Chemistry Case Study: Falsely Elevated Methotrexate

High dose methotrexate infusion is widely used in the treatment of malignancies such as leukemia, high risk lymphoma, and osteosarcoma. It can be associated with multiple adverse effects, especially renal toxicity, which could leads to acute kidney injury (AKI), delaying drug elimination and worsening its toxicity. Leucovorin, a reduce folic acid, is commonly used with methotrexate treatment to lessen its toxicity. After administration of methotrexate, serum creatinine and methotrexate concentration should be closely monitored. The levels of serum methotrexate to be associated with a high risk for nephrotoxicity are: 24 h, > 10 μmol/L; 48 h, > 1 μmol/L; 72 h, > 0.1 μmol/L.

In this case, the patient is a 33-yo old male with T-lymphoblastic leukemia in complete remission. He was given consolidation therapy with high dose methotrexate. Leucovorin rescue was given 24 hours after methotrexate administration. Patient’s methotrexate level was at 4.7 μmol/L 3 days postinfusion due to AKI and poor methotrexate clearance. An alternative rescue, glucarpidase (Garboxypeptidase G2), was then given to patient to rapidly lower serum methotrexate level. Glucarpidase cleaves methotrexate molecule to inactive metabolite, DAMPA (2,4-diamino-N-methylpteroic acid). After glucarpidase rescue, patient’s methotrexate level were still remained above the toxic level on the following two days (1.02 μmol/L and 0.68 μmol/L).

In most clinical laboratories, serum methotrexate is measured by immunoassays, and the inactive metabolite of methotrexate after glucarpidase rescue, DAMPA, cross-reacts with immunoassays and interferes the measurement of methotrexate. After glucarpidase treatment, patient’s methotrexate level can be falsely high for 5-7 days, before accurate measurement can be obtained using immunoassays. In this case, the concentrations of methotrexate after glucarpidase rescue were falsely high results due to DAMPA interference. There are laboratory-developed LC-MS methods to detect methotrexate. LC-MS methods are more specific and have no interference from the metabolite, can be used for accurate methotrexate measurement in the case of glucarpidase rescue.



-Xin Yi, PhD, DABCC, FACB, is a board-certified clinical chemist, currently serving as the Co-director of Clinical Chemistry at Houston Methodist Hospital in Houston, TX and an Assistant Professor of Clinical Pathology and Laboratory Medicine at Weill Cornell Medical College.

Jaffe vs. Enzymatic Method for Serum Creatinine Measurement

The Jaffe and enzymatic methods are the two most common methods for measuring serum creatinine. The Jaffe method is less expensive than the enzymatic assay ($0.30 vs $2.00 per test based on 2014 list prices) but is more susceptible to interferences. Although these tests are not expensive, they are high-volume tests and the savings could be substantial. We were using the enzymatic assay at the University of Utah and estimated that we could save about $50,000 per year by switching to the Jaffe assay; however, we were uncertain whether the Jaffe assay was safe to use due to the potential for interferences. For that reason, we decided to conduct a risk assessment to evaluate the suitability of the Jaffe assay.

Risk is defined as the expected cost of an action. The expected cost has two components: 1) the probability that an event will occur and 2) the consequences or cost of an event:

Risk = prob(event) x cost(event)

The event of interest was misclassification of a patient due to an error in serum creatinine measurement. Nephrologists classify kidney disease based on the estimated glomerular filtration rate which is based on the creatinine value. The distribution of eGFR for patients at our hospital is shown in Figure 1. The dashed lines show decision limits that nephrologists use to classify kidney disease. An eGFR is considered normal or healthy.

