Effect of low serum total protein on sodium and potassium measurement by ion-selective electrodes in critically ill patients

Impact of hyponatremia in patients hospitalized in Internal Medicine units: Hyponatremia in Internal Medicine units

The aim of this study was to analyze the impact and the clinical and evolutionary characteristics of hypotonic hyponatremia in patients hospitalized in Internal Medicine units. Prospective multicenter observational study of patients with hypotonic hyponatremia (<135 mmol/L) in 5 hospitals in southern Spain. Patients were included according to point prevalence studies carried out every 2 weeks between March 2015 and October 2017, by assessing demographic, clinical, analytical, and management data; each patient was subsequently followed up for 12 months, during which time mortality and readmissions were assessed. A total of 501 patients were included (51.9% women, mean age = 71.3 ± 14.24 years), resulting in an overall prevalence of hyponatremia of 8.3%. The mean comorbidities rate was 4.50 ± 2.41, the most frequent diagnoses being heart failure (115) (23%), respiratory infections (65) (13%), and oncological pathologies (42) (6.4%). Of the total number of hyponatremia cases, 180 (35.9%) were hypervolemic, 164 (32.7%) hypovolemic, and 157 (31.3%) were euvolemic. A total of 87.4% did not receive additional diagnostic tests to establish the origin of the condition and 30% did not receive any treatment. Hospital mortality was 15.6% and the mean length of stay was 14.7 days. Euvolemic and admission hyponatremia versus hyponatremia developed during admission were significantly associated with lower mortality rates (P = .037). Mortality at 1 year and readmissions were high (31% and 53% of patients, respectively). Hyponatremia was common in Internal Medicine areas, with hypervolemic hyponatremia being the most frequent type. The mortality rate was high during admission and at follow-up; yet there is a margin for improvement in the clinical management of this condition.

Fluid management in children with volume depletion

Volume depletion is a common condition and a frequent cause of hospitalization in children. Proper assessment of the patient includes a detailed history and a thorough physical examination. Biochemical tests may be useful in selected cases. Understanding the pathophysiology of fluid balance is necessary for appropriate management. A clinical dehydration scale assessing more physical findings may help to determine dehydration severity. Most dehydrated children can be treated orally; however, intravenous therapy may be indicated in patients with severe volume depletion, in those who have failed oral therapy, or in children with altered consciousness or significant metabolic abnormalities. Proper management consists of restoring circulatory volume and electrolyte balance. In this paper, we review clinical aspects, diagnosis, and management of children with volume depletion.

Erroneous potassium results: preanalytical causes, detection, and corrective actions

Potassium is one of the most requested laboratory tests. Its level is carefully monitored and maintained in a narrow physiological range. Even slightly altered potassium values may severely impact the patient's health, which is why an accurate and reliable result is of such importance. Even if high-quality analytics are available, there are still numerous ways in which potassium measurements may be biased, all of which occur in the preanalytical phase of the total laboratory testing process. As these results do not reflect the patient's in-vivo status, such results are referred to as pseudo-hyper/hypokalemia or indeed pseudo-normokalemia, depending on the true potassium result. Our goal in this review is to present an in-depth analysis of preanalytical errors that may result in inaccurate potassium results. After reviewing existing evidence on this topic, we classified preanalytical errors impacting potassium results into 4 categories: 1) patient factors like high platelet, leukocytes, or erythrocyte counts; 2) the sample type 3) the blood collection procedure, including inappropriate equipment, patient preparation, sample contamination and others and 4) the tube processing. The latter two include sample transport and storage conditions of whole blood, plasma, or serum as well as sample separation and subsequent preanalytical processes. In particular, we discuss the contribution of hemolysis, as one of the most frequent preanalytical errors, to pseudo-hyperkalemia. We provide a practical flow chart and a tabular overview of all the discussed preanalytical errors including possible underlying mechanisms, indicators for detection, suggestions for corrective actions, and references to the according evidence. We thereby hope that this manuscript will serve as a resource in the prevention and investigation of potentially biased potassium results.

Pseudohyponatremia: Mechanism, Diagnosis, Clinical Associations and Management

Pseudohyponatremia remains a problem for clinical laboratories. In this study, we analyzed the mechanisms, diagnosis, clinical consequences, and conditions associated with pseudohyponatremia, and future developments for its elimination. The two methods involved assess the serum sodium concentration ([Na]_S) using sodium ion-specific electrodes: (a) a direct ion-specific electrode (ISE), and (b) an indirect ISE. A direct ISE does not require dilution of a sample prior to its measurement, whereas an indirect ISE needs pre-measurement sample dilution. [Na]_S measurements using an indirect ISE are influenced by abnormal concentrations of serum proteins or lipids. Pseudohyponatremia occurs when the [Na]_S is measured with an indirect ISE and the serum solid content concentrations are elevated, resulting in reciprocal depressions in serum water and [Na]_S values. Pseudonormonatremia or pseudohypernatremia are encountered in hypoproteinemic patients who have a decreased plasma solids content. Three mechanisms are responsible for pseudohyponatremia: (a) a reduction in the [Na]_S due to lower serum water and sodium concentrations, the electrolyte exclusion effect; (b) an increase in the measured sample's water concentration post-dilution to a greater extent when compared to normal serum, lowering the [Na] in this sample; (c) when serum hyperviscosity reduces serum delivery to the device that apportions serum and diluent. Patients with pseudohyponatremia and a normal [Na]_S do not develop water movement across cell membranes and clinical manifestations of hypotonic hyponatremia. Pseudohyponatremia does not require treatment to address the [Na]_S, making any inadvertent correction treatment potentially detrimental.

Analysis of influencing factors of serum total protein and serum calcium content in plasma donors

Background and objectives

The adverse effects of plasma donation on the body has lowered the odds of donation. The aim of this study was to investigate the prevalence of abnormal serum calcium and total serum protein related to plasma donation, identify the influencing factors, and come up with suggestions to make plasma donation safer.

Methods

Donors from 10 plasmapheresis centers in five provinces of China participated in this study. Serum samples were collected before donation. Serum calcium was measured by arsenazo III colorimetry, and the biuret method was used for total serum protein assay. An automatic biochemical analyzer was used to conduct serum calcium and total serum protein tests.

