HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Free All Versions of this Article: 99/5/1745    most recent 00505.2005v1 Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (22) Citing Articles via Google Scholar Google Scholar Articles by Gore, C. J. Articles by Burge, C. M. Search for Related Content PubMed PubMed Citation Articles by Gore, C. J. Articles by Burge, C. M.

Errors of measurement for blood volume parameters: a meta-analysis

¹Department of Physiology, Australian Institute of Sport, Belconnen, Australian Capital Territory, Australia; ²Health Science/Sport and Recreation, Auckland University of Technology, Auckland, New Zealand; and ³Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia

Submitted 2 May 2005 ; accepted in final form 21 June 2005

	ABSTRACT

TOP ABSTRACT METHODS RESULTS DISCUSSION APPENDIX: DETAILS OF THE... ACKNOWLEDGMENTS REFERENCES

 
The volume of red blood cells (V_RBC) is used routinely in the diagnostic workup of polycythemia, in assessing the efficacy of erythropoietin administration, and to study factors affecting oxygen transport. However, errors of various methods of measurement of V_RBC and related parameters are not well characterized. We meta-analyzed 346 estimates of error of measurement of V_RBC for techniques based on Evans blue (V_RBC,Evans), ⁵¹chromium-labeled red blood cells (V_RBC,51Cr), and carbon monoxide (CO) rebreathing (V_RBC,CO), as well as hemoglobin mass with the carbon-monoxide method (M_Hb,CO), in athletes and active and inactive subjects undergoing various experimental and control treatments lasting minutes to months. Subject characteristics and experimental treatments had little effect on error of measurement, but measures with the smallest error showed some increase in error with increasing time between trials. Adjusted to 1 day between trials and expressed as coefficients of variation, mean errors for M_Hb,CO (2.2%; 90% confidence interval 1.4–3.5%) and V_RBC,51Cr (2.8%; 2.4–3.2%) were much less than those for V_RBC,Evans (6.7%; 4.9–9.4%) and V_RBC,CO (6.7%; 3.4–14%). Most of the error of V_RBC,Evans was due to error in measurement of volume of plasma via Evans blue dye (6.0%; 4.5–7.8%), which is the basis of V_RBC,Evans. Most of the error in V_RBC,CO was due to estimates from laboratories with a relatively large error in M_Hb,CO, the basis of V_RBC,CO. V_RBC,51Cr and M_Hb,CO are the best measures for research on blood-related changes in oxygen transport. With care, V_RBC,Evans is suitable for clinical applications of blood-volume measurement.

reliability; hemoglobin mass; volume of red blood cells; Evans blue dye; carbon monoxide

The methods used to measure V_Blood values are all indirect and based on dilution of tracers injected into the circulation (31). The tracers are red blood cells labeled with radioactive chromium (⁵¹Cr) for measurement of V_RBC (51), albumin labeled with radioactive iodine (¹³¹I or ¹²⁵I) for measurement of V_Plasma (128), and the dye Evans blue, which delineates V_Plasma by staining plasma proteins (43). Measurement of M_Hb is also based on dilution of a tracer, inhaled carbon monoxide (CO), which binds to and changes the color of hemoglobin (58). The ⁵¹Cr method for estimating V_RBC (V_RBC,51Cr) is regarded as the criterion method by the International Committee for Standardization in Haematology, on the "basis of reliability, reproducibility and ease of use in routine clinical use" (75). Iodine-labeled albumin is recommended for estimating V_Plasma (74, 75) in clinical settings, whereas researchers concerned about the health risks of radioactive iodine have used the Evans blue (12, 47, 90, 104, 108) or CO (25, 55, 99, 113, 151) methods extensively.

Application of a patient's V_RBC measurement to a clinical assessment requires an appreciation of population distribution of values (106) and of normal physiological within-person variation (31). Without supporting data, it is often assumed that the patient's V_RBC has been measured reliably; that is, if the test were repeated a few days later, a similar value would be obtained (32). However, meaningful interpretation of serial changes in blood parameters in myeloproliferative disease or experimentally induced erythropoiesis requires quantification of the errors of the measurement techniques (31). A reliable method to determine V_RBC or M_Hb will have small measurement error; moreover, reliability is a prerequisite of validity, the extent to which a test actually measures what it intends to measure. Measurement error is calculated as a coefficient of variation (CV) (109, 110) and is usually expressed as a percentage. The measurement error is also known as typical error (67) and includes random error (analytic error arising from using the method-specific apparatus and intraindividual biological variation) but not systematic error (bias). Measurement error can be estimated from studies that include interventions, where it will include the analytic error, the day-to-day biological variation, and the interindividual variation in response to the intervention. Measurement errors can arise in numerous ways for the different methods used to estimate V_Blood or M_Hb, as described in Table 1.

	METHODS

TOP ABSTRACT METHODS RESULTS DISCUSSION APPENDIX: DETAILS OF THE... ACKNOWLEDGMENTS REFERENCES

 
Data Sources, Techniques, and Method Variations

The data used in the meta-analysis were obtained from original publications that reported values of individual subjects and from published studies whose authors provided us with their de-identified raw data (1, 2, 4–6, 10–12, 15–17, 21, 24, 25, 33, 35–37, 39–44, 47–50, 55, 63, 65, 77–80, 83, 86–91, 93, 94, 98–102, 104, 107, 108, 111, 113, 114, 117–120, 122, 132, 137–139, 141, 143, 144, 146, 148–151). Three unpublished data sets have also been included in the analysis, courtesy of the respective senior investigator responsible for data collection (Gore CJ, Slater GJ and Schmidt W, personal communications). The first two of these studies were approved by the Australian Institute of Sport Human Ethics Committee and the third was approved by the Human Ethics Committee of the Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany.

The V_Blood techniques selected for the meta-analysis are those most commonly used to estimate V_RBC and M_Hb (Table 1). We were able to obtain acceptable amounts of data for each of the following: CO rebreathing for M_Hb (M_Hb,CO); CO rebreathing for V_RBC (V_RBC,CO); V_RBC,51Cr; and Evans blue dye for V_Plasma, V_Blood, and V_RBC (V_Plasma,Evans, V_Blood,Evans, and V_RBC,Evans). Some data sets included values for hematocrit (Hct) and/or hemoglobin concentration ([Hb]). Only one study (30) provided sufficient data for V_Plasma, estimated using ¹³¹I-labeled albumin, and none provided data for ¹²⁵I.

Modification of the CO-rebreathing technique may affect the magnitude of measurement error for M_Hb,CO and its related volumes. We have previously recommended that, to minimize likely sources of error, researchers should use relatively large doses of CO, a small rebreathing volume, and at least four replicate measures of percent carboxyhemoglobin (%HbCO) (15). Others have generally used smaller doses of CO, and/or a larger rebreathing volume, and/or duplicate or single measures of %HbCO. We took this opportunity to compare the error of measurement of the "Burge and Skinner" (15) method (4–6, 15, 48–50, 122) with that of others (10, 39–41, 55, 63, 65, 117, 119, 120).

Methodological variations of the Evans blue technique could affect the magnitude of measurement error for V_Plasma,Evans and its related volumes. These variations are in terms of extraction (column chromatography) or not of Evans blue dye from plasma. There are also variants that do or do not back-extrapolate a multitime point disappearance curve. Some authors do not back-extrapolate but use the simple change in plasma dye concentration obtained from one pre- and one postdye injection specimen (with post being obtained 10–20 min afterwards) (11, 24, 47, 55). The use of just one postinjection sample is justified by the statement of Greenleaf et al. (52) that a single 10-min post-dye-injection specimen gives the same V_Plasma value as using the more rigorous back-extrapolation method, of which there are also several mathematical approaches (43) (Table 1). The three common method variations for V_Plasma,Evans in the data that we acquired were as follows: extracted/not back-extrapolated (11, 12, 24, 44, 47, 55), not extracted/not back-extrapolated (2, 16, 21, 33, 36, 37, 42, 43, 50, 77, 78, 86–91, 93, 94, 101, 102, 104, 107, 108, 111, 118, 132, 143, 149, 150), and not extracted/back-extrapolated (17, 146).

Classically, [Hb] has been determined by pipetting blood into Drabkin's reagent, to form cyanmethemoglobin that is measured spectrophotometrically at 540 nm (76). We distinguished between those studies that used the traditional, manual cyanmethemoglobin method to determine [Hb] and those that used fully automated analyzers.

There are no substantial variants of the CO-based method for estimation of V_RBC,CO. Several altitude studies from which we obtained data (55, 98, 113, 119, 151) calculated the circulatory volumes by combining M_Hb with [Hb] or Hct (Table 1: secondary equations for CO); other studies (5, 40, 64, 117, 122, 127) reported only M_Hb,CO (15) (Table 1, primary method equation for CO).

Calculation of Error of Measurement

Studies were included in the meta-analysis if there were at least two assays of V_RBC, V_Blood, V_Plasma, or M_Hb in at least three individuals receiving the same experimental treatment. The error of measurement for each blood-related measure was calculated for pairs of assays as follows (67): after log-transformation, the standard deviation of the differences was calculated, and the result was divided by and back-transformed to a CV, which was recorded along with its degrees of freedom (df = sample size – 1). These calculations were performed in a spreadsheet designed for analysis of crossovers (68). Each estimate of error was inflated by a factor 1 + 1/(4 df) to correct for small-sample bias (56).

In studies in which more than two assays were performed per subject, one assay was chosen as the reference, and the error of measurement and change in the mean were calculated for each of the other assays paired against this reference. Where two or more baseline assays were obtained before an experimental treatment, the reference was the assay closest in time to the experimental treatment. Time between pairs of assays was recorded in days.

The values of individual subjects giving rise to an estimate of error of measurement were examined for outliers in a plot of the subjects' change score between assays against the subjects' value of the reference assay. The following outliers were excluded from the error of measurement calculation: a subject with a 40% decline in V_Plasma,CO in Poulsen et al. (111), and a subject with 40% changes in several Evans blue measures in Grover et al. (55). Individual values for the residuals and random effects in the meta-analyses (see below) were also displayed graphically for identification of other possible outliers (t values 3 or more), but none was observed. These analyses, therefore, were performed with essentially no subjective filtering of data, and any apparently large errors of measurement obtained in our analysis are not attributable to the presence of outliers.

Coding of Predictor Variables

Experimental treatments.   The treatment that occurred between each pair of assays was coded either as "altitude," "none," or "other." Treatments were coded as altitude for assays separated by a period of real or simulated altitude of 600–7,000 m, for exposures of 0.5–24 h/day, for durations of 0.3–40 days. Altitude treatments that included any time spent at or near sea level before, during, and/or after the altitude exposure were coded as altitude. Treatments were coded as none for pairs of assays from reliability studies, pairs of assays during a baseline period in experimental studies, and pairs of assays in any control group receiving no intervention that would be expected to change V_Blood parameters. Treatments coded as other were as follows: training, ingestion of propranolol during altitude exposure, effects of menstrual cycle and/or oral contraceptive pill or placebo in combination with altitude, feeding before and after Evans blue injection, bed rest with head-down tilt and/or supine cycle ergometer training, acute exercise, living 12.8 m below the ocean surface, spaceflight, weight loss before rowing races, V_Plasma expansion, heat exposure, iron supplementation, and venesection.

