scholarly journals Inaccurate Glycosylated Hemoglobin A1C Measurements in Human Immunodeficiency Virus—Positive Patients with Diabetes Mellitus

2003 ◽  
Vol 37 (4) ◽  
pp. e53-e56 ◽  
Author(s):  
Philip M. Polgreen ◽  
Darcy Putz ◽  
Jack T. Stapleton
2018 ◽  
Vol 1 (2) ◽  
pp. 112-117
Author(s):  
Shiva Raj KC

Diabetes mellitus is a global health problem in 21st century. The incidence of diabetes mellitus is in rise and is estimated to be more prevalent in coming years. It is becoming one of the most common non-infectious and non-neoplastic causes of morbidity and mortality. Various complications are associated with diabetes mellitus. With control of blood glucose level, complications of diabetes mellitus can be minimized. In different time frame, different parameters and level have been used to diagnose diabetes. Glycosylated hemoglobin A1c is one of the reliable indicator of chronic hyperglycemia. In 2011, World Health Organization has included HbA1c in the diagnostic criteria. Various methods are used to detect the level of HbA1c.  Glycosylated hemoglobin is being used in the management of diabetes mellitus. Various studies have shown its prognostic implication in micro and macrovascular complications. Here we discuss various methods of estimation of HbA1c, various role of HbA1c in the management of Diabetes Mellitus and limitation of the test.  


2014 ◽  
Vol 67 (1-2) ◽  
pp. 49-54 ◽  
Author(s):  
Mirjana Janicijevic-Petrovic ◽  
Biljana Veljkovic ◽  
Katarina Janicijevic ◽  
Tatjana Sarenac-Vulovic

Introduction. Diabetes mellitus is as old as the human race. Retinopathy, being one of complications of diabetes mellitus, is the most common cause of blindness. This study was aimed at analyzing the correlation between retinopathy and duration of disease, metabolic control, and obesity. Material and Methods. The study sample consisted of 135 patients divided into the experimental group of 90 patients with retinopathy and the control group of 45 patients without retinopathy. The patients were examined according to standard protocols: anamneses, endocrinology, ophthalmology exams, biochemical analyses, and anthropometric measurements. Results. The average age of patients was 60.13 ? 9.29 in the experimental group, while it was 57.55 ? 4.85 in the control group. The average duration of disease was 11.71 ? 5.8 and 14.40 ? 7.68 in the control group experimental group, respectively. The following statistically essential differences between the control and experimental group were found: in duration of disease (11.71 ? 5.85; 14.40 ? 7.68; r = 0.000), in glycemia (7.02 ? 2.20; 8.34 ? 3.18; p = 0.000), in glycosylated hemoglobin A1C (HbA1C) (7.16 ? 1.37; 8.22 ? 2.05; r = 0.000), in triglycerides (1.92 ? 0.72; 2.63 ? 1.60; r = 0.001), and in body mass index (23.94 ? 2.65; 27.66 ? 15.13; r = 0.000). Conclusion. There is a positive correlation between duration of disease, glycosylated hemoglobin A1C, triglycerides, body mass index - obesity and retinopathy. A significant statistical correlation among those parameters has been found in patients with diabetic retinopathy.


2021 ◽  
Vol 10 (11) ◽  
pp. 2357
Author(s):  
George Psillas ◽  
Grigorios G. Dimas ◽  
Anastasia Sarafidou ◽  
Triantafyllos Didangelos ◽  
Vasilios Perifanis ◽  
...  

The aim of this study is to evaluate the effects of diabetes mellitus, hypertension and hypercholesterolemia on the clinical presentation and outcome of Bell’s palsy. The study (comorbidity) group consisted of 50 patients with Bell’s palsy associated with diabetes, hypertension, or hypercholesterolemia; the control group included 46 patients with Bell’s palsy, but without comorbid diseases. The House–Brackmann grading system (I to VI) was used in order to assess the initial and final facial functions. Both groups of patients were treated with steroids and the antiviral agent acyclovir. The mean severity of initial facial paralysis was more significant in diabetes, hypercholesterolemia, and hypertension, in comparison to the control group. Patients suffering from Bell’s palsy and concomitant comorbidities have a poorer prognosis (HB III-VI) compared to patients without comorbidities. Increased glycosylated hemoglobin A1c levels (>6.7%) were significantly correlated with unsatisfactory facial recovery. The pathogenetic mechanisms by which diabetes, hypercholesterolemia, and hypertension affect the vasa nervosum of facial nerve have been described.


2021 ◽  
Vol 15 (12) ◽  
pp. 3513-3515
Author(s):  
Bader Alsuwayt

Aim: To describe the rate of the controlled level of glycosylated hemoglobin (HbA1c) among diabetes mellitus patients in Dammam city, Kingdom of Saudi Arabia (KSA). To assess the association between the status of HbA1c and the different patient-related factors namely: insulin use, metformin, dyslipidemia, and statin use. Methods: This cross-sectional study was performed at Security Forces Hospital, Dammam, KSA, between November 2020 and February 2021. A sample of two hundred known diabetic patients who were regularly followed up at the outpatient department (OPD) was selected randomly for the current study. Results: A very low rate (24%) of controlled HbA1C levels in patients with diabetes (type 1 DM and type 2 DM), The data showed that 85 % of all participants in our study are T2DM patients, while only 15% are T1DM patients, Our data showed that patients with dyslipidemia, hypothyroidism, or hypertension have a high level of uncontrolled HbA1C levels. Surprisingly, both dyslipidemia and statin use were predictors of uncontrolled HbA1C, Unexpectedly, non-metformin use has a protective effect toward controlling HbA1C, While insulin use is a strong predictor of uncontrolled HbA1C (OD 5.20). Conclusion: A low rate of controlled glycated hemoglobin (HbA1c) level among patients with diabetes (T1DM and T2DM) in our sample urges the need for immediate intervention to investigate and improve the current findings. Further investigations are needed to fully explain the high rate of uncontrolled HbA1c among insulin, metformin and statins users. Keywords: Glycated hemoglobin, HbA1c, Diabetes mellitus, Statins, Metformin.


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