Results

The mean serum calcium was 2.3 ± 0.15 mmol/L and total serum protein was 67.75 ± 6.02 g/L. The proportions of plasma donors whose serum calcium and total serum protein were lower than normal were 20.55% (815/3,966) and 27.99% (1,111/3,969), respectively. There were significant differences in mean serum calcium and total serum protein of plasma donors with different plasma donation frequencies, gender, age, regions, and body mass index (BMI), (all p < 0.05). Logistic regression analysis revealed that donation frequencies, age, BMI and regions were significantly associated with a higher risk of low serum calcium level, and donation frequencies, gender, age and regions were significant determinants factors of odds of abnormal total serum protein.

Conclusions

Donation frequencies, gender, age, regions, and BMI showed different effects on serum calcium and total serum protein. More attention should be paid to the age, donation frequency and region of plasma donors to reduce the probability of low serum calcium and low total serum protein.

Comparison of Point-of-Care versus Central Laboratory Testing of Electrolytes, Hemoglobin, and Bilirubin in Neonates

OBJECTIVE

Electrolyte, hemoglobin, and bilirubin values are routinely reported with point-of-care (POC) testing for blood gases. Results are rapidly available and require a small blood volume. Yet, these results are underutilized due to noted discrepancies between central laboratory (CL) and POC testing. The study aimed to determine the correlation between POC and CL measurement of electrolytes, hemoglobin, and bilirubin in neonates.

STUDY DESIGN

Electrolyte, hemoglobin, and bilirubin results obtained from capillary blood over a 4-month period were analyzed. Each CL value was matched with a POC value from the same sample or another sample less than 1-hour apart. Agreement was determined by measuring the mean difference (MD) between paired samples with 95% limits of agreement (LOA) and Lin's concordance correlation (LCC).

RESULTS

There were 355-paired sodium/potassium, 139 paired hemoglobin, and 197 paired bilirubin values analyzed. POC sodium values were lower (133.5 ± 5.8 mmol/L) than CL (140.2 ± 5.8 mmol/L), p <0.00001 with poor agreement (LCC = 0.49; MD = 6.7; 95% LOA: -13.6 to 0.14). POC potassium values were lower (4.6 ± 0.98 mmol/L) than CL (4.98 ± 1.24mEq/L), p < 0.0001, but with better concordance and agreement. (LCC = 0.6; MD = 0.4; 95% LOA: -2.3 to 1.4). There were no differences in hemoglobin between POC (14.3 ± 3.2 g/dL) and CL (14.4 ± 3.1 g/dL), p = 0.2 with good LCC (0.93) and in bilirubin values between POC (6.0 ± 3.2 mg/dL) and CL (5.8 ± 3.0 mg/dL), MD = 0.18, and p = 0.07.

CONCLUSION

POC Sodium values are lower than CL. POC potassium levels are also lower, but the differences may not be clinically important while hemoglobin and bilirubin levels are similar between POC and CL. As POC potassium, hemoglobin, and bilirubin levels closely reflect CL values, these results can be relied upon to make clinical judgments in neonates.

KEY POINTS

· Electrolyte, hemoglobin, and bilirubin are available as POC.. · POC sodium and potassium values are lower than CL results.. · Hemoglobin and bilirubin values are similar between POC and CL..

A Potassium-Based Quality-of-Service Metric Reduces Phlebotomy Errors, Resulting in Improved Patient Safety and Decreased Cost

OBJECTIVES

Poor phlebotomy technique can introduce pseudohyperkalemia without hemolysis, requiring additional workup and placing a significant burden on patients, clinical teams, and laboratories. Such preanalytical biases can be detected through systematic evaluation of potassium concentrations on a per-phlebotomist basis. We report our long-term experience with a potassium-based quality-of-service phlebotomy metric and its effects on resource utilization.

METHODS

Potassium monitoring and retraining of 26 full-time phlebotomists were piloted as a quality-of-service intervention. Changes in potassium concentrations and impact on resource utilization were assessed. An algorithm for data monitoring and phlebotomist feedback was developed, followed by institution-wide implementation.

RESULTS

Systematic intervention and retraining normalized K+ concentrations and lowered the percentage of venipunctures with K+ above 5.2 mmol/L, leading to a marked increase in phlebotomist compliance. This change resulted in resources savings of 13% to 100% for individual phlebotomists, reducing the total extra laboratory time required for repeat phlebotomies to determine hyperkalemia, mostly in the high-volume phlebotomist group.

CONCLUSIONS

A quality-of-service algorithm that involved monitoring potassium concentrations on a per-phlebotomist basis with feedback and retraining contributed to a concrete, data-based quality improvement plan. The institution-wide implementation of this metric allowed for significant cost savings and a reduction in critical value alerts, directly affecting the quality of patient care.

Diagnosis and management of hypernatraemia in children

Hypernatraemia is most commonly caused by excessive loss of solute-free water or decreased fluid intake; less often, the aetiology is salt intoxication. Especially infants, young children and individuals with a lack of access to water are at risk of developing hypernatraemia. Diagnosis is based on detailed history, physical examination and basic laboratory tests. Correction of hypernatraemia must be slow to prevent cerebral oedema and irreversible brain damage. This article reviews the aetiology, differential diagnosis and management of conditions associated with paediatric hypernatraemia. Distinguishing states with water deficiency from states with salt excess is important for proper management of hypernatraemic patients.

Performance evaluation of the i‐Smart 300E cartridge for point‐of‐care electrolyte measurement in serum and plasma

Background

Electrolytes are measured regularly in a variety of clinical settings because electrolyte imbalance can be life‐threatening. Although arterial blood‐gas analysis reports electrolyte levels, the result often is discrepant with results from serum and plasma samples. Since prompt and accurate measurement of serum electrolyte levels could allow early treatment, point‐of‐care (POC) electrolyte analyzers would be beneficial. We evaluated a POC electrolyte analyzer cartridge based on the Clinical and Laboratory Standard Institute (CLSI) guidelines.

Methods

Precision and linearity were assessed according to the CLSI EP05‐A3 and EP06‐A guidelines, respectively. A comparison study was conducted with both serum and plasma samples according to the CLSI EP09‐A3. For serum, results from the i‐Smart 300E analyzer were compared with results from the Nova 8 and i‐Smart 30 analyzers. For plasma, results were compared among the i‐Smart 300E, Nova 8, i‐Smart 30, and Cobas c702 analyzers.

Results

Coefficients of variation in the precision analysis were all less than 5%. Linearity assessment demonstrated a coefficient of determination between 0.999 and 1.000 for all analytes. The comparison study showed a high Pearson's correlation coefficient greater than 0.9 for all analytes, instruments, and specimens.

