Construction of platelet count-optical method reflex test rules using Micro-RBC#, Macro-RBC%, “PLT clumps?” flag, and “PLT abnormal histogram” flag on the Mindray BC-6800plus hematology analyzer in clinical practice

Abstract

Abstract Objectives Utilizing RBC or PLT-related parameters to establish rules for the PLT-O reflex test can assist laboratories in quickly identifying specimens with interfered PLT-I that require PLT-O retesting. Methods Prospective PLT-I and PLT-O testing was performed on 6857 EDTA-anticoagulated whole blood samples, split randomly into training and validation cohorts at a 2:3 ratio. Reflex and non-reflex groups were distinguished based on the differences between PLT-I and PLT-O results. By comparing RBC and PLT parameter differences and flags in the training set, we pinpointed factors linked to PLT-O reflex testing. Utilizing Lasso regression, then refining through univariate and multivariate logistic regression, candidate parameters were selected. A predictive nomogram was constructed from these parameters and subsequently validated using the validation set. ROC curves were also plotted. Results Significant differences were observed between the reflex and non-reflex groups for 19 parameters including RBC, MCV, MCH, MCHC, RDW-CV, RDW-SD, Micro-RBC#, Micro-RBC%, Macro-RBC#, Macro-RBC%, MPV, PCT, P-LCC, P-LCR, PLR,“PLT clumps?” flag, “PLT abnormal histogram” flag, “IDA Anemia?” flag, and “RBC abnormal histogram” flag. After further analysis, Micro-RBC#, Macro-RBC%,“PLT clumps?”, and “PLT abnormal histogram” flag were identified as candidate parameters to develop a nomogram with an AUC of 0.636 (95 %CI: 0.622–0.650), sensitivity of 42.9 % (95 %CI: 37.8–48.1 %), and specificity of 90.5 % (95 %C1: 89.6–91.3 %). Conclusions The established rules may help laboratories improve efficiency and increase accuracy in determining platelet counts as a supplement to ICSH41 guidelines.