diabetes at the Family Health Strategy in Pernambuco

Abstract OBJECTIVE Identifying factors associated with glycemic control in people with type 2 Diabetes Mellitus (DM) registered in the Family Health Strategy (FHS) in Pernambuco, Brazil. METHOD Associations between glycemic control (glycosylated hemoglobin A lower or equal to 7%) presented by people with DM and variables related to sociodemographic conditions, lifestyle, characteristics of diabetes, treatment and follow-up of patients by health services were investigated by multiple regression. RESULTS More than 65% of the participants presented inadequate glycemic control, especially those with lower age, longer illness duration, more annual contacts with FHS and complex therapeutic regimen. People with DM without referrals to specialists presented greater glycemic control. Associations with education level and obesity did not remain significant in the multivariate model. CONCLUSION The evolution of diabetes hinders adequate control, however, attention to younger people with DM and referrals to specialists are factors that can improve glycemic control.

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.

The Effect of Physician Feedback and an Action Checklist on Diabetes Care Measures

The objective was to evaluate whether physician feedback accompanied by an action checklist improved diabetes care process measures. Eighty-three physicians in an academic general medicine clinic were provided a single feedback report on the most recent date and result of diabetes care measures (glycosylated hemoglobin [A1c], urine microalbumin, serum creatinine, lipid levels, retinal examination) as well as recent diabetes medication refills with calculated dosing and adherence on 789 patients. An educational session regarding the feedback and adherence information was provided. The physicians were asked to complete a checklist accompanying the feedback on each of their patients, indicating requested actions with respect to follow-up, testing, and counseling. The physicians completed 82% of patient checklists, requesting actions consistent with patient needs on the basis of the feedback. Of the physicians, 93% felt the patient information and intervention format to be useful. The odds of urine microalbumin testing, serum creatinine, lipid profile, A1c, and retinal examination increased in the 6 months after the feedback. The increase was sustained at 1 year only for microalbumin and retinal exams. There was no significant change in refill adherence for the group overall after the feedback, although adherence did improve among patients of physicians attending the educational session. No significant change was noted in lipid or A1c levels during the study period. In conclusion, a simple physician feedback tool with action checklist can be both helpful and popular for improving rates of diabetes care guideline adherence. More complex interventions are likely required to improve diabetes outcomes.

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

OBJECTIVES

The study aimed to assess glycemic control in a Jordanian population with type 2 diabetes and to explore the sociodemographic, clinical and medication-related factors as well as the anthropometric indexes and laboratory values associated with and possibly contributing to unsatisfactory glycemic control.

METHODS

We included 237 patients previously diagnosed as having type 2 diabetes. Data were collected through direct interviews. Sociodemographic and clinical details were collected using a questionnaire designed for the purpose of the study, anthropometric measurements were obtained at the time of the interviews, and laboratory data were extracted from the medical records of King Abdullah University Hospital.

RESULTS

Of the participants, 60.8% were found to have unsatisfactory glycemic control (glycated hemoglobin levels ≥7%). Unsatisfactory glycemic control was associated with younger ages at diabetes diagnosis, higher mean weights and higher prevalences of diabetic neuropathy. No relationships were found among glycemic control and body mass index, waist circumference or central obesity. Patients with adequate control were more likely to have health insurance and to have hypothyroidism as a comorbidity. Insulin use and medication plans containing insulin were associated with unsatisfactory control. Patients with unsatisfactory control had higher mean levels of low-density lipoproteins and triglycerides and lower mean levels of high-density lipoproteins. Moreover, elevated triglycerides (≥150 mg/dL) and dyslipidemia were associated with unsatisfactory glycemic control.

CONCLUSIONS

More than half of the participants had unsatisfactory glycemic control, highlighting the need for a change in the approach and strategies used for patients with diabetes in Jordan. Factors associated with glycemic control that were found in this study should be further studied and used in the prevention and management of diabetes.

Correlates of poor glycemic control among patients with diabetes initiating hemodialysis for end-stage renal disease

Background

Maintaining tight glycemic control is important for prevention of diabetes-related outcomes in end-stage renal disease patients with diabetes, especially in light of their poor prognosis. This study aimed to determine factors associated with poor glycemic control among U.S. patients with diabetes mellitus initiating hemodialysis for end-stage renal disease.