Conclusions

The i‐Smart 300E demonstrated good analytical performance. Its use could be beneficial in terms of both efficiency and clinical outcome in point‐of‐care testing (POCT) for electrolyte levels from serum and plasma samples.

Clinical factors within a week of birth influencing sodium level difference between an arterial blood gas analyzer and an autoanalyzer in VLBWIs: A retrospective study

Neonatologists often experience sodium ion level difference between an arterial blood gas analyzer (direct method) and an autoanalyzer (indirect method) in critically ill neonates. We hypothesize that clinical factors besides albumin and protein in the blood that cause laboratory errors might be associated with sodium ion level difference between the 2 methods in very-low-birth-weight infants during early life after birth. Among very-low-birth-weight infants who were admitted to Jeonbuk National Hospital Neonatal Intensive Care Units from October 2013 to December 2016, 106 neonates were included in this study. Arterial blood sample was collected within an hour after birth. Blood gas analyzer and biochemistry autoanalyzer were performed simultaneously. Seventy-six (71.7%) were found to have sodium ion difference exceeding 4 mmol/L between 2 methods. The mean difference of sodium ion level was 5.9 ± 6.1 mmol/L, exceeding 4 mmol/L. Based on sodium ion level difference, patients were divided into >4 and ≤4 mmol/L groups. The sodium level difference >4 mmol/L group showed significantly (P < .05) higher sodium level by biochemistry autoanalyzer, lower albumin, lower protein, and higher maximum percent of physiological weight than the sodium level difference ≤4 mmol/L group. After adjusting for factors showing significant difference between the 2 groups, protein at birth (odds ratio: 0.835, 95% confidence interval: 0.760-0.918, P < .001) and percent of maximum weight loss (odds ratio: 1.137, 95% confidence interval: 1.021-1.265, P = .019) were factor showing significant associations with sodium level difference >4 mmol/L between 2 methods. Thus, difference in sodium level between blood gas analyzer and biochemistry autoanalyzer in early stages of life could reflect maximum physiology weight loss. Based on this study, if the study to predict the body's composition of extracellular and intracellular fluid is proceeded, it will help neonatologist make clinical decisions at early life of preterm infants.

Interference in Ion-Selective Electrodes Due to Proteins and Lipids

BACKGROUND

Ion-selective electrodes (ISE) have become the mainstay of electrolyte measurements in the clinical laboratory. In most automated analyzers used in large diagnostic laboratories, indirect ISE (iISE) -based electrolyte estimation is done; whereas direct ISE (dISE) -based equipment are mostly used in blood gas analyzers and in the point-of-care (PoC) setting.

CONTENT

Both the techniques, iISE as well as dISE, are scientifically robust; however, the results are often not interchangeable. Discrepancy happens between the two commonly due to interferences that affect the two measuring principles differently. Over the last decade, several studies have reported discrepancies between dISE and iISE arising due to abnormal protein and lipid contents in the sample.

SUMMARY

The present review endeavors to consolidate the knowledge accumulated in relation to interferences due to abnormal protein and lipid contents in sample with the principal focus resting on probable solutions thereof.

Effect of Hypoproteinemia on Electrolyte Measurement by Direct and Indirect Ion Selective Electrode Methods

Objective  The aim of this study was to see the effect of hypoproteinemia on electrolyte measurement by two different techniques, that is, direct ion selective electrode (ISE) and indirect ISE.

Material and Method  It was an observational study in which 90 serum samples with normal protein content (Group-1) were subjected to sodium (Na ⁺ ) and potassium (K ⁺ ) measurements by direct and indirect ISE methods. In the same way, 90 serum samples with total protein < 5 g/dL (Group-2) were subjected to Na ⁺ and K ⁺ measurements by direct and indirect ISE methods.

Result  In samples from Group-1 patients, average Na ⁺ was 138.1 ± 4.764 mmol/L by direct ISE method and 139.3 ± 3.887 mmol/L by indirect ISE method while average K ⁺ was 4.41 ± 0.644 mmol/L by direct ISE method and 4.40 ± 0.592 mmol/L by indirect ISE method. There was no statistically significant difference in Na ⁺ and K ⁺ values measured by different methods. In samples from Group-2 patients, measured value of Na ⁺ by direct ISE and indirect ISE was 134.57 ± 5.520 mmol/L and 138.64 ± 5.401 mmol/L, respectively. Difference between these two values was statistically significant with p -value of < 0.0001, but direct ISE and indirect ISE measured values of K ⁺ was 4.146 ± 0.9639 mmol/L and 4.186 ± 0.8989, respectively, with no significant difference.

Conclusion  Direct and indirect ISE methods are not comparable and showing significantly different results for Na ⁺ in case of hypoproteinemia. So, it is recommended that setups like intensive care unit or emergency department, where electrolyte values have significant treatment outcome, should follow direct ISE method and should compare its previous result with the same method. Both the methods should not be used interchangeably.

Discrepancies in Electrolyte Measurements by Direct and Indirect Ion Selective Electrodes due to Interferences by Proteins and Lipids

Objectives  We aim to report the simultaneous effect of different protein and lipid concentrations on sodium (Na ⁺ ) and potassium (K ⁺ ) measurement by direct and indirect ion selective electrodes (dISE and iISE) in patient samples.

Materials and Methods  Na ⁺ and K ⁺ were measured in 195 serum samples received in the laboratory using iISE by Roche Modular P800 autoanalyzer and using dISE by XI-921 ver. 6.0 Caretium electrolyte analyzer. Serum total protein (TP), cholesterol (Chol), and triglycerides (TG) were measured using conventional photometric methods on Roche Modular P800 autoanalyzer. Differences for each pair of results for Na ⁺ (Diff_Na ⁺ = [Na ⁺_dISE– Na ⁺_iISE ]) and K ⁺ (Diff_K ⁺ = [K ⁺_dISE– K ⁺_iISE ]) were calculated. Patient subgroups with high, normal, or low TP (< 5, 5–7.9, or ≥ 8 g/dL), Chol (< 150, 150–299, or ≥300 mg/dL), or TG (< 150, 150–299, or ≥300 mg/dL) were compared using analysis of variance. Note that 95% confidence interval of Diff_Na ⁺ and Diff_K ⁺ were calculated to see the number of samples showing clinically significant differences.