Subject characteristics.   Sex and fitness were included in some meta-analyses. Sex was coded as a covariate representing the proportion of men in the sample (examples: 0 for all women; 0.375 for 5 women and 3 men; 1 for all men). Two studies using the ⁵¹Cr method (114, 144) and one study using the Evans blue method (143) did not state the sex of the subjects. For these studies, we assigned a sex covariate value of 0.6, which was the mean value of all of the studies. Fitness was coded as "inactive" (sedentary), "active" (but not a competitive athlete), and "athlete" (competitive). Hospital inpatients [2 studies (30, 143)] were coded as "inactive." Four studies using the Evans blue method (24, 43, 98, 111), two using the ⁵¹Cr method (114, 144), and three using V_RBC,CO (25, 80, 98) did not indicate physical activity or fitness of the subjects and were coded as inactive.

Laboratories.   The effect of individual laboratories (or research groups) on error of measurement was modeled as a random effect in the meta-analysis. If a laboratory changed a particular technique substantially, a new identifier was assigned to the subsequent estimates.

Meta-analysis

The details of our unique, novel meta-analytic approach and its interpretation are contained in the APPENDIX. In summary, we used a mixed-model meta-analysis in which the dependent variable was the log-transformed error of measurement, the fixed effects were the method of measurement and characteristics of the study, and the random effects were within- and between-study variation. An unbiased weighting factor for each estimate was derived from the estimate's df. Inferences about the substantiveness of true differences between two errors of measurement were made in accordance with extent of overlap of the confidence interval of their ratio with the thresholds for substantial ratios (0.9 and 1.1).

	RESULTS

TOP ABSTRACT METHODS RESULTS DISCUSSION APPENDIX: DETAILS OF THE... ACKNOWLEDGMENTS REFERENCES

 
Raw Data

The numbers of estimates of error of measurement for each blood parameter were as follows: 69 M_Hb,CO, 32 V_Blood,Evans, 64 V_Plasma,Evans, 29 V_RBC,CO, 9 V_RBC,51Cr, 69 V_RBC,Evans, 83 [Hb], and 57 Hct. The mean df for each parameter ranged from 5 to 10. The number of estimates for each of the methods for measurement of V_Plasma,Evans were as follows: 19 extracted/not back-extrapolated, 41 not extracted/back-extrapolated, 3 not extracted/not back-extrapolated, and 1 unclear. Thirty-six of the estimates of error for M_Hb,CO used the method of Burge and Skinner, and 33 used the other method. Of the 83 estimates for [Hb], 52 used automated methods, and 31 used the cyanmethemoglobin method. The median time between measurements giving rise to the estimates of error was 22–30 days for M_Hb,CO, V_Blood,Evans, V_Plasma,Evans, V_RBC,CO, V_RBC,Evans, [Hb], and Hct, but only 1 day for V_RBC,51Cr. There were 159 estimates involving real or simulated altitude, 132 estimates involving other treatments, and 121 involving no treatment (from control groups, baseline pairs of measurements in treatment groups, or reliability studies). The median real or simulated altitude was 3,000 m (range 600–7,000 m), and median time spent at altitude was 12 days (0.3–40 days). The estimates were collected on 84 recreationally active, 165 athletic, and 161 inactive groups. For the entire data set, there was a greater proportion of men (60%) than women (40%).

Four Comparable Hematology Parameters for the Red Cell Compartment

The measurement errors for M_Hb,CO, V_RBC,CO, V_RBC,51Cr, and V_RBC,Evans are displayed in Fig. 1 as a function of time between measurements. A 10-fold increase in time between measurements had a substantial effect on the error for M_Hb,CO (by a factor of 1.5; 90% confidence limits 1.2–1.9), trivial small effects on the errors for V_RBC,51Cr (by a factor of 1.1; 1.0–1.2) and V_RBC,Evans (by a factor of 1.1; 0.9–1.2), and an unclear trivial effect on the error for V_RBC,CO (by a factor of 1.0; 0.6–1.6). The mean error of measurement predicted for 1 day between measurements and averaged over treatments ranged from 2.2 to 6.7% for the four methods (Table 2). M_Hb,CO had substantially less error than V_RBC,51Cr (ratio of errors of M_Hb,CO to V_RBC,51Cr = 0.8; 0.5–1.3), although the confidence limits indicate that the real difference was unclear. Errors for both methods were clearly less than (about one-third) those for V_RBC,CO and V_RBC,Evans. Estimates of the typical between-laboratory variations in the errors of measurement for M_Hb,CO, V_RBC,CO, and V_RBC,Evans had considerable uncertainty, but were substantial over the range of their confidence limits: observed values (and confidence limits) were x/÷1.8 (1.5–3.0), x/÷1.5 (1.3–4.2), and x/÷1.6 (1.3–2.8), respectively. Thus, for example, a new user of the M_Hb,CO method could anticipate that, in their hands, the error of measurement could easily be consistently as high as 4.0% (= 2.2 x 1.8%) or as low as 1.2% (= 2.2 ÷ 1.8%). The between-laboratory variation for V_RBC,51Cr was not estimable, owing to a paucity of data.

View larger version (21K): [in this window] [in a new window]   Fig. 1. Measurement error as a function of the time between measurements for 4 comparable hematological parameters: hemoglobin mass via CO rebreathing (MHb,CO; ), and volume of red blood cells via CO rebreathing (VRBC,CO; x), 51chromium (VRBC,51Cr; +), and Evans blue dye (VRBC,Evans; ). Values of measurement error have been adjusted to remove sample-size bias. Lines of best fit are those derived from a meta-analysis, with time between measurements as the only fixed effect for each measure.

V_Blood Compartments with Evans Blue

The mean error of measurement for V_Blood,Evans, V_Plasma,Evans, and V_RBC,Evans was 5–7% (Table 3), and there were no clear differences between the ratios of their errors. However, the variation in error between laboratories for these measures was substantial: x/÷1.6 (1.4–2.0). A 10-fold increase in the time between measurements did not substantially increase the errors in V_Blood,Evans, V_Plasma,Evans, and V_RBC,Evans; the ratio for the pooled data of all three volumes was x/÷1.0 (0.9–1.1). There was little difference between errors for the pooled treatments (6.8%; 5.6–8.4%), altitude treatments (6.3%; 5.1–7.7%), and no treatment (6.0%; 4.9–7.3%), although confidence limits allowed for small differences between some treatment groups (range of confidence limits for ratios: 0.8–1.2).

V_Plasma with ¹³¹I

In the only study providing usable data for the ¹³¹I method, the subjects were five female and eight male patients, and there was no treatment between the two trials, which were separated by 150 min. The error of measurement for V_Plasma was 4.9% (confidence limits 3.7–7.0%).

[Hb] and Hct

The mean errors of measurement for [Hb] were 2.5% (confidence limits 2.3–2.7%) and 2.1% (1.8–2.5%) for the automated and cyanmethemoglobin methods, respectively, whereas that for Hct was 3.2% (2.6–4.0%). The variation in error between laboratories for [Hb] was trivial (x/÷1.1), and its upper confidence limit was only marginally substantial (x/÷1.2). On the other hand, the variation in error between laboratories for Hct was substantial, although small: x/÷1.2 (1.1–2.8). There was little difference between men and women for the error in [Hb] (ratio men/women 1.1; 1.0–1.3) and Hct (ratio 1.0; 0.8–1.2). A 10-fold increase in time between measurements was associated with a decisive substantial increase in the error for [Hb] (ratio 1.3; 1.3–1.4); in contrast, the error in Hct was, at most, only marginally larger (ratio 1.1; 1.0–1.2) for a 10-fold increase in time.

	DISCUSSION

TOP ABSTRACT METHODS RESULTS DISCUSSION APPENDIX: DETAILS OF THE... ACKNOWLEDGMENTS REFERENCES

 
The most important results in the present study are the meta-analytic estimates of error of measurement of V_RBC and M_Hb, the blood parameters directly related to oxygen transport. The short-term errors for V_RBC,51Cr and M_Hb,CO were 2.5%, whereas those for V_RBC,Evans or V_RBC,CO were about threefold greater. Over a period of 1 mo, the errors for V_RBC,51Cr and M_Hb,CO were 3.5%, about one-half of those for V_RBC,Evans or V_RBC,CO. The errors of measurement for M_Hb,CO, V_RBC,51Cr, and V_RBC,Evans also showed wide variation between laboratories, typically by a factor of approximately x/÷1.6. Thus a poor laboratory assessing M_Hb,CO and a good laboratory assessing V_RBC,Evans could have similar errors of measurement (4%) and obtain similar precision in the estimates of effects on M_Hb and red cell volume with a given sample size, but an even greater disparity between the two methods is also possible. Unfortunately, we were unable to estimate whether V_RBC,51Cr shows substantial variation from laboratory to laboratory, owing to a paucity of data.

The substantial increase in the error for M_Hb,CO with increasing time between measurements can be accounted for partly by an increase in the contribution of biological variation. The error of measurement consists of biological variation and analytic error that are independent and combine as variances: (error of measurement)² = (biological variation)² + (analytic error)². If we assume that the 1-day error for M_Hb,CO (2.2%) comprises minimal biological variation, the 30-day error (4%) indicates additional error of 3.3% during this interval, irrespective of treatment. The sources of technical error (Table 1) should be independent of time between measurements, so this additional error appears to be entirely biological. An intriguing possibility is that it arises from cyclical variation in hematopoiesis with a period of approximately weeks, similar to but of lesser magnitude than that described in some hematological disorders (62). On the other hand, the additional error could be an artifact of studies of longer duration being conducted by laboratories with poorer measurement error. Frequent serial measurements of M_Hb and other blood parameters over several months should resolve this issue.

The measurement errors of V_RBC,CO, V_Blood,Evans, V_Plasma,Evans, and V_RBC,Evans did not increase substantially with increasing time between measures, in contrast to that of M_Hb,CO. This finding is likely attributable to large measurement error swamping any biological variation. For example, the measurement error for V_Plasma,Evans was 6% after 1 day, which, combined with biological variation of 3% (as described above), results in a total error of 6.2% [] for 30 days between measures.

Sources of Error

Sources of measurement error of the common blood measurement methods are summarized in Table 1. Several of these sources of method-specific measurement error are discussed below in relation to the results obtained in the meta-analysis.