We spoke with the nephrologists and learned that they were relatively unconcerned about errors in eGFR in healthy patients (eGFR above 60 ml/min) because there was no potential for harm. Similarly, they felt there was relatively little risk of harm to patients with low eGFRs because these patients are routinely monitored and no major decision would be based solely on a single eGFR measurement. An error in creatinine measurement in a low eGFR patient would be detected by repeat measurements or be inconsistent with other measurements. From the nephrologists’ point of view, the only area of concern was in the region around 60 ml/min.  Patients about 60 ml/min are considered healthy whereas those below 60 ml/min are diagnosed with stage 3a chronic kidney disease. In this zone, an error in serum creatinine could result in a false negative (i.e. observed eGFR greater than 60 ml/min when the true eGFR was less than 60 ml/min). In such cases, a patient may go without care and their disease could progress.  The nephrologists believed that the potential for harm was relatively minor, but potential for harm did exist.

We compared the eGFRs provided by the enzymatic and Jaffee methods to estimate how often patients might be misclassified (Figure 2).1 Focusing on the 60 ml/min decision limit, we found that 17 of 500 (3.4%) of measurements were discordant. Some of these discordant results would be due to imprecision. Discordance due to imprecision would have small differences (bottom of Figure 2) and are unavoidable – they would occur using any method. Discordance due to interference would be expected to have larger differences (top of Figure 2) and could be avoided by using the enzymatic method. We used statistical techniques to estimate the proportion of discordances that were due to interference vs imprecision and found that about 60% of the discordance at the 60 ml/min limit was due to interference. In summary, our risk analysis showed that using the Jaffe method would pose about a 2% rate of avoidable misclassification which presented some potential risk to patients. The nephrologists felt the risk was low but, in theory, disease could unnecessarily progress in a patient with a false negative diagnosis.

Our risk analysis was based on analytical error. We compared magnitude of analytical error to the biological variation in eGFR and found that the analytical error was relatively small in comparison to biological variation (data not shown).  Biological variation was likely to be a more significant cause of misclassification than analytical error.

So, what to do? Was the potential savings of the Jaffe method worth the risk? Some experts recommend against using the Jaffe method. 2-4 On the other hand, most US laboratories use the Jaffe assay. A recent College of American Pathologists proficiency challenge found that 70% of the submitted results were based on the creatinine assay.5

We decided to get the best of both worlds by using BOTH methods. We defined a zone of risk surrounding the 60 ml/min eGFR decision limit (Figure 3). Results in this zone would have some risk of misclassification whereas results outside of the zone would be unlikely to be misclassified using the Jaffee method. All creatinine measurements are initially performed using the Jaffe method. If the result is outside the risk zone, the result is reported. If results fell within the risk zone, they were repeated with the enzymatic method and the results of the enzymatic method are reported. This reflex procedure saves money while avoiding risk. The reflex rate is approximately 15%.

There are circumstances in which one would want to order the best possible test. To that end, we created a special orderable test, based on the enzymatic method, that the nephrologists could use to insure the most accurate results when required. For example, the enzymatic test may be indicated when making decisions regarding biopsies for renal transplant patients. The order volume for the special test has been less than 100 orders per year. 

Figure 1. Distribution of Estimated Glomerular Filtration rates (eGFR). The distribution is for outpatients at University of Utah for calendar year 2014. The dashed lines indicate decision limits used for classification of chronic kidney disease (15, 30, 45 and 60 ml/min). eGFRs greater than 60 ml/min are considered disease free.
Figure 2. Discordances in estimated glomerular filtration rate (eGFR) at the 60 ml/min decision limit. The length of each arrow, represents the difference between estimates based on the Jaffe (head) and enzymatic (tail) methods. The dashed line represents two standard deviations of expected imprecision of the difference. Differences greater than 2 standard deviations would most likely be due to analytical interference (loss of specificity).
Figure 3. Reflex test strategy. The figure shows the distribution of eGFR values for outpatients at the University of Utah.  The dashed lines represent clinical decision limits. The yellow zone represents the range of eGFR values where misclassification could pose a risk to patients. Creatinine is first measured by the Jaffe method. The Jaffe result is reported if the estimated eGFR is outside the yellow zone. If the eGFR is within the yellow zone, the measurement is repeated using the enzymatic method and the result based on the enzymatic method is reported.


