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Journal articles on the topic 'Haemoglobin A1c'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Siddiqui, Muhammad Saeed, Makki Ahmad Ali, Muhammad Zakaria, and Muhammad Aziz. "HAEMOGLOBIN A1C;." Professional Medical Journal 24, no. 08 (August 8, 2017): 1162–66. http://dx.doi.org/10.29309/tpmj/2017.24.08.997.

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Objectives: Our aim was to determine the prevalence of controlled diabeteson the basis of HbA1c test (Hb ≤ 7 ) in registered diabetic population in three Primary HealthCenters of Ministry of Health Makkah al Mukarrahma. Study Design: Retrospective review ofmedical records of registered adult Saudi patients with type 2 diabetes. Setting: Three PrimaryHealth Centers of Ministry of Health Makkah al Mukarrahma. Period: 20 June 2015 to 31December 2015. Methods: The sample size calculated was 354 patients with confidence levelof 95% and confidence interval of 5. The cut of values adjusted for all diabetes mellitus patientswas, haemogloblin A1c (HBA1c) ≤ 7. Three last readings were recorded and to be declared ascontrolled diabetic case (valid control), last two readings were required to be within this normallimit. Data was processed on Microsoft Excel and SPSS-23 software. Results: Overall the agerange was 21–79 (58) years and a mean of +/- SD of 56.67 +/- 11.97. Male were 206 and female148 in number. Hb A1c test entries recorded in 292. On the basis of set HbA1c criteria no validcontrol entry was found in one PHC while in other two, there were 15 (4.23% prevalence) validcontrol entries. Valid control results were found significant (P < 0.05). Conclusion: Very lowPrevalence of controlled diabetes on bases of HbA1c test in Primary Health Centers indicatenoncompliance of this test in our study group. Guidelines of the Ministry of Health regardingcare of diabetic patients in Primary Health Care should be followed to achieve the recommendedoutcome.

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2

Mo, Yifei, Jian Zhou, Xiaojing Ma, Wei Zhu, Lei Zhang, Jie Li, Jingyi Lu, Cheng Hu, Yuqian Bao, and Weiping Jia. "Haemoglobin A1c variability as an independent correlate of atherosclerosis and cardiovascular disease in Chinese type 2 diabetes." Diabetes and Vascular Disease Research 15, no. 5 (May 31, 2018): 402–8. http://dx.doi.org/10.1177/1479164118778850.

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Objective: To examine the association between haemoglobin A1c variability and macrovascular complication in type 2 diabetes. Methods: We retrospectively enrolled 5278 diabetes patients with no history of cardiovascular disease and atherosclerosis by ultrasound at their first visit to the hospital from 1999 to 2010. Patients had a median of 4 haemoglobin A1c (range = 3–9) measurements during follow-up. Average haemoglobin A1c and haemoglobin A1c variability were calculated as intra-individual mean, standard deviation, coefficient of variation and adjusted standard deviation. Cardiovascular disease events and ultrasound results were re-evaluated from the medical history at the end of the study. Results: A total of 972 patients had macrovascular complication. Compared to those without atherosclerosis/cardiovascular disease (n = 4306), haemoglobin A1c intra-individual mean and haemoglobin A1c variability levels were significantly higher in patients with macrovascular complication ( p < 0.001). Multivariable logistic regression analysis showed that haemoglobin A1c variability was associated with macrovascular complication. Moreover, 488 patients with only atherosclerosis had significantly higher haemoglobin A1c intra-individual mean and haemoglobin A1c variability values than those without atherosclerosis/cardiovascular disease ( p < 0.001), but in 484 patients with cardiovascular disease incidents, only higher haemoglobin A1c intra-individual mean level was found ( p = 0.004). Conclusions: In Chinese type 2 diabetes, haemoglobin A1c variability was associated with macrovascular complication. Long-term stabilization of glucose is important in diabetes management, especially in the early stage of atherosclerosis.

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Otabe, Shuichi, Hitomi Nakayama, Tsuyoshi Ohki, Eri Soejima, Yuji Tajiri, and Kentaro Yamada. "Haemoglobin variants may cause significant differences in haemoglobin A1c as measured by high-performance liquid chromatography and enzymatic methods in diabetic patients: a cross-sectional study." Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 54, no. 4 (August 5, 2016): 432–37. http://dx.doi.org/10.1177/0004563216664366.

