The anion gap (AG) is a time-honored acid base variable which has been employed for over 30 years as a scanning tool for the presence of unmeasured ions [
The concept of AG stems from the fundamental principle of electrical neutrality. Hence,
The difference of
A major limitation in the use of AG for the diagnosis and the evaluation of metabolic acidosis is its dependence on the concentrations of the nonvolatile weak acids, of which albumin is the most important [
Therefore, (
The right side of (
Given the previous considerations, we embarked on this study to assess the impact and the quantitative significance of each of the independent acid base variables on AG variability
This retrospective study evaluated routine acid base and biochemical data from cardiac surgical patients admitted to our ICU for postoperative care between January 2010 and March 2011. The local Ethics and Scientific Committee approved the study protocol and waived the requirement for informed consent (Ethics and Scientific Committee session number 5/14.03.2012, Chairperson Dr. Ioannis Zarifis). After reviewing the patients’ written medical records and the nurses’ flowcharts, the following paired acid base and biochemical data from the day of admission and the first postoperative day were extracted: pH, PCO2, Na, K, and Cl (from the output of the blood gas machine) and serum albumin and phosphate concentrations (from the biochemical report). A time interval of 16–18 hours intervened between consecutive measurements. In addition, we recorded clinical and demographic data from each patient, including age, sex, type of operation, and logistic Euroscore value.
Blood gas sampling was performed with the use of specifically designed commercially available syringes which come prefilled with dry electrolyte-balanced heparin (PICO sampler; Radiometer, Copenhagen, Denmark); the first 2-3 mL of blood was discarded to avoid contamination with the flushing fluid. Biochemical samples were obtained from the radial artery catheter immediately after the first blood gas samples were drawn. The blood gas samples were analyzed at 37°C for blood gases and electrolytes in the point-of-care blood gas and electrolyte analyzer (ABL800 FLEX analyzer; Radiometer, Copenhagen, Denmark). Albumin and phosphate concentrations were assessed in the hospital central laboratory using colorimetric techniques (Olympus EU 640; Olympus, Center Valley, Pennsylvania, USA).
Following the methodology employed by Park et al. [
Quantitative acid base analysis was based on the principles advanced by Stewart [
Albumin and phosphate charge concentrations were calculated according to (
Last, effective strong ion difference
Statistical analysis was performed using the Statistical Package for the Social Sciences software (SPSS Inc., Chicago, Illinois, release 17.0). Continuous variables are expressed as mean ± standard deviation (SD), unless stated otherwise, and dichotomous (categorical) variables are expressed as frequency counts (proportions).
The normality of data distribution was assessed by inspection of histograms. The multiple linear regression model was built in the forward mode with entry and removal criteria of
One hundred and twenty eight cardiac surgical patients (age
Clinical and demographic characteristics of patients (
Age (years) |
|
Males, |
103/128 (80.4) |
Logistic Euroscore | 4.65 (0.88, 78.52)* |
Types of operations, |
|
CABG | 90/128 (70.3) |
Valvular | 16/128 (12.5) |
Aortic | 8/128 (6.2) |
Combined CABG and valvular | 7/128 (5.5) |
Other | 7/128 (5.5) |
*Median (range).
CABG: coronary artery bypass grafting.
Variation of anion gap and its predictors between admission and first postoperative day (
Acid base variables | Admission | First postoperative day | Variation |
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SIDa, meq/L |
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PCO2, mmHg |
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Phosphate, mmol/L |
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Albumin, g/L |
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|
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SIG, meq/L |
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AG, meq/L |
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|
The output of the multiple linear regression model is summarized in Table
Output of the multiple linear regression model correlating AGvar (dependent variable) with SIGvar,
Unstandardized coefficients |
Standardized coefficients |
|
Tolerance | VIF | |
---|---|---|---|---|---|
Constant | 0 (−0.014, 0.012) | 0.883 | |||
SIGvar, meq/L | 0.934 (0.931, 0.938) | 0.948 | <0.001 | 0.310 | 3.228 |
|
0.251 (0.248, 0.253) | 0.260 | <0.001 | 0.680 | 0.1471 |
|
1.704 (1.685, 1.723) | 0.191 | <0.001 | 0.821 | 1.218 |
|
−0.042 (−0.044, −0.041) | −0.067 | <0.001 | 0.623 | 1.606 |
SIDa,var, meq/L | 0.065 (0.062, 0.068) | 0.071 | <0.001 | 0.283 | 3.530 |
CI: confidence intervals.
In this study we endeavored to identify the independent predictors of AG variation and assess their quantitative importance. The results of our multiple linear regression model suggest that AG variation is determined mainly by two factors: the concentration of the unmeasured ions and the concentrations of nonvolatile weak acids, namely, albumin and phosphate. An important finding of our study is that strong ion difference and PCO2 also participate independently in the prediction of AG variation although their contributions are quantitatively less important. Indeed, it should be noted that, within the usual clinical settings, the variations of SIDa and PCO2 are unlikely to be the cause of significant bias in the AG value. For instance, assuming a zero change for the other parameters, a decrease in PCO2 by 10 mmHg or an increase in SIDa by 10 meq/L would increase AG value by 0.42 and 0.65 meq/L, respectively. Interestingly, in an
To our knowledge, this is the first study that evaluated the role of respiratory perturbations on the value of the AG
On the other hand, the possibility that changes in SIDa may influence the AG value has not been considered so far in quantitative acid base analyses. This fact is likely to be partly related to the persistence of previous firmly established premises of traditional acid base physiology. Thus, the traditional classification of acidosis distinguished between the “hyperchloremic” and the “nonhyperchloremic” types and ignored the other strong ions, while the change in [Cl−] was thought to be more or less cancelled out by an opposite change in
Furthermore, although the homeostases of Cl− and CO2 are thought to be interlinked at the level of the erythrocytes [
Based on the output of the model (Table
If the quantitatively minimal contributions from SIDa and PCO2 are ignored and the correlation coefficients are rounded, our model’s master equation (
Alternatively we can write
Equation (
If we integrate both sides of (
It should be noted here that Kellum proposed a similar empirical calculation rule for the unmeasured ion concentration (termed corrected AG), by averaging albumin and phosphate charges over the acidemic pH range and subtracting them from the observed AG value [
The validity of Figge’s algorithm for the correction (adjustment) of AG value according to albumin concentration has been assessed in several clinical studies. Generally, studies in critically ill [
Our approach is limited by the fact that we did not prospectively validate our model on an independent patient population. However the formalisms derived from this model (see (
In addition, we should point out that this mathematical model is only applicable within the ranges of the independent variable variations observed in this study. On the other hand, a major advantage of our approach is that it does neither require nor resort to assumptions or approximations regarding the pH value or albumin and phosphate charge concentrations. Only the knowledge of the independent variables of acid base equilibrium, that is, SIDa, [Albumin], [Phosphate], SIG, and PCO2, suffices for the prediction of AG value.
To conclude, we have developed a comprehensive mathematical model which correlates AG variation with the respective variations of SIG, [Albumin], [Phosphate], SIDa, and PCO2. All the above acid base variables exert an independent influence on the AG value, although SIG, [Albumin], and [Phosphate] are quantitatively the most important predictors. Moreover, the AG seems to be a robust index for the assessment of metabolic acid base disorders in patients with coexistent respiratory or strong ion acid base disturbances.
The authors declare that there is no conflict of interests regarding the publication of this paper.