Javascript must be enabled to continue!
Combined measurement uncertainty of HbA 1c and glucose using ISO 20914:2019 and outcome-based simulation
View through CrossRef
Abstract
Objectives
This study aimed to calculate the measurement uncertainty (MU) of HbA
1c
and glucose according to ISO/TS 20914:2019 guideline and to evaluate using indirect outcome-based analytical performance specifications (APS).
Methods
MU was estimated using internal quality control data collected between October 2023 and August 2025. A total of 13,270 and 13,824 IQC results for HbA
1c
and 1,329 and 1,208 results for glucose were analyzed for Level 1 and Level 2 controls, respectively. HbA
1c
was measured by capillary electrophoresis using two analyzers (12 capillaries each), and glucose was measured using the hexokinase method on three platforms. Maximum allowable uncertainty (MAU) targets were determined using the APS Simulator based on 2,000 patient samples with simultaneous HbA
1c
and fasting plasma glucose results. Clinical decision limits were defined as 5.7 % (39 mmol/mol) and 6.5 % (48 mmol/mol) for HbA
1c
, and 5.6 and 7 mmol/L for glucose. Overall agreement was used as the primary performance metric.
Results
Relative expanded MU (Urel) ranged from 4.56 to 4.59 % for HbA
1c
expressed in %, 6.36–7.87 % for HbA
1c
expressed in mmol/mol, and 3.68–4.36 % for glucose. Glucose Urel values remained below the minimum MAU limit (5.1 %), whereas HbA
1c
values exceeded the corresponding limits (2.8 and 4.7 % for % and mmol/mol). Sensitivity and specificity ranged from 83.9 to 96 % and 93.4 to 99 % for glucose, and 85.4 to 93.4 % and 89 to 97.6 % for HbA
1c
.
Conclusions
Glucose measurements met the minimum APS targets derived from the simulation model, whereas HbA
1c
measurements exceeded these limits, indicating higher MU and a potential impact on patient classification around clinical decision limits.
Walter de Gruyter GmbH
Title: Combined measurement uncertainty of HbA
1c
and glucose using ISO 20914:2019 and outcome-based simulation
Description:
Abstract
Objectives
This study aimed to calculate the measurement uncertainty (MU) of HbA
1c
and glucose according to ISO/TS 20914:2019 guideline and to evaluate using indirect outcome-based analytical performance specifications (APS).
Methods
MU was estimated using internal quality control data collected between October 2023 and August 2025.
A total of 13,270 and 13,824 IQC results for HbA
1c
and 1,329 and 1,208 results for glucose were analyzed for Level 1 and Level 2 controls, respectively.
HbA
1c
was measured by capillary electrophoresis using two analyzers (12 capillaries each), and glucose was measured using the hexokinase method on three platforms.
Maximum allowable uncertainty (MAU) targets were determined using the APS Simulator based on 2,000 patient samples with simultaneous HbA
1c
and fasting plasma glucose results.
Clinical decision limits were defined as 5.
7 % (39 mmol/mol) and 6.
5 % (48 mmol/mol) for HbA
1c
, and 5.
6 and 7 mmol/L for glucose.
Overall agreement was used as the primary performance metric.
Results
Relative expanded MU (Urel) ranged from 4.
56 to 4.
59 % for HbA
1c
expressed in %, 6.
36–7.
87 % for HbA
1c
expressed in mmol/mol, and 3.
68–4.
36 % for glucose.
Glucose Urel values remained below the minimum MAU limit (5.
1 %), whereas HbA
1c
values exceeded the corresponding limits (2.
8 and 4.
7 % for % and mmol/mol).
Sensitivity and specificity ranged from 83.
9 to 96 % and 93.
4 to 99 % for glucose, and 85.
4 to 93.
4 % and 89 to 97.
6 % for HbA
1c
.
Conclusions
Glucose measurements met the minimum APS targets derived from the simulation model, whereas HbA
1c
measurements exceeded these limits, indicating higher MU and a potential impact on patient classification around clinical decision limits.
Related Results
Estimation of post-transfusion HbA level is relevant after RBC exchange in sickle cell adult patients
Estimation of post-transfusion HbA level is relevant after RBC exchange in sickle cell adult patients
Abstract
Background Transfusion (TF), or exchange transfusion (ExTF), is a major therapy for sickle cell disease (SCD) p...
Glycometabolic Control and Fibrinolysis in Diabetic Patients
Glycometabolic Control and Fibrinolysis in Diabetic Patients
We investigated 148 diabetic patients with regard to their relationship between fibrinolysis (D-dimer and plasminogen activator inhibitor; PAI) and glycometabolic control (HbA<s...
Abstract P230: Measures of Glycaemia (Fasting and 2 hr Glucose, Glycosylated Haemoglobin) in Relation to Incident Vascular Disease in Non-diabetic Adults
Abstract P230: Measures of Glycaemia (Fasting and 2 hr Glucose, Glycosylated Haemoglobin) in Relation to Incident Vascular Disease in Non-diabetic Adults
Introduction:
Glycosylated haemoglobin (HbA
1c
) has recently been accepted for diagnosing diabetes in New Zealand. A 2 hour 75g oral glucose te...
New Perspectives for 3D Visualization of Dynamic Reservoir Uncertainty
New Perspectives for 3D Visualization of Dynamic Reservoir Uncertainty
This reference is for an abstract only. A full paper was not submitted for this conference.
Abstract
1 Int...
Telemedicine’s Impact on Diabetes Care during the COVID-19 Pandemic: A Cohort Study in a Large Integrated Healthcare System
Telemedicine’s Impact on Diabetes Care during the COVID-19 Pandemic: A Cohort Study in a Large Integrated Healthcare System
ABSTRACT
Introduction
To examine if patients exposed to primary care telemedicine (telephone or video) ear...
Outcomes of an Asynchronous Care Model for Chronic Conditions in a Diverse Population: 12-Month Retrospective Chart Review Study (Preprint)
Outcomes of an Asynchronous Care Model for Chronic Conditions in a Diverse Population: 12-Month Retrospective Chart Review Study (Preprint)
BACKGROUND
Diabetes and hypertension are some of the most prevalent and costly chronic conditions in the United States. However, outcomes continue to lag be...
Reserves Uncertainty Calculation Accounting for Parameter Uncertainty
Reserves Uncertainty Calculation Accounting for Parameter Uncertainty
Abstract
An important goal of geostatistical modeling is to assess output uncertainty after processing realizations through a transfer function, in particular, to...
The relationship between the ability of sperm to bind hyaluronic acid with the DNA fragmentation and sperm parameters
The relationship between the ability of sperm to bind hyaluronic acid with the DNA fragmentation and sperm parameters
Objectives: To evaluate the relationship between the ability of sperm to bind hyaluronic acid with the level of DNA fragmentation and sperm parameters. Material and methods: A cros...

