Clinical utility of standard base excess in the diagnosis and interpretation of metabolic acidosis in critically ill patients

Abstract

The aims of this study were to determine whether standard base excess (SBE) is a useful diagnostic tool for metabolic acidosis, whether metabolic acidosis is clinically relevant in daily evaluation of critically ill patients, and to identify the most robust acid-base determinants of SBE. Thirty-one critically ill patients were enrolled. Arterial blood samples were drawn at admission and 24 h later. SBE, as calculated by Van Slyke's (SBE VS) or Wooten's (SBE W) equations, accurately diagnosed metabolic acidosis (AUC = 0.867, 95%CI = 0.690-1.043 and AUC = 0.817, 95%CI = 0.634-0.999, respectively). SBE VS was weakly correlated with total SOFA (r = -0.454, P < 0.001) and was similar to SBE W (r = -0.482, P < 0.001). All acid-base variables were categorized as SBE VS <-2 mEq/L or SBE VS <-5 mEq/L. SBE VS <-2 mEq/L was better able to identify strong ion gap acidosis than SBE VS <-5 mEq/L; there were no significant differences regarding other variables. To demonstrate unmeasured anions, anion gap (AG) corrected for albumin (AG A) was superior to AG corrected for albumin and phosphate (AG A+P) when strong ion gap was used as the standard method. Mathematical modeling showed that albumin level, apparent strong ion difference, AG A, and lactate concentration explained SBE VS variations with an R² = 0.954. SBE VS with a cut-off value of <-2 mEq/L was the best tool to diagnose clinically relevant metabolic acidosis. To analyze the components of SBE VS shifts at the bedside, AG A, apparent strong ion difference, albumin level, and lactate concentration are easily measurable variables that best represent the partitioning of acid-base derangements.

Metabolic acidosis; Clinical outcome; Strong ion gap; Standard base excess; Van Slyke equation; Sequential organ failure assessment

Braz J Med Biol Res, March 2008, Volume 41(3) 241-249

Clinical utility of standard base excess in the diagnosis and interpretation of metabolic acidosis in critically ill patients

M. Park¹, L.U. Taniguchi¹, D.T. Noritomi¹, A.B. Libório², A.T. Maciel¹ and L.M. Cruz-Neto¹

¹Departamento de Emergência, Unidade de Terapia Intensiva, ²Departamento de Nefrologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brasil

References ^{Correspondence and Footnotes}

Abstract

The aims of this study were to determine whether standard base excess (SBE) is a useful diagnostic tool for metabolic acidosis, whether metabolic acidosis is clinically relevant in daily evaluation of critically ill patients, and to identify the most robust acid-base determinants of SBE. Thirty-one critically ill patients were enrolled. Arterial blood samples were drawn at admission and 24 h later. SBE, as calculated by Van Slyke's (SBE_VS) or Wooten's (SBE_W) equations, accurately diagnosed metabolic acidosis (AUC = 0.867, 95%CI = 0.690-1.043 and AUC = 0.817, 95%CI = 0.634-0.999, respectively). SBE_VS was weakly correlated with total SOFA (r = -0.454, P < 0.001) and was similar to SBE_W (r = -0.482, P < 0.001). All acid-base variables were categorized as SBE_VS <-2 mEq/L or SBE_VS <-5 mEq/L. SBE_VS <-2 mEq/L was better able to identify strong ion gap acidosis than SBE_VS <-5 mEq/L; there were no significant differences regarding other variables. To demonstrate unmeasured anions, anion gap (AG) corrected for albumin (AG_A) was superior to AG corrected for albumin and phosphate (AG_A+P) when strong ion gap was used as the standard method. Mathematical modeling showed that albumin level, apparent strong ion difference, AG_A, and lactate concentration explained SBE_VS variations with an R² = 0.954. SBE_VS with a cut-off value of <-2 mEq/L was the best tool to diagnose clinically relevant metabolic acidosis. To analyze the components of SBE_VS shifts at the bedside, AG_A, apparent strong ion difference, albumin level, and lactate concentration are easily measurable variables that best represent the partitioning of acid-base derangements.