  1. Schmidt RL, Straseski JA, Raphael KL, Adams AH, Lehman CM. A Risk Assessment of the Jaffe vs Enzymatic Method for Creatinine Measurement in an Outpatient Population. PloS one. 2015;10(11):e0143205.
  2. Cobbaert CM, Baadenhuijsen H, Weykamp CW. Prime time for enzymatic creatinine methods in pediatrics. Clinical Chemistry. 2009;55(3):549-558.
  3. Drion I, Cobbaert C, Groenier KH, et al. Clinical evaluation of analytical variations in serum creatinine measurements: Why laboratories should abandon Jaffe techniques. BMC Nephrology. 2012;13(1).
  4. Panteghini M. Enzymatic assays for creatinine: time for action. Scand J Clin Lab Invest Suppl. 2008;241:84-88.
  5. College of American Pathologists. Chemistry/Therapeutic Monitoring, Participant Survey. 2014.



-Robert Schmidt, MD, PhD, MBA, MS is currently an Associate Professor at the University of Utah where he is Medical Director of the clinical laboratory at the Huntsman Cancer Institute and Director of the Center for Effective Medical Testing at ARUP Laboratories.

Chemistry Case Study: Protein Bands in All Lanes of the Immunofixation Electrophoresis

Waldenstrom Macroglobulinemia (WM) is defined as lymphoplasmacytic lymphoma (LPL) with IgM paraprotein and bone marrow involvement. The IgM paraprotein is an important serum marker for WM diagnosis, symptom prediction, disease burden assessment, treatment decision and drug response evaluation. Serum protein electrophoresis (SPEP) in conjunction with immunofixation electrophoresis (IFE) are the routine laboratory tests for IgM paraprotein detection, quantitation and characterization. A monoclonal protein typically presents as a sharp band on SPEP and selective lanes of IFE, allowing characterization of the immunoglobulin heavy chain isotypes and light chain classes. In rare situations, a monoclonal band is seen on all immunofixation lanes, suggesting cryoglobulin and/or soluble immune complex. We encountered a recent case of WM with a strong demarcated band on all immunofixation lanes.

The patient is a 76-year-old Chinese man diagnosed as WM/LPL by bone marrow biopsy. Peripheral blood showed pancytopenia with rouleaux formation. The serum IgM was up to 6900 mg/dL. Serum viscosity was increased up to 3.1 cP (normal range 1.5-1.9 cP). Serum rheumatoid factor was negative (<10 IU/ml). Serum protein electrophoresis (SPEP) on Sebia Hydrasys 2 showed a wide smearing pattern (Fig 1A). Serum protein immunofixation electrophoresis (IFE) showed a monoclonal band on all lanes with equal intensity, preventing isotype identification (Fig 1B). This pattern is generally believed to be due to cryoglobulin and/or polymerization of monoclonal proteins, similar to rheumatoid factor activity. Urine electrophoresis was consistent with an overflow pattern and urine immunofixation showed monoclonal free lambda light chain.

Previously it was demonstrated that cryogolublin dissolution was achieved by pre-treatment of serum samples with Fluidil. The IgM polymer can be disrupted by adding reducing agents such as beta-mercaptoethanol (bME) to disrupt the disulfide bonds (1-2). In our case, despite pretreatment with Fluidil and bME, no isotype resolution was achieved on serum IFE, prompting us to develop a novel method through the addition of sodium dodecyl sulfate (SDS) to the pretreatment process. Different combinations of reaction conditions were tested, including SDS concentration ranging from 0.01 to 1%, three different temperatures (37, 56 and 95 °C), three different concentrations of bME (1%, 2% and 4%) and three different serum volume (25 µL, 50 µL and 75 µL). Optimal isotype resolution was achieved using 0.1% SDS/0.25%bME/Fluidil incubated at 56°C for 30 mins (Fig 1C).




