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Revista Brasileira de Terapia Intensiva

AMIB - Associação de Medicina Intensiva Brasileira

OFFICIAL JOURNAL OF THE ASSOCIAÇÃO BRASILEIRA DE MEDICINA INTENSIVA AND THE SOCIEDADE PORTUGUESA DE CUIDADOS INTENSIVOS

ISSN: 0103-507X
Online ISSN: 1982-4335

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Park M, Noritomi DT, Toledo-Maciel A, Azevedo LCP, Pizzo VR, Cruz-Neto LM. Determinantes da evolução do standard base excess em pacientes com choque séptico. Rev Bras Ter Intensiva. 2007;19(4):437-443

 

 

2007;19(4):437-443
Original Article

http://dx.doi.org/10.1590/S0103-507X2007000400006

Partitioning evolutive standard base excess determinants in septic shock patients

Determinantes da evolução do standard base excess em pacientes com choque séptico

Marcelo Park, Danilo Teixeira Noritomi, Alexandre Toledo-Maciel, Luciano Cesar Pontes de Azevedo, Vladimir Ribeiro Pizzo, Luiz Monteiro da Cruz-Neto

Assistant Doctor - Intensive Care Unit - Emergency Department - Hospital das Clínicas - University of São Paulo Medical School

Presented in June, 26, 2007
Accepted in October, 18, 2007

Corresponding author:

Marcelo Park, M.D.
Rua Francisco Preto, 46, B3, Apto 64
05623-010, São Paulo, SP - Brazil
E-mail: [email protected]

 

Abstract

BACKGROUND AND OBJECTIVES: The amount of metabolic acidosis measured through the standard base excess (SBE) has been shown to be an outcome marker and its improvement has been associated with better survival. We studied the mechanism of standard base excess variation in the first three days of intensive care unit (ICU) stay through the evaluation of independent variables of physico-chemical approach.
METHODS: Data were retrieved from our prospective collected data base from patients with diagnosis of septic shock, daily up to the third day after the ICU admission. Single correlations between SBE and independent variables were performed as well as a mathematical multilinear model was built to disclose the SBE variation determinants.
RESULTS: We have shown that in septic shock patients the standard base excess variation during the first three days of ICU stay is weakly correlated to strong ion gap (SIG), lactate, creatinin and PaCO2 when individually analyzed. Analyzing concomitantly those independent variables, we built a mathematical model with a stepwise multilinear regression composed by apparent strong ion difference (SIDa), SIG, PaCO2, albumin and diuresis that resulted in a R2 coefficient of 0.866 to determine SBE variation.
CONCLUSIONS: Variations of metabolic acidosis measured through the standard base excess in septic shock patients when analyzed until the third day after intensive care unit admission, is resultant of interaction of several independent determinants as PaCO2, diuresis, SIG, SIDa and albumin.

Keywords: lactate, metabolic acidosis, monitorization, septic shock, severe sepsis

 

 

INTRODUCTION

Base excess is the quantity of metabolic acidosis or alkalosis, defined as the amount of acid or base that must be added to a sample of whole blood in vitro in order to restore the pH of the sample to 7.40 while the PCO2 is held at 40 mmHg1. Currently the most commonly used methodology for acquire base excess is the Van Slyke equation which takes into account the bicarbonate serum level, hemoglobin and pH2. Base excess is quite accurate in vitro, although inaccuracy has always been a problem when Van Slyke is applied in vivo, where base excess changes slightly with changes in arterial carbon dioxide partial pressure (PaCO2)3. Thus, the base excess equation has been modified to standardize the effect of hemoglobin in order to improve the accuracy of base excess in vivo2. The term standard base excess (SBE) has been given to this last described variable, which better quantifies the change in metabolic acid base status in multicompartment systems, highlighting the plasmatic compartment2,3.

In 1981, Dr. Peter Stewart, a Canadian physiologist, proposed a novel physico-chemical theory of acid base balance based mainly on an explicit master fourth-order polynomial equation that relates the pH to three independent variables: 1. SID which is the difference of charge of all strong ions (cations - anions), 2. PCO2 and 3. Atot which is the total concentration of weak acids, represented in the human physiology by albumin and phosphate4,5. This new theory has brought new light to the area of acid base disturbances of critically ill patients.

In critically ill subjects, the presence of metabolic acidosis is very common, particularly in septic shock patients6. The amount of metabolic acidosis measured through the SBE has been shown to be an outcome marker, when it is evaluated isolated on admission or during the first days after ICU admission7. Its improvement has been associated with better survival. However, so far it is not clear which are the factors associated with SBE variations in critically ill septic patients.