Key words: Metabolic acidosis; Clinical outcome; Strong ion gap; Standard base excess; Van Slyke equation; Sequential organ failure assessment

Introduction

Various contemporary studies of acid-base physiology that quantify previously described acid-base derangements have been published recently (1,2). These studies have refined our understanding of the basic mechanisms that control blood pH in health and disease, and have described the epidemiology and clinical significance of acid-base imbalances in more detail than was previously possible (3-5). In the current literature, it has been established with mathematical calculation that the modern (quantitative) and traditional (descriptive) approaches are easily interchangeable at a fundamental level. This interchange has resulted in clarification of the limitations of each approach and has revealed how a combinatorial approach can be used to achieve a more complete understanding of clinical acid-base physiology (3,6).

At the bedside of a critically ill patient, it is important to note that there appears to be a difference in physiologic variables and outcomes between patients with respiratory acidosis and those with metabolic acidosis, leading some investigators to hypothesize that it is the cause of acidosis, rather than the acidosis per se, that drives the association with clinical outcomes (6). When taking metabolic acidosis into account, there are many possible mechanisms involved, and it seems that there is a different reflex on the outcome based on the mechanism, again suggesting the concept that the cause of acidosis is more important than the acidosis per se (7-10).

Standard base excess (SBE) has been used to identify metabolic acidosis (4) and to determine the prognosis of critically ill patients at the time of admission to the intensive care unit (8,9,11). The SBE is therefore a useful tool at the bedside, despite the fact that many complex metabolic disturbances cannot be disclosed by the SBE alone (4). Based on the current literature, there are two different methodologies with which to calculate the SBE, and there are two different cut-offs of SBE (<-2 mEq/L (6,7) or <-5 mEq/L (3)) that are used to discriminate metabolic acidosis. However, there is no concise definition of these issues.

The severity of disease in critically ill patients can be quantified by the number of organ failures added to the severity of dysfunction of each organ. The sequential organ failure assessment (SOFA) score was created to evaluate organ failure, focusing on morbidity instead of mortality (12). The SOFA score was developed through a consensus process (13) and subsequently validated in a larger population of 1449 critically ill patients (14). The total SOFA is composed of scores from six organ systems (respiratory, cardiovascular, hepatic, coagulation, renal, and neurologic), graded from 0 to 4 according to the degree of dysfunction/failure (15). The SOFA score was initially described in septic patients (13). During the last decade, however, SOFA scoring has been adapted to other situations (14,16). The progressive elevation of the total SOFA score is a marker of poor outcome in the daily evaluation of critically ill patients (17), and by 48 h after admission, the highest SOFA score is a clinically meaningful outcome marker (18). The total SOFA score is thus a reliable tool to quantify on a daily basis the severity of disease in critically ill patients (12).

The aims of this study were to determine whether the SBE was a useful tool to evaluate metabolic acidosis and whether it was clinically relevant in the daily evaluation of critically ill patients. In order to show the clinical relevancy of daily SBE evaluation, the total SOFA score was used as a tool to quantify the severity of disease of critically ill patients. In addition, we ascertained the best methodology by which to calculate the SBE, the best value of SBE by which to define metabolic acidosis, and identified the best metabolic determinants of SBE, according to the traditional and modern acid-base concepts.

Material and Methods

From February to March 2004, 31 patients consecutively admitted to the 7 beds of the intensive care unit of Hospital das Clínicas, a tertiary care teaching hospital in Brazil, were enrolled in the study. After approval of the protocol, written informed consent was obtained from the patient or next-of-kin as per the hospital's Ethics Committee recommendations. Arterial blood samples were drawn from the arterial line both at the time of admission and 24 h later. Data such as age, acute physiology and chronic health evaluation (APACHE) II score, total SOFA score, weight, height, diagnosis, vasopressor and/or inotropic use, fluid management, renal replacement requirements, mechanical ventilation requirements, and clinical outcomes were also recorded. Albumin, phosphate, and serum Mg²⁺ levels were analyzed by colorimetric techniques, and other serum electrolyte levels were measured with an ion-selective electrode. Arterial blood gases and lactate concentrations were measured by the OMNI analyzer (Roche Diagnostics System, F. Hoffmann, La Roche Ltd., Basel, Switzerland).

Each patient had 2 measures of acid-base status analyzed. Thus, 62 samples were obtained. All mathematical calculations were performed following standard formulas (see Appendix).

Two levels of SBE, as calculated by Van Slyke's equation, have been reported to recognize metabolic acidosis (SBE_VS): an SBE_VS <-2 mEq/L (6,7) and an SBE_VS <-5 mEq/L (3). A physicochemical analysis of the groups categorized by these values of SBE_VS was performed. Likewise, arterial blood sample values were extracted from normal volunteers, and their 2.5th and 97.5th percentiles were established as normal ranges.

