Antibody Identification Using Both Automated Solid-phase Red Cell Adherence Assay and Tube Polyethylene Glycol Antiglobulin Method: A Comparative Study

BACKGROUND: Accurate antibody identification is crucial for safe transfusion practices. Conventionally, tube antiglobulin methods using polyethylene glycol (PEG-AHG) are considered the gold standard. However, recent advances such as automated solid-phase red cell adherence (SPRCA) assays have improved standardization and reduced subjectivity. OBJECTIVE: The objective of this study was to compare the performance, efficiency, and concordance of antibody identification using the automated SPRCA method (Immucor NEO platform) with the conventional tube PEG-AHG method in a tertiary care transfusion laboratory. MATERIALS AND METHODS: This prospective, observational study included 1000 patient samples received for antibody screening and identification over a period of 12 months. Each sample was tested simultaneously using the Immucor NEO automated SPRCA system and the conventional tube PEG-AHG method. The parameters compared included detection rate, specificity, sensitivity, turnaround time (TAT), and concordance with clinical history. RESULTS: Out of 1000 samples, antibodies were detected in 108 (10.8%) by at least one method. The SPRCA method detected 106 antibodies (10.6%), whereas the PEG-AHG method detected 98 (9.8%). Complete concordance between both the methods was observed in 940 (94%) samples, while 60 (6%) samples showed discordant results. SPRCA demonstrated higher sensitivity (98.1%) and reduced manual error with an average TAT of 18 min per batch, compared to 35 min for the PEG-AHG method. Commonly identified antibodies included anti-D, anti-E, anti-K, and combinations thereof. CONCLUSION: The automated SPRCA method using the Immucor NEO platform offers superior sensitivity, reproducibility, and efficiency for antibody identification compared to the conventional tube PEG-AHG method. Integration of automation into transfusion laboratories enhances workflow and patient safety by minimizing subjectivity and variability.