An algorithmic approach to serological work-up of ABO sub-groups which present as ABO discrepancies in resource constraint settings

ABO subgroups or weaker variants of A or B are group A or B subjects whose erythrocytes give a weak or negative reaction serologically with anti-A or Anti – B antisera respectively. Occurrence of these subgroups may lead to an ABO discrepancy which often puts transfusion services in a quandary. ABO subgroups which present as ABO discrepancies can be missed if reverse grouping is not performed.This study was planned to estimate the prevalence of different subgroups which can present as an ABO discrepancy in Indian population, and provide an insight to transfusion services for identification of subgroups serologically.A cross-sectional, analytical study was performed at a tertiary healthcare based blood bank on whole blood donors and patients from January 2017 to July 2018. All suspected type II and Type IV (with Anti-A1) ABO discrepant samples were projected to an algorithmic testing process, to confirm discrepancy and then narrow down to the probable subgroup.A total of 33 subgroup discrepancies; 26 of A group and 7 of B group were identified out of 73,380 patient and 35,279 donor samples tested for blood grouping. Following the algorithm, the overall prevalence of weak subgroups which can present as an ABO discrepancy was found to be 1 in 3293 or 0.03% in our population by serological testing. Out of the discrepancies caused by subgroups, the prevalence of subgroups of A were 0.0101%, 0.0018%, 0.0009%, 0.0027%, 0.0027% and 0.0018% for A2 with anti-A1, A3, Aend, Ax, Am and Ael respectively while those of B were 0.009%, 0.0009%, 0.0009% and 0.009% for B3, Bx, Bm and Bel respectively.Algorithmic approach for resolution of ABO discrepancies caused by subgroups helps in identifying the subgroup which is important because these individuals may be mistyped as group O individuals.