Performance of Point-of-Care Testing Compared with the Standard Laboratory Diagnostic Test in the Measurement of HbA1c in Indonesian Diabetic and Nondiabetic Subjects

Berbudi, Afiat; Rahmadika, Nofri; Tjahjadi, Adi Imam; Ruslami, Rovina

doi:10.1155/2020/2037565

Cited by 11 publications

(9 citation statements)

References 40 publications

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“…The same results were obtained by Berbudi et al, where the Bland-Altman plot analysis showed that the HbA1c by POCT and the standard laboratory method of HbA1c were within the range of agreement limits (− 1.67 to 1.3). They concluded that POCT-HbA1c is a potential method for diabetes screening and monitoring, especially when a rapid result is needed [ 36 ]. Moreover, the study by Raalten et al demonstrated high limits of agreement between the POCT HbA1c and the central laboratory HbA1c tests in non-diabetic, obese patients in the preoperative outpatient setting [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

Level of Agreement and Correlation Between the Estimated Hemoglobin A1c Results Derived by Continuous or Conventional Glucose Monitoring Systems Compared with the Point-of-Care or Laboratory-Based Measurements: An Observational Study

et al. 2022

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Introduction Hemoglobin A1C (HbA1c) is an important marker for diabetes care management. With the increasing use of new technologies such as continuous glucose monitoring (CGM) and point-of-care testing (POCT), patients and their physicians have been able to monitor and continuously check their blood glucose levels in an efficient and timely manner. This study aimed to investigate the level of agreement between the standard laboratory test for HbA1c (Lab-HbA1c) with point-of-care testing (POCT-HbA1c) and glucose monitoring index (GMI) derived by intermittently scanned CGM (isCGM) or estimated average glucose (eAG) derived by conventional self-monitored blood glucose (SMBG) devices. Methods A cross-sectional study was conducted at the Diabetes Treatment Center, Prince Sultan Military Medical City, Saudi Arabia, between May and December 2020 with 81 patients with diabetes who used the isCGM system ( n = 30) or conventional finger-pricking SMBG system ( n = 51). At the same visit, venous and capillary blood samples were taken for routine HbA1c analysis by the standard laboratory and POCT methods, respectively. Also, for isCGM users, the GMI data for 28 days (GMI-28) and 90 days (GMI-90) were obtained, while for SMBG users, eAG data for 30 days (eAG-30) and 90 days (eAG-90) were calculated. The limits of agreement in different HbA1c measurements were evaluated using a Bland-Altman analysis. Pearson correlation and multivariate linear regression analyses were also performed. Results Based on the Bland-Altman analysis, HbA1c levels for 96.7% and 96.1% of the patients analyzed by the POCT and the standard laboratory methods were within the range of the 95% limit of agreement in both isCGM and conventional SMBG users, respectively. About 93.3% of the GMI measurements were within the 95% limit of agreement. Also, about 94.12% of the eAG-30 and 90.2% of the eAG-90 measurements were within the 95% limit of agreement. Moreover, the correlation analysis revealed a statistically significant positive correlation and linear regression among Lab-HbA1c, POCT-HbA1c, GMI, and eAG in both conventional SMBG and isCGM users (all p < 0.001). These positive results persisted significantly after adjusting for different factors (all p < 0.001). Conclusion GMI derived by isCGM or eAG derived by conventional SMBG systems, as well as the POCT-HbA1c measurements, showed a high level of agreement; therefore, we recommend them as potential methods for diabetes monitoring, especially when a rapid result is needed or with patients with uncontrolled diabetes or on intensive insulin therapy.

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Section: Discussionmentioning

confidence: 99%

Level of Agreement and Correlation Between the Estimated Hemoglobin A1c Results Derived by Continuous or Conventional Glucose Monitoring Systems Compared with the Point-of-Care or Laboratory-Based Measurements: An Observational Study

et al. 2022

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“…The classification of our participants into two age groups, young individuals (aged 0-59 years) and older adults (aged ≥60 years), revealed that there was no significant difference in HbA1c levels between these two groups. This finding suggests that HbA1c levels do not exhibit a substantial age-related variation within our study cohort [20,21]. Such uniformity in HbA1c levels across age groups may have implications for diabetes management and prevention strategies across the lifespan.…”

Section: Discussionmentioning

confidence: 63%

A Comparative Evaluation of HbA1c Measurement Methods and Their Implications for Diabetes Management