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Background We aimed to determine whether the discrepancy between haemoglobin A1c values determined by high-performance liquid chromatography and enzymatic haemoglobin A1c measurements in diabetic patients was clinically relevant. Methods We randomly recruited 1421 outpatients undergoing diabetic treatment and follow-up who underwent at least three haemoglobin A1c measurements between April 2014 and March 2015 at our clinic. In 6369 samples, haemoglobin A1c was simultaneously measured by HA-8160 and MetaboLead (enzymatic assay), and the values were compared. Results haemoglobin A1c measurements by high-performance liquid chromatography and enzymatic assay were strongly correlated (correlation coefficient: 0.9828, linear approximation curve y = 0.9986x − 0.2507). Mean haemoglobin A1c (6.8 ± 1.0%) measured by high-performance liquid chromatography was significantly higher than that measured by enzymatic assay (6.5 ± 1.0%, P < 0.0001). During the sample processing, four (0.3%) subjects presented consistently lower haemoglobin A1c values (<0.7%) by high-performance liquid chromatography than those from enzymatic assay. Of these, three had Hb Toranomon [β112 (G14) Cys→Trp]. The fourth had Hb Ube-2 [α68 (E17) Asn→Asp]. One other subject presented consistently higher haemoglobin A1c values (>1%) by high-performance liquid chromatography than those from enzymatic assay and was diagnosed with a −77 (T > C) mutation in the δ-globin gene. These unrelated asymptomatic subjects had normal erythrocyte profiles, without anaemia. Conclusions We showed that haemoglobin A1c values measured by high-performance liquid chromatography were significantly higher than those measured by enzymatic assay in diabetic subjects. However, when an oversized deviation (>0.7%) between glycaemic control status and haemoglobin A1c is apparent, clinicians should check the methods used to measure haemoglobin A1c and consider the possible presence of a haemoglobin variant.

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4

Wenk, R. E., H. McGann, and J. Gibble. "Haemoglobin A1c in donor erythrocytes." Transfusion Medicine 21, no. 5 (July 5, 2011): 349–50. http://dx.doi.org/10.1111/j.1365-3148.2011.01089.x.

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5

John, W. G. "Haemoglobin A1c towards global standardization." Diabetic Medicine 27, no. 7 (April 2, 2010): 733–34. http://dx.doi.org/10.1111/j.1464-5491.2010.03044.x.

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6

Lo, V. M. H., E. S. K. Ma, E. M. C. Chau, and J. C. C. So. "A spuriously 'normal' haemoglobin A1c result." Annals of Clinical Biochemistry 49, no. 4 (May 15, 2012): 408–11. http://dx.doi.org/10.1258/acb.2011.011202.

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7

Sharp, Patrick, and Sandra Rainbow. "Continuous glucose monitoring and haemoglobin A1c." Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 39, no. 5 (September 1, 2002): 516–17. http://dx.doi.org/10.1258/000456302320314557.

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Background: Measurement of HbA1c is the standard test for assessment of glycaemic control in diabetic subjects. Using new glucose sensing technology we re-evaluated the significance of HbA1c in terms of the aspects of the blood profile it measures in patients with diabetes. Methods: In a group of 27 patients with type 1 diabetes, interstitial fluid glucose concentrations were monitored for a mean of 2·6 days using the Continuous Glucose Monitoring SystemTM (MiniMed Inc, CA, USA). Results were correlated with an HbA1c measurement taken at the time of sensor insertion. Results: Results were available in 25 subjects, two datasets being lost due to patient error. There was a correlation between mean sensor glucose value, and the HbA1c value ( r=0·59, P=0·002). The correlation with standard deviation of the readings was weaker (r=0·3, P=0·15). No other descriptor of the sensor glucose concentration correlated with HbA1c. Conclusion: The mean interstitial glucose concentration recorded with the Continuous Glucose Monitoring System correlates with HbA1c level recorded at the time, but with no other marker of glucose control in diabetic subjects. These results have implications for the interpretation of HbA1c concentrations in type 1 diabetes.

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8

Yang, W. "Diagnosing diabetes using glycated haemoglobin A1c." BMJ 340, may17 2 (May 17, 2010): c2262. http://dx.doi.org/10.1136/bmj.c2262.

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9

Lee, I.-Te. "Mean and variability of annual haemoglobin A1c are associated with high-risk peripheral artery disease." Diabetes and Vascular Disease Research 17, no. 3 (March 2020): 147916412090903. http://dx.doi.org/10.1177/1479164120909030.

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Background: Glucose variability is predictive of cardiovascular events and all-cause mortality. However, the association between peripheral artery disease and glucose variability has not been thoroughly investigated. Therefore, the standard deviation of annual haemoglobin A1c was assessed in patients with type 2 diabetes for evaluating the different risks of peripheral artery disease. Methods: A total of 4144 patients underwent an evaluation for the ankle-brachial index and the percentage of mean arterial pressure at the ankle. The first haemoglobin A1c record was retrospectively collected from each year until the ankle-brachial index measurement. Results: The standard deviation of annual haemoglobin A1c was higher in patients with ankle-brachial index ⩽0.90 than in those with ankle-brachial index >0.90 (1.1 ± 0.9% vs 1.0 ± 0.8%, p = 0.009) and was higher in patients with percentage of mean arterial pressure ⩾45% than in those with percentage of mean arterial pressure <45% (1.1 ± 0.8% vs 1.0 ± 0.8%, p = 0.007). A high standard deviation and mean of annual haemoglobin A1c are associated with high-risk peripheral artery disease, which is defined as a combination of ankle-brachial index ⩽0.90, percentage of mean arterial pressure ⩾45% or both (odds ratio = 1.306; 95% confidence interval = 1.057–1.615; p = 0.014). Conclusion: Fluctuation in the haemoglobin A1c value indicates higher risk for peripheral artery disease in patients with type 2 diabetes and poor glucose control.