  1. Attaelmannan M, Levinson SS. Understanding and identifying monoclonal gammopathies. Clin Chem. 2000 Aug; 46(8 Pt 2):1230-8.
  2. Yusra Othman. Protein Bands in All Lanes of the Immunofixation Electrophoresis Pattern of Serum From a 50-Year-Old Saudi Woman. Lab Med (2006) 37 (3): 152-154.



-Huifei Liu, MD, PhD. Former PGY4 resident in the Department of Pathology and Genomic Medicine, Houston Methodist Hospital. She currently serves as the associate medical director at Hematologics, Inc., Seattle, WA.  


-Xin Yi, PhD, DABCC, FACB, is a board-certified clinical chemist, currently serving as the Co-director of Clinical Chemistry at Houston Methodist Hospital in Houston, TX and an Assistant Professor of Clinical Pathology and Laboratory Medicine at Weill Cornell Medical College.

Pathologist On Call: Fluctuating Parathyroid Hormone with Normal Calcium in an Elderly Man


A 75 year old Alzheimer’s dementia patient.  Parathyroid hormone (PTH) levels were ordered.




05/13 10/13 12/13 7/14 10/14 04/15 09/15 03/16 07/16

(10-65 pg/mL)

869 42 864 47 1180 48

(8.8-10.2 mg/mL)

10.3 10.5 10 10 9.6 10
Vit D

(2-100 ng/mL)

26 21 39 49 39 57 19


Why order PTH? 

PTH is ordered to assess for hyperparathyroidism.  There are two forms of hyperparathyroidism: primary and secondary.  Primary hyperparathyroidism can be caused by a parathyroid (PT) adenoma,  PT hyperplasia, or a non-PT malignancy such as squamous cell cancer or multiple myeloma.  Secondary hyperparathyroidism occurs in response to hypocalcemia which can arise from insufficient intake of vitamin D or chronic renal failure (which results in insufficient vitamin D).   There is weak evidence suggesting a positive correlation between PTH and cognitive decline.(1, 2)  Progression of cognitive decline is slowed when PTH and vit D levels are normalized.

Action of PTH: PTH is a peptide hormone that controls calcium levels in the blood. It is secreted as a prohormone and is cleaved in the blood.  The 34 residue N-terminal fragment is active and has a half-life of about 5 minutes.  The C-terminal end has a half-life or 2 hours and is diagnostically insignificant because it is physiologically inactive.  PTH activates receptors on osteoclasts which causes them to release bone calcium.  PTH also increases renal synthesis of 1,25 OH2 vitamin D which, in turn, increases intestinal absorption of calcium.

What would make the PTH level fluctuate so much?

This is most likely a case of incipient normocalcemic primary hyperparathyroidism (NPH).(3-5)  PTH levels are higher than normal but calcium levels are normal.  PTH levels tend to fluctuate. Calcium can also be sometimes elevated as well.   The disease is thought to be a mild or early form of hyperparathyroidism and 20 percent of patients go on to develop worsening hyperparathyroidism. How should NPH be managed?  Parathyroidectomy or monitoring are the primary alternatives; however, the best way to manage this disease is unknown.



  1. Lourida I, Thompson-Coon J, Dickens CM, et al. Parathyroid hormone, cognitive function and dementia: A systematic review. PLoS ONE 2015;10.
  1. Björkman MP, Sorva AJ, Tilvis RS. Does elevated parathyroid hormone concentration predict cognitive decline in older people? Aging Clinical and Experimental Research 2010;22:164-9.
  1. Shlapack MA, Rizvi AA. Normocalcemic primary hyperparathyroidism-characteristics and clinical significance of an emerging entity. Am J Med Sci 2012;343:163-6.
  1. Lowe H, McMahon DJ, Rubin MR, Bilezikian JP, Silverberg SJ. Normocalcemic primary hyperparathyroidism: Further characterization of a new clinical phenotype. Journal of Clinical Endocrinology and Metabolism 2007;92:3001-5.
  1. Crowley RK, Gittoes NJ. Elevated PTH with normal serum calcium level: A structured approach. Clinical Endocrinology 2016;84:809-13.