Recently, Wooten (19,20) have developed a new correction to the SBE (SBE_w) based on albumin and phosphate variations, a common scenario in critically ill patients. In order to show the difference between Van Slyke's and Wooten's equations, we measured the correlation and agreement for both values. For the diagnostic evaluation of SBE, the sensitivity, specificity, and accuracy were calculated with both the Van Slyke's and Wooten's equations, taking into account the physicochemical methodology as the gold standard for the diagnosis of metabolic acidosis. Subsequently, the diagnosis of metabolic acidosis with the two different cut-off levels of SBE_VS previously described (<-2 mEq/L and <-5 mEq/L) were compared to the diagnosis of metabolic acidosis by the physicochemical (quantitative) methodology.

The severity of the disease was correlated to several acid-base variables using the daily total SOFA score, in order to recognize which acid-base variables were clinically relevant at the bedside. Newer and more complex acid-base variables were compared to simpler and more classic ones, in order to show the best methodology for partitioning the acid-base metabolism.

Data distribution was analyzed with the Kolmogorov-Smirnov goodness-of-fit model, and later shown as medians and an interquartile range. Single medians were compared between groups using the Mann-Whitney U-test, and the within-group comparison between SBE_VS and SBE_W was performed with the Wilcoxon test. Sensitivity and specificity, as well as the accuracy (area under the curve of the receiver operator characteristic (ROC) curve with a 95% confidence interval), were calculated for SBE_VS and SBE_W. The ROC curve was also used to analyze the anion gap corrected for albumin (AG_A), and the anion gap corrected for albumin and phosphate (AG_A+P) as a discriminator of a strong ion gap (SIG) acidosis. The correlation analysis was carried out with Spearman's test and agreement was analyzed with the Bland-Altman plot. The commercially available SPSS, version 10.0 (Chicago, IL, USA) was used, designating P < 0.05 as a significant level.

Results

The general characteristics of the patients at the time of admission, the main support measures, the clinical outcomes, and the diagnoses are shown in Table 1. The ROC curves of SBE_VS and SBE_W used to diagnose metabolic acidosis are shown in Figure 1. Figure 2 shows the correlation and agreement between the SBE, as calculated by Van Slyke's and Wooten's equations. In Table 2, the biochemical results from the arterial blood samples are split into groups according to the two pre-selected cut-off levels of SBE_VS (-2 and -5 mEq/L). Age, APACHE II score, and total SOFA score are also shown for each group. The metabolic component of acid-base derangements was classified according to Stewart's physicochemical approach variables (21) that is, an apparent strong ion difference (SID_a) acidosis, an SIG acidosis, acidosis associated with an excess of albumin and inorganic phosphorus (P_i; derived from phosphate (see Appendix)), and the overlap of these three components. Table 3 shows the classification and the number of samples that fit the criteria of a specific acidosis according to Stewart's physicochemical approach. The samples were split according to SBE_VS cut-offs. The normal values considered were those between the 2.5th and 97.5th percentiles obtained from the venous blood samples of normal volunteers. Only two measures did not show any metabolic acidosis according to the physicochemical approach. Therefore, an SBE_VS <-5 mEq/L and an SBE_VS <-2 mEq/L were able to detect metabolic acidosis in 100% of the samples (Table 3).

The AG_A and AG_A+P were analyzed individually as possible surrogates of the SIG method to detect unmeasured anions. The sensitivities, specificities, and accuracies are shown in Table 4. These reports represent the entire group of measurements and are stratified for the different cut-offs of SBE_VS. Figure 3 shows the correlation and agreement between the SIG and the AG_A and the correlation and agreement between the SIG and the AG_A+P. In Table 5, the main acid-base variables were correlated to the total SOFA of the day when the blood sample was obtained.

Since SBE_VS is an appropriate tool to diagnose metabolic acidosis, we built several models using a multilinear regression with SBE_VS as a dependent factor. The results, in terms of a determinant coefficient, using the following 5 variables as independent factors, were as follows: 1) SIG, SID_a, the sum of albumin + P_i, and lactate (R² = 0.958); 2) SIG, SID_a, and lactate (R² = 0.890); 3) SIG, SID_a, lactate, and albumin (R² = 0.911); 4) AG_A, chloride, lactate, and albumin (R² = 0.640), and 5) AG_A, SID_a, lactate, and albumin (R² = 0.954).