Methods

Using data from the U.S. Renal Data System, electronic health records of a large national dialysis provider, and U.S. Census data, we performed a cross-sectional multivariable Poisson regression analysis to characterize risk factors associated with poor glycemic control, defined as glycated hemoglobin (HbA1c) >7 vs. ≤7 %, in adult patients with diabetes who initiated hemodialysis at an outpatient facility between 2006 and 2011.

Results

Of 16,297 patients with diabetes, 21.2 % had HbA1c >7 %. In multivariable analysis, younger patients, patients of Native American race, and those of Hispanic ethnicity had higher prevalence of poor glycemic control. Independent correlates of poor glycemic control further included higher platelet count, white blood cell count, and ferritin; higher body mass index, systolic blood pressure, total cholesterol and triglyceride concentrations; lower HDL and albumin concentrations; lower normalized protein catabolic rate; and higher estimated glomerular filtration rate at initiation of dialysis (all P < 0.05). No independent associations were found with area-level socioeconomic indicators. Occurrence of diabetes in patients <40 years of age, a proxy for type 1 diabetes, was associated with poor HbA1c control compared with that in patients ≥40 years of age, which was classified as type 2 diabetes. These findings were robust to the different outcome definitions of HbA1c >7.5 % and >8 %.

Conclusion

In this cohort of incident end-stage renal disease patients with diabetes, poor glycemic control was independently associated with younger age, Native American race, Hispanic ethnicity, higher body mass index, and clinical risk factors including atherogenic lipoprotein profile, hypertension, inflammation, and markers indicative of malnutrition and a more serious systemic disease.

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.

Glycosylated hemoglobin level and number of oral antidiabetic drugs predict whether or not glycemic target is achieved in insulin-requiring type 2 diabetes

AIMS

Factors predicting success (glycosylated hemoglobin (A1C)<7%) with insulin therapy in patients with insulin-requiring type 2 diabetes need to be identified.

METHODS

A retrospective, multi-center, observational study was conducted for outpatients with oral antidiabetic drug (OAD)-treated type 2 diabetes whose A1C levels remained above 7%. Patients were begun on basal insulin between January 2005 and December 2006. Biochemical variables and demographic data were collected before and after 52 weeks of insulin therapy.

RESULTS

A total of 565 patients (age, 60.4±11.9 years; A1C levels, 10.11 ±1.81%; duration of diabetes, 11.5±6.8 years) were studied. By study end, 63 patients (11.2%) had achieved the glycemic goal (A1C<7%). The glycemic goal attainment rate was only 9.1% in patients with A1C>8.8% and who were taking >2 OADs at baseline. The highest rate (32.7%) of successful glycemic control was observed in the group of patients with A1C ≤ 8.8% and who used ≤ 2 OADs at baseline.

CONCLUSIONS

Insulin-naïve diabetic patients with A1C>8.8%, especially those who are taking >2 OADs, have small chance to achieve good glycemic control with adding only basal insulin therapy.

Why do some people with type 2 diabetes who are using insulin have poor glycaemic control? A qualitative study

OBJECTIVE

To explore factors influencing poor glycaemic control in people with type 2 diabetes using insulin.

RESEARCH DESIGN

A qualitative method comprising in-depth individual interviews. A semistructured interview guide was used. The interviews were audiorecorded, transcribed verbatim and analysed using a thematic approach.

PARTICIPANTS

Seventeen people with type 2 diabetes using insulin with glycated haemoglobin (HbA1c) ≥9% for >1 year.

SETTING

The Primary Care Clinic and Diabetes Clinic in the University of Malaya Medical Centre (UMMC), Malaysia.

RESULTS

Data analysis uncovered four themes: lifestyle challenges in adhering to medical recommendations; psychosocial and emotional hurdles; treatment-related factors; lack of knowledge about and self-efficacy in diabetes self-care.

CONCLUSIONS

Factors that explain the poor glycaemic control in people with type 2 diabetes using insulin were identified. Healthcare providers could use these findings to address patients' concerns during consultations and help to improve glycaemic control.

Uncontrolled diabetes mellitus: prevalence and risk factors among people with type 2 diabetes mellitus in an Urban District of Karachi, Pakistan

AIMS

This study aimed to explore the prevalence of, and factors associated with, uncontrolled diabetes mellitus (UDM) in a community setting in Pakistan.