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Rajaratnam, HN, MI Weerakkody, M. Weerasinghe, and S. Siriwardena. "A diabetic with high haemoglobin A1c due to persistent haemoglobin F." Sri Lanka Journal of Diabetes Endocrinology and Metabolism 1, no. 1 (March 25, 2012): 45. http://dx.doi.org/10.4038/sjdem.v1i1.4192.

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Catchpole, B. "Haemoglobin A1c testing for dogs with diabetes." Veterinary Record 163, no. 12 (September 20, 2008): 372. http://dx.doi.org/10.1136/vr.163.12.372-c.

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12

Lenters-Westra, Erna, Roger K. Schindhelm, Henk J. Bilo, and Robbert J. Slingerland. "Haemoglobin A1c: Historical overview and current concepts." Diabetes Research and Clinical Practice 99, no. 2 (February 2013): 75–84. http://dx.doi.org/10.1016/j.diabres.2012.10.007.

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13

Lamar, Melissa, Robert S. Wilson, Lei Yu, Bryan D. James, Christopher C. Stewart, David A. Bennett, and Patricia A. Boyle. "Associations of literacy with diabetes indicators in older adults." Journal of Epidemiology and Community Health 73, no. 3 (December 7, 2018): 250–55. http://dx.doi.org/10.1136/jech-2018-210977.

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BackgroundLiteracy, the ability to access, understand and utilise information and concepts from diverse sources in ways that promote good outcomes is key to successful ageing. Domain-specific health and financial literacy are particularly relevant to older adults as they face increasingly complex health and financial demands including those related to chronic conditions like type 2 diabetes. We therefore investigated the associations of literacy, including health and financial literacy, with diabetes indicators (ie, haemoglobin A1c and blood glucose) in a community-based cohort study of ageing.MethodsParticipants were 908 non-demented older adults (age ~81 years;75% women) from the Rush Memory and Aging Project. Literacy was measured using questions designed to assess comprehension of health and financial information and concepts and yielded a total score and domain-specific health and financial literacy scores. Non-fasting haemoglobin A1c and blood glucose samples were collected, participants were queried about diabetes status and medications for diabetes were visually inspected and coded. Participants also underwent a cognitive assessment, medical history and depressive symptom screening.ResultsIn separate multivariable linear regression models, total (p values <0.03) and health (p values <0.009) literacy were inversely associated with haemoglobin A1c and blood glucose levels after adjusting for age, sex, education, hypertension, global cognitive functioning and depressive symptoms. Financial literacy was inversely associated with haemoglobin A1c levels in adjusted models (p=0.04). Sensitivity analyses conducted among individuals without diabetes revealed similar results.ConclusionLower literacy levels are associated with higher diabetes indicators, particularly haemoglobin A1c which is suggestive of longer-term glycaemic instability.

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Tin, SS, and V. Wiwanitkit. "Haemoglobin variant and falsely high haemoglobin A1c value on ion-exchange chromatography." Singapore Medical Journal 55, no. 11 (November 2014): 603. http://dx.doi.org/10.11622/smedj.2014159.

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15

Wei, Junping, Huijuan Zheng, Liansheng Wang, Qiuhong Wang, Fan Wei, and Litao Bai. "Effects of telephone call intervention on cardiovascular risk factors in T2DM: A meta-analysis." Journal of Telemedicine and Telecare 25, no. 2 (December 11, 2017): 93–105. http://dx.doi.org/10.1177/1357633x17745456.