M_Hb,CO.   The major contributions to test-retest random analytic error for the CO rebreathing method include gas leaks in the mouthpiece, noseclip, and rebreathing system, inadequate CO dose, and using a rebreathing bag with excessive volume (15). The importance of careful attention to these sources of error is reinforced by the result that, in our hands, the Burge and Skinner method has less than one-half the error of the equivalent method used by others. An adequate dose of CO becomes particularly important if estimating %HbCO levels with commercial CO-oximeters that display readings only to a single decimal place (usually ±0.1%) (15). With progressively lower doses of CO, a 0.1% difference in the %HbCO is associated with a substantial increase in the measurement error of M_Hb,CO (15); for example, doses of 75 and 25 ml produce errors of 1.3 and 4.1%, respectively, for a woman with 600 g of hemoglobin. Investigators can perform replicate measurements with each specimen to improve the single-replicate precision (15, 18). We have successfully used a CO dose of 1.25–1.5 ml/kg in athletes with low body mass index to induce a pre- to postdose change in %HbCO of 6.5% and performed at least five replicate measures of %HbCO (OSM-3, Radiometer, Copenhagen, Denmark) on each blood sample (50). In clinical situations, a CO dose of 1 ml/kg at sea level (aiming to increase %HbCO by 6%) to a maximum dose of 100 ml is adequate, with appropriate dose reduction for patients with significant anemia and/or morbid obesity. Use of high-precision gas chromatography to measure %HbCO (23) allows much smaller doses of CO to be administered but requires well-trained technical staff. On the other hand, well-maintained CO-oximeters require minimal staff training and are routinely found in major hospital emergency departments and intensive care units and now increasingly in exercise physiology laboratories. The increased CO dose required when using CO-oximetry to obtain adequate precision makes no substantial difference to the safety of the method (15).

Our meta-analysis indicates that the measurement error of M_Hb,CO is small in most laboratories. Nevertheless, the CO method has sustained criticism of its validity, particularly the claim that inspired CO leaves the vascular space and binds to extravascular porphyrin moieties, such as myoglobin (73, 115, 126), leading to overestimation of M_Hb,CO (84, 100, 123, 126). However, at relatively low HbCO saturation (<15% HbCO) and at the elevated blood oxygen tension induced in the CO method (15, 48), HbCO remains stable (9), and oxygen rather than CO is taken up by myoglobin (19, 95). Observations on the effects of ischemia on deoxymyoglobin in resting muscle in the presence of 20% HbCO using magnetic resonance spectroscopy (116) support our earlier findings (15) that measures of M_Hb,CO do not need to be corrected for loss of CO to myoglobin. Mathematical modeling of CO uptake during 40 min of rebreathing (14) indicates that loss of CO to extravascular sites is, at most, a negligible 1% of the CO dose over 10 min. Thus concerns of poor validity of M_Hb with CO rebreathing appear to be unwarranted. Additionally, the low rate of extravascular loss of CO appears to be consistent within an individual and, therefore, will have little or no substantial effect on the random error of 2%.

V_RBC,51Cr.   V_RBC,51Cr is the defined criterion method of the International Committee for Standardization in Haematology (75). Our meta-analysis confirms the low measurement error of V_RBC,51Cr, as concluded 25 years ago (75) and more recently (31, 32). A common misconception, however, is that the ⁵¹Cr method primarily measures V_RBC. The primary estimate is actually V_Blood,51Cr (32), because counts in a whole blood specimen are compared with the assay reference counts. V_RBC,51Cr must then be secondarily derived from V_Blood,51Cr using the Hct (Table 1). It is difficult, and potentially unethical, to perform multiple ⁵¹Cr studies on individuals simply for the sake of establishing the method measurement error. With multiple estimations in the same subject, residual radioactivity from previous estimations increases measurement error, unless compensated by progressively larger doses of ⁵¹Cr (0.5–4 MBq for one estimate, 4–20 MBq after three consecutive estimates within 28 days). The radiation exposure is thus a concern, especially if the studies are conducted in healthy people for nondiagnostic purposes. Hence, use of the ⁵¹Cr method is rare. A variation of the chromium-labeling of red blood cells that may warrant further investigation is the use of the nonradioactive isotope ⁵³Cr (142).

Fairbanks and colleagues (32) simulated best case scenario sources of variability affecting the measurement error of V_RBC,51Cr as follows: whole blood ⁵¹Cr dose (8,000 counts: pipetting error 1%, blood resuspension and reinjection errors 2.0%), whole blood specimen (pipetting error 1.0%, mixing error 1.0%), scintillation count error (1.1%), and Hct (1.7% biological within-person variability, 1.0% analytic variability), giving an overall estimate of the measurement error of V_RBC,51Cr of 3.4%. Scintillation count errors of 1.5% (100) and 1.6% (148) have also been reported. The measurement error obtained in our meta-analysis for V_RBC,51Cr was of similar magnitude to that from Fairbanks' modeling (Table 2).

In our meta-analysis, the mean measurement error for V_RBC,51Cr was substantially more than that for M_Hb,CO, but the confidence limits of the ratio of errors indicate that the true difference between the methods is unclear (Table 2). If the real difference is substantial, it could be due to the fact that V_RBC,51Cr, unlike M_Hb,CO, requires Hct for its estimation (Table 1). An interesting anomaly obtained in our results, however, was that the measurement error for V_RBC,51Cr is somewhat less than our estimate of the measurement error for Hct, which is not possible in reality (31). Our result can be explained as follows: the studies that we meta-analyzed for V_RBC,51Cr all had measurement errors for Hct < 3%, which is near the lower 90% confidence limit for Hct. Our results are consistent with the model of Fairbanks and associates (32) that the random, biological variation in Hct from day to day is the major source of error in V_RBC,51Cr (31).

V_RBC,Evans.   The primary estimate of the Evans blue method is V_Plasma,Evans, and V_RBC,Evans must be derived subsequently with the Hct (Table 1). It follows that the measurement errors for V_RBC,Evans consist of those for V_Plasma,Evans (6.0%) and Hct (3.2%) that combine as variances: V_RBC,Evans² = error in V_Plasma,Evans² + error in Hct². Thus error in , which is consistent with our meta-analytic estimate of 6.7%. It is, therefore, clear that most of the error in V_RBC,Evans derives from the measurement of V_Plasma,Evans.

The existence of a wide variety of Evans blue methods is suggestive of attempts by researchers to improve method reliability. However, errors of V_Plasma,Evans were not decisively different, whether a dye-extraction procedure was used (11, 12, 47, 55) or not used (43, 90, 94, 104, 108, 118), and whether (43, 88, 93, 111, 118, 143) or not (11, 12, 17, 24, 55) multiple data points were back-extrapolated to obtain the volume of distribution of Evans blue. Consequently, our analysis does not support use of one method variant over another. Analysis of multiple replicates of specimens improves analytic precision, and it is noteworthy that Gordon et al. (47), who achieved one of the lowest measurement errors for V_Plasma,Evans, routinely performed triplicate spectrophotometric assays of Evans blue dye concentration. Among the other studies from which we acquired data for meta-analysis, only Branch et al. (11, 12), Chien et al. (17), and Levine et al. (personal communication) reported at least duplicate spectrophotometric assays. Different numbers of assayed replicates likely contribute to some of the variation in measurement error between laboratories, but it is unclear whether the use of multiple assays would be sufficient to make the error for V_Plasma,Evans comparable to that of M_Hb,CO.

The Evans blue method has sustained criticism about its validity, particularly that variable loss of the dye from the vascular space causes overestimation of V_Plasma as well as a relatively high measurement error (8, 29, 54). Evans blue is primarily an estimate of the albumin space (112), but the dye also binds to globulins (85), fibrinogen (8), and connective tissue (129). The albumin space includes variable flux among the vascular, interstitial, and lymphatic spaces (8, 34); postinjection disappearance curves are consistent with a rapid mixing phase and a slow disappearance phase (143), as initially described by Gibson and Evans in 1937 (43). The rates of decline in the two phases vary between individuals (96), and substantial change within an individual between two trials would increase measurement error, especially if there were changes in extravascular flux due to increased vascular permeability. Capillary permeability to albumin increases during acute exposure to high altitude (60, 61, 92, 152) but appears to be an inconsistent response (81, 82) at the moderate altitudes used by athletes. Serum vascular endothelial growth factor [VEGF; also known as vascular permeability factor (20, 130, 131)] increases substantially at moderate altitude (3), secondary to increased oxygen-regulated gene expression (147) mediated by hypoxia inducible factor-1 (26). An increase in VEGF provides a possible means by which vascular permeability is increased at moderate altitude, and its mechanism of action appears related to disruption of endothelial tight junctions (145). The chronic increase in vascular permeability resulting from an increase in VEGF persists for at least 24 h, but not 72 h (7). Consequently, Evans blue estimates of V_Plasma conducted at altitude, or 1 or 2 days after return to sea level, may be affected by an enhanced rate of loss of dye. Our analysis indicates little difference in measurement error for Evans blue volumes with various treatments, but additional error arising from a small and variable change in vascular permeability at or after altitude may have been overwhelmed by the noise of the Evans blue method.

V_RBC,CO.   The meta-analysis demonstrated that there was threefold greater 1-day error for V_RBC,CO than for M_Hb,CO. Part of this difference arises from the contributions that [Hb] and Hct make, along with the contribution of M_Hb, to the error in V_RBC,CO (Table 1). If we assume little or no biological variation in M_Hb, [Hb], and Hct over 1 day, the errors in these three measures are methodological and, therefore, independent. Thus (V_RBC,CO error)² = (M_Hb,CO error)² + (Hct error)² + ([Hb] error)². In the meta-analysis, the 1-day error was 2.2% for M_Hb,CO, 3.2% for Hct, and 2.5% for [Hb] via the cyanmethemoglobin method. The expected error in V_RBC,CO is, therefore, , which is still substantially less than the meta-analyzed value of 6.7%. The simple explanation for this difference is that errors in V_RBC,CO came from studies with a higher than average error for M_Hb, which is certainly the case for the studies that provided estimates for both of these measures (55, 119, 120).

Our estimate of total error for Hct agrees well with Thirup's (140) value of 4.2% for day-to-day variation in centrifuged micro-Hct, which he estimated as consisting of 3% biological variation and 3% analytic variation. Analytic error has been reported for automated Hct to be 2.3% and 0.8% for [Hb] (38). Using the lowest values from above, the likely minimal measurement error for V_RBC,CO with 1 day between measures = . This indicates that, in careful hands, the total error for V_RBC,CO should approach that of M_Hb,CO. However, the additional propagated error in V_RBC,CO from the measurement of Hct and [Hb] does little to support the former method if one needs to monitor small changes in the red cell compartment.

Implications for Monitoring Individuals

What are the implications of measurement error for a clinician's uncertainty in the assessment of an individual? Applying statistical first principles, the observed value of a measurement plus or minus the error of measurement is 68% confidence limits for the true value of a normally distributed single measurement, or 52% confidence limits for a change between two such measurements; the observed value plus or minus twice the measurement error is, respectively, 95 and 84% confidence limits (66). For the clinician to be reasonably confident that an observed small but substantial positive value is not, in reality, substantially negative, it follows that the error of measurement has to be less than the least clinically important difference (66, 69, 70). In other words, to measure a signal confidently, the noise must be less than the signal (67). A measure with an error of 7% is, therefore, useful only for characterizing differences >7%. Differences in V_Blood of this magnitude are probably the least clinically important difference in most clinical situations, when one considers that a healthy individual can donate 500 ml of blood from a total volume of 5 liters with little risk. Evans blue used carefully would, therefore, be suitable in many clinical settings, as an alternative to ¹³¹I or ¹²⁵I (32). Clinicians should, nevertheless, be aware that the error of measurement with Evans blue will sometimes produce unrealistically large differences in V_Blood. Discounting such differences to an extent guided by clinical experience is sensible and an appropriate application of Bayesian reasoning (22, 70).