In this study, we splitted septic shock patients in two groups, one group of patients who improved SBE from the day of ICU admission to the third day of ICU stay, and one group who worsened SBE in the same period. The aim of this study was to characterize the acid-base variables, according to the Stewart's theory, responsible for SBE improvement and worsening within the first three days of ICU stay.

METHODS

Data were retrieved from our prospective collected data base of a tertiary teaching seven beds intensive care unit (ICU) in São Paulo - Brazil. The period investigated was from January 2004 to May 2004. Age, gender, APACHE II score, length of stay in ICU, clinical outcome, needing for mechanical ventilation, previous diagnosis of chronic renal failure, needing for dialysis, fluids handling, general laboratorial data and infection source were collected from patients with diagnosis of septic shock daily up to the third day after ICU admission. The diagnosis of septic shock was performed according to the consensus conference criteria8.

Blood samples and fluids handling data were obtained at the end of each day. The arterial line was used to collect blood samples. Albumin, phosphate and serum Mg2+ were analyzed by colorimetric techniques, and other serum electrolytes were measured with an ion-selective electrode. Arterial blood gases and lactate were measured by the OMNI analyzer (Roche Diagnostics System, F. Hoffmann - La Roche Ltd, Basel, Switzerland) and to determine SBE value the Van Slyke method was used2. All standard formulas used to calculate physico-chemical variables are described in the appendix.

Data were considered normal using Shapiro-Wilk goodness-of-fit model, and are shown as means and standard deviation. Means between groups were compared using Student t test and categorical data were compared using Fisher or Chi-square analysis as indicated. Determinants of metabolic acidosis according to Stewart's physico-chemical approach were independently correlated with variations SBE using Pearson's correlation and afterward a mathematical model was built to correlate SBE variations with the components of physico-chemical approach using a stepwise multilinear regression model. The commercially available SPSS 10.0 statistical package was used, considering p < 0.05 as a significant level.

RESULTS

During five months, thirty eight patients with septic shock treated according to the surviving sepsis campaign, were observed. General characteristics and infection sites of whole group are shown in table 1.

The SBE evolution was linear beyond the three first days in both groups (Figure 1 - Panel A). A slight variation around 35 mmol/L was the feature of SIDa behavior, and lactate also had a small variation. Unmeasured anions, disclosed by SIG, fall in the group who improved SBE and rise in the group who worsened SBE (Figure 1 - Panel B). Albumin levels fall in the group who worsened SBE, and initially fall in the first day rising in the second day in the group who improved SBE (Figure 1 - Panel C).

The SBE variation was individually correlated with lactate, PaCO2, creatinin and SIG (Table 4). When a stepwise multilinear regression model with SBE as a dependent variable was built, the independent variables albumin, PaCO2, SIDa, SIG and diuresis have composed an equation with the determination coefficient (R2) of 0.866. Beta unstandardized coefficients of the multilinear regression model are shown in table 4. When analyzing the group of patients who SBE improved or worsened individually the results are similar.

DISCUSSION

In our study, we have shown that in septic shock patients the SBE variation during the first three days of ICU stay is weakly correlated to SIG, lactate, creatinin and PaCO2 when individually analyzed. Analyzing concomitantly those independent variables, we built a mathematical model with a stepwise multilinear regression composed by SIDa, SIG, PaCO2, albumin and diuresis that resulted in a R2 coefficient of 0.866 to determine SBE variations.

Since the description of base excess in 19601, it has been largely used in the clinical practice to disclose and measure metabolic acidosis3,4,9. However, base excess or its clinical derivation SBE are limited to detect true metabolic acidosis in adult critically ill patients and in pediatric cardiac postoperative10,11. This limitation has been ascribed to hypoalbuminemia, which can cause metabolic alkalosis hiding or attenuating any kind of installed metabolic acidosis11. In spite of the apparent limited information's given by the SBE, low values of SBE at the admission to ICU has been associated with poor outcome12-15, and in the same way the improvement of SBE by the third day after the ICU admission has been independently correlated with better prognosis7. In the hemodynamic early goal directed therapy study performed by Rivers et al.16 to severe sepsis and septic shock patients, the interventional group improved SBE close to normal values by the third day, starting from very low initial values. Those characteristics turn SBE an important clinical physiological tool to be used in the modern ICU.