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Background Mobile health interventions utilising telephone calls are promising tools for diabetes management. However, there is still a lack of convincing evidence demonstrating their beneficial effects on cardiovascular risk factors. The aim of this meta-analysis of randomised controlled trials was to assess the effect of telephone calls on glycaemic control and other cardiovascular risk factors in type 2 diabetes mellitus patients. Methods Two independent reviewers searched three online databases (PubMed, the Cochrane Library and EMBASE) to identify relevant English-language randomised controlled trials up to September 2017. Randomised controlled trials that assessed the effects of telephone calls on glycaemic control and other cardiovascular risk factors in type 2 diabetes mellitus patients were included. Effect size was calculated for changes in glycosylated haemoglobin A1c, weight, blood pressure and lipid levels using fixed- or random-effects models. Results Eighteen studies involving 3954 patients were included in the meta-analysis. Compared with usual care, telephone calls significantly decreased glycosylated haemoglobin A1c, by 0.12% (95% confidence interval: −0.22% to −0.02%). Univariate regression analysis showed that none of the covariates (number of participants, baseline age, baseline glycosylated haemoglobin A1c, duration of diabetes, call maker, number of calls and duration of study) had an impact on glycosylated haemoglobin A1c. For other cardiovascular risk factors, telephone calls significantly reduced systolic blood pressure by 0.19 mm Hg (95% confidence interval: −0.34% to −0.03%) but non-significantly changed diastolic blood pressure, body mass index, low-density lipoprotein cholesterol, total cholesterol, triglyceride or high-density cholesterol levels. Conclusions This meta-analysis supports the hypothesis that telephone calls offer moderate benefits for glycosylated haemoglobin A1c and systolic blood pressure reduction among type 2 diabetes mellitus patients. However, the data remain insufficient regarding the association of telephone calls with lowered diastolic blood pressure, body mass index or improved lipoprotein profiles.

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Hare, M. J. L., J. E. Shaw, and P. Z. Zimmet. "Current controversies in the use of haemoglobin A1c." Journal of Internal Medicine 271, no. 3 (February 14, 2012): 227–36. http://dx.doi.org/10.1111/j.1365-2796.2012.02513.x.

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Gama, R., and T. Likhari. "Haemoglobin A1c: ethnic differences apply to the UK." BMJ 339, dec31 1 (December 31, 2009): b5648. http://dx.doi.org/10.1136/bmj.b5648.

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Chantelau, E. "Decay of haemoglobin a1c upon return to normoglycaemia." Diabetologia 35, no. 2 (February 1992): 191. http://dx.doi.org/10.1007/bf00402556.

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Griffiths, Rosemary J., Paul S. Vinall, Max H. Stickland, and John K. Wales. "Haemoglobin A1c levels in normal and diabetic pregnancies." European Journal of Obstetrics & Gynecology and Reproductive Biology 24, no. 3 (March 1987): 195–200. http://dx.doi.org/10.1016/0028-2243(87)90018-9.

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20

John, W. Garry. "Global standardisation of haemoglobin A1c using metrological principles." Clinical Biochemistry 45, no. 13-14 (September 2012): 1048–50. http://dx.doi.org/10.1016/j.clinbiochem.2012.07.105.

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21

Wiener, K., N. B. Roberts, and B. N. Green. "The Effect of an Unusual Haemoglobin Variant (β51Pro → His) on Haemoglobin A1c Measurement." Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 35, no. 2 (March 1998): 321–23. http://dx.doi.org/10.1177/000456329803500221.

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22

Story, C. J., A. P. Roberts, and R. G. Ryall. "Borderline maintenance of erythrocyte 2,3-diphosphoglycerate concentrations in normoxic type 1 (insulin dependent) diabetic subjects." Clinical Science 70, no. 2 (February 1, 1986): 127–29. http://dx.doi.org/10.1042/cs0700127.

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1. Erythrocyte 2,3-diphosphoglycerate and haemoglobin A1C concentrations were measured in 26 clinically normoxic patients with type 1 (insulin dependent) diabetes mellitus. The concentration of 2,3-diphosphoglycerate theoretically required to maintain normal erythrocyte oxygen delivery function in each subject was calculated and compared with the measured concentrations. 2. In the majority of diabetic patients 2,3-diphosphoglycerate concentrations were sufficient to keep the erythrocyte oxygen dissociation curve within the normal range under otherwise normal blood conditions. There was, however, a minority of patients in which this was not true. 3. It is concluded that the increased erythrocyte 2,3-diphosphoglycerate concentrations in clinically normoxic diabetic subjects are generally less than compensatory for the effect of haemoglobin A1C formation on the haemoglobin-oxygen dissociation curve.

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Kauffman, Amy B., Thomas Delate, Kari L. Olson, Alicia A. Cymbala, Kara A. Hutka, Sheila L. Kasten, and Jon R. Rasmussen. "Relationship between Haemoglobin A1C Values and Recurrent Cardiac Events." Clinical Drug Investigation 28, no. 8 (2008): 501–7. http://dx.doi.org/10.2165/00044011-200828080-00005.

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Hughes, Ruth C. E., Jonathan A. Williman, and Joanna E. Gullam. "Antenatal haemoglobin A1c centiles: does one size fit all?" Australian and New Zealand Journal of Obstetrics and Gynaecology 58, no. 4 (November 2, 2017): 411–16. http://dx.doi.org/10.1111/ajo.12738.

