“Mind the gap please…”: estimated vs. measured A<sub>1</sub>c from continuous measurement of interstitial glucose over a 3-month period in patients with type 1 diabetes

Oriot, Philippe; Hermans, Michel P.

doi:10.1080/17843286.2018.1561780

Cited by 13 publications

(19 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Given that lab‐tested HbA1c can only be reviewed infrequently, eA1c was developed as a way to monitor glycaemic control in between HbA1c tests, by using mean glucose values that were more readily available. However, partly because of the nomenclature, it became widely assumed that eA1c was intended to track HbA1c itself, with many publications and then directed to highlighting the fact that eA1c tended to differ from HbA1c, often by a wide margin 25,30‐32 . The understanding that eA1c should be expected to differ from HbA1c became lost in translation.…”

Section: Discussionmentioning

confidence: 99%

“…25,[30][31][32] The understanding that eA1c should be expected to differ from HbA1c became lost in translation. Several of these publications and others have noted the tendency of average glucose and HbA1c to differ based on ethnicity, with eA1c commonly being higher than HbA1c in Caucasian subjects 10,32 and lower than HbA1c in black and Asian people with diabetes. 10,25,31 By replacing eA1c with GMI, routinely captured from the last 14 days, it has been possible to distance the role of a short-term measure of average glucose from that of long-term HbA1c but there is still a need for diabetes health care professionals to acknowledge that GMI and long-term HbA1c are expected to differ.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Understanding the clinical implications of differences between glucose management indicator and glycated haemoglobin

Gómez-Peralta

Choudhary

Cosson

et al. 2022

Diabetes Obesity Metabolism

View full text Add to dashboard Cite

Laboratory measured glycated haemoglobin (HbA1c) is the gold standard for assessing glycaemic control in people with diabetes and correlates with their risk of long‐term complications. The emergence of continuous glucose monitoring (CGM) has highlighted limitations of HbA1c testing. HbA1c can only be reviewed infrequently and can mask the risk of hypoglycaemia or extreme glucose fluctuations. While CGM provides insights in to the risk of hypoglycaemia as well as daily fluctuations of glucose, it can also be used to calculate an estimated HbA1c that has been used as a substitute for laboratory HbA1c. However, it is evident that estimated HbA1c and HbA1c values can differ widely. The glucose management indicator (GMI), calculated exclusively from CGM data, has been proposed. It uses the same scale (% or mmol/mol) as HbA1c, but is based on short‐term average glucose values, rather than long‐term glucose exposure. HbA1c and GMI values differ in up to 81% of individuals by more than ±0.1% and by more than ±0.3% in 51% of cases. Here, we review the factors that define these differences, such as the time period being assessed, the variation in glycation rates and factors such as anaemia and haemoglobinopathies. Recognizing and understanding the factors that cause differences between HbA1c and GMI is an important clinical skill. In circumstances when HbA1c is elevated above GMI, further attempts at intensification of therapy based solely on the HbA1c value may increase the risk of hypoglycaemia. The observed difference between GMI and HbA1c also informs the important question about the predictive ability of GMI regarding long‐term complications.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Understanding the clinical implications of differences between glucose management indicator and glycated haemoglobin

Gómez-Peralta

Choudhary

Cosson

et al. 2022

Diabetes Obesity Metabolism

View full text Add to dashboard Cite

show abstract

“…Acute hyperglycemia in patients with diabetes could result from acute physiological stress, a high baseline blood glucose, or both. Glycosylated hemoglobin (HbA1c) is used to represent the premorbid glycemia in the 3 months prior to intensive care unit (ICU) admission 13 and is used widely to judge the adequacy of diabetes treatment and to adjust therapy 14 . Furthermore, the glycemic gap, the difference between the admission blood glucose and the A1C‐derived average glucose (ADAG) levels, which has been used to evaluate disease severity, predict outcomes and explore the relationship between stress‐induced hyperglycemia (SIH) and mortality in critically ill patients with diabetes.…”

