Evaluation of automated flow cytometer single-platform for absolute CD4+ T-lymphocytes enumeration in HIV patients, Trat Province, Thailand

Abstract

Background: The routine analysis of CD4+ T-lymphocyte percentages and absolute counts in HIV patients commonly employs the dual-platform method (blood cell analyzer and flow cytometer). However, variability related to equipment, methodology, or operator performance may affect accuracy. This study introduces the single-platform method, which relies solely on a flow cytometer to reduce variability, streamline workflow, and shorten turnaround times, in alignment with the Rational Laboratory Use guidelines of the Department of Medical Sciences, Ministry of Public Health.

Objectives: To evaluate and compare the single-platform and dual-platform methods for determining CD4+ T-lymphocyte percentages and absolute counts.

Materials and methods: The study was conducted from January 24 to November 29, 2024, encompassing the entire research process — from conceptual development, problem analysis, and study design to data collection, statistical analysis, interpretation, and application of findings. Routine diagnostic data were collected from HIV-infected patients in Trat Province, Thailand, between April 1 and July 31, 2024, as part of the data collection phase. Samples were analyzed using a semi-automated blood cell analyzer and a flow cytometer, and results were compared with those obtained using the single-platform method, which employed only the flow cytometer. Statistical analyses were performed to assess the accuracy, precision, and reliability of the singleplatform method compared with the conventional approach. Descriptive statistics, correlation, linear regression, and Bland–Altman analysis were applied to evaluate agreement and systematic bias. All statistical tests were conducted at a 95% confidence interval, with p-values <0.05 considered statistically significant.

Results: Both methods produced data that followed a normal distribution (Kolmogorov–Smirnov test; p>0.05). Correlation coefficients demonstrated excellent agreement for CD4+ T-lymphocyte percentages (r=0.9914) and absolute counts (r=0.9697). Linear regression analysis showed a strong association, with r²=0.9403 for absolute counts. Bland–Altman analysis indicated a mean difference of 61.06 cells/μL (95% CI: -73.91 to 196.04), with most values falling within the confidence limits. Among patients with CD4+ T-lymphocyte percentages ≤ 20%, the mean difference was 28.56 cells/μL (95% CI: -61.98 to 119.09).

Conclusion: The single-platform method is comparable to the dual-platform method for analyzing CD4+ T-lymphocytes in HIV patients. Both methods demonstrated normal data distribution, confirming statistical robustness. High correlations for percentages and absolute counts ensured consistent and reliable results, while regression analysis indicated strong predictive capability of the single-platform method for dual-platform results. Bland–Altman analysis further confirmed the equivalence of the two methods, supporting the reliability of the single-platform approach. Overall, the singleplatform method offers a reliable and efficient alternative, reducing variability, workload, and turnaround time in laboratory settings while maintaining analytical accuracy.