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Kilpatrick, E. S., Z. T. Bloomgarden, and P. Z. Zimmet. "Is haemoglobin A1c a step forward for diagnosing diabetes?" BMJ 339, no. 10 1 (November 10, 2009): b4432. http://dx.doi.org/10.1136/bmj.b4432.

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Li, Qing, Yi Ju, Ting Jin, Biqiong Pang, Jiade Deng, Tongxin Du, and Hong Wang. "Haemoglobin A1c measurement in patients with chronic kidney disease." Clinical Biochemistry 47, no. 6 (April 2014): 481–84. http://dx.doi.org/10.1016/j.clinbiochem.2013.12.005.

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Hansen, Klavs Würgler. "Converting haemoglobin A1c and average glucose. Time to change?" Diabetes Research and Clinical Practice 153 (July 2019): 194–95. http://dx.doi.org/10.1016/j.diabres.2019.03.013.

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Baltatescu, Anatolie, Elio Striglia, Marina Trento, Aurora Mazzeo, Franco Cavallo, Lorena Charrier, and Massimo Porta. "Detection of perimacular red dots and blots when screening for diabetic retinopathy: Refer or not refer?" Diabetes and Vascular Disease Research 15, no. 4 (May 18, 2018): 356–59. http://dx.doi.org/10.1177/1479164118775318.

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Purpose: Detection of microaneurysms and/or microhaemorrhages near the fovea when screening for diabetic retinopathy poses a problem because referral to retinal specialists may alarm patients and unnecessarily burden ophthalmologists. Methods: Six-month prospective study of patients found to have minimal red lesions within one disc diameter of the fovea when screened for diabetic retinopathy. Two 45° digital photographs, one centred on the macula and the other nasal including the optic disc, were taken for each eye. All patients received a 6-month re-screening appointment. Results: Out of 70 patients, 41 returned for re-screening. Diabetic retinopathy had worsened in 3 who required referral but no treatment, was unchanged in 19 and was undetectable in the other 19. Haemoglobin A1c decreased from 7.76% ± 1.50% (61.3 ± 16.2 mmol/mol) to 6.93% ± 1.7% (52.3 ± 18.9 mmol/mol) in the patients in whom diabetic retinopathy worsened but did not change in the other groups. Baseline haemoglobin A1c ( p = 0.048) and systolic blood pressure ( p = 0.007) were lower in the patients in whom diabetic retinopathy improved, but a multivariate model including haemoglobin A1c, blood pressure and known disease duration could not identify any independent risk factor. Conclusion: Minimal red lesions near the fovea, though commanding early re-screening, do not require immediate referral to retinal specialists.

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Amidu, Nafiu, William Kwame Boakye Ansah Owiredu, Lawrence Quaye, Peter Paul Mwinsanga Dapare, and Yussif Adams. "Comparative Abilities of Fasting Plasma Glucose and Haemoglobin A1c in Predicting Metabolic Syndrome among Apparently Healthy Normoglycemic Ghanaian Adults." International Journal of Chronic Diseases 2019 (July 24, 2019): 1–8. http://dx.doi.org/10.1155/2019/2578171.

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There are arguments as to whether haemoglobin A1c (HbA1c) better predicts Metabolic syndrome (MetS) than fasting plasma glucose. The aim of the study was to explore the comparative abilities of HbA1c and Fasting plasma glucose (FPG) in predicting cardiometabolic risk among apparently healthy adults in the Tamale metropolis. This study was a cross-sectional study conducted in the Tamale metropolis from September, 2017, to January, 2018, among one hundred and sixty (160) apparently healthy normoglycemic adults. A self-designed questionnaire was administered to gather sociodemographic data. Anthropometric and haemodynamic data were also taken and blood samples collected for haemoglobin A1c (HbA1c), fasting plasma glucose (FPG), and lipid profile. MetS was classified using the harmonised criteria as indicated in the joint interim statement (JIS). Out of the 160 participants, 42.5% were males and 57.5% were females. FPG associated better with MetS and other cardiovascular risk markers, compared to HbA1c. FPG had the largest area under curve for predicting MetS and its components. This study shows a stronger association between FPG and MetS compared with haemoglobin A1c; it also provides evidence of a superior ability of FPG over HbA1c in predicting MetS and other adverse cardiovascular outcomes in apparently heathy normoglycemic individuals.

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Schnedl, W. J., E. C. Reisinger, S. Katzensteiner, R. W. Lipp, F. Schreiber, P. Hopmeier, and G. J. Krejs. "Haemoglobin O Padova and falsely low haemoglobin A1c in a patient with type I diabetes." Journal of Clinical Pathology 50, no. 5 (May 1, 1997): 434–35. http://dx.doi.org/10.1136/jcp.50.5.434.