Implications for Controlled Trials

Adequacy of sample size is one of the most important issues in quantitative studies. With the traditional requirement of 80% chance of statistical significance at the 5% level for the smallest clinically important difference, statistical first principles show that the sample size of each group in a randomized controlled trial needs to be 32 d²/e², where d is the smallest difference and e is the standard error of measurement. In studies of athletes, a 2% increase in M_Hb or V_RBC would be important, because it would likely produce a useful change in endurance performance. A researcher interested in detecting such an increase in M_Hb using the CO method with an error of measurement of 2% would, therefore, need 32 subjects in each of the control and experimental groups. Samples in the studies that we reviewed were typically less than one-half this size. Detecting the same change in V_RBC using an Evans blue method with an error of 7% would require an unprecedented nine times as many subjects in each group. Less conservative approaches to sample size estimation based on adequate precision of estimation would make the usual sample sizes adequate for characterizing the smallest changes in M_Hb,CO, but these sample sizes would be adequate for changes in V_RBC,Evans only when the changes are greater than the error of measurement for V_RBC,Evans: 7% for the typical laboratory.

In our view, mean changes in V_RBC in excess of 7% are likely only following radical interventions, such as exposure to high altitude, administration of large doses of erythropoietin, and direct substantial manipulation of red cell volume by venesection or blood transfusion. There are, nevertheless, claims in the literature for even larger changes in V_RBC,Evans following less severe interventions, for example 4 wk of training at sea level (88) and 4 wk living and training at moderate altitude (16, 88). The fact that the findings were not consistent in similar studies of V_RBC,CO at higher altitude (55, 113, 151) points to type I error as an alternative explanation to such large physiological effects. Publication and other biases, such as deleting apparent outliers before analysis (e.g., a physiologically improbable large negative change in V_RBC), would make the rate of reporting of such large effects substantially greater than the usual type I error rate of 5%. It might help to limit such biases if researchers routinely reported the magnitude of the error of measurement in their studies, not only from any reliability study but also from the data in the control and experimental groups.

Methods with the Smallest Error

For researchers and clinicians seeking to improve their measurement error, we have identified the studies that demonstrated the smallest measurement errors for each of the four methods illustrated in Fig. 1.

M_Hb,CO.   The lowest measurement error of 0.9% [90% confidence limits (CL), 0.5–1.5%] was obtained by Burge and Skinner (15).

V_RBC,51Cr.   The smallest measurement error of 1.4% (90% CL = 0.6–2.9%) was obtained by Johnson et al. (79).

V_RBC,Evans.   Although the lowest estimates were 2%, these were derived from studies of only three to four subjects [Faura and Reynefarje (33), and a subset of the 1992–2002 data from Levine and coworkers (16, 42, 86–88, 150)]. The 90% uncertainties in these estimates are, therefore, a factor of approximately x/÷2.5. Allowing also for regression to the mean with extreme values when there is such large sampling error, it is likely that the true error in these studies was substantially greater.

V_RBC,CO.   This method would also have acceptable error in a laboratory, with a good technique for M_Hb,CO and good reliability for Hct and [Hb]. The lowest errors (2–4%) were obtained by Myhre et al. (99), although the small sample size (4–5 subjects) implies considerable uncertainty in these estimates.

Finally, it is critical that, for all measures reliant on Hct or [Hb] and to derive V_RBC, V_Plasma, or V_Blood, subjects should adopt a consistent posture for at least 20 min before blood sampling (15). Venous stasis of any duration should also be avoided because it introduces substantial and unquantifiable error due to regionally increased hydrostatic pressure and localized hemoconcentration.

In conclusion, M_Hb,CO has error of measurement similar to that of V_RBC,51Cr, which is considered the gold standard (32, 75, 106). Both V_RBC,51Cr and M_Hb,CO have only about one-third of the error of Evans blue dye or V_RBC,CO and thus are more suitable to monitor small changes in red cell volume and M_Hb, respectively. Given the relative ease of handling CO compared with ⁵¹Cr, arising from the fact that M_Hb,CO is independent from biological variation in Hct, and the shorter biological half-life of CO (46), this review supports the routine use of CO rebreathing in clinical as well as research situations to monitor changes. Our results also reinforce the importance of researchers estimating and reporting the error of measurement of the method in their hands to improve the analysis and interpretation of their data.

	APPENDIX: DETAILS OF THE META-ANALYTIC APPROACH AND ITS INTERPRETATION

TOP ABSTRACT METHODS RESULTS DISCUSSION APPENDIX: DETAILS OF THE... ACKNOWLEDGMENTS REFERENCES

 
Meta-Analysis

The main outcome from a meta-analysis is a weighted mean of values of the statistic of interest (measurement error in this instance) from the various studies, where the weighting factor is the inverse of the square of the sampling standard error of the statistic. We performed mixed-linear model meta-analyses, where effects of blood measures, treatment, and subject characteristics on the estimates were estimated as fixed effects, and the remaining unexplained true variation (heterogeneity) within and between studies was estimated as one or more random effects. Mixed-model meta-analysis is more realistic than traditional meta-analysis (in which "outlier" estimates are progressively eliminated until the test of heterogeneity is no longer statistically significant).

Data transformation.   Meta-analysis of untransformed errors of measurement was not an option, because it would result potentially in negative values for means and confidence limits, which is not possible in reality. Analysis of the errors as variances was attractive for several reasons but suffers from the same problem. We, therefore, opted for log transformation, which was used successfully in an earlier meta-analysis of error of measurement (assessing reliability of power in physical performance tests) (72). Meta-analysis with mixed linear modeling provides confidence limits based on the assumption that random effects (including the residuals) are uniform and that any nonnormality in the individual observations is normalized in the outcome statistics by the central limit theorem. Gross departures from normality in the distribution of the individual observations are, therefore, to be avoided. We, therefore, used simulation to check that the sampling distribution of a log-transformed standard deviation derived from small sample sizes (>3) had an acceptably near-normal distribution.

Weighting factor.   The sampling standard error for the log-transformed error of measurement was derived semi-empirically by initially assuming it was defined approximately by the 68.4% confidence limits of the standard error of measurement. These limits were derived from the usual formula involving the ² distribution and df, and then converted to a single times/divide factor (x/÷ factor) by taking the square root of the upper limit divided by the lower limit. The squared log of this x/÷ factor should approximate the inverse of the weighting factor used in the meta-analysis. The accuracy of the inverse weighting factor was checked by comparing the average of its value computed for a standard deviation from each of 10,000 samples of a given size with the mean value of the variance of the log of the standard deviations of the same samples. The weighting factor was found to be biased low for small sample sizes, and a correction factor of 1 + 1/[2(df + 1)] was found by trial and error. This factor corrected the bias to within 1% for df 2.

Fixed effects.   The fixed-effects model varied with the blood measures under analysis as follows.

M_HB, V_RBC,EVANS, V_RBC,CO, AND V_RBC,51CR.   For this main comparison of error of measures, a paucity of data for V_RBC,51Cr dictated a simple model, consisting of the interaction of measure (representing these four blood parameters) with treatment (two levels: none and other) and with log₁₀ time (the base-10 logarithm of time between pairs of measurements). Sex and fitness level were excluded from the analysis because the subtle effects of these predictors were masked by the considerably larger errors of measurement for V_RBC,Evans and V_RBC,CO.

M_HB.   A more complex fixed-effects model was used in the analysis of M_Hb, because of its low error of measurement (see RESULTS) and a relatively large amount of available data. The predictors were sex (proportion of men in the sample), fitness (three levels: athlete, active nonathlete, and inactive), treatment (three levels: none, altitude, and other), method (Burge and Skinner and other), and log₁₀ time. The interaction of treatment with log₁₀ time was included in a preliminary analysis.

EVANS BLUE VOLUMES.   The predictors were measure (three levels: V_Blood,Evans, V_Plasma,Evans, and V_RBC,Evans), treatment (three levels: none, altitude, and other), and log₁₀ time.

EVANS BLUE METHOD VARIATIONS.   The error of measurement of V_Plasma was the dependent variable in a model where three Evans-blue method variations (three levels: extracted/not back-extrapolated, not extracted/not back-extrapolated, and not extracted/back-extrapolated) were coded as levels of measure. The other predictors were treatment (two levels: none and other) and log₁₀ time.

[HB] AND HCT.   In separate analyses for these parameters, the models were the same as for M_Hb, with the inclusion of method (two levels: automated and cyanmethemoglobin) for [Hb].

All meta-analyzed estimates of measurement error for a given blood parameter shown in the RESULTS are values predicted for 1 day between measurements and, where relevant, for equal contributions from each level of predictors in the model and for equal proportions of men and women. Comparisons of effects of different levels of individual predictors (e.g., no treatment vs. all other treatments) on measurement error are shown as x/÷ factors, derived by back-transformation of the log-transformed measurement error. For example, the difference between the error of measurement (ratio of CV between measures) for M_Hb,CO and that for V_RBC,Evans is a ratio of 3.0 (Table 2). Ratios can be reinterpreted as percent differences, for example, a ratio of 1.25 represents 25% more error, but we have opted to present all differences as ratios to minimize potential confusion with the percent units of the error of measurement. Because the time between measurements was log₁₀ transformed, its effect on measurement error is shown as a factor per 10-fold multiple of time.

Random effects.   For the main comparison of blood parameters and for the analyses of M_Hb,CO, [Hb], and Hct, the random effects coded for each measure were an identifier for the estimate (to provide the pure within-laboratory, between-estimate variation), an identifier for the laboratory technique (to provide pure between-laboratory variation), and the residual. Owing to a paucity of data for some Evans blue volumes and Evans blue methods, the between-laboratory random effect in each analysis was modeled to have the same magnitude for the three volumes and for the three method variations. The between-laboratory variance for [Hb] was negative and, therefore, set to zero; the confidence limits for the between-estimate variation were estimable only by allowing the lower confidence limit of the variance to be negative. In initial analyses, an identifier for each series of estimates of error coming from the same subjects was included as a random effect, but the paucity of data too often resulted in negative variance for one or more of the random effects. This identifier was, therefore, excluded from all analyses.