Section: Introductionmentioning

confidence: 99%

Effect of glycemic gap upon mortality in critically ill patients with diabetes

Lou

Jiang

Zhu

2021

J of Diabetes Invest

View full text Add to dashboard Cite

Aims/Introduction: Hyperglycemia, hypoglycemia, and blood glucose fluctuation are associated with the outcome in critically ill patients, but the target of blood glucose control is debatable especially in patients with diabetes regarding the status of blood glucose control before admission to ICU. This study aimed to investigate the association between the glycemic gap which is calculated as the mean blood glucose level during the first 7 days after admission to ICU minus the A1C-derived average glucose and the outcome of critically ill patients with diabetes. Method: This study was undertaken in two intensive care units (ICUs) with a total of 30 beds. Patients with diabetes who were expected to stay for more than 24 h were enrolled, the HbA1c was tested within 3 days after admission and converted to the A1C-derived average glucose (ADAG) by the equation: ADAG = [(HbA1c * 28.7) -46.7 ] * 18 -1 , arterial blood glucose measurements were four per day routinely during the first 7 days after admission, the APACHE II score within the first 24 h, the mean blood glucose level (MGL), standard deviation (SD), and coefficient of variation (CV) during the first 7 days were calculated for each person, the GAP adm and GAP mean were calculated as the admission blood glucose and MGL minus the ADAG, respectively, the incidence of moderate hypoglycemia (MH) and severe hypoglycemia (SH), the total dosage of glucocorticoids and average daily dosage of insulin within 7 days, the duration of renal replacement therapy (RRT), ventilator-free hours, and non-ICU stay days within 28 days were also collected. The enrolled patients were divided into a survival group and a nonsurvival group according to survival or not at 28 days and 1 year after admission, and the relationship between parameters derived from blood glucose and mortality in the enrolled critically ill patients was explored. Results: Five hundred and two patients were enrolled and divided into a survival group (n = 310) and a nonsurvival group (n = 192). It was shown that the two groups had a comparable level of HbA1c, the nonsurvivors had a greater APACHE II, MGL, SD, CV, GAP adm , GAP mean , and a higher incidence of hypoglycemia. A lesser duration of ventilatorfree, non-ICU stay, and a longer duration of RRT were recorded in the nonsurvival group, who received a lower carbohydrate intake, a higher daily dosage of insulin and glucocorticoid. GAP mean had the greatest predictive power with an AUC of 0.820 (95%CI: 0.781-0.850), the cut-off value was 3.60 mmol/L (sensitivity 78.2% and specificity 77.3%). Patients with a low GAP mean tended to survive longer than the high GAP mean group 1 year after admission. Conclusions: Glycemic GAP between the mean level of blood glucose within the first 7 days after admission to ICU and the A1C-derived average glucose was independently associated with a 28 day mortality of critically ill patients with diabetes, the predictive power extended to 1 year. The incidence of hypoglycemia was associated with mortality either.

show abstract

“…Ez főleg akkor jelent problémát, ha a HbA 1c mért értéke nem felel meg a beteg vércukrának. A probléma nem oldódott meg az önellenőrzés és a kontinuális vércukormérés bevezetésével sem [17][18][19][20].…”

Section: Megbeszélésunclassified

A glikációs index lehetséges magyarázata a hemoglobinglikáció biokinetikus modellje alapján