Yun,

Park,

Kim

2023

Diagnostics

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In this study, we assessed the correlations between hemoglobin A1c (HbA1c) measurements obtained using three different diagnostic methods, namely reversed-phase cation-exchange chromatography, high-performance liquid chromatography, and lateral flow immunoassay (LIFA) with an AnyLab F instrument. HbA1c levels measured with the AnyLab F instrument and those measured with the HA8190V, HA8180, and D100 instruments were strongly correlated. High R-square values and low p-values indicated significant and reliable correlations, supporting the clinical interchangeability of these methods. Notably, demographic and clinical analyses revealed uniform HbA1c levels across age groups, suggesting minimal age-related variations in HbA1c levels in the cohort. This finding has implications for diabetes management strategies across different age groups, emphasizing the versatility of the AnyLab F instrument. Overall an average HbA1c level of 7.857% among diabetes mellitus-diagnosed participants suggests moderately elevated HbA1c levels, underscoring the need for improved diabetes management. Younger individuals exhibited lower HbA1c levels, potentially owing to heightened awareness and treatment plan adherence. Conversely, older adults had higher HbA1c levels, likely influenced by age-related changes and comorbidities. Larger sample sizes and a comprehensive evaluation of various measurement principles are needed to strengthen the findings herein. Additionally, exploring additional biomarkers and assessing LIFA performance in larger sample sets will advance the clinical utility of HbA1c measurements.

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“…Berbudi A et al reported similar findings, revealing that the POCT-HbA1c and Lab-HbA1c were within the range of the agreement values. They came to the conclusion that POCT-HbA1c is a promising approach to screening and monitoring DM, particularly when a quick result is required [ 25 ]. Moreover, in non-diabetic obese patients, van Raalten F et al showed similar results [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

Comparison of Point-of-Care and Laboratory Glycated Hemoglobin A1c and Its Relationship to Time-in-Range and Glucose Variability: A Real-World Study

Hayek¹,

Alzahrani²,

Sobki³

et al. 2023

Cureus

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Introduction The main objective of the current study was to perform a comparison of point-of-care testing for hemoglobin A1c (POCT-HbA1c) versus the standard laboratory method (Lab HbA1c) and their relationship to time-in-range (TIR) and glucose variability (GV) among patients with diabetes mellitus (DM) presented to the outpatient diabetes clinics. Methods This single-center cross-sectional study was carried out on diabetic patients (aged ≥14 years of both genders) who undergo routine follow-up at our institution and whose physicians ordered HbA1c analysis for routine care. The included patients were those using the intermittently scanned continuous glucose monitoring (isCGM) Abbott’s FreeStyle Libre system for at least three months and regular CGM users with at least 70% use. Results We included 97 diabetic patients (41 female and 56 male), with a median age of 25 years (Interquartile range= 18) and a mean DM duration of 10.33±5.48 years. The mean values of Lab-HbA1c and POCT HbA1c were 8.82%±0.85% and 8.53%±0.89%, respectively. The TIR, time below range, and time above range were 33.47±14.38 minutes (47.78%±14.32%), 5.44±2.58 minutes (8.41%±4.42%), and 28.8±8.27 minutes (43.81%±13.22%), respectively. According to the Bland-Altman plot analysis, the POCT-HbA1c values are consistent with the standard Lab-HbA1c values (SD of bias= 0.55, and 95% CI= -0.78 to 1.4). The univariate linear regression analysis showed a statistically significant relationship between laboratory HbA1c and POCT HbA1c (R2= 0.637, p <0.001), TIR (R2= 0.406, p <0.001), and GV (R2= 0.048, p = 0.032). After adjusting for age, gender, disease duration, diabetes type, and percentage of sensor data in a multivariable linear regression model, the linear associations remained significant (all p < 0.05). Conclusion The current findings show that TIR and GV can be used as endpoints and valuable parameters for the therapy of DM.

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Performance of Point-of-Care Testing Compared with the Standard Laboratory Diagnostic Test in the Measurement of HbA1c in Indonesian Diabetic and Nondiabetic Subjects

Cited by 11 publications

References 40 publications

Level of Agreement and Correlation Between the Estimated Hemoglobin A1c Results Derived by Continuous or Conventional Glucose Monitoring Systems Compared with the Point-of-Care or Laboratory-Based Measurements: An Observational Study

Level of Agreement and Correlation Between the Estimated Hemoglobin A1c Results Derived by Continuous or Conventional Glucose Monitoring Systems Compared with the Point-of-Care or Laboratory-Based Measurements: An Observational Study

A Comparative Evaluation of HbA1c Measurement Methods and Their Implications for Diabetes Management

Comparison of Point-of-Care and Laboratory Glycated Hemoglobin A1c and Its Relationship to Time-in-Range and Glucose Variability: A Real-World Study

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