Prevalence Of Glycemic Control Research Articles

A hospital-based assessment of glycemic control and medication adherence in type 2 diabetes mellitus in Eastern Nepal.

Poor glycemic control in type 2 diabetes mellitus (T2DM) causes damage to various organs and leads to the development of disabling and life-threatening complications. To find out the prevalence of glycemic control and medication adherence (MA) and the factors affecting them. A cross-sectional study was conducted among patients with T2DM. The patients were categorized as good glycemic control (HbA1c <7.0%) and poor glycemic control (HbA1c ≥7.0%). MA was categorized as low (score <6), medium (score 6 or 7), and high (score 8). The Statistical Package for Social Science (version 11.5) was used for statistical analysis at a P value less than 0.05. Of 129 patients, 65 (50.39%) were females. The mean age was 48.33 ± 12.86 years. The combination of metformin and glimepiride was prescribed to 37 (28.68%) patients. Diabetic knowledge was poor in 84 (65.12%) patients. Glycemic control was good in 108 (83.72%) patients. MA was medium in 72 (55.81%) patients. Patients taking regular fruit, having shorter duration of drug therapy, and having good diabetic knowledge had good glycemic control and were statistically significant (P value < 0.05). Patients having family support, nonalcoholic, taking regular fruit, being involved in daily jogging, having shorter duration of drug therapy, and having good diabetic knowledge had high MA and were statistically significant (P value < 0.05). The majority of the diabetic patients had good glycemic control and medium MA. Patients taking regular fruit, being involved in daily jogging, having a shorter duration of drug therapy, and having good diabetic knowledge were identified as factors that affect both glycemic control and MA.

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

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

National trends in the prevalence of glycemic control among patients with type 2 diabetes receiving continuous care in Thailand from 2011 to 2018

Diabetes is one of the largest global health problems and exhibits a constantly increasing trend. A series of nationwide hospital-based cross-sectional surveys of clinical outcomes was performed annually from 2011 to 2015 and 2018 among patients with type 2 diabetes aged ≥ 20 years receiving medical care for at least 12 months. A two-stage stratified cluster that was proportional to the size sampling technique was used to select a nationally and provincially representative sample of patients with type 2 diabetes in Thailand. A total of 186,010 patients with type 2 diabetes were enrolled in the study from 2011 to 2018. The prevalence of adequate glycemic control (hemoglobinA1c level < 7.0%) among patients with type 2 diabetes were estimated to be 34.5% (95%CI 33.8–35.2%) in 2011, 33.0% (95%CI 32.4–33.6%) in 2012, 34.7% (95%CI 34.1–35.4%) in 2013, 35.5 (95%CI 34.9–36.1%) in 2014, 35.6 (95%CI 35.0–36.2%) in 2015, and 35.6% (95%CI 35.0–36.2%) in 2018, respectively (p for trend < 0.001). Independent factors related to poor glycemic control (hemoglobinA1c ≥ 7%) were being female, younger aged, living in the northeastern region, received care form hospitals lower than regional level, under universal health coverage scheme, greater duration of diabetes, higher body mass index level and absence of hypertension comorbidity.

Diabetes Control During Massachusetts Insurance Reform.

Racial/ethnic disparities in glycemic control-a key diabetes outcome measure-continue to widen, even though the overall prevalence of glycemic control in the US has improved. Health insurance coverage may be associated with improved glycemic control, but few studies examine effects during a period of policy change. We assessed changes in glycemic control by racial/ethnic groups following the Massachusetts Health Insurance Reform for patients at two urban safety-net academic health systems between January 2005 and December 2013. We analyzed outcomes for three measures of poor glycemic control: 1) lack of a hemoglobin A1C (A1C) measure during a 6-month period; 2) A1C >8%; 3) A1C >9% before, during, and after implementation of insurance reform. We did not find increased rates of A1C monitoring or control following insurance reform overall or for specific racial/ethnic groups. We found evidence of worsened, not improved, glycemic control in some racial/ethnic groups in the post-reform period. The expansion of affordable insurance coverage was not associated with improved glycemic control in vulnerable populations.

Prevalence of Glycemic Control in the Elderly Adult: A Retrospective Study

Prevalence of Glycemic Control in the Elderly Adult: A Retrospective Study

Prevalence of Glycemic Control and Factors Associated With Increasing Levels of Hba1c Among A Sample of Palestinian Patients With Type 2 Diabetes Mellitus

Prevalence of Glycemic Control and Factors Associated With Increasing Levels of Hba1c Among A Sample of Palestinian Patients With Type 2 Diabetes Mellitus

Abstract #262: Prevalence of Glycaemic Control During Follow Up in Mexican Diabetic Patients

Abstract #262: Prevalence of Glycaemic Control During Follow Up in Mexican Diabetic Patients

Intelligent Internet-based information system optimises diabetes mellitus management in communities.

To evaluate the effect of an intelligent Internet-based information system upon optimising the management of patients diagnosed with type 2 diabetes mellitus (T2DM). In 2015, a T2DM information system was introduced to optimise the management of T2DM patients for 1 year in Fangzhuang community of Beijing, China. A total of 602 T2DM patients who were registered in the health service centre of Fangzhuang community were enrolled based on an isometric sampling technique. The data from 587 patients were used in the final analysis. The intervention effect was subsequently assessed by statistically comparing multiple parameters, such as the prevalence of glycaemic control, standard health management and annual outpatient consultation visits per person, before and after the implementation of the T2DM information system. In 2015, a total of 1668 T2DM patients were newly registered in Fangzhuang community. The glycaemic control rate was calculated as 37.65% in 2014 and significantly elevated up to 62.35% in 2015 ( p < 0.001). After application of the Internet-based information system, the rate of standard health management was increased from 48.04% to 85.01% ( p < 0.001). Among all registered T2DM patients, the annual outpatient consultation visits per person in Fangzhuang community was 24.88% in 2014, considerably decreased to 22.84% in 2015 ( p < 0.001) and declined from 14.59% to 13.66% in general hospitals ( p < 0.05). Application of the T2DM information system optimised the management of T2DM patients in Fangzhuang community and decreased the outpatient numbers in both community and general hospitals, which played a positive role in assisting T2DM patients and their healthcare providers to better manage this chronic illness.

Glycemic control in diabetic patients served by community health centers.

The Community Health Center Network measured the prevalence of glycemic control in diabetic patients at 7 community health centers as part of its clinical quality improvement program. A cross-sectional survey was carried out in a random sample of 1817 diabetic patients having 1 or more encounters from October 1, 2000 to September 30, 2001. Computerized laboratory results for hemoglobin A1c (HbA1c) tests were available for half the sample. Manual review of medical charts was carried out for the rest. The proportion of diabetic patients with 1 or more HbA1c tests in the measurement year was 91% (CI95%: 90-93%) and poor glycemic control (HbA1c > 9%) occurred in 27% (CIM%: 25-30%). The mean of the most recent test was 7.8%. The frequency of testing varied significantly by clinic from 79% to 94% and increased with the number of encounters. Poor glycemic control also varied significantly by clinic (17-48%) and was significantly better in females and older patients. Measures of glycemic control were not associated with ethnicity or insurance status in multivariate analyses. A high proportion of diabetic patients received appropriate care, and this care was not associated with ethnicity or insurance status. The data warehouse was an essential tool for the clinical quality improvement program.