-Robert Schmidt, MD, PhD, MBA, MS is currently an Associate Professor at the University of Utah where he is Medical Director of the clinical laboratory at the Huntsman Cancer Institute and Director of the Center for Effective Medical Testing at ARUP Laboratories.



Chemistry Case Study: Unexplained Metabolic Acidosis

Case Workup

A 24-year-old female at 34 weeks of gestation was transferred from an outside hospital with history of nephrolithiasis and right side pyelonephritis, for which she underwent stent placement 2 weeks ago. She started experiencing severe pain and muscle spasms in her hip and was unable to move her leg due to the pain. She had decreased appetite and also noted vomiting. Her bilirubin and aminotransferases were found to be elevated. Additionally, her blood gas analysis showed a bicarbonate of 9 mEq/L, pH of 7.2 with 99% SpO2. Our clinical chemistry team was consulted on her low pH.

Patient’s laboratory workup is shown in the table below. We first ruled out some common causes of metabolic acidosis, including lactic acidosis and diabetic ketoacidosis. Ingestion of toxic alcohols was ruled out based on normal osmolality and osmolar gap. Normal BUN, creatinine, and their ratio ruled out renal failure.

Positive urinary ketones were noted, with an elevated anion gap. Serum beta-hydroxybutyrate was therefore measured and a result of 3.0 mmol/L (ref: <0.4 mmol/L) confirmed ketoacidosis. Patient had no history of diabetes and no recent alcohol consumption. On the basis of excluding other causes, and also considering her decreased appetite and recurrent vomiting, it is believed that ketoacidosis was caused by “starvation.”

Test Result Ref * Test Result Ref *
Albumin 2.0 3.5 – 5.0 g/dL pH 7.24 7.32-7.42
ALK 139 35 – 104 U/L pCO2 (V) 21 45-51 mmHg
ALT 177 5 – 50 U/L pO2 (V) 46 25-40 mmHg
AST 159 10 – 35 U/L O2 Sat (V) 72 40 – 70 %
Total Bili 2.0 0.0 – 1.2 mg/dL Glucose 74 65-99 mg/dL
Direct Bili 1.5 0.0 – 0.3 mg/dL Urine ketones 2+ Negative
Lactic acid 0.9 0.5 – 2.2 mmol/L Urine protein 2+ Negative
Protein 6.0 6.3 – 8.3 g/dL Chloride 104 98-112 mEq/L
Sodium 138 135-148 mEq/L CO2 9 24-31 mEq/L
Potassium 4.6 3.5-5.0 mEq/L Anion gap 25 7-15 mEq/L
Creatinine 0.6 0.5 – 0.9 mg/dL eGFR >90  >90 mL/min/1.73 m2
BUN 8 6 – 20 mg/dL Osmolality 286 275 – 295 mOsm/kg

* Reference ranges are for normal adults, not for pregnant women.


With optimal glucose level and sufficient insulin secretion, glucose is converted by glycolysis to pyruvate, which is then converted into acetyl-CoA and subsequently into the citric acid cycle to release chemical energy in the form of ATP. When glucose availability becomes limited, fatty acid is used as an alternative fuel source to generate acetyl-CoA. Ketone bodies are generated in this process, and their accumulation result in metabolic acidosis. In healthy individual, fasting is seldom suspected to be the cause of metabolic acidosis. Sufficient insulin secretion prevents significant free fatty acid accumulation. However, under certain conditions when there is a relatively large glucose requirement or with physiologic stress, 12 to 14 hour fast could lead to significant ketone bodies formation, resulting in overt ketoacidosis (1-3).