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Loh, Tze Ping, Huan Lin Zhang, and Jin Seng Cheah. "Extremely high (>20 %) glycated haemoglobin A1c in patients with normal haemoglobin and erythrocyte parameters." Endocrine 44, no. 2 (March 14, 2013): 542–43. http://dx.doi.org/10.1007/s12020-013-9920-3.

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Ang, Shu Hwang, Choo Yee Yu, Geik Yong Ang, Yean Yean Chan, Yatimah binti Alias, and Sook Mei Khor. "A colloidal gold-based lateral flow immunoassay for direct determination of haemoglobin A1c in whole blood." Analytical Methods 7, no. 9 (2015): 3972–80. http://dx.doi.org/10.1039/c5ay00518c.

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Schwarz, C., N. Loft, C. Zachariae, and L. Skov. "Effect of Anti-interleukin-17 Treatment on Haemoglobin A1c Levels." Acta Dermato Venereologica 100, no. 16 (2020): adv00265. http://dx.doi.org/10.2340/00015555-3620.

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Pereira, Maria Teresa Rocha e. Pinho, Domingos Lira, Conceição Bacelar, José Carlos Oliveira, and André Couto de Carvalho. "Seasonal variation of haemoglobin A1c in a Portuguese adult population." Archives of Endocrinology and Metabolism 59, no. 3 (June 2015): 231–35. http://dx.doi.org/10.1590/2359-3997000000043.

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Kilpatrick, E. S. "Haemoglobin A1c in the diagnosis and monitoring of diabetes mellitus." Journal of Clinical Pathology 61, no. 9 (August 28, 2008): 977–82. http://dx.doi.org/10.1136/jcp.2007.054304.

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Haemoglobin A1c (HbA1c) is due to celebrate its 40th birthday. Many people would argue that the clinical studies relating the test to diabetes complications while in its late 20s are likely to be its finest ever achievement. However, this article looks at how HbA1c has matured since then and discusses in detail how its many strengths and idiosyncrasies as a marker of glycaemic risk have, as a 30-something, become more clearly understood.As HbA1c approaches middle age, this paper also describes how the test appears to be developing a mid-life crisis, as debate over how its results should be expressed seems likely to divide opinion among clinicians for some time to come.

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Kilpatrick, E. S., W. S. Kilpatrick, M. H. Dominiczak, and M. Small. "Are European standard deviation targets for haemoglobin A1c too strict?" Diabetic Medicine 15, no. 11 (November 1998): 920–23. http://dx.doi.org/10.1002/(sici)1096-9136(1998110)15:11<920::aid-dia700>3.0.co;2-p.

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Low, Serena, Xiao Zhang, Jiexun Wang, Lee Ying Yeoh, Yan Lun Liu, Keven Kue Loong Ang, Wern Ee Tang, et al. "Long-term prospective observation suggests that glomerular hyperfiltration is associated with rapid decline in renal filtration function: A multiethnic study." Diabetes and Vascular Disease Research 15, no. 5 (May 28, 2018): 417–23. http://dx.doi.org/10.1177/1479164118776465.

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Aim: Glomerular hyperfiltration usually occurs early in development of kidney complications in diabetes. To understand hyperfiltration as a marker of renal disease progression in type 2 diabetes mellitus, we aimed to examine association between glomerular hyperfiltration (estimated glomerular filtration rate ⩾ 120 mL/min/1.73 m2) and rapid renal decline (annual estimated glomerular filtration rate loss ⩾ 3 mL/min/1.73 m2). Methods: This was a prospective cohort comprising 1014 patients with type 2 diabetes mellitus attending a Diabetes Centre of a regional hospital in 2002–2014. A separate prospective cohort, comprising 491 patients who attended Diabetes Centre or primary-care polyclinics, was used for validation. We performed binary mediation analysis to examine role of hyperfiltration on relationship between baseline haemoglobin A1c and rapid renal decline. Results: Among patients in discovery cohort, 5.2% had baseline hyperfiltration. Over mean follow-up of 6 years, 22.9% had rapid glomerular filtration rate decline. Baseline hyperfiltration was significantly associated with greater odds of rapid renal decline after adjusting for demographics, diabetes duration and clinical covariates (odds ratio: 2.57; 95% confidence interval: 1.21–5.46; p = 0.014). Similar finding was found in validation cohort (odds ratio: 2.98; 95% confidence interval: 1.06–8.42; p = 0.034). Hyperfiltration significantly accounted for 35.3% of association between increasing baseline haemoglobin A1c and rapid renal decline. Conclusion: Glomerular hyperfiltration is an independent risk factor of rapid renal decline. It mediates the association between increasing haemoglobin A1c and rapid renal decline.

