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Evaluating Systematic and Proportional Bias in Point-of-care Glucose Testing: A Correlation and Bland-Altman Analysis

2026Open accessNovena University

In plain language

Point-of-care testing devices for blood glucose offer rapid results, but questions persist regarding their accuracy compared with central laboratory equipment. An evaluation conducted in a secondary healthcare centre within a low-resource setting examined 120 paired blood glucose measurements taken simultaneously on a portable glucometer and a laboratory auto-analyser. The readings demonstrated a strong positive correlation, with mean values of 6.59 millimoles per litre for the portable device and 6.33 millimoles per litre for the laboratory analyser. However, statistical evaluations identified both systematic and proportional bias, with agreement worsening at higher glucose concentrations. The overall mean difference was minus 0.26 millimoles per litre, alongside wide limits of agreement. Consequently, whilst portable glucometers remain effective for rapid screening and ongoing routine monitoring, laboratory auto-analyser systems remain essential for accurate diagnostic evaluations and critical treatment decisions.

Key takeaways

  • A strong positive correlation was recorded between point-of-care glucometers and central laboratory auto-analysers across 120 paired samples.
  • Measurements displayed proportional and systematic bias, with an overall mean difference of minus 0.26 millimoles per litre.
  • Discrepancies between the two testing methods increased notably at higher blood glucose concentrations.
  • Handheld glucometers are suitable for rapid monitoring, but laboratory auto-analysers remain necessary for definitive diagnosis and critical care decisions.

Why it matters

Managing blood sugar levels requires reliable measurements, especially in resource-limited clinics where portable monitors are often used instead of full laboratory facilities. Demonstrating that portable glucometers lose precision at higher glucose levels helps healthcare staff understand the boundaries of rapid testing. It ensures that clinicians know when to rely on immediate bedside results and when to confirm critical values using standard laboratory analysers to avoid diagnostic mistakes.

Commercialisation angle

This comparative study evaluates existing, commercially available diagnostic equipment rather than developing a new technology. It provides clinical validation data that health centres and laboratory managers in resource-limited regions can use when integrating point-of-care devices into care pathways. For instrument manufacturers, the identified proportional bias and divergence at elevated glucose concentrations highlight specific calibration targets needed to improve the performance of future rapid testing hardware.

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Abstract

Background and Aims: Point-of-care testing (POCT) for blood glucose provides rapid results and is widely used in clinical practice; however, concerns remain regarding its accuracy and agreement with laboratory auto-analyser methods. The purpose of this study was to compare glucose measurements obtained using POCT and a laboratory auto-analyser in a secondary healthcare centre within a low-resource setting. Methods: A comparison study was conducted using 120 paired blood glucose measurements obtained simultaneously by a POCT glucometer and a laboratory auto-analyser. Descriptive statistics were used to summarise glucose values. Pearson correlation and linear regression analyses assessed the relationship between methods, while agreement was evaluated using Bland-Altman analysis. Statistical significance was set at P < .05. Results: The mean glucose concentration measured by POCT was 6.59 ± 2.27 mmol/L, while that measured by the auto-analyser was 6.33 ± 2.93 mmol/L. A strong positive correlation was observed between the two methods ( r = 0.971, P < .001). Linear regression analysis yielded the equation auto-analyser = 1.249 × POCT − 1.905 ( R ² = 0.943), indicating proportional bias. Bland-Altman analysis demonstrated a mean bias of −0.26 mmol/L, with 95% limits of agreement ranging from −2.03 to +1.50 mmol/L. Greater variability in differences was observed at higher glucose concentrations. Conclusion: POCT glucose measurements show excellent correlation with laboratory auto-analyser results but exhibit systematic and proportional bias, particularly at higher glucose levels. While POCT is suitable for rapid glucose assessment and monitoring, laboratory auto-analyser methods remain the preferred reference for diagnostic and critical clinical decision-making.

Research topics

  • Hyperglycemia and glycemic control in critically ill and hospitalized patients
  • Clinical Laboratory Practices and Quality Control
  • Diabetes, Cardiovascular Risks, and Lipoproteins

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DOI: 10.1177/09760016261475766

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