Effect of Total Hemoglobin level on HbA1c value in Type 2 Diabetes Mellitus patients

Narayanan, Sreedev; Dash, Prakruti; Mahajan, Preetam

doi:10.3329/bjms.v19i1.43882

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…This finding is in accordance with the previous study ( r =0.148, p=0.56) conducted in India. 31 However, contrary to our finding, there was a statistically significant inverse correlation between HGB and HbA1c in T2 DM patients from the study of Rashid et al ( r =−0.979, p<0.05). 32 The discrepancy might be due to differences in the study population, and T2 DM patients with known diabetic nephropathy were included in the previous study.…”

Section: Discussioncontrasting

confidence: 99%

Evaluation of Red Blood Cell Parameters as a Biomarker for Long-Term Glycemic Control Monitoring Among Type 2 Diabetic Patients in Southwest Ethiopia: A Cross-Sectional Study

Mengstie¹,

Sime²,

Kene³

et al. 2021

DMSO

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Objective The main aim of this study was to assess red blood cell parameters as a biomarker for long-term glycemic monitoring among T2 DM patients. Methods Facility-based cross-sectional study through a consecutive sampling technique was conducted among 124 T2 DM patients at the chronic illness follow-up clinic of Jimma Medical Center (JMC) from July 27 to August 31, 2020. A structured questionnaire was used to collect socio-demographic and clinical-related data. Five milliliters of the blood specimen were collected from each eligible T2 DM patient. Glycated hemoglobin (HbA1c) and red blood cell parameters were determined by Cobas 6000 and DxH 800 fully automated analyzers, respectively. Data were entered into EpiData software version 3.1 and exported to SPSS 25 version for analysis. Independent t -test and Pearson’s correlation coefficient were used to address the research questions. A P-value <0.05 was considered statistically significant. Results The mean age of study participants was 51.84± 11.6 years. Moreover, 60.5% of T2 DM patients were in poor glycemic control. There was a significant mean difference between good and poor glycemic controlled T2 DM patients in red blood cell count (4.79±0.5 vs 4.38±0.8), hemoglobin (14.13±1.4 vs 13.60±1.6), mean corpuscular volume (89.52±4.7 vs 92.62±7.5), mean corpuscular hemoglobin (29.63±1.6 vs 30.77±2.9), and red cell distribution width (13.68±1.1 vs 14.63±1.2) respectively. Red blood cell count was inversely correlated ( r =−0.280, p=0.002) with HbA1c while mean corpuscular volume ( r =0.267, p=0.003), mean corpuscular hemoglobin ( r =0.231, p=0.010), and red cell distribution width ( r = 0.496, p=0.000) were positively correlated with level of HbA1c. Conclusion Red cell count, mean corpuscular volume, mean corpuscular hemoglobin, and red cell distribution width could be useful indicators to monitor the glycemic status of T2 DM patients instead of HbA1c, though large prospective studies should be considered.

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Section: Discussioncontrasting

confidence: 99%

Evaluation of Red Blood Cell Parameters as a Biomarker for Long-Term Glycemic Control Monitoring Among Type 2 Diabetic Patients in Southwest Ethiopia: A Cross-Sectional Study

Mengstie¹,

Sime²,

Kene³

et al. 2021

DMSO

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show abstract

“…In the present study, the HGB level was significantly reduced in T2 DM patients with PGC (Table 2). This finding is in accordance with the previous study (r= 0.148, p= 0.56) conducted in India [28]. But in contrary to our finding, there was a statistically significant inverse correlation between HGB and HbA1c in T2 DM patients from the study of Rashid et al (r= -0.979, p< 0.05) [29].…”

Section: Discussionsupporting

confidence: 90%

Evaluation of Red Blood Cell Parameters as a Biomarker for Long-Term Glycemic Control Monitoring Among Type 2 Diabetic Patients in Southwest Ethiopia: A Cross-Sectional Study

