Level of agreement of point-of-care and laboratory HbA1c measurements in the preoperative outpatient clinic in non-diabetic patients who are overweight or obese

Floris van Raalten, Yasmine L Hiemstra, Noor Keulen, Yoni van Duivenvoorde, Katrin Stoecklein, Evert A Verhagen, Christa Boer

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Implementation of point-of-care HbA1c devices in the preoperative outpatient clinic might facilitate the early diagnosis of glycemic disturbances in overweight or obese patients undergoing surgery, but validation studies in this setting do not exist. We determined the level of agreement between a point-of-care and laboratory HbA1c test in non-diabetic patients visiting the outpatient clinic for preoperative risk profiling. Point-of-care HbA1c levels were measured in whole blood obtained by a finger prick (Siemens DCA Vantage HbA1c analyzer) and in hemolysed EDTA blood in the central laboratory (LAB). Bland Altman and Clarke's error grid analysis were used to analyze the agreement between the point-of-care and laboratory measurements. Patients (n = 49) were 55 ± 11 years old, 47% were male with a body mass index (BMI) of 30.6 ± 3.4 kg/m2. The mean HbA1c was 38.1 ± 3.7 mmol/mol or 5.6 ± 0.3%. One patient was diagnosed with a HbA1c indicative for diabetes mellitus (6.7%). Bland Altman analysis revealed a bias of - 0.53 ± 1.81 mmol/mol with limits of agreement of - 4.09 to 3.03 mmol/mol and a bias of - 0.05 ± 0.17% with limits of agreement - 0.39 to 0.28%. The percentage error was 9.2% and 5.9% for HbA1c expressed in mmol/mol and %, respectively. Clarke's error grid analysis showed that 48 out of 49 measurements were located in area A (98%). Point-of-care HbA1c measurements showed a high level of agreement with the laboratory test in the outpatient setting, and may be used for preoperative risk profiling in patients prone to cardiometabolic complications.Trial registration: Netherlands Trial Register NTR3057.

Original languageEnglish
Pages (from-to)1139-1144
Number of pages6
JournalJournal of Clinical Monitoring and Computing
Volume33
Issue number6
Early online date18 Jan 2019
DOIs
Publication statusPublished - 1 Dec 2019

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