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Nakajima, Katsuyuki, Isao Koyama, Makoto Watanabe, Masakazu Nakamura, Yoshihiro Miyamoto, Yoshiharu Tokita, Koji Sakamaki, Shin-Ichi Yatsuzuka, and Yohnosuke Shimomura. "Comparison of the International Federation of Clinical Chemistry and Japan Diabetes Society reference methods for conversion to the National Glycohemoglobin Standardization Program values." Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 56, no. 4 (April 11, 2019): 508–14. http://dx.doi.org/10.1177/0004563219834965.

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Background The national programmes for the harmonization of haemoglobin A1c measurement in the US and Japan are based on differently designated comparison methods. The future basis for international standardization is expected to be the reference system developed by the International Federation of Clinical Chemistry (IFCC) Working Group on haemoglobin A1c Standardization. The aim of the present study is to compare the relationship between the IFCC reference method (RM) and Japanese Diabetes Society (JDS) RM used for the conversion to the National Glycohemoglobin Standardization Program (NGSP) values. Methods Three different method-comparison studies were performed. All blood samples were measured at the National Cerebral and Cardiovascular Centers (Lipid Reference Laboratories) that serve as Level 1 reference laboratories of the NGSP Network. Regression equations were calculated for the IFCC RM and JDS RM for the conversion to NGSP values. Results Differences were found between the haemoglobin A1c values of the IFCC RM and those of JDS. However, in all cases, the relationships of the IFCC RM and JDS RM were linear and commutable. The relationship is described by the following regression equations: NGSP-HbA1c = 0.915(IFCC-HbA1c) + 2.15% (r2 = 0.998); JDS/JSCC-HbA1c = 0.927(IFCC-HbA1c) + 1.73% (r2 = 0.997). Conclusion There is a firm and reproducible link between the IFCC and JDS-HbA1c values. However, the values calibrated by JDS RM were consistently and significantly higher than the IFCC values (0.1–0.2%) when used for conversion to the NGSP values.

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SIDDIQUI, MUHAMMAD SAEED, MAKKI AHMAD ALI, MUHAMMAD ZAKARIA, and MUHAMMAD AZIZ. "HAEMOGLOBIN A1C; PREVALENCE OF CONTROLLED DIABETES IN REGISTERED DIABETIC PATIENTS WITH HAEMOGLOBIN A1C (HBA1C) ≤ 7 OF THREE SELECTED MOH PRIMARY HEALTH CARE CENTERS OF MAKKAH." PROFESSIONAL MEDICAL JOURNAL 24, no. 08 (August 1, 2017): 1162–66. http://dx.doi.org/10.17957/tpmj/17.3972.

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Loh, Tze Ping, Weng Kung Peng, Lan Chen, and Sunil Kumar Sethi. "Application of smoothed continuous labile haemoglobin A1c reference intervals for identification of potentially spurious HbA1c results." Journal of Clinical Pathology 67, no. 8 (June 11, 2014): 712–16. http://dx.doi.org/10.1136/jclinpath-2014-202346.

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AimsWe aim to develop smoothed continuous 2.5th and 97.5th percentile values for labile glycated haemoglobin A1c to glycated haemoglobin A1c (LHbA1c:HbA1c) ratio against HbA1c, and apply them on our patient population for identification of potentially spurious HbA1c measurements.MethodsThe LHbA1c and HbA1c were measured using Bio-rad Variant II high-performance liquid chromatography system. We recorded the LHbA1c and HbA1c values of 1555 patients who had normal chromatograms. Using these results, the 2.5th and 97.5th percentile reference limits of the LHbA1c:HbA1c ratio were described by LHbA1c:HbA1c=−0.0072×HbA1c +0.2925 and LHbA1c:HbA1c=−0.0132×HbA1c +0.5327, respectively.ResultsWhen the reference intervals were applied on a separate 1000 patients, 34 and 29 of them had abnormally high and low LHbA1c:HbA1c ratios, respectively. Most of the observed high ratios were associated concurrently with elevated plasma glucose, anaemia, chronic liver and kidney diseases. A suppressed ratio was mostly associated with haemoglobin variants. Patients with heterozygous HbE or HbS variants tend to have lower LHbA1c:HbA1c ratios while the converse is true for heterozygous HbJ.ConclusionsThe continuous LHbA1c:HbA1c ratio may be used to detect confounding factors or spurious HbA1c results, but its performance is confounded and reduced by the ambient plasma glucose.

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Kilpatrick, ES, and PH Winocour. "ABCD position statement on haemoglobin A1c for the diagnosis of diabetes." Practical Diabetes International 27, no. 7 (August 16, 2010): 306–10. http://dx.doi.org/10.1002/pdi.1508.

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Engström, G., J. G. Smith, M. Persson, P. M. Nilsson, O. Melander, and B. Hedblad. "Red cell distribution width, haemoglobin A1c and incidence of diabetes mellitus." Journal of Internal Medicine 276, no. 2 (January 28, 2014): 174–83. http://dx.doi.org/10.1111/joim.12188.