Asmamaw

Sime

Kene

et al. 2021

Preprint

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Background: Type 2 Diabetes Mellitus (T2 DM) is a common type of DM characterized by hyperglycemia. Glycation of hemoglobin and related proteins in DM can affect the physiological and structural properties of red blood cells. Although glycated hemoglobin (HbA1c) test continues to be the gold standard for the assessment of long-term glycemic control accessibility and affordability of the test in routine diagnosing service are still limited in developing countries. Hence, this study was aimed to assess red blood cell parameters as a biomarker for long-term glycemic monitoring among T2 DM patients.Methods: Facility-based cross-sectional study through a consecutive sampling technique was conducted among 124 T2 DM patients at the chronic illness follow-up clinic of Jimma Medical Center (JMC) from July 27 to August 31, 2020. A structured questionnaire was used to collect socio-demographic and clinical-related data. Five milliliters of the blood specimen was collected from each eligible T2 DM patient. HbA1c and red blood cell parameters were determined by Cobas 6000 and DxH 800 fully automated analyzers respectively. Data were entered into Epi-data software version 3.1 and exported to SPSS 25 version for analysis. Independent t-test and Pearson’s correlation coefficient were used to address the research questions. A P-value < 0.05 was considered statistically significant. Results: The mean age of study participants was 51.84± 11.6 years. 60.5% of T2 DM patients were in poor glycemic control. There was a significant mean difference between good and poor glycemic controlled T2 DM patients in red blood cell count (4.79±0.5 vs 4.38±0.8), hemoglobin (14.13±1.4 vs 13.60±1.6), mean corpuscular volume (89.52±4.7 vs 92.62±7.5), mean corpuscular hemoglobin (29.63±1.6 vs 30.77±2.9), and red cell distribution width (13.68±1.1 vs 14.63±1.2) respectively. Red blood cell count was inversely correlated (r=-0.280, p=0.002) with HbA1c while mean corpuscular volume (r=0.267, p=0.003), mean corpuscular hemoglobin (r=0.231, p=0.010), and red cell distribution width (r= 0.496, p=0.000) were positively correlated with level of HbA1c. Conclusion: Red cell count, mean corpuscular volume, mean corpuscular hemoglobin, and red cell distribution width could be useful indicators to monitor the glycemic status of T2 DM patients instead of HbA1c, though large prospective studies should be considered.

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“…(16,17). Additionally, Indian studies reflecting more day to day practice scenario didn't find any correlation between A1c and Hb in mild to moderate anemia (7,18) allying the fears of A1c's possible diagnostics inaccuracy in the setting of mild to moderate Anemia in routine clinical practice. The present study had a substantial proportion of anemic patients (sixty percent), more than double…”

Section: Discussionmentioning

confidence: 99%

Effect of Mild to Moderate Anemia on HbA1c levels in Type 2 Diabetic Patients in Routine Clinical Practice

Khandal

Khandal²,

Chakradhar

2022

Int J Res Rev

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Background: Iron deficiency anemia remains a common condition in India and Hemoglobin A1c (HbA1c) is commonly being used in diabetic individuals both as a parameter of glycemic control over previous three months and as a diagnostic tool. HbA1c levels have been reported to be altered by the presence of nutritional anemias, hemolytic anemia and variant hemoglobin (Hb) among others. Interestingly, iron deficiency anemia effect on HbA1c levels were not found in many studies. Hence a study is conducted to observe the effects if any in routine clinical practice scenario of mild to moderate anemia on HbA1c. Methods: sixty Type 2 Diabetic (T2D) patients HbA1c was analyzed with their Fasting Blood Sugar (FBS), Post Lunch Blood Sugar (PLBS), along with Hemoglobin levels. T2D patients coming for routine follow-up were studied after their consent, with ethical committee clearance. All the parameters were found to have a normal distribution, i.e., they had an acceptable level of skewness — 0.5 to -0.5 -- were then analyzed further with statistical tools viz., Pearson’s correlate and linear regression. Results: The mean HbA1c was found to be 8.9. Further, the mean Hemoglobin (Hb), FBS and PLBS were: 12.29, 157.9 and 229 respectively. The Pearson’s correlate and linear regression analysis was done. HbA1c correlated well with FBS and PLBS, one tailed significance p value being <0.01 for both FBS and PLBS; but was not found to correlate with Hb: p value 0.146 (not significant). Conclusions : In the present study representing field scenario, the HbA1c was not correlated with mild anemia but was significantly correlated with FBS and PLBS. Hence in a routine clinical practice scenario the presence of mild anemia didn’t appear to interfere with the HbA1c levels. Keywords: Diabetes mellitus, HbA1c, Fasting Blood Sugar, Hemoglobin, Nutritional Anemia, Regression analysis

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Effect of Total Hemoglobin level on HbA1c value in Type 2 Diabetes Mellitus patients

Cited by 3 publications

References 15 publications

Evaluation of Red Blood Cell Parameters as a Biomarker for Long-Term Glycemic Control Monitoring Among Type 2 Diabetic Patients in Southwest Ethiopia: A Cross-Sectional Study

Evaluation of Red Blood Cell Parameters as a Biomarker for Long-Term Glycemic Control Monitoring Among Type 2 Diabetic Patients in Southwest Ethiopia: A Cross-Sectional Study

Evaluation of Red Blood Cell Parameters as a Biomarker for Long-Term Glycemic Control Monitoring Among Type 2 Diabetic Patients in Southwest Ethiopia: A Cross-Sectional Study

Effect of Mild to Moderate Anemia on HbA1c levels in Type 2 Diabetic Patients in Routine Clinical Practice

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