Ana-Maria Šimundić
Department of Medical Laboratory Diagnostics
University Hospital "Sveti Duh"
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Case report:


Goce Dimeski*, Kendra Bassett, Nigel Brown.Paraprotein interference with turbidimetric gentamicin assay. Biochemia Medica 2015;25(1):117-24


Department of Chemical Pathology, Pathology Queensland, Princess Alexandra Hospital, Brisbane, Australia

*Corresponding author: goce_dimeski [at] health [dot] qld [dot] gov [dot] au




Introduction: Gentamicin due to its low level of resistance and rapid bactericidal activity is commonly used to treat gram-negative bacteria. However, due to its toxic effects it needs to be monitored. To date, no interference has been reported with gentamicin assays. 

Materials and methods: A patient with leg cellulitis and sepsis received a single dose of gentamicin and a sample was sent for gentamicin analysis. The sample showed high blank absorbance readings on Beckman DxC800 and DC800 analysers with various dilutions. A second sample was received and analysed on a Roche Cobas system to obtain a result. A third sample was received 107 hours later with the same results and this sample was then analysed neat and post ethanol precipitation on all the turbidimetric assays available on the DxC800 analyser.

Results: The high blank absorbance was observed upon addition of the reactive reagents due to protein precipitation. Although not obvious from the patient protein results, it was shown the presence of high IgM paraprotein, 18.9 g/L (reference range 0.4-2.3 g/L) was the cause of precipitation, giving high blank readings. Of all the other turbidimetric assays, only vancomicin and valproate showed similar high blank absorbance readings. To be able to provide more rapid results it was shown ethanol could be used as a precipitant of proteins in both calibrators and patient samples with acceptable recovery.

Conclusion: IgM paraprotein was identified as the cause of interference with the gentamicin, vancomicin and valproate assays. Protein interference in these assays can be overcome by precipitation with ethanol. 

Key words: turbidimetry; IgM; paraprotein; interference

Received: December 01, 2014                                                                                                   Accepted: January 15, 2015




Gentamicin belongs to the aminoglycosides group of antibiotics which are among the oldest antibiotics available to treat serious infections caused primarily by gram-negative bacteria. When the use of aminoglycosides became more widespread, the toxic effects, ototoxicity and nephrotoxicity, became more apparent and there was a switch to other, safer, antimicrobial agents, and the use of aminoglycosides sharply declined. However, the development of multi-drug resistance among bacteria has now led to resurgent use of the aminoglycosides in the treatment of serious infections. Not only does gentamicin offer comparable low levels of resistance but it is rapid in its bactericidal activity. However due to toxicity, there is a need to monitor plasma concentrations to prevent the rare occurrence of sudden idiosyncratic deafness and nephrotoxicity with prolong therapy (1,2). Even though guidelines exist for monitoring plasma concentrations (3) a recent study reported 20% of collected samples were outside the required sampling window (6 -14 hours post dose), and 15% of doses were adjusted without monitoring and approximately half of all dose adjustments were based on inadequate information or inaccurate nomogram interpretation (4).

Serum protein abnormalities have been shown to interfere with turbidimetric assays such as vancomicin on the Beckman DxC800 general chemistry analyzer (5). Interferences have also been reported with other turbidimetric assays, C-reactive protein (6,7) phenytoin (8), and transferrin (9), as well as with nephelometric assays, IgA and IgG (10), and other non turbidimetric/nephelometric assays such as total bilirubin (11), thyroid-stimulating hormone (12), lactate dehydrogenase, uric acid and alkaline phosphatase (13), glucose and gamma-glutamyl transferase (14), HDL-cholesterol and as well as glucose interference being observed with glucose analyses on a hexokinase method but not on an oxidase method (15). From our searches no such interferences have been reported with gentamicin.


Materials and methods



A 93 year old female with severe dementia presented with leg cellulitis and sepsis and was administered 320 mg gentamicin (Pfizer, Perth, Australia) at one of our smaller hospitals. No further gentamicin was administered during her hospital stay. On presentation the patient’s sample was analysed on a Beckman DxC600 general chemistry analyser (Beckman Coulter, Brea, CA, USA) as per Beckman Coulter recommendations and the results were: creatinine 177 µmol/L (reference range (RR) 46-108), urea 12.0 mmol/L (RR 2.9-8.2), total protein 63 g/L (RR 60-83), albumin 22 g/L (RR 35-50), and globulins 41 g/L (RR 25-45). A blood sample was collected ~40 hours post gentamicin administration and the laboratory could not obtain a result due to persistent high blank absorbance errors on the Beckman DxC600 general chemistry analyzer (Beckman Coulter, Brea, CA, USA). The sample was diluted with normal saline with ratios starting from 1/3 and going as high as 1/20. The sample was then referred to our laboratory and dilutions were repeated on a Beckman DxC800 general chemistry analyzer using the exact same method. The absorbance error could not be eliminated to obtain a result as shown by the absorbance curves in Figure 1.