Results  Diff_Na ⁺ ( p = 0.007) and Diff_K ⁺ ( p = 0.002) were found significant between samples with normal and high TP. However, effect of TG was not significant. Chol concentration affected Diff_Na ⁺ significantly between low versus normal ( p = 0.002), and high versus normal ( p = 0.031) Chol groups. Diff_K ⁺ was significant ( p = 0.009) between low versus normal Chol. Clinically relevant disagreement of ≥|5| mmol/L for Na ⁺ was observed in high percentage of samples including all subcategories; however, for K ⁺ only 3.6% of the total samples showed disagreement of ≥ |0.5| mmol/L. A multivariate regression equation based on fit regression model was also derived.

Conclusion  Summarily, interchangeable use of electrolyte results from dISE and iISE is not advisable, especially in a setting of hyperproteinemia (≥8 g/dL) or hypercholesterolemia (≥300 mg/dL); more so for Na ⁺ .

Vecuronium- and Esmolol-Induced Pseudohypernatremia Due to Drug Interference With Ion-Selective Electrodes

Objectives

We observed that patients treated with continuous vecuronium or esmolol infusions showed elevated plasma sodium measurements when measured by the routine chemistry analyzer as part of the basic metabolic panel (Vitros 5600; Ortho Clinical Diagnostics, Raritan, NJ), but not by blood gas analyzers (RAPIDLab 1265; Siemens, Tarrytown, NY). Both instruments use direct ion-selective electrode technology, albeit with different sodium ionophores (basic metabolic panel: methyl monensin, blood gas: glass). We questioned if the basic metabolic panel hypernatremia represents artefactual pseudohypernatremia.

Design

We added vecuronium bromide or esmolol hydrochloric acid to pooled plasma samples and compared sodium values measured by both methodologies. We queried sodium results from the electronic medical records of patients admitted at Children's Hospital of Philadelphia from 2016 to 2018 and received vecuronium and/or esmolol infusion treatment during their admissions.

Setting

PICU of a quaternary, free-standing children's hospital.

Patients

Children admitted to the hospital who received vecuronium and/or esmolol infusion.

Measurements and Main Results

Sodium was measured in pooled plasma samples by basic metabolic panel and blood gas methodologies after adding vecuronium bromide or esmolol hydrochloric acid, leading to a dose-response increase in basic metabolic panel sodium measurements. A repeated measures regression analysis of our electronic medical records showed that the vecuronium dose predicted the Δ sodium (basic metabolic panel-blood gas) sodium within 12 hours of the vecuronium administration (p < 0.0018). Esmolol showed a similar trend (p = 0.13). This occurred primarily in central line samples with continuous vecuronium or esmolol infusions.

Conclusions

Vecuronium and esmolol can falsely elevate direct ion-selective electrode sodium measurements on Vitros chemistry analyzers. Unexpectedly high sodium measurements in patients receiving vecuronium and/or esmolol infusions should be further investigated with an alternate sample type (i.e., peripheral blood) or measurement methodology (i.e., blood gas) to guide treatment decisions.

Isotonic versus Hypotonic Intravenous Maintenance Fluids in Children: A Randomized Controlled Trial

OBJECTIVE

To compare the incidence of hyponatremia during the first 48 h in hospitalized children receiving normal saline vs. N/2 saline as maintenance intravenous fluid.

METHODS

This open label, randomized controlled trial to compare the incidence of hyponatremia in hospitalized children receiving normal saline (0.9% sodium chloride in 5% dextrose) vs. N/2 saline (0.45% sodium chloride in 5% dextrose) as maintenance fluid was conducted from December 2014 through November 2015 in a tertiary care teaching hospital. Children between 1 mo and 18 y requiring maintenance intravenous fluids were randomized to receive normal saline with 5% dextrose (n = 75) or N/2 saline with 5% dextrose (n = 75).

RESULTS

Both groups were comparable for demographic variables and illness severity at baseline. Incidence of hyponatremia at 24 h of hospitalization was comparable between normal saline and N/2 saline group, 3(4%) vs. 6(8%) cases, respectively; p value 0.494. Mean serum sodium levels were marginally higher in normal saline group (138.3 ± 6.0 mEq/L) as compared with N/2 saline group (135.1 ± 4.4 mEq/L) (p value <0.01) at 24 h of hospitalization. Incidence of hyponatremia at 48 h and hypernatremia at 24 and 48 h was comparable in two groups.

CONCLUSIONS

The use of either N/2 saline or normal saline in sick children at standard maintenance fluid rates is associated with low but comparable incidence of hypo or hypernatremia in first 24 h of hospitalization. Both types of fluids appear acceptable in hospitalized sick children.

Determination of Electrolytes in Critical Illness Patients at Different pH Ranges: Whom Shall We Believe, the Blood Gas Analysis or the Laboratory Autoanalyzer?

Introduction

The determination of the electrolytes sodium and potassium is essential in critical care. In daily clinical practice, both the blood gas analyzer (ABG) and the laboratory autoanalyzer (AA) are generally applied. However, there is still uncertainty regarding the convergence of the prementioned assays, and data about the comparability dependent on the pH value are still lacking.

Materials and Methods

One hundred samples from intensive care unit patients with a range in pH values between 7.20 and 7.49 were evaluated in this retrospective cohort study. All patients suffered an infarct-related cardiogenic shock and were intubated and not under therapeutical hypothermia at the time of blood collection. We used scatter plots to compare different distributions of sodium and potassium values between the methods. Comparability of the analyses was assessed using the Bland–Altmann approach, and intraclass correlations (ICC) as estimates of interrater reliability were calculated.

Results

The mean potassium level measured on ABG was 4.33 mmol/L (SD 0.48 mmol/L), and the value obtained using the AA was 4.40 mmol/L (SD 0.55 mmol/L). A Bland–Altman comparison for total potassium measurements revealed that the limits of agreement were small (−0.241 to 0.391 mmol/L). Total ICC displayed a very good correlation of 0.949. For sodium, we found average values of 140 mmol/L (SD 5.20 mmol/L) in the AA and 140 mmol/L (SD 5.80 mmol/L) in the ABG assessment. Contrarily, the Bland–Altman comparison for sodium displayed that the 95% limits of agreement were very wide (−5.99 to 6.59 mmol/L) for total measurements as well as in every pH subgroup. Total ICC only reached a value of 0.830.

Conclusion

Data from our single-center study indicate that urgent and vital decisions based on potassium measurements can be made by trusting the value obtained on the ABG machine irrespective of pH values.

Comparison of Total Bilirubin Values Measured with ABL 735 Blood Gas Analyzer and Roche Cobas C8000 Chemistry Analyzer in Age-Segregated Pediatric Patients

Aim: Measurement of blood bilirubin levels is a crucial analysis because of the toxic effects of bilirubin on brain tissue, particularly in preterm neonates. The aim of this study was to investigate the consistency of the total bilirubin values obtained by the blood gas analyzer and the autoanalyzer.