It is interesting to note that among our patients there were not admission characteristics that have identified the subjects who could improve or worse SBE until the third day. The amount and quality of fluids used in resuscitation of shock can, theoretically, be related to acid base state modifications3,9. In our study, the amount of fluids used in both groups were similar (Table 2) and the standard fluid used was ringer lactate, in this way, the great acid base derangements expected using crystalloids would be SIDa variations, by contrast, our finding point out to SIG as a correlate with SBE in the univariate analysis (Table 4). SIG actually quantify unmeasured anions3,5, and it can be raised by colloids3, which were not used in our patients. Other possible sources of SIG acidosis in septic shock patients are: 1. mitochondrial dysfunction, which can be secondary to oxygen deprivation17 or inflammatory mediators18, and 2. renal dysfunction by reducing clearance of non volatile acids19. Currently, there are some investigations about the unmeasuble anions components of SIG acidosis, and some metabolic intermediates of Krebs' cycle as isocitrate, a-ketoglutarate and malate has been associated with SIG acidosis20, although, the definitive list of endogenous anions that can cause metabolic SIG acidosis in sepsis and shock states is far from complete21. There are some evidences that SIG acidosis is correlated with outcome13,14, and it is additive with prognostic information of serum lactate level12.

Serum lactate level is a well known cause of metabolic acidosis in critically ill patients22, but its clinical and physiological importance has been shared with other unmeasured anions12,14. It has been associated with oxygen deprivation, inflammation and hepatic dysfunction22. Our correlation finding between SBE and lactate is physiologically rational (Table 4)9, and the lactate exclusion of the final stepwise regression model can be explained by the fact that the unmeasured anions calculated by SIG physiologically behave quite similar to lactate17,20, likewise, in the mathematical model the inclusion of lactate could not be of great importance in the modification of F probability statistics, and this fact is an acquard reflection of clinical association among SIG, SBE and lactate12,14,20.

Creatinin was other finding associated with SBE variation. Low renal clearance is associated with increments in SIG19, but in our patients it is hard to affirm that SIG acidosis has been caused by low renal clearance or SIG acidosis has been epiphenomena which has resulted from the critical illness and multiorgan dysfunction18,23. Diuresis is an immediate reflection of renal clearance and can disclose renal impairment earlier than creatinin elevations24. Otherwise, few patients can present oliguria without elevations of creatinin, but acidosis will be present only if renal failure is present19. In this way, we can understand why diuresis was associated with SBE variations only in the mathematical multilinear model25.

Partial pressure of carbon dioxide was positively associated with SBE variations as expected by the mathematical calculus using the Van Slyke equation, where bicarbonate concentration is one of the independent variables besides pH2. Thus, from the stoichiometric point of view, one can expect that rising PaCO2 the bicarbonate and then SBE will also rise1. Otherwise, in our multilinear mathematical model, an interesting finding was the negative correlation of PaCO2 and SBE variations, contrasting with the single correlation. This finding can represent the clinical status of patients, where higher the severity of the disease, higher the probability to be on mechanical ventilation, reflecting in low SBE due to the severity of disease and PaCO2 dependent of mechanical ventilation strategy. In this way, we would like to stress that fourteen patients (37%) accomplished acute respiratory distress syndrome (ARDS) criteria of consensus conference26, and in our patients the open lung approach with permissive hypercapnia has been used to ventilate ARDS patients27. The advantage of the mathematical stepwise multilinear regression in this case was the representation of SBE as a multicomponent tool, reproducing the complex clinical acid base environment25.

Albumin and phosphate have been considered as the main weak acids in organic systems that are responsible for acid base modulation10,28-30. Hypoalbuminemia is a frequent finding in critically ill patients and also in our patients (Table 1, Figure 2), being an important source of metabolic alkalosis and pH and SBE neutralization in this setting as we can observe in table 4, in the mathematical model11.

Funk et al.31 studied the acid base behavior in a general ICU population, showing chloride and SIDa as the main determinants of acid base behavior. By contrast, in septic shock patients, according to our findings the acidosis variation measured by the SBE results from a complex situation, and SIDa was important only in the mathematical multilinear model when analyzed together with other components associated with metabolic acidosis.

We would like to stress that the physico-chemical approach is not superior to the traditional approach at bedside to diagnose acid-base derangements32. However, this methodology allows the quantification of respiratory and / or metabolic shifts to statistical measurement. In this way, we have used the physico-chemical approach in our study.

In conclusion, variations of metabolic acidosis measured through the SBE in septic shock patients when analyzed until the third day after ICU admission, is resultant of interaction of several independent determinants as PaCO2, diuresis, SIG, SIDa and albumin.