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Huang, J., J. Schmeidler, M. S. Beeri, C. Rosendorff, S. Bhatia, R. K. West, I. N. Bespalova, R. Mavris, and J. M. Silverman. "Haemoglobin A1c and cognitive function in very old, cognitively intact men." Age and Ageing 41, no. 1 (September 18, 2011): 125–28. http://dx.doi.org/10.1093/ageing/afr124.

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Moore, Kevin J., Erin C. Dunn, Erin N. Marcus, and Tulay Koru-Sengul. "Glycaemic indices and haemoglobin A1c as predictors for non-healing ulcers." Journal of Wound Care 27, Sup4 (April 2018): S6—S11. http://dx.doi.org/10.12968/jowc.2018.27.sup4.s6.

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Hussain, Nadia. "Haemoglobin A1c and Iron Deficiency Anaemia our Understanding Through the Decades." Romanian Journal of Diabetes Nutrition and Metabolic Diseases 22, no. 3 (September 1, 2015): 289–96. http://dx.doi.org/10.1515/rjdnmd-2015-0035.

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Abstract HbA1c concentrations are affected by several factors including red blood cell turnover. The International Expert Committee has highlighted this observation for the benefit of physicians who evaluate HbA1c in diabetics. There are many types of anaemia that affect glycated haemoglobin (HbA1c) values but iron deficiency anaemia, one of the most common, has been proved to show higher than true values of HbA1c. The mechanism of how iron deficiency anaemia affects HbA1c has yet to be understood. Several studies have been conducted in order to unravel the mechanisms but there still remains a dearth of information. Future research needs to focus on the mechanistic reasons why HbA1c is higher in patients with iron deficiency anaemia in particular. This can pave the way for possible large scale studies to address the HbA1c enhancing effect and the mechanism of increased HbA glycation in iron deficiency properly.

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Simon, D., C. Senan, P. Garnier, M. Saint-Paul, and L. Papoz. "Epidemiological features of glycated haemoglobin A1c-distribution in a healthy population." Diabetologia 32, no. 12 (December 1989): 864–69. http://dx.doi.org/10.1007/bf00297451.

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Yoon, Hei Jin, J. W. Song, J. K. Shim, and Y. L. Kwak. "Preoperative haemoglobin A1c predicts outcome following off-pump coronary bypass surgery." Journal of Cardiothoracic and Vascular Anesthesia 32 (August 2018): S1. http://dx.doi.org/10.1053/j.jvca.2018.08.025.

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Song, Yan, Ying Dang, Hao Li, Jun Feng, and Litao Ruan. "Relationship between carotid intraplaque neovascularization and haemoglobin A1c in diabetic patients." Clinical Neurology and Neurosurgery 203 (April 2021): 106515. http://dx.doi.org/10.1016/j.clineuro.2021.106515.

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GREY, V., M. WILKINSON, L. PHELAN, C. HUGHES, and B. J. BAIN. "Inaccuracy of high-performance liquid chromatography estimation of haemoglobin F in the presence of increased haemoglobin A1c." Clinical and Laboratory Haematology 29, no. 1 (February 2007): 42–44. http://dx.doi.org/10.1111/j.1365-2257.2006.00805.x.

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Chao, Yan, Zemin Wan, Xiaobin Wu, Feng Qiu, Xinzhong Wu, Yunxiu Wang, Peifeng Ke, Jianhua Xu, Junhua Zhuang, and Xianzhang Huang. "Identification of haemoglobin New York by haemoglobin A1c measurement using the Sebia Capillarys 2 Flex Piercing system." Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 54, no. 1 (October 20, 2016): 178–82. http://dx.doi.org/10.1177/0004563216671756.

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Haemoglobinopathies may interfere with the haemoglobin A1c (HbA1c) measurement, leading to incorrect diagnosis and inappropriate treatment. It is essential that HbA1c assays are capable of identifying haemoglobinopathies. We report two cases of haemoglobin New York (HbNY) discovered through HbA1c analysis using capillary electrophoresis (Capillarys 2 Flex Piercing [C2FP], Sebia). We used these samples to evaluate the ability of three other HbA1c assays to identify this variant: ion-exchange high-performance liquid chromatography (Variant II Turbo [VII-T], Bio-Rad); boronate affinity high-performance liquid chromatography (Ultra2, Trinity Biotech) and immunoassay (Cobas c501 Tina-quant Generation 3, Roche Diagnostics). Each method was used for HbA1c assay of in samples from two cases of heterozygous haemoglobinopathy: β0-thalassemia/HbNY (Case 1) and HbA/NY (Case 2). Only the C2FP system detected HbNY (an additional peak appeared between HbA1c and HbA0). Clinical laboratories should be aware of the limitations of their HbA1c assay methods especially in geographic areas, where haemoglobinopathy prevalence is high.

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