When the residual variance is scaled to unity (153), the standard deviation of the estimate identifier gives the typical variation of mean measurement error (CV) obtained for a method performed routinely in a specified laboratory (within-laboratory, between-estimate variation). The standard deviation of combined variances for the estimate and laboratory identifiers represents typical variation in mean method measurement error obtained between laboratories. The df for the combined variances was estimated by using the Satterthwaite (121) approximation and applied to the ² distribution to estimate confidence limits for the combined variance (in the same manner that confidence limits for the individual variances are estimated in the statistics program). The square root of the variances and their confidence limits were back-transformed to times/divide factors. As an example, a between-laboratory typical variation of x/÷1.80 obtained for a blood measure with mean measurement error (CV) of 6.7% is interpreted as follows: researchers applying the method will obtain, on average, a true CV of 6.7%, but the true value for any given researcher could be typically between 12.1% (6.7 x 1.80%) and 3.7% (6.7 ÷ 1.80%). The uncertainty is actually wider, because uncertainty represented by the confidence limits for the 6.7% have not been taken into account in this example. However, since the focus of the present study is primarily examination of the fixed effects, we have shown the random effects only to illustrate the generally wide variation in the errors of measurement between assays (within laboratories) and between laboratories. These estimates of error of measurement apply only to true values or to values from large sample sizes, because sampling variation will further inflate the variation between observed estimates of error of measurement when sample sizes are small (for example, by a factor of x/÷1.52 for samples of 10 subjects).

SAS mixed-modeling procedure.   The meta-analyses were performed with the mixed-modeling procedure (Proc Mixed) in the Statistical Analysis System (version 8.2, SAS Institute, Cary, NC). Key elements of the code of the Proc Mixed step, adapted from Yang (153), are shown below for the analysis of the four related blood measures: M_Hb,CO, V_RBC,Evans, V_RBC,CO, and V_RBC,51Cr. The statements for estimating the fixed effects and for back-transforming the fixed and random effects have been omitted:

proc mixed covtest cl alpha=0.1;

class ErrorID LabID Measure Treatment;

weight inverr;

model LnError=Measure*Treatment Measure*Log10Time/cl

ddfm = sat outp=pred;

random ErrorID LabID /s group=Measure;

parms(10)(10)(10)(10)(10)(10)(10)(10)(1)/hold=9;

Statistical inferences.   We made inferences about population (true) values of statistics via precision of estimation (using confidence limits) rather than via hypothesis testing (using P values and statistical significance). We also used 90% rather than 95% confidence limits to discourage attempts to reinterpret the limits in terms of statistical significance at the 5% level (135). Furthermore, 90% confidence limits represent adequate precision for making probabilistic inferences, because the probability that the true value is less than the lower confidence interval and more than the upper confidence interval is both only 0.05, which we interpreted as very unlikely. Inferences about the substantiveness of true differences between two errors of measurement were made by interpreting the confidence limits of the ratio in relation to the thresholds for substantial ratios (0.9 and 1.1). Ratios >1.1 or <0.9 were considered substantial on the basis of the impact of error on sample size: in controlled trials, sample size is inversely proportional to the square of the error of measurement (71), so an increase in error by a factor of 1.1 represents an increase in sample size of 1.21, or 21%. The difference between two errors was inferred to be clear, decisive, or conclusive in relation to one or other threshold, if the confidence interval for the ratio of the errors did not overlap the threshold. Thus one error would be clearly greater than another, if the entire confidence interval of their ratio was >1.1; one error would be possibly greater than another, if the confidence interval overlapped 1.1 but not 0.9; the difference in the errors would be clearly or decisively trivial, if the confidence interval was within or abutted 0.9 to 1.1; and the difference would be unclear or indecisive, if the confidence interval overlapped 0.9 and 1.1. Overlap of a threshold that was slight relative to the width of the confidence interval was characterized by terms such as "marginal" and "unlikely," whereas greater overlap was characterized by "possible" and "likely."

	ACKNOWLEDGMENTS

TOP ABSTRACT METHODS RESULTS DISCUSSION APPENDIX: DETAILS OF THE... ACKNOWLEDGMENTS REFERENCES

 
We thank all those who contributed de-identified raw data for us to meta-analyze. These include Clarence Alfrey, Michael Ashenden, David Branch, Kevin Davy, Birgit Friedmann, Christopher Gordon, Robert Grover, Katja Heinicke, Benjamin Levine, Jack Loepkky, Jack Reeves, Paul Robach, Philo Saunders, Walter Schmidt, Gary Slater, Ian Stewart, Jim Stray-Gundersen, and Darren Warburton.

A detailed summary table of all data sources used in the meta-analysis is available from the corresponding author on request.

	FOOTNOTES

 

Address for reprint requests and other correspondence: C. J. Gore, Australian Institute of Sport, P.O. Box 176, Belconnen, ACT 2616, Australia (e-mail: chris.gore{at}ausport.gov.au)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

	REFERENCES

TOP ABSTRACT METHODS RESULTS DISCUSSION APPENDIX: DETAILS OF THE... ACKNOWLEDGMENTS REFERENCES

 

