Changes in hematocrit based on incremental blood sampling: mathematical models perform poorly

Abstract

Excessive blood sampling, with its inherent risks, is of growing concern among clinicians. We performed this study to measure the changes in hematocrit (Hct) during a laboratory investigation where multiple blood samples are collected. The performance of a simple mathematical model, used in clinical practice to predict Hct changes, is evaluated. Eight healthy male volunteers participated in this study. The equation Hct(f) = Hct(i)*(EBV-BL)/EBV is used to predict changes in Hct. Where Hct(f) and Hct(i) are, respectively, the final and initial Hct, EBV is the estimated blood volume and BL is the blood loss. Thirty-five pharmacokinetic samples per subject were collected totalling 314 mL of BL. The Hct decreased from 44.2% +/- 2.2% to 39.9% +/- 2.5% (P = 0.001). On average, model predictions tended to have a discrete tendency to underestimate the Hct changes (-0.5% points of bias). While the predictions of the Hct were very accurate in 50% of the subjects, the discrepancy of the Hct predictions was clinically significant in the other 50% of the subjects. Consistent with the model prediction, this study demonstrated a significant reduction in the Hct values in healthy subjects undergoing incremental phlebotomy. On average, the model successfully predicted the decrease in Hct. However, the inter- and intra-individual variabilities in the Hct changes are clinically significant. In clinical settings, which are not well controlled environments, the variability is likely to be greater and the clinical use of the model cannot replace the need to monitor the Hct.