Material and Methods: In this study, we used total bilirubin data of 407 pediatric patients from Kocaeli University Medical Faculty Education and Research Hospital Central Laboratory System. Total bilirubin data, provided that it was measured simultaneously, was obtained from ABL 735 blood gas analyzer and Roche Cobas C8000 chemistry analyzer. Pediatric patients (neonates, infant and children under 17 years old) were selected retrospectively by year between 2015-2017.

Results: Under a cut-off value (14.6 mg/dL) ABL 735 blood gas analyzer and Roche COBAS C8000 chemistry analyzer had strong correlation (r = 0.939) for total bilirubin measurements. It was found that 2-15 days old neonates give more scattered total bilirubin data by Bland Altman analysis in two measurements. Statistical analysis performed to compare whole total bilirubin data identity between two measurements: correlation coefficient was found r = 0.949 a statistically significant positive correlation (p < 0.001).

Conclusion: According to our analysis which was supported by previous studies in the literature, we can say that the compatibility between the blood gas analyzer (multi-wave-length spectrophotometric technique) and the chemistry analyzer becomes weaker when the total bilirubin levels exceed 14.6 mg/dL.

Management of electrolyte disorders: also the method matters!

Introduction: For the last few decades, electrolyte determinations in plasma or serum are carried out by reliable potentiometric methods. In recent years, a marked technical evolution has taken place, where the clinical analysis of common analytes (e.g. electrolytes) is partly moving from centralised clinical core laboratories to near-patient point-of-care testing. Methods: As the measuring principle used by point-of-care testing markedly differs from the one used in core laboratories, sodium results are not always interchangeable in critically ill patients due to the different sensitivity of the analytical methods for the electrolyte exclusion effect. Results: This effect mainly occurs in patients with decreased plasma protein values. The observed differences in generated test results might significantly affect the judgment and the treatment of electrolyte disturbances. As technical solutions are not likely to occur in the near future, clinicians and laboratorians should be well aware of this growing problem. Mathematical correction of the sodium results for plasma protein concentration may resolve the problem to a certain extent. Discussion: Although electrolyte determinations are generally very reliable, analytical interferences can occur for sodium rarely, mainly due to contamination by surfactants, benzalkonium in particular. For potassium, the major problem is hemolysis. To a lesser extent, leukocyte lysis and thrombocytopenia may also interfere. For chloride determination, the selectivity of the electrodes used is not ideal. Occasionally, false positive signals can be observed in presence of interfering ions (e.g. bromide).

Concordance of the ions and GAP anion obtained by gasometry vs standard laboratory in critical care

OBJECTIVE

To evaluate the differences observed in ion and GAP anion determinations obtained by point-of-care (POC) blood gas versus laboratory biochemical testing, and to analyze the possible errors according to the limits of normality.

MATERIAL AND METHODS

A descriptive, cross-sectional retrospective study was made to assess concordance between two diagnostic tests in patients admitted to the Critical Care Unit of Ourense University Hospital Complex (Spain), between July and November 2015, involving at least one coinciding biochemical test and POC determination. Patients under 18years of age were excluded.

RESULTS

A total of 1,073 samples were analyzed. Lin's concordance correlation coefficients for sodium, potassium and chlorine were 0.87, 0.84 and 0.72, respectively. Kappa concordance of the normality limits for sodium, potassium and chlorine was 0.63, 0.74 and 0.32. The results indicated poor correlation of the anion GAP and null concordance between POC and biochemical testing, including the value corrected for albumin.

CONCLUSIONS

Poor concordance was observed between the ion values as determined by biochemistry and blood gases; the two methods are therefore not interchangeable. Kappa agreement with normality limits was good for sodium and potassium, and weak for chlorine. Possible validity was noted in orienting the classification within the ion limits, with the exception of chlorine. No agreement was recorded in relation to the anion GAP, even that corrected for albumin.

Concordance between point-of-care blood gas analysis and laboratory autoanalyzer in measurement of hemoglobin and electrolytes in critically ill patients

BACKGROUND

We tested the hypothesis that the results of the same test performed on point-of-care blood gas analysis (BGA) machine and automatic analyzer (AA) machine in central laboratory have high degree of concordance in critical care patients and that the two test methods could be used interchangeably.

METHODS

We analyzed 9398 matched pairs of BGA and AA results, obtained from 1765 patients. Concentration pairs of the following analytes were assessed: hemoglobin, glucose, sodium, potassium, chloride, and bicarbonate. We determined the agreement using concordance correlation coefficient (CCC) and Bland-Altman analysis. The difference in results was also assessed against the United States Clinical Laboratory Improvement Amendments (US-CLIA) 88 rules. The test results were considered to be interchangeable if they were within the US-CLIA variability criteria and would not alter the clinical management when compared to each other.

RESULTS

The median time interval between sampling for BGA and AA in each result pair was 5 minutes. The CCC values ranged from 0.89(95% CI 0.89-0.90) for chloride to 0.98(95% CI 0.98-0.99) for hemoglobin. The largest bias was for hemoglobin. The limits of agreement relative to bias were largest for sodium, with 3.4% of readings outside the US-CLIA variation rule. The number of readings outside the US-CLIA acceptable variation was highest for glucose (7.1%) followed by hemoglobin (5.9%) and chloride (5.2%).

CONCLUSION

We conclude that there is moderate to substantial concordance between AA and BGA machines on tests performed in critically ill patients. However, the two tests methods cannot be used interchangeably, except for potassium.

Role of Correction Factor in Minimizing Errors While Calculating Electrolyte Values between Blood-gas Analyzer and Laboratory Autoanalyzer: A Comparative Study

Aims:

Electrolytes are charged elements that play important functions in the body. They are measured by both arterial blood–gas (ABG) analyzers and autoanalyzers (AA). In this study, we tried to find out the correction factor for sodium and potassium to establish the concordance between ABG and AA values.

Materials and Methods:

We prospectively studied 100 samples of patients, and for validation of the result, we applied our result on 30 patients later. 1.5 ml of blood collected in the 2.0 ml syringe preflushed with heparin and analyzed using blood–gas analyzer (ABG). Another sample was sent, to central laboratory, where serum Na+ and K+ concentrations were analyzed. Means, standard deviations, and coefficients of variation with Karl Pearson's correlation coefficients were found out. Deming regression analysis was performed and Bland–Altman plots were also constructed.

