A laboratory association between hemoglobin and VerifyNow P2Y12 reaction unit: A systematic review and meta-analysis

Abstract

VerifyNow P2Y12 assay is used widely to evaluate residual platelet reactivity in patients taking P2Y12 receptor antagonists. However, a laboratory association between VerifyNow P2Y12 reaction unit (PRU) and hemoglobin, which might lead to wrong interpretation of the data, is reported. We performed these systematic review and meta-analysis to clearly define the relationship between PRU and hemoglobin and to elucidate whether the relationship, if any, is a true biological association or is just a laboratory error. Through a comprehensive electronic and manual search, 10 studies were selected for the cohort level meta-analysis. Among 10 studies, we were able to retrieve the raw data of 5 studies, and a patient-level meta-analysis was performed. Potential publication bias was searched by funnel plot analysis and was actively adjusted, if present, by trim and fill method. The pooled analysis revealed a significant inverse correlation between PRU and hemoglobin (r=-0.349; P<.001; 10 studies with 4,793 patients). VerifyNow P2Y12 base unit, which reflects off-drug platelet reactivity, was also inversely correlated with hemoglobin (r=-0.526; P<.001; 8 studies with 4,395 patients). % Inhibition (r=0.081; P=.059; 6 studies with 3,832 patients) and ΔPRU (r=-0.037; P=.188; 5 studies with 3,521 patients) were not associated with hemoglobin. A significant inverse association between PRU and hemoglobin was also observed in the patient-level meta-analysis (3,533 patients pooled from 5 studies; r=-0.335; P<.001). Light transmission aggregometry (r=0.160; P=.072; 4 studies with 1,144 patients) and multiple electrode platelet aggregometry (r=-0.029; P=.394; 3 studies with 7,645 patients) showed no significant association with hemoglobin. A significant inverse association was observed between PRU and hemoglobin which is likely to be a laboratory error. Clinicians should be aware that this association might lead to wrong interpretation of the data.