METHODOLOGY

A single-center, cross-sectional study, conducted in a community-based specialized care center (SCC) for diabetes in District Central Karachi, in 2003, registered 452 type 2 DM participants, tested for HbA1c and interviewed face-to-face for other information. Logistic regression analysis was conducted to identify factors associated with UDM.

RESULTS

Prevalence of UDM among diabetes patients was found to be 38.9% (95% CI: 34.4-43.4%). Multivariable logistic regression model analysis indicated that age <50 years (OR: 1.9; 95% CI: 1.2-2.9), being diagnosed in a hospital (vs. a clinic) (OR: 1.8; 95% CI: 1.1-2.8), diabetes information from a doctor or nurse only (vs. multiple sources) (OR: 1.8; 95% CI: 1.2-2.9), higher monthly treatment cost (OR: 1.3; 95% CI: 1.1-1.6; for every extra 500 PKR), and higher consumption of tea (OR: 1.5; 95% CI: 1.0-2.2; for every 2 extra cups) were independently associated with UDM.

CONCLUSION

The prevalence of UDM was approximately 39% among persons with type 2 diabetes visiting a community based SCC for diabetes. Modifiable risk factors such as sources of diabetes information and black tea consumption can be considered as potential targets of interventions in Karachi.

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.

Psychosocial influences on glycemic control in women with pre-existing diabetes preparing for pregnancy

OBJECTIVE

The purpose of this study was to identify psychosocial factors associated with glycemic control in a sample of adult women with type 1 or type 2 diabetes mellitus preparing for pregnancy.

METHODS

This was a cross-sectional study. Participants comprised a subsample (n=38) of a larger study investigating predictors of prepregnancy care uptake in women with pre-existing diabetes. Participants were recruited from the diabetes and pregnancy clinics at 2 major hospitals and completed self-report questionnaires on personality, coping style, social support and knowledge of diabetes and pregnancy. The main outcome was glycemic control using glycated hemoglobin (A1C) as the outcome of interest.

RESULTS

The sample was divided into good (n=20) vs. poor (n=18) glycemic control based on their A1C at entry to the study. Univariate tests indicated no differences between the 2 groups on any of the variables except that the good control group were better educated. Hierarchical multiple regression analysis revealed that problem-focused coping and higher education remained significantly associated with better glycemic control when controlling for potential confounds.

CONCLUSIONS

Providing women with enhanced prepregnancy diabetes education with a particular emphasis on problem-solving and coping skills may enable them to take more proactive approaches to challenges they face in managing their diabetes. That in turn can improve glycemic control at the critical period.

Clustering of cardiometabolic risk factors and risk of elevated HbA1c in non-Hispanic White, non-Hispanic Black and Mexican-American adults with type 2 diabetes

AIM

To determine which cardiometabolic risk factors and clusters of cardiometabolic risk factors that are mostly associated with elevated HbA1c in non-Hispanic White (NHW), non-Hispanic Black (NHB) and Mexican-American (MA) adults who have type 2 diabetes.

METHODS

Data (n=2910) from the United States National Health and Nutritional Examination Surveys were used in this study. Elevated HbA1c was defined as having HbA1c value was 7% or greater. Race/ethnicity-specific associations of individual and clustered (2-5 factors) cardiometabolic risk factors with elevated HbA1c were determined using prevalence odds ratio from multivariate logistic regression analyses. Statistical adjustments were made for sex, age, education, income and marital status.

RESULTS

Joint occurrence of abdominal obesity, high blood pressure, and elevated triglycerides and joint occurrence of high blood pressure, elevated triglycerides and low HDL were more highly associated with elevated odds of HbA1c compared to other cardiometabolic risk factors joint occurrences. Joint occurrences of abdominal obesity, high blood pressure, and elevated triglycerides was associated with 2.3 (95% CI: 1.2-3.3), 9.1 (95% CI: 2.9-28.7) and 4.8 (95% CI: 2.0-11.5) increased odds of elevated HbA1c in NHW, NHB and MA, respectively. The corresponding values for the joint occurrence of high blood pressure, elevated triglycerides and low HDL was associated with 2.4 (95% CI: 1.2-3.7), 3.5 (95% CI: 1.1-5.5) and 2.6 (95% CI: 1.5-4.7) increased odds of elevated HbA1c in NHW, NHB and MA, respectively.

CONCLUSION

This finding calls for consideration of cardiovascular risk factor clustering in deciding medical therapies to optimize glycemic control in individuals with type 2 diabetes. Interventions designed to achieve glycemic control coupled with modification of cardiometabolic risk factors may be crucial in alleviating sequelae resulting from type 2 diabetes.