Results:

The mean sodium and potassium were 130.27 ± 7.85 mmol/L and 3.542 ± 0.76 mmol/L using ABG and 139.28 ± 7.89 mmol/L and 4.196 ± 0.72 mmol/L using AA. Concordance between ABG and AA is done by adding the correction factor: for sodium, correction factor is 9.01, standard error = 1.113, class interval = 6.815–11.205; and for potassium (K+), correction factor is 0.654, standard error = 0.1047, class interval = 0.4475–0.8605.

Conclusion:

The instrument type and calibration methods differ in different hospitals, so it is important that each center conducts an in-hospital study to know the correction factor before installation of an ABG, and the factor should be used accordingly to minimize all errors.

Prevalence of pseudonatremia in a clinical laboratory - role of the water content

BACKGROUND

Sodium concentration is a frequently used marker to discriminate between differential diagnoses or for clinical follow-up. Pseudonatremia, as a result of indirect ion-selective electrode (ISE) measurements in automated chemistry analyzers, can lead to incorrect diagnosis and treatment. We investigated whether the estimated water content, based on total protein and lipid concentrations, can be used to reduce diagnoses of pseudonatremia.

METHODS

Indirect and direct ISE measurements of sodium were compared in blood samples from intensive care unit (ICU) (n = 98) and random non-ICU patients (n = 100). Differences between direct measurements using whole blood and lithium-heparin plasma were also determined. Water content, estimated by a linear combination of total protein and lipid concentrations, was used to correct indirectly measured sodium concentrations. The prevalence of pseudonatremia was evaluated in the ICU patient group.

RESULTS

An absolute difference of 3 mmol/L was observed between direct measurements using lithium-heparin plasma and whole blood, with higher concentrations in plasma. Additionally, we observed that differences between indirect and direct measurements displayed a linear relationship with the estimated water content. The prevalence of pseudohypernatremia after indirect measurements (32%) was reduced when measurements were corrected for water content (19%).

CONCLUSIONS

In critically ill patients, sodium concentrations should be preferably measured by direct measurements. Whole blood is the preferred material for these measurements. For routine sodium analyses in other patients, correction using the estimated water content appears promising in reducing the prevalence of pseudohypernatremia by indirect measurements.

Point-of-Care Versus Central Laboratory Measurements of Hemoglobin, Hematocrit, Glucose, Bicarbonate and Electrolytes: A Prospective Observational Study in Critically Ill Patients

Introduction

Rapid detection of abnormal biological values using point-of-care (POC) testing allows clinicians to promptly initiate therapy; however, there are concerns regarding the reliability of POC measurements. We investigated the agreement between the latest generation blood gas analyzer and central laboratory measurements of electrolytes, bicarbonate, hemoglobin, hematocrit, and glucose.

Methods

314 paired samples were collected prospectively from 51 critically ill patients. All samples were drawn simultaneously in the morning from an arterial line. BD Vacutainer tubes were analyzed in the central laboratory using Beckman Coulter analyzers (AU 5800 and DxH 800). BD Preset 3 ml heparinized-syringes were analyzed immediately in the ICU using the POC Siemens RAPIDPoint 500 blood gas system. We used CLIA proficiency testing criteria to define acceptable analytical performance and interchangeability.

Results

Biases, limits of agreement (±1.96 SD) and coefficients of correlation were respectively: 1.3 (-2.2 to 4.8 mmol/L, r = 0.936) for sodium; 0.2 (-0.2 to 0.6 mmol/L, r = 0.944) for potassium; -0.9 (-3.7 to 2 mmol/L, r = 0.967) for chloride; 0.8 (-1.9 to 3.4 mmol/L, r = 0.968) for bicarbonate; -11 (-30 to 9 mg/dL, r = 0.972) for glucose; -0.8 (-1.4 to -0.2 g/dL, r = 0.985) for hemoglobin; and -1.1 (-2.9 to 0.7%, r = 0.981) for hematocrit. All differences were below CLIA cut-off values, except for hemoglobin.

Conclusions

Compared to central Laboratory analyzers, the POC Siemens RAPIDPoint 500 blood gas system satisfied the CLIA criteria of interchangeability for all tested parameters, except for hemoglobin. These results are warranted for our own procedures and devices. Bearing these restrictions, we recommend clinicians to initiate an appropriate therapy based on POC testing without awaiting a control measurement.

Graded interference with the direct potentiometric measurement of sodium by hemoglobin

OBJECTIVES

Sodium concentration is measured by either indirect (I_Na) or direct potentiometry (D_Na), on chemistry and gas panels, respectively. A spurious difference between these methods (ΔNa=I_Na-D_Na) can be confusing to the clinician. For example, variation in serum total protein (TP) is well known to selectively interfere with I_Na. Red cells have been suggested to interfere with D_Na, but both positive and negative interference have been reported. In this study, the effect of gas panel hemoglobin (Hb) on ΔNa was examined.

METHODS

ΔNa was calculated in 772 pairs of closely-timed chemistry and gas panels (median: 4min. apart), retrospectively collected from our critical care units, with 1 pair per patient. Hb was treated as a categorical or continuous variable and tested for linear and non-linear effects, with adjustment for 3 known influences on ΔNa-TP, bicarbonate (tCO₂), and the chemistry-gas panel glucose difference (ΔGlu).

RESULTS

Hb ranged from 3.5 to 22.0g/dL [35-220g/L]. In categorical analysis, ΔNa increased with Hb, and the effect was essentially linear. By simple regression, ΔNa rose 0.06±0.03[SE]mmol/L per 1g/dL [10g/L] increase in Hb (p<0.05), but confounding was suspected because Hb also correlated (p<10^-3) with TP, tCO₂, and ΔGlu. Using multiple regression to adjust for the confounders, ΔNa rose 0.15±0.03mmol/L per 1g/dL [10g/L] rise in Hb (p<10^-6).

CONCLUSIONS

Increasing Hb spuriously decreases D_Na and increases ΔNa. A linear correction for this artifact can reduce the discordance between I_Na and D_Na, promoting their interchangeable use.

Comparison of sodium ion levels between an arterial blood gas analyzer and an autoanalyzer in preterm infants admitted to the neonatal intensive care unit: a retrospective study

BACKGROUND

The difference in sodium ion levels determined with direct and indirect methods often exceeds the permissible limit clinically. Additionally, no previous study has assessed the difference in the sodium ion levels between direct and indirect methods in premature infants. Therefore, the present study aimed to compare sodium ion levels obtained using an arterial blood gas analyzer (ABGA; direct method) and an autoanalyzer (indirect method) to determine whether they are equivalent in premature infants.