1. Alfrey CP, Udden MM, Leach-Huntoon C, Driscoll T, and Pickett MH. Control of red blood cell mass in spaceflight. J Appl Physiol 81: 98–104, 1996.[Abstract/Free Full Text]
2. Arbab-Zadeh A, Zuckerman JH, Zhang R, Neimi H, and Levine BD. Endurance training increases left ventricular distensibility in humans (Abstract). Med Sci Sports Exerc 34: S7, 2002.
3. Asano M, Kaneoka K, Nomura T, Asano K, Sone H, Tsurumaru K, Yamashita K, Matsuo K, Suzuki H, and Okuda Y. Increase in serum vascular endothelial growth factor levels during altitude training. Acta Physiol Scand 162: 455–459, 1998.[CrossRef][Web of Science][Medline]
4. Ashenden MJ, Gore CJ, Burge CM, Clough ML, Bourdon PC, Dobson GP, and Hahn AG. Skin-prick blood samples are reliable for estimating Hb mass with the CO-dilution technique. Eur J Appl Physiol 79: 535–537, 1999.
5. Ashenden MJ, Gore CJ, Dobson GP, and Hahn AG. "Live high, train low" does not change the total haemoglobin mass of male endurance athletes sleeping at a simulated altitude of 3000 m for 23 nights. Eur J Appl Physiol 80: 479–484, 1999.[CrossRef][Web of Science]
6. Ashenden MJ, Gore CJ, Martin DT, Dobson GP, and Hahn AG. Effects of a 12-day "live high, train low" camp on reticulocyte production and haemoglobin mass in elite female road cyclists. Eur J Appl Physiol 80: 472–478, 1999.[CrossRef][Web of Science]
7. Bates DO and Curry FE. Vascular endothelial growth factor increases microvascular permeability via a Ca²⁺-dependent pathway. Am J Physiol Heart Circ Physiol 273: H687–H694, 1997.[Abstract/Free Full Text]
8. Bent-Hansen L. Initial plasma disappearance and distribution volume of [¹³¹I] albumin and [¹²⁵I] fibrinogen in man. Acta Physiol Scand 136: 455–461, 1989.[Web of Science][Medline]
9. Blackmore DJ. Distribution of HbCO in human erythrocytes following inhalation of CO. Nature 227: 386, 1970.[CrossRef][Medline]
10. Borisch S, Bärtsch P, and Friedmann B. Effects of strength endurance training in hypoxia on endurance capacity, blood volume on erythropoietin (Abstract). Int J Sports Med 23: S80, 2002.
11. Branch JD III, Pate RR, Bourque SP, Convertino VA, Durstine JL, and Ward DS. Effects of exercise mode on hematologic adaptations to endurance training in adult females. Aviat Space Environ Med 68: 788–794, 1997.[Medline]
12. Branch JD III, Pate RR, Bourque SP, Convertino VA, Durstine JL, and Ward DS. Exercise training and intensity does not alter vascular volume responses in women. Aviat Space Environ Med 70: 1070–1076, 1999.[Medline]
13. Brotherhood J, Brozovic B, and Pugh LGC. Haematological status of middle- and long-distance runners. Clin Sci Mol Med 48: 139–145, 1975.[Web of Science][Medline]
14. Bruce EN and Bruce MC. A multicompartment model of carboxyhemoglobin and carboxymyoglobin responses to inhalation of carbon monoxide. J Appl Physiol 95: 1235–1247, 2003.[Abstract/Free Full Text]
15. Burge CM and Skinner SL. Determination of hemoglobin mass and blood volume with CO: evaluation and application of a method. J Appl Physiol 79: 623–631, 1995.[Abstract/Free Full Text]
16. Chapman RF, Stray-Gundersen J, and Levine BD. Individual variation in response to altitude training. J Appl Physiol 85: 1448–1456, 1998.[Abstract/Free Full Text]
17. Chien S, Usami S, Simmons RL, McAllister FF, and Gregersen MI. Blood volume and age: repeated measurements on normal men after 17 years. J Appl Physiol 21: 583–588, 1966.[Free Full Text]
18. Christensen P, Eriksen B, and Hennebero SW. Precision of a new bedside method for estimation of the circulating blood volume. Acta Anaesthesiol Scand 37: 622–627, 1993.[Web of Science][Medline]
19. Clark BJ and Coburn RF. Mean myoglobin oxygen tension during exercise at maximal oxygen uptake. J Appl Physiol 39: 135–144, 1975.[Abstract/Free Full Text]
20. Connolly DT, Heuvelman DM, Nelson R, Olander JV, Eppley BL, Delfino JJ, Siegel NR, Leimgruber RM, and Feder J. Tumor vascular permeability factor stimulates endothelial cell growth and angiogenesis. J Clin Invest 84: 1470–1478, 1989.[Web of Science][Medline]
21. Crandall CG, Wilson TE, Shibasaki M, Cui J, and Levine BD. Prolonged head-down tilt exposure reduces maximal cutaneous vasodilator and sweating capacity in humans. J Appl Physiol 94: 2330–2336, 2003.[Abstract/Free Full Text]
22. D'Agostini G. Bayesian Reasoning in Data Analysis, A Critical Introduction. River Edge, NJ: World Scientific Publishing, 2003.
23. Dahms TE and Horvath SM. Rapid, accurate technique for determination of carbon monoxide in blood. Clin Chem 20: 533–537, 1974.[Abstract]
24. Davy KP and Seals DR. Total blood volume in healthy young and older men. J Appl Physiol 76: 2059–2062, 1994.[Abstract/Free Full Text]
25. Dill DB, Horvath SM, Dahms TE, Parker RE, and Lynch JR. Hemoconcentration at altitude. J Appl Physiol 27: 514–518, 1969.[Free Full Text]
26. Dor Y, Porat R, and Keshet E. Vascular endothelial growth factor and vascular adjustments to perturbations in oxygen homeostasis. Am J Physiol Cell Physiol 280: C1367–C1374, 2001.[Abstract/Free Full Text]
27. Ekblom B. Blood doping and erythropoietin. The effects of variation in hemoglobin concentration and other related factors on physical performance. Am J Sports Med 24: S40–S42, 1996.[Web of Science][Medline]
28. Ekblom B, Goldbarg AN, and Gullbring B. Response to exercise after blood loss and reinfusion. J Appl Physiol 33: 175–180, 1972.[Free Full Text]
29. El Sayed H, Goodall SR, and Hainsworth R. Re-evaluation of Evans blue dye dilution method of plasma volume measurement. Clin Lab Haematol 17: 189–194, 1995.[Web of Science][Medline]
30. Ernest D, Hartman NG, Deane CP, Belzberg AS, and Dodek PM. Reproducibility of plasma and extracellular fluid volume measurements in critically ill patients. J Nucl Med 33: 1468–1471, 1992.[Abstract/Free Full Text]
31. Fairbanks VF. Myeloproliferative disease: polycythemia vera: the packed cell volume and the curious logic of the red cell mass. Hematology 4: 381–395, 2000.[Medline]
32. Fairbanks VF, Klee GG, Wiseman GA, Hoyer JD, Tefferi A, Petitt RM, and Silverstein MN. Measurement of blood volume and red cell mass: re-examination of ⁵¹Cr and ¹²⁵I methods. Blood Cells Mol Dis 22: 169–186, 1996.[CrossRef][Web of Science][Medline]
33. Faura J and Reynafarje C. Uso de la metandrostenolona para acelerar la eritropoyesis en la exposicion a la altura. Arch Inst Biol Andina 3: 94–98, 1970.
34. Ferrebee JW, Leigh OC, and Berliner RW. Passage of the blue dye T-1824 from the blood stream into the lymph. Proc Soc Exp Biol Med 46: 549–553, 1941.[CrossRef]
35. Fischer CL, Johnson PC, and Berry CA. Red blood cell mass and plasma volume changes in manned space flight. JAMA 200: 579–583, 1967.[Abstract/Free Full Text]
36. Franco F, Morrow MJ, Zuckerman JH, Zhang R, Peshock RM, and Levine BD. Right ventricular enlargement precedes left ventricular enlargement during long-term endurance training (Abstract). Circulation 98: I-85, 1998.
37. Franco F, Peshock RM, Morrow MJ, Zuckerman JH, Zhang R, and Levine BD. Left ventricular hypertrophic response to long term endurance exercise (Abstract). Circulation 98: I-85, 1998.
38. Fraser CG, Wilkinson SP, Neville RG, Knox JD, King JF, and MacWalter RS. Biologic variation of common hematologic laboratory quantities in the elderly. Am J Clin Pathol 92: 465–470, 1989.[Web of Science][Medline]
39. Frese F, Menold E, Jost J, Jedamsky A, Bartsch P, and Friedmann B. Interindividuelle Variabilität im Erythropoetinanstieg und in der Zunahme des Gesamtkörperhämoglobins bei Höhentraining (Abstract). Dtsch Z Sportmed 54: S78, 2003.
40. Friedmann B, Jost J, Rating T, Weller E, Werle E, Eckardt KU, Bartsch P, and Mairbaurl H. Effects of iron supplementation on total body hemoglobin during endurance training at moderate altitude. Int J Sports Med 20: 78–85, 1999.[Web of Science][Medline]
41. Friedmann B, Weller E, Mairbaurl H, and Bartsch P. Effects of iron repletion on blood volume and performance capacity in young athletes. Med Sci Sports Exerc 33: 741–746, 2001.
42. Ge RL, Witkowski S, Zhang Y, Alfrey C, Sivieri M, Karlsen T, Resaland GK, Harber M, Stray-Gundersen J, and Levine BD. Determinants of erythropoietin release in response to short-term hypobaric hypoxia. J Appl Physiol 92: 2361–2367, 2002.[Abstract/Free Full Text]
43. Gibson JG and Evans WAJ. Clinical studies of the blood volume. I. Clinical application of a method employing the azo dye "Evans blue" and the spectrophotometer. J Clin Invest 16: 301–316, 1937.[Web of Science][Medline]
44. Gillen CM, Lee R, Mack GW, Tomaselli CM, Nishiyasu T, and Nadel ER. Plasma volume expansion in humans after a single intense exercise protocol. J Appl Physiol 71: 1914–1920, 1991.[Abstract/Free Full Text]
45. Gledhill N, Warburton D, and Jamnik V. Haemoglobin, blood volume, cardiac function, and aerobic power. Can J Appl Physiol 24: 54–65, 1999.[Web of Science][Medline]
46. Godin G and Shephard RJ. On the course of carbon monoxide uptake and release. Respiration 29: 317–329, 1972.[Web of Science][Medline]
47. Gordon CJ, Fogarty AL, Greenleaf JE, Taylor NA, and Stocks JM. Direct and indirect methods for determining plasma volume during thermoneutral and cold-water immersion. Eur J Appl Physiol 89: 471–474, 2003.[Web of Science][Medline]
48. Gore C, Craig N, Hahn A, Rice A, Bourdon P, Lawrence S, Walsh C, Stanef T, Barnes P, Parisotto R, Martin D, and Pyne D. Altitude training at 2690m does not increase total haemoglobin mass or sea level O_{2 max} in world champion track cyclists. J Sci Med Sport 1: 156–170, 1998.[CrossRef][Medline]
49. Gore CJ, Hahn AG, Burge CM, and Telford RD. O_{2 max} and haemoglobin mass of trained athletes during high intensity training. Int J Sports Med 18: 477–482, 1997.[Web of Science][Medline]
50. Gore CJ, Stray-Gundersen J, Rodríguez FA, Truijens MJ, Townsend NE, and Levine BD. Comparison of blood volume via CO re-breathing and Evans blue dye (Abstract). Med Sci Sports Exerc 36: S336, 2004.
51. Gray SJ and Sterling K. Determination of circulating red cell volume by radioactive chromium. Science 112: 179–180, 1950.[Free Full Text]
52. Greenleaf JE, Convertino VA, and Mangseth GR. Plasma volume during stress in man: osmolality and red cell volume. J Appl Physiol 47: 1031–1038, 1979.[Abstract/Free Full Text]
53. Greenleaf JE, Van Beaumont W, Brock PJ, Morse JT, and Mangseth GR. Plasma volume and electrolyte shifts with heavy exercise in sitting and supine positions. Am J Physiol Regul Integr Comp Physiol 236: R206–R214, 1979.[Abstract/Free Full Text]
54. Gregersen MI and Rawson RA. Blood volume. Physiol Rev 39: 511–518, 1959.[Medline]
55. Grover RF, Selland MA, McCullough RG, Dahms TE, Wolfel EE, Butterfield GE, Reeves JT, and Greenleaf JE. -Adrenergic blockade does not prevent polycythemia or decrease in plasma volume in men at 4300 m altitude. Eur J Appl Physiol 77: 264–270, 1998.[CrossRef][Web of Science]
56. Gurland J and Tripathi RC. A simple approximation for unbiased estimation of the standard deviation. American Statistician 25: 30–32, 1971.
57. Haldane J and Smith JL. The absorption of oxygen by the lungs. J Physiol 22: 231–258, 1897.[Free Full Text]
58. Haldane J and Smith JL. The mass and oxygen capacity of the blood in man. J Physiol 25: 331–343, 1899.
59. Hannon JP, Chinn KSK, and Shields JL. Effects of acute high-altitude exposure on body fluids. Fed Proc 28: 1178–1184, 1969.[Web of Science][Medline]
60. Hansen JM, Kanstrup IL, Richalet JP, and Olsen NV. High altitude-induced albuminuria in normal man is enhanced by infusion of low-dose dopamine. Scand J Clin Lab Invest 56: 367–372, 1996.[Web of Science][Medline]
61. Hansen JM, Olsen NV, Feldt-Rasmussen B, Kanstrup IL, Déchaux M, Dubray C, and Richalet JP. Albuminuria and overall capillary permeability of albumin in acute altitude hypoxia. J Appl Physiol 76: 1922–1927, 1994.[Abstract/Free Full Text]
62. Haurie C, Dale DC, and Mackey MC. Cyclical neutropenia and other periodic hematological disorders: a review of mechanisms and mathematical models. Blood 92: 2629–2640, 1998.[Abstract/Free Full Text]
63. Heinicke K, Heinicke I, Schmidt W, and Wolfarth B. A three-week traditional altitude training increases hemoglobin mass and red cell volume in elite biathlon athletes. Int J Sports Med 26: 350–355, 2005.
64. Heinicke K, Prommer N, Cajigal J, Viola T, Behn C, and Schmidt W. Long-term exposure to intermittent hypoxia results in increased hemoglobin mass, reduced plasma volume, and elevated erythropoietin plasma levels in man. Eur J Appl Physiol 88: 535–543, 2003.[Web of Science][Medline]
65. Heinicke K, Wolfarth B, Winchenbach P, Biermann B, Schmid A, Huber G, Friedmann B, and Schmidt W. Blood volume and hemoglobin mass in elite athletes of different disciplines. Int J Sports Med 22: 504–512, 2001.[CrossRef][Web of Science][Medline]
66. Hopkins WG. Applications of reliability [Online]. Sport Science. http://sportsci.org/resource/stats/relyappl.html [2000].
67. Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 30: 1–15, 2000.[CrossRef][Web of Science][Medline]
68. Hopkins WG. A spreadsheet for analysis of straightforward controlled trials [Online]. Sport Science. http://www.sportsci.org/jour/03/wghtrials.htm [2003].
69. Hopkins WG. Clinical significance and decisiveness [Online]. Sport Science. http://www.sportsci.org/jour/04/inbrief.htm#clinical [2004].
70. Hopkins WG. How to interpret changes in an athletic performance test [Online]. Sport Science. http://www.sportsci.org/jour/04/wghtests.htm [2004].
71. Hopkins WG and Hewson DJ. Variability of competitive performance of distance runners. Med Sci Sports Exerc 33: 1588–1592, 2001.
72. Hopkins WG, Schabort EJ, and Hawley JA. Reliability of power in physical performance tests. Sports Med 31: 211–234, 2001.[CrossRef][Web of Science][Medline]
73. Hopper J Jr, Tabor H, and Winkler AW. Simultaneous measurements of the blood volume in man and dog by means of Evans Blue dye, T1824, and by means of carbon monoxide I normal subjects. J Clin Invest 23: 628–635, 1944.[Medline]
74. International Committee for Standardization in Haematology. Standard techniques for the measurement of red-cell and plasma volume. A report by the International Committee for Standardization in Hematology (ICSH): Panel on Diagnostic Applications of Radioisotopes in Haematology. Br J Haematol 25: 801–814, 1973.[Web of Science][Medline]
75. International Committee for Standardization in Haematology. Recommended methods for measurement of red-cell and plasma volume: International Committee for Standardization in Haematology. J Nucl Med 21: 793–800, 1980.[Free Full Text]
76. International Committee for Standardization in Haematology. Recommendations for reference method for haemoglobinometry in human blood (ICSH standard 1986) and specifications for international haemiglobincyanide reference preparation (3rd edition) International Committee for Standardization in Haematology; Expert Panel on Haemoglobinometry. Clin Lab Haematol 9: 73–79, 1987.[Web of Science][Medline]
77. Iwasaki K, Zhang R, Perhonen MA, Zuckerman JH, and Levine BD. Reduced baroreflex control of heart period after bed rest is normalized by acute plasma volume restoration. Am J Physiol Regul Integr Comp Physiol 287: R1256–R1262, 2004.[Abstract/Free Full Text]
78. Iwasaki K, Zhang R, Zuckerman JH, and Levine BD. Dose-response relationship of the cardiovascular adaptation to endurance training in healthy adults: how much training for what benefit? J Appl Physiol 95: 1575–1583, 2003.[Abstract/Free Full Text]
79. Johnson PC, Driscoll TB, and Fischer CL. Blood volume changes in divers of Tektite I. Aerospace Med 42: 423–426, 1971.[Medline]