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.

Obesity independently predicts responders to biphasic insulin 50/50 (Humalog Mix50 and Insuman Comb 50) following conversion from other insulin regimens: a retrospective cohort study

AIMS

This study aims to examine the metabolic effects of intensification or initiation of insulin treatment with biphasic insulin 50/50, and determine the predictors of responders or non-responders to biphasic insulin 50/50.

METHODS

A cohort of 2183 patients ≥18 years with diabetes, newly treated with biphasic insulin 50/50 between January 2000 and May 2012, were sourced from UK General Practices via The Health Improvement Network (THIN) database. Baseline clinical parameters of 1267 patients with suboptimal glycated hemoglobin (HbA1c) >7.5% (>58 mmol/mol) who had received background insulin regimens for at least 6 months preceding biphasic insulin 50/50 were compared against 12-month outcome data. Responders were defined as those with HbA1c <7.5% (58 mmol/mol) and/or HbA1c reduction of ≥1% (10.9 mmol/mol) at 12 months. Comparative analyses were carried out on subgroups of 237 patients initiating insulin therapy with biphasic insulin 50/50, and between users of the Humalog Mix50 (HM50) versus Insuman Comb 50 (IC50). Associations were examined using t tests and multivariate logistic regression techniques.

RESULTS

The overall mean HbA1c reduction at 12 months as a result of intensification and initiation with biphasic insulin 50/50 was 0.5% (5.5 mmol/mol) and 1.6% (17.5 mmol/mol), respectively. Adjusted ORs show obesity (body mass index >30 kg/m(2)), treatment duration for ≥9 months, and baseline HbA1c are independent determinants of responders. In addition, stratified for baseline HbA1c levels, HM50 was associated with better HbA1c outcome compared with IC50.

CONCLUSIONS

biphasic insulin 50/50 is effective for achieving glycemic control in suboptimal HbA1c levels, especially among obese patients with insulin-treated diabetes. Stratified for baseline HbA1c, HM50 was associated with improved HbA1c outcome compared with IC50.

Poor glycemic control in younger women attending Malaysian public primary care clinics: findings from adults diabetes control and management registry

BACKGROUND

Women of reproductive age are a group of particular concern as diabetes may affect their pregnancy outcome as well as long-term morbidity and mortality. This study aimed to compare the clinical profiles and glycemic control of reproductive and non-reproductive age women with type 2 diabetes (T2D) in primary care settings, and to determine the associated factors of poor glycemic control in the reproductive age group women.

METHODS

This was a cross-sectional study using cases reported by public primary care clinics to the Adult Diabetes Control and Management registry from 1st January to 31st December 2009. All Malaysian women aged 18 years old and above and diagnosed with T2D for at least 1 year were included in the analysis. The target for glycemic control (HbA1c < 6.5%) is in accordance to the recommended national guidelines. Both univariate and multivariate approaches of logistic regression were applied to determine whether reproductive age women have an association with poor glycemic control.

RESULTS

Data from a total of 30,427 women were analyzed and 21.8% (6,622) were of reproductive age. There were 12.5% of reproductive age women and 18.0% of non-reproductive age women that achieved glycemic control. Reproductive age group women were associated with poorer glycemic control (OR = 1.5, 95% CI = 1.2-1.8). The risk factors associated with poor glycemic control in the reproductive age women were being of Malay and Indian race, longer duration of diabetes, patients on anti-diabetic agents, and those who had not achieved the target total cholesterol and triglycerides.

CONCLUSION

Women with T2D have poor glycemic control, but being of reproductive age was associated with even poorer control. Health care providers need to pay more attention to this group of patients especially for those with risk factors. More aggressive therapeutic strategies to improve their cardiometabolic control and pregnancy outcome are warranted.

Depressive temperament, distress, psychological adjustment and depressive symptoms in type 2 diabetes

Major depression, depressive symptoms, distress with diabetes and psychological adjustment to type 2 diabetes (T2DM) are somehow overlapping constructs with shared covariance. Nevertheless, diabetes distress remains the most prevalent long-lasting factor associated with hyperglycemia in T2DM. This ought to be taken on account when treatment is planned, namely when one is looking for metabolic control and emotional distress integrative care. Temperament or other long-term individual characteristics may support the interplay of distress, psychological adjustment and depressive states in T2DM. Depressive temperament may constitute a vulnerability factor to behavioral or biological T2DM outcome or even a potential risk factor to T2DM later incidence.

