Impact of pre-analytical variables on HbA1c measurement in primary care laboratories: an empirical study

Thesis Abstract

Pre-analytical variables have a critical impact on the accuracy and reliability of HbA1c measurements in primary care laboratories, yet practical evidence from routine settings remains limited. This study addresses the problem that pre-analytical factors such as sample collection timing, patient preparation, specimen type, storage duration, and transport conditions may introduce bias or imprecision that undermines diagnostic and therapeutic decisions for diabetes management. The aim is to quantify the influence of these variables on HbA1c results and to identify controllable pre-analytical factors that maximize analytical validity in primary care contexts. Specific objectives include (i) assessing the association between specimen type (EDTA whole blood, plasma, and capillary samples) and HbA1c values using high-performance liquid chromatography (HPLC) and immunoassay platforms; (ii) evaluating the effect of time-to-analysis, storage temperature, and freeze-thaw cycles on HbA1c stability; (iii) examining the impact of patient-related pre-analytical factors such as fasting status, recent illness, and hemolysis indicators; (iv) comparing results across solar and indoor transport conditions to determine temperature and humidity effects; and (v) developing a practical protocol for standardizing pre-analytical processes in primary care laboratories. The study adopts a cross-sectional, multicenter empirical design conducted in ten primary care laboratories across three urban regions. A target sample size of 1,200 paired HbA1c measurements will be collected over six months, with each site contributing a minimum of 120 measurements. Data collection will utilize standardized data capture forms integrated with laboratory information systems, capturing variables including specimen type, collection time, time-to-analysis, storage conditions, transport modality, storage duration, temperature and humidity logs, hemolysis indicators, patient demographics, and clinical context. HbA1c results will be generated using two commonly employed analytical techniques—high-performance liquid chromatography (HPLC) and immunoassay methods—allowing method-comparison analyses. Instrument calibration records, lot numbers, and quality control data will be retrieved to adjust for analytic bias where appropriate. Data analysis will proceed in three stages (1) descriptive statistics to characterize the distribution of pre-analytical variables and HbA1c results; (2) multivariate regression models to quantify the independent effect of each pre-analytical factor on HbA1c values, controlling for age, sex, and comorbidities; (3) Bland-Altman analyses and Deming regression to assess agreement between specimen types and analytical platforms. An exploratory subgroup analysis will examine effect modification by index of sample integrity (e.g., presence of hemolysis) and by storage duration categories. The theoretical framework anchors on the Pre-Analytical Quality Improvement (PAQI) model and the Theory of Planned Behavior to interpret workflow-related determinants of pre-analytical practices in primary care laboratories, supplemented by a systems-thinking perspective to map interdependencies among process steps. Expected findings include quantification of HbA1c variation attributable to specimen type, time-to-analysis, and temperature exposure, with capillary and EDTA whole-blood samples anticipated to yield greater dispersion under suboptimal conditions relative to plasma. Storage durations beyond 48 hours at room temperature and repeated freeze-thaw cycles are expected to be associated with statistically significant HbA1c deviations exceeding clinically important thresholds (e.g., >0.5% HbA1c). Differences between HPLC and immunoassay platforms are anticipated to be modest but clinically relevant in specific pre-analytical contexts. The study will identify key modifiable factors—such as adherence to specified maximum time-to-analysis and validated transport protocols—that substantially reduce analytical variance, enabling harmonization across primary care settings. The contribution to knowledge lies in providing robust, context-specific estimates of pre-analytical impacts on HbA1c measurements in routine primary care laboratories, informing evidence-based guidelines and standard operating procedures. It will offer a validated, pragmatic protocol for standardizing pre-analytical processes, with an emphasis on resource-constrained environments. The main conclusion is that stringent control of pre-analytical variables—particularly specimen type selection, timely analysis, and stable transport conditions—substantially improves HbA1c measurement reliability, thereby enhancing diabetes management decisions. Recommendations include implementing uniform specimen handling practices, investing in validated transport solutions, routine auditing of pre-analytical processes, and embedding PAQI-informed training for laboratory personnel within primary care networks. Further research should explore longitudinal impacts on patient outcomes and cost-effectiveness analyses of standardized pre-analytical protocols.