BACKGROUND: The CBC is an essential test for assessing the health of rats used in drug development studies. Because of limited blood volume, estimates of cell counts from a blood smear would be valuable when other analytical methods of enumerating cells are not possible or available. OBJECTIVE: The purpose of this study was to develop a statistical model to accurately estimate WBC, platelet (PLT), and RBC counts in blood smears from rats. METHOD: Blood smears and quantitative cell counts were obtained from vehicle-treated male and female Fischer 344 rats (n=65) involved in a variety of studies. The numbers of WBCs, PLTs, and RBCs were estimated in 10 fields in the monolayer of smears using x 20 (WBC) or x 100 (PLT, RBC) objectives. Using a statistical model and the quantitative cell counts obtained on an ADVIA 120 hematology analyzer, formulas were developed to predict the quantitative counts from the estimates. RESULTS: Data were log-transformed before analysis. A formula was derived using the slope and intercept of the regression line between cell estimates and ADVIA counts to predict WBC, PLT, and RBC counts based only on estimates. A second formula was developed for situations in which limited quantitative analyses may be available, and resulted in even more accurately predicted counts from smear estimates. CONCLUSION: The formulas developed in this study can be a valuable tool in estimating cell counts from a blood smear when cell counting instruments are not available or when an instrument cell count needs to be verified. These formulas may be useful in the assessment of rat blood in discovery and lead optimization studies.
BACKGROUND: The CBC is an essential test for assessing the health of rats used in drug development studies. Because of limited blood volume, estimates of cell counts from a blood smear would be valuable when other analytical methods of enumerating cells are not possible or available. OBJECTIVE: The purpose of this study was to develop a statistical model to accurately estimate WBC, platelet (PLT), and RBC counts in blood smears from rats. METHOD: Blood smears and quantitative cell counts were obtained from vehicle-treated male and female Fischer 344 rats (n=65) involved in a variety of studies. The numbers of WBCs, PLTs, and RBCs were estimated in 10 fields in the monolayer of smears using x 20 (WBC) or x 100 (PLT, RBC) objectives. Using a statistical model and the quantitative cell counts obtained on an ADVIA 120 hematology analyzer, formulas were developed to predict the quantitative counts from the estimates. RESULTS: Data were log-transformed before analysis. A formula was derived using the slope and intercept of the regression line between cell estimates and ADVIA counts to predict WBC, PLT, and RBC counts based only on estimates. A second formula was developed for situations in which limited quantitative analyses may be available, and resulted in even more accurately predicted counts from smear estimates. CONCLUSION: The formulas developed in this study can be a valuable tool in estimating cell counts from a blood smear when cell counting instruments are not available or when an instrument cell count needs to be verified. These formulas may be useful in the assessment of rat blood in discovery and lead optimization studies.
Authors: Gregory A Lewbart; John A Griffioen; Alison Savo; Juan Pablo Muñoz-Pérez; Carlos Ortega; Andrea Loyola; Sarah Roberts; George Schaaf; David Steinberg; Steven B Osegueda; Michael G Levy; Diego Páez-Rosas Journal: Conserv Physiol Date: 2018-02-16 Impact factor: 3.079