Factors associated with poor glycemic control or wide glycemic variability among diabetes patients in Hawaii, 2006-2009

Introduction

Although glycemic control is known to reduce complications associated with diabetes, it is an elusive goal for many patients with diabetes. The objective of this study was to identify factors associated with sustained poor glycemic control, some glycemic variability, and wide glycemic variability among diabetes patients over 3 years.

Methods

This retrospective study was conducted among 2,970 diabetes patients with poor glycemic control (hemoglobin A1c [HbA1c] >9%) who were enrolled in a health plan in Hawaii in 2006. We conducted multivariable logistic regressions to examine factors related to sustained poor control, some glycemic variability, and wide glycemic variability during the next 3 years. Independent variables evaluated as possible predictors were age, sex, type of insurance coverage, morbidity, diabetes duration, history of cardiovascular disease, and number of medications.

Results

Longer duration of diabetes, being under age 35, and taking 15 or more medications were significantly associated with sustained poor glycemic control. Preferred provider organization and Medicare (vs health maintenance organization) enrollees and patients with high morbidity were less likely to have sustained poor glycemic control. Wide glycemic variability was significantly related to being younger than age 50, longer duration of diabetes, having coronary artery disease, and taking 5 to 9 medications per year.

Conclusion

Results indicate that duration of diabetes, age, number of medications, morbidity, and type of insurance coverage are risk factors for sustained poor glycemic control. Patients with these characteristics may need additional therapies and targeted interventions to improve glycemic control. Patients younger than age 50 and those with a history of coronary heart disease should be warned of the health risks of wide glycemic variability.

Diabetes distress, but not depressive symptoms, is associated with glycaemic control among Japanese patients with type 2 diabetes: Diabetes Distress and Care Registry at Tenri (DDCRT 1)

AIMS

To investigate the association between glycaemic control, diabetes distress and depressive symptoms among Japanese patients with Type 2 diabetes.

METHODS

Cross-sectional data from 3305 patients with Type 2 diabetes were obtained from a baseline assessment of a diabetes registry at a general hospital in Japan. The Centre for Epidemiologic Studies Depression scale and Problem Areas in Diabetes scale were used to measure depressive symptoms and diabetes-related distress, respectively. Modified Poisson regression analysis was used to estimate the relative risks for poor glycaemic control across the quartiles of Centre for Epidemiologic Studies Depression scale and Problem Areas in Diabetes scale scores.

RESULTS

The average age of the participants was 64.9 years and the average HbA(1c) level was 58.1 mmol/mol (7.5%). Clinically significant levels of depressive symptoms (Centre for Epidemiologic Studies Depression scale scores ≥ 16) were reported by 27.8% of participants. These scores significantly correlated with Problem Areas in Diabetes scale scores (r = 0.4354, P < 0.0001). Diabetes distress, but not depressive symptoms, was significantly associated with higher HbA(1c) levels. The relative risks for poor glycaemic control (HbA(1c) ≥ 64 mmol/mol; 8.0%), when adjusted for age, sex, BMI, type of diabetes therapy and duration of diabetes, was 67% higher among patients with Problem Areas in Diabetes scale scores in the highest quartile (≥ 26.25) compared with those in the lowest quartile (0-3.75).

CONCLUSION

A significant association between glycaemic control and diabetes-related distress, but not depressive symptoms, was observed in Japanese patients with Type 2 diabetes.

Assessment of diabetic distress and disease related factors in patients with type 2 diabetes in Isfahan: A way to tailor an effective intervention planning in Isfahan-Iran

BACKGROUND

The purpose of this study was to assess diabetes distress and its related factors among type 2 diabetic patients to better tailor intervention planning in Isfahan-Iran.

METHODS

A cross-sectional study was conducted in 2011. Study population was patients with type 2 diabetes referring to Omolbanin, an outpatient diabetic center in Isfahan. 140 diabetic patients met the inclusion criteria and were all included in the study. Patient's diabetes distress was measured by DDS. A 17-item self-report diabetes distress scale was used with subscales reflecting 5 domains: 1) Emotional burden (5 items), 2) Physician distress (4 items), 3) Regimen distress (5 items) and 4) Interpersonal distress (3 items). The responses to each item were rated between 1 and 6 (1 = not a problem, 2 = a slight problem, 3 = a moderate problem, 4 = somewhat serious problem, 5 = a serious problem, 6 = a very serious problem). The minimum and the maximum of score in the scale were 17 and 114 respectively. Collected data was analyzed by using SPSS software version 11.5.