METHODS

The present retrospective study included 450 preterm infants (weight, <2500 g) who were admitted to the neonatal intensive care unit (NICU) of our hospital between March 2012 and April 2014. We compared sodium ion levels in 1041 samples analyzed using an ABGA (Stat Profile® CCX Series, Nova Biomedical, Waltham, MA) and an autoanalyzer (ADVIA® 2400 Clinical Chemistry System, Siemens, Tarrytown, NY). The data were evaluated using Spearman's correlation coefficient analysis, Bland-Altman plot, Deming regression analysis, and multivariate logistic regression analysis.

RESULTS

The mean sodium ion levels were 134.6 ± 3.5 mmol/L using the ABGA and 138.8 ± 4.7 mmol/L using the autoanalyzer (P < 0.001). Among the 1041 samples, 957 (91.9 %) showed lower sodium ion levels with the ABGA than with the autoanalyzer and 74 (7.1 %) showed lower sodium ion levels with the autoanalyzer than with the ABGA. The incidence of hyponatremia identified using the ABGA was 51.9 % (541/1041), while the incidence of hyponatremia identified using the autoanalyzer was only 14.0 % (146/1041). The Deming regression analysis of the sodium ion levels between the ABGA and the autoanalyzer yielded the following formula: autoanalyzer Na (mmol/L) = 20.7 + (0.9 × ABGA Na [mmol/L]). In the multivariate logistic regression analysis, low plasma protein level (<4.3 g/dL) was found to be an independent risk factor for a sodium ion level difference of >4 mmol/L between the two methods (odds ratio = 2.870, P < 0.001).

CONCLUSION

The sodium ion levels determined using the ABGA and the autoanalyzer might not be equivalent in premature infants admitted to the NICU. Therefore, clinicians should be careful when diagnosing sodium ion imbalance in premature infants and providing treatment.

Are sodium and potassium results on arterial blood gas analyzer equivalent to those on electrolyte analyzer?

Objectives:

The present study was conducted with the aim to compare the sodium (Na) and  potassium (K) results on arterial blood gas (ABG) and electrolyte analyzers both of which use direct ion selective electrode technology.

Materials and Methods:

This was a retrospective study in which data were collected for simultaneous ABG and serum electrolyte samples of a patient received in Biochemistry Laboratory during February to May 2015. The ABG samples received in heparinized syringes were processed on Radiometer ABL80 analyzer immediately. Electrolytes in serum sample were measured on ST-100 Sensa Core analyzer after centrifugation. Data were collected for 112 samples and analyzed with the help of Excel 2010 and  Statistical software for Microsoft excel XLSTAT 2015 software.

Results:

The mean Na level in serum sample was 139.4 ± 8.2 mmol/L compared to 137.8 ± 10.5 mmol/L in ABG (P < 0.05). The mean difference between the results was 1.6 mmol/L. Mean K level in serum sample was 3.8 ± 0.9 mmol/L as compared to 3.7 ± 0.9 mmol/L in ABG sample (P < 0.05). The mean difference between the results was 0.14 mmol/L. Statistically significant difference was observed in results of two instruments in low Na (<135 mmol/L) and normal K (3.5-5.2 mmol/L) ranges. The 95% limit of agreement for Na and K on both instruments was 9.9 to −13.2 mmol/L and 0.79 to −1.07 mmol/L respectively.

Conclusions:

The clinicians should be cautious in using the electrolyte results of electrolyte and ABG analyzer in inter exchangeable manner.

How to Solve the Underestimated Problem of Overestimated Sodium Results in the Hypoproteinemic Patient

OBJECTIVES

The availability of a fast and reliable sodium result is a prerequisite for the appropriate correction of a patient's fluid balance. Blood gas analyzers and core laboratory chemistry analyzers measure electrolytes via different ion-selective electrode methodology, that is, direct and indirect ion-selective electrodes, respectively. Sodium concentrations obtained via both methods are not always concordant. A comparison of results between both methods was performed, and the impact of the total protein concentration on the sodium concentration was investigated. Furthermore, we sought to develop an adjustment equation to correct between both ion-selective electrode methods.

DESIGN

A model was developed using a pilot study cohort (n = 290) and a retrospective patient cohort (n = 690), which was validated using a prospective patient cohort (4,006 samples).

SETTING

ICU and emergency department at Ghent University Hospital.

PATIENTS

Patient selection was based on the concurrent availability of routine blood gas Na⁺(direct) as well as core laboratory Na⁺(indirect) results.

INTERVENTIONS

In the pilot study, left-over blood gas syringes were collected for further laboratory analysis.

MEASUREMENT AND MAIN RESULTS

There was a significant negative linear correlation between Na⁺(indirect) and Na⁺(direct) relative to changes in total protein concentration (Pearson r = -0.69; p < 0.0001). In our setting, for each change of 10 g/L in total protein concentration, a deviation of ~1.3 mmol/L is observed with the Na⁺(indirect) result. Validity of our adjustment equation protein-corrected Na⁺(indirect) = Na⁺(indirect) - 10.53 + (0.1316 × total protein) was demonstrated on a prospective patient cohort.

CONCLUSIONS

As Na⁺(direct) measurements on a blood gas analyzer are not influenced by the total protein concentration in the sample, they should be preferentially used in patients with abnormal protein concentrations. However, as blood gas analyzers are not available at all clinical wards, the implementation of a protein-corrected sodium result might provide an acceptable alternative.

Comparison of blood gas, electrolyte and metabolite results measured with two different blood gas analyzers and a core laboratory analyzer

BACKGROUND

Blood gas analyzers (BGAs) are important in assessing and monitoring critically ill patients. However, the random use of BGAs to measure blood gases, electrolytes and metabolites increases the variability in test results. Therefore, this study aimed to investigate the correlation of blood gas, electrolyte and metabolite results measured with two BGAs and a core laboratory analyzer.

METHODS

A total of 40 arterial blood gas samples were analyzed with two BGAs [(Nova Stat Profile Critical Care Xpress (Nova Biomedical, Waltham, MA, USA) and Siemens Rapidlab 1265 (Siemens Healthcare Diagnostics Inc., Tarrytown, NY, USA)) and a core laboratory analyzer [Olympus AU 2700 autoanalyzer (Beckman-Coulter, Inc., Fullerton, CA, USA)]. The results of pH, pCO₂, pO₂, SO₂, sodium (Na⁺), potassium (K⁺), calcium (Ca⁺²), chloride (Cl⁻), glucose, and lactate were compared by Passing-Bablok regression analysis and Bland-Altman plots.