80. Jung RC, Dill DB, Horton R, and Horvath SM. Effects of age on plasma aldosterone levels and hemoconcentration at altitude. J Appl Physiol 31: 593–597, 1971.[Medline]
81. Kaner RJ and Crystal RG. Pathogenesis of high altitude pulmonary edema: does alveolar epithelial lining fluid vascular endothelial growth factor exacerbate capillary leak? High Alt Med Biol 5: 399–409, 2004.[CrossRef][Medline]
82. Kleger GR, Bärtsch P, Vock P, Heilig B, Roberts LJ II, and Ballmer PE. Evidence against an increase in capillary permeability in subjects exposed to high altitude. J Appl Physiol 81: 1917–1923, 1996.[Abstract/Free Full Text]
83. Lange RD, Jones JB, and Johnson PC Jr. Comparative aspects of hematological responses in animal and human models in simulations of weightlessness and space flight. Physiologist 30: S113–S116, 1987.[Medline]
84. Lawson HC. The volume of blood–a critical examination of methods for its measurement. In: Handbook of Physiology. Circulation. Washington, DC: Am. Physiol. Soc., 1962, sect. 2, vol. I, chapt. 3, p. 23–49.
85. LeVeen HH and Fishman WH. Combination of Evans Blue with plasma protein: its significance in capillary permeability studies, blood dye disappearance curves, and its use as a protein tag. Am J Physiol 151: 26–33, 1947.[Free Full Text]
86. Levine BD. Intermittent hypoxic training: fact and fancy. High Alt Med Biol 3: 177–193, 2002.[CrossRef][Medline]
87. Levine BD and Stray-Gundersen J. A practical approach to altitude training: where to live and train for optimal performance enhancement. Int J Sports Med 13: S209–S212, 1992.[CrossRef][Web of Science][Medline]
88. Levine BD and Stray-Gundersen J. "Living high-training low": effect of moderate-altitude acclimatization with low altitude training on performance. J Appl Physiol 83: 102–112, 1997.[Abstract/Free Full Text]
89. Levine BD, Zuckerman JH, Morrow MJ, Franco F, and Zhang R. Gender differences in the cardiac adaptation to endurance training (Abstract). Circulation 98: I-86, 1998.
90. Levine BD, Zuckerman JH, and Pawelczyk JA. Cardiac atrophy after bed-rest deconditioning: a nonneural mechanism for orthostatic intolerance. Circulation 96: 517–525, 1997.[Abstract/Free Full Text]
91. Levine BD, Zuckerman JH, Zhang R, and Morrow M. Prolonged intensive endurance training improves ventricular performance via the Frank-Starling mechanism (Abstract). Med Sci Sports Exerc 30: S27, 1998.
92. Lewis DM, Bradwell AR, Shore AC, Beaman M, and Tooke JE. Capillary filtration coefficient and urinary albumin leak at altitude. Eur J Clin Invest 27: 64–68, 1997.[CrossRef][Web of Science][Medline]
93. Loeppky JA, Luther DK, Maes D, Riboni K, Hinghofer-Szalkay H, Charlton GA, and Icenogle MV. Plasma volume by Evans blue: effects of eating and comparison with other methods at altitude. Aviat Space Environ Med 73: 902–906, 2002.[Medline]
94. Loeppky JA, Scotto P, Charlton GC, Gates L, Icenogle M, and Roach RC. Ventilation is greater in women than men, but the increase during acute altitude hypoxia is the same. Respir Physiol 125: 225–237, 2001.[CrossRef][Web of Science][Medline]
95. Luomanmäki K and Coburn RF. Effects of metabolism and distribution of carbon monoxide on blood and body stores. Am J Physiol 217: 354–363, 1969.[Free Full Text]
96. Mather K, Bowler RG, Crooke AC, and Morris CJOR. The precision of plasma volume determinations by the Evans blue method. Br J Exp Pathol 28: 12–24, 1947.
97. Maw GJ, Mackenzie IL, and Taylor NA. Human body-fluid distribution during exercise in hot, temperate and cool environments. Acta Physiol Scand 163: 297–304, 1998.[CrossRef][Web of Science][Medline]
98. Myhre LG, Brown DK, Hall FG, and Dill DB. The use of carbon monoxide and T-1824 for determining blood volume. Clin Chem 14: 1197–1205, 1968.[Abstract]
99. Myhre LG, Dill DB, Hall FG, and Brown DK. Blood volume changes during three-week residence at high altitude. Clin Chem 16: 7–14, 1970.[Abstract]
100. Nomof N, Hopper J, Brown E, Scott K, and Wennesland R. Simultaneous determinations of the total volume of red blood cells by use of carbon monoxide and chromium⁵¹ in healthy and diseased subjects. J Clin Invest 33: 1382–1387, 1954.[Medline]
101. Palmer D, Perhonen M, Zuckerman J, Witkowski S, Zhang R, and Levine BD. Prolonged exercise training during head-down tilt bedrest preserves upright exercise capacity (Abstract). Med Sci Sports Exerc 33: S299, 2001.
102. Palmer D, Perhonen M, Zuckerman JH, Witkowski S, Zhang R, and Levine BD. Prolonged exercise training during head-down tilt bedrest coupled with Dextran infusion prevents orthostatic intolerance (Abstract). Med Sci Sports Exerc 34: S112, 2002.
103. Parisotto R, Gore CJ, Emslie KR, Ashenden MJ, Brugnara C, Howe C, Martin DT, Trout GJ, and Hahn AG. A novel method utilising markers of altered erythropoiesis for the detection of recombinant human erythropoietin abuse in athletes. Haematologica 85: 564–572, 2000.[Abstract/Free Full Text]
104. Pawelczyk JA, Zuckerman JH, Blomqvist CG, and Levine BD. Regulation of muscle sympathetic nerve activity after bed rest deconditioning. Am J Physiol Heart Circ Physiol 280: H2230–H2239, 2001.[Abstract/Free Full Text]
105. Pearson TC. Evaluation of diagnostic criteria in polycythemia vera. Semin Hematol 38: 21–24, 2001.[Web of Science][Medline]
106. Pearson TC, Guthrie DL, Simpson J, Chinn S, Barosi G, Ferrant A, Lewis SM, and Najean Y. Interpretation of measured red cell mass and plasma volume in adults: Expert Panel on Radionuclides of the International Council for Standardization in Haematology. Br J Haematol 89: 748–756, 1995.[Web of Science][Medline]
107. Perhonen MA, Zuckerman JH, Hinojosa JR, Zhang R, Iwasaki K, and Levine BD. Exercise training reverses cardiac atrophy during head down tilt bed rest (Abstract). Med Sci Sports Exerc 93: S53, 2000.
108. Perhonen MA, Zuckerman JH, and Levine BD. Deterioration of left ventricular chamber performance after bed rest: "cardiovascular deconditioning" or hypovolemia? Circulation 103: 1851–1857, 2001.[Abstract/Free Full Text]
109. Petersen PH, Fraser CG, Jorgensen L, Brandslund I, Stahl M, Gowans E, Libeer JC, and Ricos C. Combination of analytical quality specifications based on biological within- and between-subject variation. Ann Clin Biochem 39: 543–550, 2002.[CrossRef][Web of Science][Medline]
110. Petersen PH, Stockl D, Westgard JO, Sandberg S, Linnet K, and Thienpont L. Models for combining random and systematic errors. Assumptions and consequences for different models. Clin Chem Lab Med 39: 589–595, 2001.[CrossRef][Web of Science][Medline]
111. Poulsen TD, Klausen T, Richalet JP, Kanstrup IL, Fogh-Andersen N, and Olsen NV. Plasma volume in acute hypoxia: comparison of a carbon monoxide rebreathing method and dye dilution with Evans' blue. Eur J Appl Physiol 77: 457–461, 1998.[CrossRef][Web of Science]
112. Rawson RA. The binding of T-1824 and structurally related diazo dyes by the plasma proteins. Am J Physiol 138: 708–717, 1943.[Free Full Text]
113. Reeves JT, Zamudio S, Dahms TE, Asmus I, Braun B, Butterfield GE, McCullough RG, Muza SR, Rock PB, and Moore LG. Erythropoiesis in women during 11 days at 4,300 m is not affected by menstrual cycle phase. J Appl Physiol 91: 2579–2586, 2001.[Abstract/Free Full Text]
114. Reilly WA, French RM, Lau FYK, Scott KG, and White WE. Whole blood volume determined by radiochromium-tagged red cells. Comparative studies on normal and congestive heart failure patients. Circulation 9: 571–580, 1954.[Web of Science][Medline]
115. Remington JW and Baker CH. Evaluation of blood volume measurement techniques. Circ Res 9: 60–68, 1961.[Abstract/Free Full Text]
116. Richardson RS, Noyszewski EA, Saltin B, and Gonzalez-Alonso J. Effect of mild carboxy-hemoglobin on exercising skeletal muscle: intravascular and intracellular evidence. Am J Physiol Regul Integr Comp Physiol 283: R1131–R1139, 2002.[Abstract/Free Full Text]
117. Robach P, Brugniaux JV, Schmitt L, Nicolet G, Fouillot JP, Lasne F, Moutereau S, Olsen NV, and Richalet JP. Living High-Training Low: Effect On Red Cell Mass And Aerobic Performance In Elite Middle-Distance Runners (Abstract). Congress of the European College of Sports Sciences Proceedings, 2004, p. 11–12.
118. Robach P, Dechaux M, Jarrot S, Vaysse J, Schneider JC, Mason NP, Herry JP, Gardette B, and Richalet JP. Operation Everest III: role of plasma volume expansion on O_{2 max} during prolonged high-altitude exposure. J Appl Physiol 89: 29–37, 2000.[Abstract/Free Full Text]
119. Robach P, Lafforgue E, Olsen NV, Dechaux M, Fouqueray B, Westerterp-Plantenga M, Westerterp K, and Richalet JP. Recovery of plasma volume after 1 week of exposure at 4,350 m. Pflügers Arch 444: 821–828, 2002.[CrossRef][Web of Science][Medline]
120. Robach P, Schmitt L, Roels B, Millet G, Brugniaux JV, Nicolet G, Duvallet A, Fouillot JP, Mouteréau S, Lasne F, Hellard P, Olsen NV, and Richalet JP. Vivre en Haut–S'entraîner en Bas: Effect Sur le Volume de Globules Rouges et al Performance Aérobie Chez L'athlète de Haut Niveau (Abstract). XII Congrès de l'ACAPS, 2003, p. 146–147.
121. Satterthwaite FW. An approximate distribution of estimates of variance components. Biometrics 2: 110–114, 1946.[CrossRef][Web of Science]
122. Saunders PU, Telford RD, Pyne DB, Cunningham RB, Gore CJ, Hahn AG, and Hawley JA. Improved running economy in elite runners after 20 days of moderate simulated altitude exposure. J Appl Physiol 96: 931–937, 2004.[Abstract/Free Full Text]
123. Sawka MN, Convertino VA, Eichner ER, Schnieder SM, and Young AJ. Blood volume: importance and adaptations to exercise training, environmental stresses, and trauma/sickness. Med Sci Sports Exerc 32: 332–348, 2000.
124. Sawka MN and Coyle EF. Influence of body water and blood volume on thermoregulation and exercise performance in heat. Exerc Sport Sci Rev 27: 167–218, 1999.[Medline]
125. Sawka MN, Young AJ, Muza SR, Gonzalez RR, and Pandolf KB. Erythrocyte reinfusion and maximal aerobic power. An examination of modifying factors. JAMA 257: 1496–1499, 1987.[Abstract/Free Full Text]
126. Sawka MN, Young AJ, Pandolf KB, Dennis RC, and Valeri CR. Erythrocyte, plasma, and blood volume of healthy young men. Med Sci Sports Exerc 24: 447–453, 1992.
127. Schmidt W, Heinicke K, Rojas J, Manuel GJ, Serrato M, Mora M, Wolfarth B, Schmid A, and Keul J. Blood volume and hemoglobin mass in endurance athletes from moderate altitude. Med Sci Sports Exerc 34: 1934–1940, 2002.
128. Sear H, Allen TH, and Gregersen MI. Simultaneous measurement in dogs of plasma volume with I¹³¹ human albumin and T-1824 with comparisons of their long term disappearance from the plasma. Am J Physiol 175: 240–242, 1953.[Free Full Text]
129. Semple RE, Thomsen AET, and Ball AJ. Description and evaluation of a dextran-dilution technique for the determination of plasma volume in the dog and man. Clin Sci (Colch) 17: 511–518, 1958.[Medline]
130. Senger DR, Galli SJ, Dvorak AM, Perruzzi CA, Harvey VS, and Dvorak HF. Tumor cells secrete a vascular permeability factor that promotes accumulation of ascites fluid. Science 219: 983–985, 1983.[Abstract/Free Full Text]
131. Senger DR, Van de Water L, Brown LF, Nagy JA, Yeo KT, Yeo TK, Berse B, Jackman RW, Dvorak AM, and Dvorak HF. Vascular permeability factor (VPF, VEGF) in tumor biology. Cancer Metastasis Rev 12: 303–324, 1993.[CrossRef][Web of Science][Medline]
132. Shibasaki M, Wilson TE, Cui J, Levine BD, and Crandall CG. Exercise throughout 6 degrees head-down tilt bed rest preserves thermoregulatory responses. J Appl Physiol 95: 1817–1823, 2003.[Abstract/Free Full Text]
133. Sjöstrand T. Blood volume. In: Handbook of Physiology. Circulation. Washington, DC: Am. Physiol. Soc., 1962, sect. 2, vol. I, chapt. 4, p. 51–62.
134. Stachenfeld NS, Mack GW, DiPietro L, Morocco TS, Jozsi AC, and Nadel ER. Regulation of blood volume during training in post-menopausal women. Med Sci Sports Exerc 30: 92–98, 1998.
135. Sterne JA and Davey Smith G. Sifting the evidence—what's wrong with significance tests? Br Med J 322: 226–231, 2001.[Free Full Text]
136. Stevenson ET, Davy KP, and Seals DR. Maximal aerobic capacity and total blood volume in highly trained middle-aged and older female endurance athletes. J Appl Physiol 77: 1691–1696, 1994.[Abstract/Free Full Text]
137. Stewart IB, Warburton DE, Hodges AN, Lyster DM, and McKenzie DC. Cardiovascular and splenic responses to exercise in humans. J Appl Physiol 94: 1619–1626, 2003.[Abstract/Free Full Text]
138. Surks MI, Chinn KS, and Matoush LR. Alterations in body composition in man after acute exposure to high altitude. J Appl Physiol 21: 1741–1746, 1966.[Free Full Text]
139. Tavassoli M. Anemia of spaceflight. Blood 60: 1059–1067, 1982.[Abstract/Free Full Text]
140. Thirup P. Haematocrit: within-subject and seasonal variation. Sports Med 33: 231–243, 2003.[CrossRef][Web of Science][Medline]
141. Udden MM, Driscoll TB, Pickett MH, Leach-Huntoon CS, and Alfrey CP. Decreased production of red blood cells in human subjects exposed to microgravity. J Lab Clin Med 125: 442–449, 1995.[Web of Science][Medline]
142. Veillon C, Patterson KY, Nagey DA, and Tehan AM. Measurement of blood volume with an enriched stable isotope of chromium (⁵³Cr) and isotope dilution by combined gas chromatography-mass spectrometry. Clin Chem 40: 71–73, 1994.[Abstract/Free Full Text]
143. Von Porat BTD. Blood volume determinations with the Evans Blue dye method. Acta Med Scand 256: 1–108, 1951.
144. Walser M and Duffy B. Body fluids in hypertension and mild heart failure. JAMA 160: 858–864, 1956.[Abstract/Free Full Text]
145. Wang W, Dentler WL, and Borchardt RT. VEGF increases BMEC monolayer permeability by affecting occludin expression and tight junction assembly. Am J Physiol Heart Circ Physiol 280: H434–H440, 2001.[Abstract/Free Full Text]
146. Warburton DE, Haykowsky MJ, Quinney HA, Blackmore D, Teo KK, Taylor DA, McGavock J, and Humen DP. Blood volume expansion and cardiorespiratory function: effects of training modality. Med Sci Sports Exerc 36: 991–1000, 2004.
147. Wenger RH. Cellular adaptation to hypoxia: O₂-sensing protein hydroxylases, hypoxia-inducible transcription factors, and O₂-regulated gene expression. FASEB J 16: 1151–1162, 2002.[Abstract/Free Full Text]
148. Wennesland R, Brown E, Hopper J Jr, Scott KG, Hodges JL Jr, and Bradley B. Experiences with the radiochromium method for determination of red cell volume. Scand J Clin Lab Invest 14: 355–367, 1962.[Web of Science][Medline]
149. Wilson TE, Shibasaki M, Cui J, Levine BD, and Crandall CG. Effect of head-down tilt bed rest on human cutaneous vasoconstrictor responses to exogenous norepinephrine (Abstract). Med Sci Sports Exerc 34: S218, 2002.
150. Witkowski S, Karlsen T, Resaland G, Sivieri M, Yates R, Harber M, Ge R, Stray-Gundersen J, and Levine BD. Optimal altitude for "living high-training low" (Abstract). Med Sci Sports Exerc 33: S292, 2001.
151. Wolfel EE, Groves BM, Brooks GA, Butterfield GE, Mazzeo RS, Moore LG, Sutton JR, Bender PR, Dahms TE, McCullough RE, McCullough RG, Huang S, Sun S, Grover RF, Hultgren HN, and Reeves JT. Oxygen transport during steady-state submaximal exercise in chronic hypoxia. J Appl Physiol 70: 1129–1136, 1991.[Abstract/Free Full Text]
152. Wood JG, Johnson JS, Mattioli LF, and Gonzalez NC. Systemic hypoxia increases leukocyte emigration and vascular permeability in conscious rats. J Appl Physiol 89: 1561–1568, 2000.[Abstract/Free Full Text]
153. Yang M. A review of random effects modelling in SAS (release 8.2) [Online]. Centre for Multilevel Modelling. Institute of Education, Univ. of London. http://multilevel.ioe.ac.uk/softrev/reviewsas.pdf [2003].

