Erythrocyte Volume, Plasma Volume, and Lean Body Mass in Adult Men and Women

Abstract

Erythrocyte volume, plasma volume, hematocrit, lean body mass (from total body water), skinfold thickness (at three sites), arm circumference, height, and weight were measured in 40 normal males, 38 normal females, and 12 obese females. From these data on the normal subjects, equations for estimating erythrocyte and plasma volumes were derived. Equations utilizing combined height-weight, surface area, height-weight-skinfold thickness, or lean body mass were found to be the most accurate for predicting erythrocyte and plasma volumes in normal and in obese subjects. The body:venous hematocrit ratio (BH:VH) and the variability of this ratio in our subjects were determined and discussed. Errors in indirect estimates of blood volumes based on this ratio are presented. Erythrocyte and plasma volume standards based on height-weight regression equations or surface area ratio equation are suggested for use in clinical laboratories. Tables and a nomogram based on these equations have been prepared and are available on request.

Variance inflation in sequential calculations of body surface area, plasma volume, and prostate‐specific antigen mass

“…2). The Boer PV was most consistently correlated with those from [31][32][33][34]36], with all correlations having an r 2 of 1.00 and root mean-squared errors (RMSE) of <0.001 ( Fig. 2A-G, respectively).…”

“…in the management of haemophilia [44]. With many PV formulae available [29][30][31][32][33][34][35][36][37][38][39][40], researchers have arbitrarily chosen to use certain PV formulae [1]. Previously, a report compiled by an expert panel on radionuclides of the International Council for Standardization in Hematology [45] mandated the correction of estimated PV by 23.9%, which is too broad for statistical analysis and clinical application.…”

“…As the present patients comprised men being treated for prostate cancer and who were predominantly in the older group, it is possible that the PV formula from [30] might not be applicable in this case. Interestingly, Ockelford and Johns [44] reported a significant error in previous PV formulae that used explanatory variables present in predictive equations for BSA, and instead [29] based on the BSA calculation from [7]; correlation analysis between PV [29] and PV based on different PV formulae; [36] (A), [32] (B), [33] (C), [30] (D), [34] (E), [39] (F), [31] (G), and the mean PV calculated from different formulae (H). advocated using body weight alone, with a multiplicative factor to determine PV.…”

“…Based on our observations of significant variance inflation in the sequential calculation of BSA, PV and PSA mass, we advocate a rigorous statistical treatment of extremes in formulae that produce high and low variation, before choosing one set of formulae for retrospective analysis and clinical practice. Bonferroni post-hoc analysis on PSA mass calculations indicated derivation from the following sets were similar: [34] and [29], [36] and [31], [31] and [29], [31] and [30], [30] and [29], and [30] and [39].…”

“…PV can be directly measured with the indicator-dilution technique (Evans blue and indocyanine green) and single or dual isotope tracers such as 51 Cr for tagging red blood cells or 131 I/ 125 I for tagging human serum albumin [28]. However, for retrospective data, PV is calculated with BSA as a predictor [29][30][31][32][33][34][35][36][37][38][39][40]. In previous reports there are both contradictions on the reliability of the Du Bois BSA approximation [6,21,23,41] and many formulae for estimating PV, with no accepted guideline; this presents a conundrum of choice.…”