RESULTS

The present study showed that there was negligible variability of blood gases (pCO₂, pO₂, SO₂), K⁺ and lactate values between the blood gas and core laboratory analyzers. However, the differences in pH were modest, while Na⁺, Cl⁻, Ca²⁺ and glucose showed poor correlation according to the concordance correlation coefficient.

CONCLUSIONS

BGAs and core laboratory autoanalyzer demonstrated variable performances and not all tests met minimum performance goals. It is important that clinicians and laboratories are aware of the limitations of their assays.

Distribution of serum total protein in elderly Chinese

The serum total protein levels of the elderly possibly decrease gradually with aging. However, serum total protein levels are not suitable as a uniform reference standard for the elderly at different ages and genders. Thus, we investigated the total serum protein distribution in different gender and age groups of 11,453 elderly individuals aged ≥60 years and without liver or renal disease from Lianyungang, Jiangsu, China. The total protein levels (TPL) of these individuals exhibited normal distribution (Z = 1.206, P = 0.109), whereas the reference range (95% CI) was 54.1 g/L to 82.3 g/L. TPL was higher in females than in males for those aged between 60 and 75 years, whereas no significant difference was observed for those aged between 80 and 95 years. TPL was negatively correlated with age in males (r = −0.1342, P<0.05), females (r = −0.304, P<0.05), and the total group (r = −0.2136, P<0.05). TPL also decreased with aging and showed a faster rate in women than in men. These results indicated that an appropriate range of serum total protein based on age and gender differences should be used for clinical applications.

Use of a blood gas analyzer and a laboratory autoanalyzer in routine practice to measure electrolytes in intensive care unit patients

Background

Electrolyte values are measured in most critically ill intensive care unit (ICU) patients using both an arterial blood gas analyzer (ABG) and a central laboratory auto-analyzer (AA). The aim of the present study was to investigate whether electrolyte levels assessed using an ABG and an AA were equivalent; data on sodium and potassium ion concentrations were examined.

Methods

We retrospectively studied patients hospitalized in the ICU between July and August 2011. Of 1,105 test samples, we identified 84 instances of simultaneous sampling of arterial and venous blood, where both Na⁺ and K⁺ levels were measured using a pHOx Stat Profile Plus L blood gas analyzer (Nova Biomedical, Waltham MA, USA) and a Roche Modular P autoanalyzer (Roche Diagnostics, Mannheim, Germany). Statistical measures employed to compare the data included Spearman's correlation coefficients, paired Student’s t-tests, Deming regression analysis, and Bland-Altman plots.

Results

The mean sodium concentration was 138.1 mmol/L (SD 10.2 mmol/L) using the ABG and 143.0 mmol/L (SD 10.5) using the AA (p < 0.001). The mean potassium level was 3.5 mmol/L (SD 0.9 mmol/L) using the ABG and 3.7 mmol/L (SD 1.0 mmol/L) using the AA (p < 0.001). The extent of inter-analyzer agreement was unacceptable for both K⁺ and Na⁺, with biases of 0.150-0.352 and −0.97-10.05 respectively; the associated correlation coefficients were 0.88 and 0.90.

Conclusions

We conclude that the ABG and AA do not yield equivalent Na⁺ and K⁺ data. Concordance between ABG and AA should be established prior to introduction of new ABG systems.

Disagreement between ion selective electrode direct and indirect sodium measurements: estimation of the problem in a tertiary referral hospital

PURPOSE

We estimated the proportion of indirect ion selective electrode (ISE) plasma sodium analyses in intensive care unit (ICU) and hospital wide, exhibiting important disagreement with direct ISE results in relation to abnormal plasma protein concentrations.

MATERIALS AND METHODS

Direct and indirect ISE plasma sodium measurements were performed on 346 clinical specimens selected to reflect low, normal, or high total protein concentrations. Important intermethod disagreement was defined as |4| mmol/L or higher. Results were extrapolated to a 3-month laboratory series of 48,033 indirect ISE assays, including 2877 samples from intensive care.

RESULTS

Intermethod sodium disagreement at |4| mmol/L or higher was predicted for 25% of ICU samples. Almost all (97%) occurred in hypoproteinemic samples where indirect tended to exceed direct ISE estimates. Hospital wide, such disagreement was projected to occur in 8% of samples, of which the majority (70%) were also hypoproteinemic.

CONCLUSIONS

Important disagreement between indirect and direct ISE sodium measurements may exist in up to 1 in 4 ICU specimens and 1 in 12 hospital-wide samples. The main problem is indirect ISE overestimation associated with hypoproteinemia, potentially leading to misclassifications of pseudohypernatremia and pseudonormonatremia. We recommend that hospital laboratories consider standardization using direct ISE sodium measurement.

Comparison of the point-of-care blood gas analyzer versus the laboratory auto-analyzer for the measurement of electrolytes

BACKGROUND

Electrolyte values are measured both by arterial blood gas (ABG) analyzers and central laboratory auto-analyzers (AA), but a significant time gap exists between the availability of both these results, with the ABG giving faster results than the AA. The authors hypothesized that there is no difference between the results obtained after measurement of electrolytes by the blood gas and auto-analyzers.

METHODS

After approval by the ethics committee, an observational cohort study was conducted in which 200 paired venous and arterial samples from patients admitted to the Medical Intensive Care Unit (ICU) of Apollo Hospital, Hyderabad, India, were analyzed for electrolytes on the ABG machine and the AA. Analyses were done on the ABL555 blood gas analyzer and the Dade Dimension RxL Max, both located in the central laboratory. Statistical analyses were performed using paired Student's t test.

RESULTS

A total of 200 paired samples were analyzed. The mean ABG sodium value was 131.28 (SD 7.33), and the mean AA sodium value was 136.45 (SD 6.50) (p < 0.001). The mean ABG potassium value was 3.74 (SD 1.92), and the mean AA potassium value was 3.896 (SD 1.848) (p = 0.2679).

CONCLUSION

Based on the above analysis, the authors found no significant difference between the potassium values measured by the blood gas machine and the auto-analyzer. However, the difference between the measured sodium was found to be significant. We therefore conclude that critical decisions can be made by trusting the potassium values obtained from the arterial blood gas analysis.