This article has been cited by other articles:

				P. Robach, S. Recalcati, D. Girelli, C. Gelfi, N. J. Aachmann-Andersen, J. J. Thomsen, A. M. Norgaard, A. Alberghini, N. Campostrini, A. Castagna, et al. Alterations of systemic and muscle iron metabolism in human subjects treated with low-dose recombinant erythropoietin Blood, June 25, 2009; 113(26): 6707 - 6715. [Abstract] [Full Text] [PDF]

				A. Eastwood, W. G. Hopkins, P. C. Bourdon, R. T. Withers, and C. J. Gore Stability of hemoglobin mass over 100 days in active men J Appl Physiol, April 1, 2008; 104(4): 982 - 985. [Abstract] [Full Text] [PDF]

				M. J. Wilson, M. Lopez, M. Vargas, C. Julian, W. Tellez, A. Rodriguez, A. Bigham, J. F. Armaza, S. Niermeyer, M. Shriver, et al. Greater uterine artery blood flow during pregnancy in multigenerational (Andean) than shorter-term (European) high-altitude residents Am J Physiol Regulatory Integrative Comp Physiol, September 1, 2007; 293(3): R1313 - R1324. [Abstract] [Full Text] [PDF]

				M. Vargas, E. Vargas, C. G. Julian, J. F. Armaza, A. Rodriguez, W. Tellez, S. Niermeyer, M. Wilson, E. Parra, M. Shriver, et al. Determinants of blood oxygenation during pregnancy in Andean and European residents of high altitude Am J Physiol Regulatory Integrative Comp Physiol, September 1, 2007; 293(3): R1303 - R1312. [Abstract] [Full Text] [PDF]

				C. J. Gore, F. A. Rodriguez, M. J. Truijens, N. E. Townsend, J. Stray-Gundersen, and B. D. Levine Increased serum erythropoietin but not red cell production after 4 wk of intermittent hypobaric hypoxia (4,000-5,500 m) J Appl Physiol, November 1, 2006; 101(5): 1386 - 1393. [Abstract] [Full Text] [PDF]

				J. P. Wehrlin, P. Zuest, J. Hallen, and B. Marti Live high-train low for 24 days increases hemoglobin mass and red cell volume in elite endurance athletes J Appl Physiol, June 1, 2006; 100(6): 1938 - 1945. [Abstract] [Full Text] [PDF]

				S. Keslacy, R. S. Mazzeo, D. A. Giussani, A. S. Thakor, G. Insalaco, M. R. Bonsignore, F. A. Rodriguez, K. S. Mark, C. Reboul, S. Tanguy, et al. Commentary on Point-Counterpoint J Appl Physiol, January 1, 2006; 100(1): 363 - 363. [Full Text] [PDF]

This Article Abstract Full Text (PDF) Free All Versions of this Article: 99/5/1745    most recent 00505.2005v1 Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (22) Citing Articles via Google Scholar Google Scholar Articles by Gore, C. J. Articles by Burge, C. M. Search for Related Content PubMed PubMed Citation Articles by Gore, C. J. Articles by Burge, C. M.