Figure 1.
Receiver operator characteristic curve of standard base excess calculated by Van Slyke's equation (SBE_VS, area under the curve = 0.867, CI95% = 0.690-1.043) and Wooten's equation (SBE_W, area under the curve = 0.817, CI95% = 0.634-0.999) formulas to disclose metabolic acidosis diagnosed by Stewart's methodology. Using the Youden's (J) index the best value of SBE_VS to disclose metabolic acidosis was -2.7 with sensitivity of 100% and specificity of 75%, and the best value of SBE_W to disclose metabolic acidosis was -3.6 with sensitivity of 100% and specificity of 70%.

Figure 2.
Correlation and agreement between the standard base excess calculated by Van Slyke's (SBE_VS) and Wooten's (SBE_W) equations. A, Correlation and equation derived from the linear regression between the SBE_VS and SBE_W equations. B, Bland Altman plot disclosing the agreement between the SBE_VS and SBE_W equations. The number shown on the right side of the plot is the bias.

Figure 3.
Correlation and agreement between the strong ion gap (SIG) and the anion gap corrected for albumin (AG_A) and correlation and agreement between SIG and the anion gap corrected for albumin and phosphate (AG_A+P). A and B show the correlation and the linear regression model between SIG and AG_A and AG_A+P, respectively. C and D show the Bland Altman plot with the agreement between SIG and AG_A and AG_A+P, respectively. The numbers shown on the right side of each plot are the bias.

Table 1.
General characteristics of patients at admission, support measures, outcome, and diagnosis.

Table 2.
Clinical and biochemical characteristics of patients with standard base excess cut-off values of -5 or -2 mEq/L, and normal values obtained from healthy volunteers.

Table 3.
Classification of acid-base measures using the physicochemical criteria according to the standard base excess (SBE) cut-offs.

Table 4.
Sensitivity, specificity, and accuracy of AG_A and AG_A+P to predict elevated level of unmeasured anions (SIG >6.1 mEq/L).

Table 5.
Correlation between total sequential organ failure assessment score (SOFA) and acid-base variables.

Discussion

In our study, SBE_VS was the best acid-base variable correlated with the daily total SOFA. An SBE_VS <-2 mEq/L was better able to differentiate SIG acidosis than an SBE_VS <-5 mEq/L, with no significant differences regarding the other variables. To show unmeasured anions, AG_A was superior to the AG_A+P when the SIG was taken as the standard method. A mathematical model showed that variations of albumin, SID_a, AG_A, and lactate accounted for the SBE_VS variations with an R² = 0.954.

Clinical relevance of standard base excess

Acid-base derangements are extremely common in critically ill patients, and their clinical significance makes their precise detection and interpretation a necessity (6). Using the SBE as the marker for metabolic acidosis can lead to a misdiagnosis in the absence of metabolic acidosis (4,22). However, the diagnosis of metabolic acidosis using the SBE seems to be clinically relevant in terms of predicting clinical outcome (8,9,11).

We performed an analysis in which we attempted to correlate the SBE obtained from the patient with the total SOFA on the same day. A correlation of r = -0.454 (P < 0.001) was shown between the SBE_VS and the total SOFA, and a correlation of r = -0.482 (P < 0.001) was shown between the SBE_W and the total SOFA (Table 5). With 62 blood samples, there was a statistically significant correlation between the SBE and the total SOFA, showing that the SBE value can be used as a reflection of the disease severity of a critically ill patient (Table 5). In view of the correlation with clinical outcome and severity, SBE can be a reliable tool to diagnose metabolic acidosis (8,9,11).

Methods used to calculate standard base excess

Since the initial description of SBE (2), mathematical approaches have been described that simplify the SBE calculation (3,23,24). The SBE is a derivation of the base excess, in which the base excess equation is modified to standardize the effect of hemoglobin and improve the accuracy of base excess. Currently, the commercially available arterial blood gas machine calculates base excess using a 14-variable equation (3). In addition, although base excess is quite accurate in vitro, inaccuracy has always been a problem when applied in vivo in that base excess changes slightly with changes in PaCO₂. This effect is thought to be due to equilibration across the entire extracellular fluid space. Thus, the base excess equation was modified to standardize the effect of hemoglobin in order to improve the accuracy of base excess in vivo (25).