Ketoacidosis is most commonly seen in patients with diabetic ketoacidosis. Similar metabolic changes are seen with poor dietary intake or prolonged fasting and resulting acidosis is referred to as “starvation ketoacidosis” (2). During pregnancy, especially in late pregnancy, there is an increased risk for starvation ketoacidosis, due to reduced peripheral insulin sensitivity, enhanced lipolysis, and increased ketogenesis. In this setting, short period of starvation can precipitate ketoacidosis (1-2, 4). Other cases described with starvation ketoacidosis include patients on strict low-carbohydrate diet (5-6), young infants after fasting (7), and patients with prolonged fasting before surgery (3).

Although starvation ketoacidosis is rare, healthcare provider should be aware of this entity especially in pregnant patients, because late recognition and delay in treatment are associated with a greater risk for impaired neurodevelopment and fetal loss (2). Moreover, given the popularity of low-carbohydrate diet nowadays, starvation ketoacidosis should be considered when assessing patient’s acid-base imbalance in conjunction with their dietary lifestyles.


  1. Frise CJ,Mackillop L, Joash K, Williamson C. Starvation ketoacidosis in pregnancy. Eur J Obstet Gynecol Reprod Biol. 2013 Mar;167(1):1-7.
  2. Sinha N,Venkatram S, Diaz-Fuentes G. Starvation ketoacidosis: a cause of severe anion gap metabolic acidosis in pregnancy. Case Rep Crit Care. 2014;2014:906283.
  3. Mostert M, Bonavia A. Starvation Ketoacidosis as a Cause of Unexplained Metabolic Acidosis in the Perioperative Period. Am J Case Rep. 2016; 17: 755–758.
  4. Mahoney CA. Extreme gestational starvation ketoacidosis: case report and review of pathophysiology. Am J Kidney Dis. 1992 Sep;20(3):276-80.
  5. Shah P,Isley WL. Ketoacidosis during a low-carbohydrate diet. N Engl J Med. 2006 Jan 5;354(1):97-8.
  6. Chalasani S, Fischer J. South Beach Diet associated ketoacidosis: a case report. J Med Case Rep. 2008;2:45. Epub 2008 Feb 11.
  7. Toth HL, Greenbaum LA. Severe acidosis caused by starvation and stress. Am J Kidney Dis. 2003;42(5):E16.



-Xin Yi, PhD, DABCC, FACB is a board-certified clinical chemist. She currently serves as the Co-director of Clinical Chemistry at Houston Methodist Hospital in Houston, TX and an Assistant Professor of Clinical Pathology and Laboratory Medicine at Weill Cornell Medical College.

Vitamin Deficiency or Acute Leukemia?

67 year old patient with a history of uterine carcinoma (leiomyosarcoma), presented with pancytopenia and history of B-12 deficiency. CBC showed

  • WBC 4.1 K/ul
  • RBC *2.37 M/ul
  • Hgb *7.2 g/dl
  • MCV 91.1 fl
  • MCH 30.4 pg
  • MCHC 33.3 %
  • Platelets *25 K/ul

Peripheral blood differential count showed 3.5 % bands, 68.5 % Neutrophils, 3.5 % Eosinophils, 11.5 % Lymphocytes and 13.0 % Monocytes

Bone marrow differential count of the bone marrow showed 65.0 % Erythroid Precursors with 48.4% erythroblasts and 7% myeloblasts

Several erythroblasts were seen, which often had overlapping morphological features with myeloblasts. Erythroblasts had slightly coarser nuclear chromatin compared to myeloblasts and often had deeply basophilic vacuolated cytoplasm. Erythroid maturation was markedly megaloblastic /dysplastic and left shifted with marked preponderance of erythroblasts. Dysplastic forms characterized by presence of precursors with irregular nuclear borders along with few multinucleated forms and gigantoblasts were present.

Cells counted as myeloblasts had high N/C ratio, finer nuclear chromatin with occasionally distinct 1 to 2 nucleoli and scant cytoplasm.

Bone marrow with erythroid hyperplasia
Bone marrow with erythroid hyperplasia
Megaloblastic erthroid precursors with binucleate forms
Megaloblastic erthroid precursors with binucleate forms


The current WHO classification subtypes acute erythroid leukemia into two categories based on the presence or absence of significant myeloid component.