REFERENCES

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02. Morgan TJ, Clark C, Endre ZH - Accuracy of base excess--an in vitro evaluation of the Van Slyke equation. Crit Care Med, 2000;28:2932-2936.

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06. MacKenzie IM - The haemodynamics of human septic shock. Anaesthesia, 2001;56:130-144.

07. Palma LC, Ferreira GF, Amaral ACKB et al - Acidosis and mortality in severe sepsis and septic shock evaluated by base excess variation. Crit Care, 2003;7(Suppl3):P39.

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10. Murray DM, Olhsson V, Fraser JI - Defining acidosis in postoperative cardiac patients using Stewart's method of strong ion difference. Pediatr Crit Care Med, 2004;5:240-245.

11. Fencl V, Jabor A, Kazda A et al - Diagnosis of metabolic acid-base disturbances in critically ill patients. Am J Respir Crit Care Med, 2000;162:2246-2251.

12. Smith I, Kumar P, Molloy S et al - Base excess and lactate as prognostic indicators for patients admitted to intensive care. Intensive Care Med, 2001;27:74-83.

13. Balasubramanyan N, Havens PL, Hoffman GM - Unmeasured anions identified by the Fencl-Stewart method predict mortality better than base excess, anion gap, and lactate in patients in the pediatric intensive care unit. Crit Care Med, 1999;27:1577-1581.

14. Kaplan LJ, Kellum JA - Initial pH, base deficit, lactate, anion gap, strong ion difference, and strong ion gap predict outcome from major vascular injury. Crit Care Med, 2004;32:1120-1124.

15. Dondorp AM, Chau TT, Phu NH et al - Unidentified acids of strong prognostic significance in severe malaria. Crit Care Med, 2004;32:1683-1688.

16. Rivers E, Nguyen B, Havstad S et al - Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med, 2001;345:1368-1377.

17. Kellum JA, Bellomo R, Kramer DJ et al - Hepatic anion flux during acute endotoxemia. J Appl Physiol, 1995;78:2212-2217.

18. Brealey D, Brand M, Hargreaves I et al - Association between mitochondrial dysfunction and severity and outcome of septic shock. Lancet, 2002;360(9328):219-223.

19. Rocktaeschel J, Morimatsu H, Uchino S et al - Acid-base status of critically ill patients with acute renal failure: analysis based on Stewart-Figge methodology. Crit Care, 2003;7:R60.

20. Forni LG, McKinnon W, Lord GA et al - Circulating anions usually associated with the Krebs cycle in patients with metabolic acidosis. Crit Care, 2005;9:R591-R595.

21. Bowling FG, Morgan TJ - Krebs cycle anions in metabolic acidosis. Crit Care, 2005;9(5):E23.

22. De Backer D - Lactic acidosis. Intensive Care Med, 2003;29:699-702.

23. Singer M, De Santis V, Vitale D et al - Multiorgan failure is an adaptive, endocrine-mediated, metabolic response to overwhelming systemic inflammation. Lancet, 2004;364(9433):545-548.

24. Bellomo R, Ronco C, Kellum JA et al - Acute renal failure - definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care, 2004;8:R204-R212.

25. Marill KA - Advanced statistics: linear regression, part II: multiple linear regression. Acad Emerg Med, 2004;11:94-102.

26. Bernard GR, Artigas A, Brigham KL et al - The American-European Consensus Conference on ARDS. Definitions, mechanisms, relevant outcomes, and clinical trial coordination. Am J Respir Crit Care Med, 1994;149:818-824.

27. Amato MB, Barbas CS, Medeiros DM et al - Effect of a protective-ventilation strategy on mortality in the acute respiratory distress syndrome. N Engl J Med, 1998;338:347-354.

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APPENDIX - Standard Formulas

1. Standard base excess (Van Slyke's equation) (SBEVS) (mEq/L) = 0.9287 x (HCO3 - 24.4 + 14.83 X [pH - 7.4])

2. Apparent strong ion difference (SIDa) (mEq/L) = Na+ + K+ + Ca2+ + Mg2+ - Cl- - Lactate

3. Effective strong ion difference (SIDe) (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)]

4. SIG (mEq/L) = SIDa - SIDa

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

6. Inorganic phosphate (Pi)(mEq/L) = (PO4(mg/dL) x 10/30,97) x (0.309 x pH - 0.469)

7. The unit of all strong ions was mEq/L

 

 

Received from Intensive Care Unit - Emergency Department - Hospital das Clínicas - University of São Paulo Medical School - Brazil

 

 

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