The SBE calculation by Van Slyke's method still yields results that are slightly unstable as the PaCO₂ changes (25). Furthermore, the equation assumes normal levels of weak acids (i.e., phosphate + albumin) (3,26). Further instability results when albumin or phosphate is decreased, as commonly occurs in critically ill patients (4,27). Recently, Wooten developed a multi-compartment model using quantitative techniques and suggested a correction for SBE that results in a formula for SBE that agrees much more closely with experimental data in humans (23,24). To date, uncertainty about the appropriate method persists, in addition to the fact that many of the commercially available arterial blood gas machines calculate SBE using Van Slyke's equation.

By analyzing the differences between SBE_VS and SBE_W, we found that their accuracy in predicting metabolic acidosis was quite similar (Figure 1) and that they were both clinically and statistically equivalent (Table 2 and Figure 1) with respect to all categorized cut-off values of SBE_VS, as both correlated well (r = 0.992, P < 0.001) and had good agreement (bias, 0.816 mEq/L; limits of agreement, -2.216 to 0.584 mEq/L; Figure 1). As stated, the SBE_VS and the SBE_W were similarly correlated with the severity of the acute disease (SOFA score; Table 5). Since it is much easier to obtain the SBE_VS from standard blood gas analyzers, and since SBE_VS and SBE_W are numerically and clinically interchangeable, the SBE_VS can be used at the bedside in a safe and easy way.

Standard base excess cut-off value to identify metabolic acidosis

The next parameter to identify patients with metabolic acidosis was the best cut-off value of SBE_VS. Some consider a value of SBE_VS <-5 mEq/L (3) to be useful, while others use an SBE_VS <-2 mEq/L (6,7). Considering the value of SBE_VS <-5 mEq/L, we observed that many variables related to acid-base metabolism were different between the groups with SBE_VS measurements >2 and <-5 mEq/L (Table 2). Some variables were statistically equivalent when the SBE_VS cut-off was changed to -2 mEq/L, such as albumin, albumin + P_i, creatinine, and SID_a (Table 2). In contrast, the clinical relevance of these findings did not seem to be important. Considering the physicochemical approach as the reference to diagnose acid-base disturbances, the SBE_VS cut-off of -5 mEq/L and the SBE_VS cut-off of -2 mEq/L were both able to identify 100% of measures with metabolic acidosis (Table 3).

Partitioning the metabolic acidosis as proposed by Stewart (1), an SBE_VS <-5 mEq/L was able to identify 35 of 53 (66%) measures with SIG acidosis, while an SBE_VS <-2 mEq/L was able to identify 44 of 53 (84%) measures with SIG acidosis (Table 3). An SID_a acidosis was similarly identified by the two SBE_VS cut-offs, with 20 of 24 (84%) identified with an SBE_VS <-5 mEq/L and 21 of 24 (89%) identified with an SBE_VS <-2 mEq/L (Table 3). Thus, the identification of SIG acidosis appears to be a valid clinical outcome marker (7-9). There are no measurements with acidosis determined by weak acids (albumin + P_i; Table 3). The capacity to disclose more measures with SIG acidosis, besides the non-significant differences in other variables related to acid-base metabolism, makes the value of SBE_VS <-2 mEq/L a good reference value to be used at the bedside in identifying metabolic acidosis in critically ill patients.

Evaluation of unmeasured anions

Hyperchloremic (SID_a) acidosis is experimentally associated with low renal blood flow (10), inflammation (28), and death (29). These findings are not associated with clinical outcomes, however (7). By contrast, SIG acidosis is related to prognosis in humans (7,8) and its theoretical surrogate, AG, is also related to outcomes (8). As recently described, AG is correlated and agrees well with SIG when corrected by weak acids (7). We tested SIG with AG corrected for albumin (AG_A; r = 0.869, P < 0.001, bias, -12.4 mEq/L, and limits of agreement, -15.84 to -8.94 mEq/L; Figure 2) and SIG with AG corrected for albumin and phosphate (AG_A+P; r = 0.820, P < 0.001, bias, -6.4 mEq/L, and limits of agreement, -14.1 to 1.3 mEq/L; Figure 2). The correlation between AG_A and SIG was similar to the AG_A+P.