Erythroleukemia or Erythroid/Myeloid (FAB subtype A – M6a) comprises of more than 50% erythroid precursors among all nucleated cell population of bone marrow and more than 20% myeloblasts among non erythroid cells.

Pure erythroid leukemia (FAB subtype B – M6b) comprises of more than 80% immature cells of erythroid lineage with no evidence of a significant myeloid component

The most common reactive process that can mimic acute erythroid leukemia is megaloblastic anemia caused by vitamin B12 and folate deficiency. Features associated with pernicious anemia are hemolysis with increased mean corpuscular volume (MCV), hypersegmented neutrophils, leukopenia and thrombocytopenia increased LDH and urobilinogen. Bone marrow findings show hypercellular marrow witn marked erythroid hyperplasia. Other non-neoplastic diseases mimicking acute erythroid leukemia are post-chemotherapy recovery, parvovirus infection, drug effect, heavy metal intoxication and congenital dyserythropoiesis. A detailed clinical history, laboratory work up, peripheral blood and bone marrow examination, cytochemical, immunoshistochemical, flow cytometry, cytogenetic and molecular studies are required for the diagnosis of acute erythroid leukemia.

The oncologist was contacted and it was confirmed that B12 was repleted before the bone marrow study was performed. Diagnosis of acute erythroid /myeloid leukemia was only made after it was confirmed with the oncologist that patient was not B12 deficient at the time of the study.


-Neerja Vajpayee, MD, is an Associate Professor of Pathology at the SUNY Upstate Medical University, Syracuse, NY. She enjoys teaching hematology to residents, fellows and laboratory technologists.

Sample Stability and PO2–A Learning Opportunity

One of the interesting things about working in the field of laboratory medicine is that there are always opportunities for learning new things. Almost every call I get from my colleagues outside the lab allows me and the lab team these opportunities. And sometimes we are reminded of the reason we do the things we do, basically re-learning them.

Case in point: An ICU physician contacted the lab, understandably concerned. He had been monitoring the pO2 in a patient using an I-Stat point of care analyzer. Values had been in the range of 50-70 mmHg, and he had been adjusting ventilation on the basis of those results. A blood gas sample was sent to the main lab, analyzed on an ABL analyzer and gave a result of 165 mmHg, repeated shortly thereafter on a new sample with a 169 mmHg. Understandably, the physician wanted to know which analyzer was wrong and how he should be adjusting his patient’s ventilation.

We quickly did an investigation and determined an interesting fact that we hadn’t paid much attention to previously. A blood gas sample that is sent through the tube system that has any amount of air in the sample, will give falsely elevated pO2 result. We investigated this by collecting blood gas samples, running them on both the I-Stat and the ABL, and then sending them through the tube system and rerunning them on both instruments after tubing. The pO2 values matched on both instruments, both before and after tubing. But interestingly, if there was any air in the collection device when the device was sent through the tube system, the pO2 after tubing still matched on the two instruments, but the values were more than double the original values. If no air was present, there was very little change before and after tubing. We tested this by expressing all air from one set of samples before tubing and leaving air in the syringe on the other set.

The collection process for blood gas samples in our institution has always specified that the collector should express any air in the sample before sending the sample to the lab through the tube system, and after this incident the reason for that step became clear. However, the staff collecting blood gases on the floors needs to be periodically retrained in the collection, and the lab staff needs to be reminded that air in a blood gas syringe arriving through the tube station is a reason to reject the sample. We were reminded that education needs to be a continuous process. We also learned that when we discover the reason for a process, it’s a good idea to document that reason in order to both understand the need and to help motivate people to follow it.

-Patti Jones PhD, DABCC, FACB, is the Clinical Director of the Chemistry and Metabolic Disease Laboratories at Children’s Medical Center in Dallas, TX and a Professor of Pathology at University of Texas Southwestern Medical Center in Dallas.