RESULTS

Mean age of participants were 53.23 years (SD = 7.82). 54.3% was female, 97.1% was married, and 57.1% had education lower than diploma. The average score of total diabetes distress was 2.96 ± 0.83. The average score of each domain was (3.40 ± 1.18), (2.57 ± 0.88), (2.97 ± 0.90), (2.76 ± 0.91) respectively. 'Emotional Burden' was considered as the most important domain in measuring diabetes distress. Total diabetes distress had significant association with age (p = 0.02), duration of diabetes (p<0.001), marital status, comorbidity, complications (p<0.001), and history of diabetes (p = 0.01). Pearson correlation coefficient revealed that diabetes distress of type 2 diabetic patients has a linear and direct relation with HbAlc (r = 0.63, p<0.001).

CONCLUSION

It seems some keywords have a main role in diabetes distress such as emotional support, communication with patient and physician, self-efficacy and social support. All of these points are achievable through empowerment approach in diabetes care plan.

Patient factors and glycaemic control--associations and explanatory power

AIMS

To investigate the association between glycaemic control and patient socio-demographics, activation level, diabetes-related distress, assessment of care, knowledge of target HbA(1c), and self-management behaviours, and to determine to what extent these factors explain the variance in HbA(1c) in a large Danish population of patients with Type 2 diabetes.

METHODS

Cross-sectional survey and record review of 2045 patients from a specialist diabetes clinic. Validated scales measured patient activation, self-management behaviours, diabetes-related emotional distress, and perceived care. The electronic patient record provided information about HbA(1c), medication, body mass index, and duration of diabetes. Data were analysed using multiple linear regression models with stepwise addition of covariates.

RESULTS

The response rate was 54% (n = 1081). Good glycaemic control was significantly associated with older age, higher education, higher patient activation, lower diabetes-related emotional distress, better diet and exercise behaviours, lower body mass index, shorter duration of disease and knowledge of HbA(1c) targets (P < 0.05 for all). Patient socio-demographics, behaviour; perceptions of care and diabetes distress accounted for 14% of the total variance in HbA(1c) levels (P = 0.0134), but the variance explained was higher for respondents treated with medications other than insulin.

CONCLUSIONS

Our study emphasizes the complex relationships between patient activation, distress and behaviour, specific treatment modalities and glycaemic control. Knowledge of treatment goals, achieving patient activation in coping with diabetes, and lowering disease-related emotional stress are important patient education goals. However, the large unexplained component of HbA(1c) variance highlights the need for more research to understand the mechanisms of glycaemic control.

The association between problem areas in diabetes scale scores and glycemic control is modified by types of diabetes therapy: diabetes distress and care registry in Tenri (DDCRT 2)

AIM

To evaluate the joint association of Problem Areas in Diabetes (PAID) Scale scores and glycemic control with diabetes therapy.

METHODS

We used 3479 patients' data with type 1 and type 2. Modified Poisson regression analysis was used to estimate relative risks (RRs) for poor glycemic control (HbA1c≥7.0%) across quartiles of PAID scores.

RESULTS

Compared with the 1st quartile of PAID score, multivariable-adjusted RRs for poor glycemic control were 0.99 (95%CI, 0.87-1.11), 1.05 (95%CI, 0.93-1.18), and 1.12 (95%CI, 1.00-1.27), respectively, for 2nd to 4th quartiles, and we observed significant trend (p for trend=0.03). We observed significant interaction of PAID score and HbA1c with diabetes therapy (p=0.0469). In patients receiving diet only therapy, the RRs for poor glycemic control were 1.38 (95%CI, 0.93-2.05), 1.18 (95%CI, 0.51-5.13), and 1.81 (95%CI, 1.16-2.79), respectively for 2nd to 4th quartiles of PAID score compared with the 1st quartile (p for trend=0.025); while we did not observe significant association between PAID and poor glycemic control in patients receiving medication therapy.

CONCLUSIONS

Diabetes distress measured by PAID survey was associated with poor glycemic control, and this association was modified by diabetes therapy.