The Bland-Altmann plot agreement showed that the bias between AG_A and SIG was superior to the bias between AG_A+P and SIG, which is consistent with the concept that the AG_A+P is actually a rough SIG rather than an anion gap (3). The dispersion of the individual differences between AG corrected and SIG on the graph was quite similar between AG_A and AG_A+P (Figure 2). By contrast, AG_A was more sensitive to disclose unmeasured anions than AG_A+P, but with the same accuracy when all measurements were taken into account (Table 4). This higher sensitivity of AG_A to disclose unmeasured anions was especially striking with SBE_VS <-2 mEq/L (98%), while the sensitivity of AG_A+P was 75% despite the same non-significant accuracy (Table 4). It is easier to calculate AG_A than AG_A+P and SIG (4), and AG_A is very sensitive in detecting SIG acidosis. Thus, it is a useful tool to detect unmeasured anions in critically ill patients.

In practice, the SBE_VS can be in a normal range with a low SID_a and a low albumin (albumin + P_i), which is a common finding in critically ill patients. In this situation, some have considered a low SID_a to be an adaptation to a low albumin level, rather than a complex acid-base disturbance (5). Our patients had the stated low levels of SID_a and albumin, and an alternative interpretation of our data is that the low SID_a was appropriate for the scenario.

Metabolic determinants of standard base excess variations

Considering the SBE_VS to be an appropriate tool to diagnose metabolic acidosis, and that the metabolic component of acid-base derangements correlated quite well with strong ions, unmeasured anions, lactate concentration, and weak acids (1,4), we constructed five models of SBE_VS variation determinants. It is clear that the first model (i.e., the model with the Stewart's variables) fits very well with the SBE_VS variations, showing the importance of Stewart's physicochemical quantitative approach (1). In order to facilitate this approach at the bedside, the fifth model considered some variables that use simple calculations (i.e., AG_A, SID_a, albumin level, and lactate concentration) and fits quite well with the SBE_VS variations.

In conclusion, our study showed that the SBE_VS with a cut-off value <-2 mEq/L was the best tool to diagnose metabolic acidosis. In analyzing the components of the SBE_VS shifts at the bedside, the AG_A, the SID_a, the albumin level, and the lactate concentration are easily obtainable variables that represent the partitioning of physicochemical quantitative analyses of acid-base derangements.

Standard base excess (Van Slyke's equation) (SBE_VS) (mEq/L) = 0.9287 x (HCO₃^- - 24.4 + 14.83 x pH - 7.4)

Standard base excess (Wooten's equation) (SBE_W) (mEq/L) = (HCO₃^- - 24.4) + ((8.3 x albumin (g/dL) x 0.15) + (0.29 x phosphate (mg/dL) x 0.32)) x pH - 7.4

Anion gap (corrected for albumin) (AG_A) (mEq/L) = (Na⁺ + K⁺) - (Cl^- + HCO₃^-) + 2.5 x (4 - albumin (g/dL))

Anion gap (corrected for albumin and phosphate) (AG_A+P) (mEq/L) = (Na⁺ + K⁺) - (Cl^- + HCO₃^-) - (2 x albumin (g/dL) + 0.5 x phosphate (mg/dL))

Apparent strong ion difference (SID_a) (mEq/L) = Na⁺ + K⁺ + Ca²⁺ + Mg²⁺ - Cl^-

Effective strong ion difference (SID_e) (mEq/L) = 2.46 x 10^-8 x PCO₂ / 10^-pH + (albumin (g/dL)) x (0.123 x pH - 0.631) + (phosphate (mg/dL) / 3 x pH - 0.469)

SIG (mEq/L) = SID_a - SID_e

Albumin (mEq/L) = 10 x albumin (g/dL) x (0.123 x pH - 0.631)

Inorganic phosphate (P_i) (mEq/L) = (PO₄ (mg/dL) x 10 / 30.97) x (0.309 x pH - 0.469)

The unit of all strong ions was mEq/L.

Address for correspondence: M. Park, Rua Francisco Preto, 46, Bloco 3, Aptº 64, 05623-010 São Paulo, SP, Brasil. E-mail: [e-mail]

Publication supported by FAPESP. Received July 12, 2007. Accepted October 25, 2007.

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Appendix

Correspondence and Footnotes

Publication Dates

• Publication in this collection
  25 Feb 2011
• Date of issue
  Mar 2008

History

• Accepted
  25 Oct 2007
• Received
  12 July 2007