Rácz

Barkai

Eigner

et al. 2021

View full text Add to dashboard Cite

Összefoglaló. Bevezetés: A HbA1c integrált retrospektív mutatója az elmúlt időszak vércukrának, rendszeres vizsgálata a cukorbetegek anyagcserekontrolljának megítélésében elengedhetetlen. Helyes értékelése azonban nem egyszerű, mert a HbA1c és a vércukor közötti összefüggés nem lineáris. A mérést közvetlenül megelőző hyperglykaemiás epizódok hatása a HbA1c szintjére nagyobb, mint azoké, amelyek régebben történtek. A jelenségre a glikáció biokinetikus modellje ad magyarázatot. Célkitűzés: A mért és a biokinetikus modell alapján számított HbA1c közötti egyezés, illetve diszkordancia vizsgálata. Módszer: A vizsgálatokat 157, 1-es és 2-es típusú cukorbeteg 1793, laboratóriumban mért éhomi vércukor- és 511 HbA1c-adatából végeztük. A különbséget a glikációs index segítségével számítottuk, amely a mért és a számított HbA1c-érték aránya. Eredmények: Egyezést mindössze a vizsgált betegek kevesebb mint egyötödödében találtunk, 60%-ban az index értéke alacsony (<0,95) és 21%-ban magas (>1,05) volt. Az adatok részletes analízise szerint jó anyagcserekontroll esetében gyakoribb a vártnál magasabb, mért HbA1c-érték, mint a biokinetikus egyenlet által számítotté, és rosszabb kontroll (magasabb átlagos vércukor) esetében ez fordítva van. Egyezés esetén a regressziós egyenlet együtthatói gyakorlatilag azonosak a modell alapján számított értékekkel. Következtetés: Vizsgálataink felvetik azt a lehetőséget, hogy a biokinetikus modell magyarázatot adhat a vércukor és a HbA1c közötti diszkordanciára. Orv Hetil. 2021; 162(41): 1652–1657. Summary. Introduction: HbA1c is an integrated retrospective marker of previous blood glucose concentrations and its regular measurement is indispensable in the assessment of glycaemic compensation of diabetic patients. However, its proper interpretation is not simple becasuse the relationship between HbA1c and average glycemia is not a linear one. Hyperglycemic episodes occuring immediately before the measurement have greater impact on the HbA1c level as compared with those taking place earlier. Objective: Assessment of concordance and discordance between measured and according to the biokinetic model calculated values of HbA1c. Method: The calculations were made from averages of 1793 fasting blood glucose and 511 HbA1c of 157, type 1 and 2 diabetic patients. The glycation index is the quotient between measured and calculated HbA1c. Results: Agreement was found in less than one fifth of the 157 patients; in 60% the value of glycation was low (<0.95) and in 21% high (>1.05). Analysis of the glycation index according to the level of glycemic compensation revealed that in patients with good compensation, the measured HbA1c value was more often higher than the expected and in patients with unsatisfactory compensation the opposite was true. Conclusion: These results raise the possibility that the discordance between average glycemia and measured HbA1c can be explained by the biokinetic model. Orv Hetil. 2021; 162(41): 1652–1657.

show abstract

“Mind the gap please…”: estimated vs. measured A₁c from continuous measurement of interstitial glucose over a 3-month period in patients with type 1 diabetes

Cited by 13 publications

References 20 publications

Understanding the clinical implications of differences between glucose management indicator and glycated haemoglobin

Understanding the clinical implications of differences between glucose management indicator and glycated haemoglobin

Effect of glycemic gap upon mortality in critically ill patients with diabetes

A glikációs index lehetséges magyarázata a hemoglobinglikáció biokinetikus modellje alapján

Contact Info

Product

Resources

About

“Mind the gap please…”: estimated vs. measured A1c from continuous measurement of interstitial glucose over a 3-month period in patients with type 1 diabetes

Cited by 13 publications

References 20 publications

Understanding the clinical implications of differences between glucose management indicator and glycated haemoglobin

Understanding the clinical implications of differences between glucose management indicator and glycated haemoglobin

Effect of glycemic gap upon mortality in critically ill patients with diabetes

A glikációs index lehetséges magyarázata a hemoglobinglikáció biokinetikus modellje alapján

Contact Info

Product

Resources

About

“Mind the gap please…”: estimated vs. measured A₁c from continuous measurement of interstitial glucose over a 3-month period in patients with type 1 diabetes