Impact of demographics and disease progression on the relationship between glucose and HbA1c

Does the SDMQ-9 Predict Changes in HbA1c Levels? An Ecuadorian Cohort

Background and Objectives: Diabetes mellitus affects 422 million people around the world, positioning it as a major health problem. According to the WHO(World Health Organization), 90% corresponds to type 2. The shared-decision making (SDM) is a method used to facilitate patient control, medication, maintenance, and assessment of health status according to their priorities and preferences. With the application of SDM in patients with diabetes, it is expected there will be an increase in treatment adherence and a reduction in HbA1c levels. The aim of this study is to determine the predictors of the change in HbA1c. Material and Methods: A sample of 76 participants attending as endocrinology outpatients was obtained. Data collected within the sample included: sex, age, educational level, body mass index, and the level of SDM using the SDMQ-9. In addition, HbA1c levels were measured twice: at baseline and three months after the first measurement. Results: The linear regression indicates that the level of SDM is a significant predictor of the change in HbA1c, specifically in men. However, the direction of the relationship was a somewhat opposite trend than we expected. Higher levels of SDM imply an increase in HbA1c rather than a reduction. Conclusions: Contrary to the literature, our results shows that elevated levels of perceived SDM may be associated with worse diabetic control. However, more investigation is needed as these results are not generalizable, due to the specific population used and the sample size. Furthermore, to better understand the effect of SDM on the change in HbA1c in patients with poorly controlled diabetes.

Assessment of Self-Management Care and Glycated Hemoglobin Levels Among Type 2 Diabetes Mellitus Patients: A Cross-Sectional Study From the Kingdom of Saudi Arabia

The prevalence of type 2 diabetes mellitus (T2DM) is increasing every year, along with its health and economic burden/impact. Achieving glycemic control remains challenging, and only 9-15% of diabetic patients manage to reach the optimal level. A few strategies have been found to improve diabetic control, including self-management care (SMC). This study aimed to explore the relationship between patient characteristics, SMC, and glycated hemoglobin (HbA1c) levels, as an indicator of optimal glycemic control. This was a cross-sectional study of 200 participants conducted at the King Fahd University Hospital (KFUH) in Saudi Arabia. A pre-structured questionnaire including sociodemographic data and aspects of diabetes self-management was distributed among patients at KFUH and the Family and Community Medicine Center (FAMCO) of Imam Abdulrahman Bin Faisal University, Dammam, Kingdom of Saudi Arabia. HbA1c data were extracted from patients' records. Unfortunately, the majority of the participants (65%) were found to have poor glycemic control. Glucose management was better in patients having T2DM for more than five years (mean: 4.01; p<0.05). In addition, an income of less than 5,000 Saudi Riyals (SR) was associated with lower physical activity (mean: 2.95; p<0.05). The level of blood sugar was uncontrolled among the majority of surveyed patients. Our study found variables associated with SMC and HbA1c levels, which might help to guide future initiatives aiming to enhance the care of patients with T2DM.

The diabetes quality of life brief clinical inventory in combination with the management strategies in type 1 diabetes mellitus with or without the use of insulin pump

Aims

The aims of this study are to evaluate any differences in the Quality of life among Continuous Subcutaneous Insulin Infusion (CSII) and Multiple Dose Injection (MDI) insulin delivery, applying the Diabetes Quality of life Brief Clinical Inventory (DQoL-BCI) questionnaire, and assess the diabetes management strategies between the two groups.

Methods

One hundred and ten adult participants (male/female ratio 1:2.7) with type 1 diabetes were recruited in this online survey. Forty-eight of them were using CSII and the rest 62 (were using) MDI insulin delivery. A 23-item socio-demographic/diabetes management strategies questionnaire and the 15-item DQoL-BCI were administered.

Results

CSII users scored statistically, significantly better at the satisfaction treatment subscale (p = 0.032) of the DQoL-BCI and emerged that they were implemented more management strategies such as dietician guidance services (p = 0.002), carbohydrate education seminars (p = 0.03). Predictive factors were also detected regarding the HbA_1c < 7% (53 mmol/mol) and β-coefficients in relation to DQoL-BCI questionnaire with the subscales of a negative impact and satisfaction treatment.

Conclusion

Diabetes self-management education plays a key role to a better compliance with the treatment. Client-centered multidisciplinary centers in T1DM education are essential so that they be applicable for all T1DM patients irrespective of the type of insulin delivery they used.

Association of characteristics of people with type 2 diabetes mellitus with discordant values of fasting glucose and HbA1c

BACKGROUND

Primary care physicians frequently encounter people with type 2 diabetes mellitus (T2DM) with discordant values for fasting glucose and HbA1c. The aim of this study was to identify the prevalence and characteristics of people in whom blood glucose and HbA1c did not match.

METHODS

Overall, 64 553 people with T2DM from 939 general or internal medicine practices (Disease Analyzer database, Germany; January 2013-December 2015) were analyzed. Multivariable logistic regression models were used to identify associations between baseline clinical characteristics, comorbidity, and glucose-lowering treatment and discordance of fasting glucose and HbA1c values measured at the same visit.

RESULTS

Overall, 8582 (13%) patients had fasting glucose ≥140 mg/dL and HbA1c <7% (<53 mmol/mol), and 6508 (10%) had HbA1c ≥7% (≥53 mmol/mol) and fasting glucose <140 mg/dL. Using patients with both fasting glucose <140 mg/dL and HbA1c <7% as the reference (n = 31 834; 49%), solitary high fasting glucose values (and HbA1c <7%) were positively associated with higher age, male sex, longer diabetes duration, obesity, liver disease, low estimated glomerular filtration rate (eGFR), and glucose-lowering treatment. High HbA1c (and fasting glucose <140 mg/dL) was positively related to longer diabetes duration, obesity, neuropathy, retinopathy, low eGFR, and insulin treatment. There were lower odds of having solitary increased HbA1c ≥7% (fasting glucose <140 mg/dL) with higher age, hypertension, depression, and the number of diabetes patients (>200) per practice.

CONCLUSIONS

A considerable number of people with T2DM in primary care practices have discordant fasting blood glucose and HbA1c values. People who have discordant glycemic values have different characteristics.

Comparison of Power, Prognosis, and Extrapolation Properties of Four Population Pharmacodynamic Models of HbA1c for Type 2 Diabetes

Reusing published models saves time; time to be used for informing decisions in drug development. In antihyperglycemic drug development, several published HbA1c models are available but selecting the appropriate model for a particular purpose is challenging. This study aims at helping selection by investigating four HbA1c models, specifically the ability to identify drug effects (shape, site of action, and power) and simulation properties. All models could identify glucose effect nonlinearities, although for detecting the site of action, a mechanistic glucose model was needed. Power was highest for models using mean plasma glucose to drive HbA1c formation. Insulin contribution to power varied greatly depending on the drug target; it was beneficial only if the drug target was insulin secretion. All investigated models showed good simulation properties. However, extrapolation with the mechanistic model beyond 12 weeks resulted in drug effect overprediction. This investigation aids drug development in decisions regarding model choice if reusing published HbA1c models.