Figure 1. Reaction absorbance curves for 1. Gentamicin:  A- normal sample, B -case study neat sample, C-case study 1/20 diluted sample; 2. Vancomicin:  D- normal sample, E- case study neat sample; 3. Valproate: F- normal sample, G- case study neat sample.


A second sample was then collected at ~50 hours post gentamicin administration and this was dispatched for analysis on a Roche Cobas system (Roche Diagnostics, Mannheim, Germany) and the result was 3.3 mg/L. No further gentamicin was administered. Review of the absorbance curves suggested an interference related problem. Although the total protein level did not suggest presence of paraproteins the globulins level was high enough not to rule out the presence of paraproteins. The sample was then diluted off board with the reagent A (reaction buffer) in the ratio used in the method and no precipitation was observed. Unfortunately by this stage due to limited volume no further tests could be conducted.

A third sample was received at ~107 hours post gentamicin administration and the gentamicin result on the Roche Cobas method was 1.2 mg/L. The remaining portion of this sample was analysed for all the turbidimetric assays utilised on the Beckman DxC800: C-RP, carbamazepine, digoxin, haptoglobin, phenytoin, transferrin, tobramycin, theophylline, valproate, vancomicin, to see if any of these would exhibit any limitations. Like the gentamicin method all these methods are particle enhanced turbidimetric inhibition immunoassay methods. Only vancomicin and valproate showed high blank absorbance readings. Additionally the sample was analysed for immunoglobulins (rheumatoid factor, IgA, IgG and IgM) by nephelometry on a BNTM II System (Siemens Diagnostic, Deerfield, IL, USA) as per manufacturer recommendations.

To determine if a suitable precipitation method could be implemented to provide more rapid results the Beckman calibrator sets for each of the three assays were precipitated to ensure accuracy is maintained post recovery from these known concentrations. We then precipitated 10 patient samples routinely requested independently for gentamicin, vancomicin and valproate were sele­cted covering the broadest possible concentration range that is encountered for these analytes. The patient samples were precipitated by both 100% ethanol and polyethylene glycol (PEG), 24 g/100 mL (Fluka#812160, polyethylene glycol 6000, Sigma Aldrich) separately. Both of these reagents are commonly available in most laboratories. Based on the chemical structure of gentamicin (made up of amino groups attached to glycosides), and vancomicin (a tricyclic glycopeptide made up of glycans covalently attached to the side chains of the amino acid residues) it was possible PEG would not be suitable as it could precipitate these antibiotics, hence ethanol was considered as a milder alternative. The samples were processed in a single batch for each of the three analytes. Samples were mixed with equal volumes of the ethanol or PEG solution (0.25 mL : 0.25 mL), vortex mixed, than centrifuged (10 min, 3000 x g ), and the supernatant removed and analysed. For each sample the reaction curve was checked that it was normal to ensure there was no paraprotein interference.

Statistical analysis was performed using the Microsoft Excel (Microsoft Corporation, Redmond, WA, USA) and Analyse-It statistical add-on for Microsoft Excel (Analyse-It Software, Leeds, UK) for the Passing Bablok regression analysis. Recovery was calculated by subtracting the neat sample result from the post precipitation result, and the difference was then divided by the neat result and multiplied by 100% to provide the recovery percentage.




Besides the gentamicin only vancomicin and valproate were affected as shown from the absorbance plots, Figure 1. The patient medical record indicated the patient was not on vancomicin or valproate. Comparing the reaction curve with the normal sample reaction curve it was clear the precipitation in the gentamicin assay was occurring upon addition of the reactive reagents (reagent B and C). The vancomicin and valproate plots equally showed the precipitation was observed upon addition of the reactive reagents (vancomicin has reagent B and C and valproate only has reagent C) (Figure 1E and G).  

The immunoglobulin analysis showed the following results: rheumatoid factor < 20 IU/mL (RR < 20); IgG 2.39 g/L (RR 7.0-16.0); IgA 2.56 g/L (RR 1.0-4.0); and IgM 18.9 g/L (RR 0.4-2.3).  The results confirmed the Sia test findings that the absorbance error was induced by the paraprotein (IgM) precipitation (16).

The Passing Bablok regression correlation results, concentration ranges and recovery data is shown in Table 1. The PEG precipitation produced unsuitable recoveries (mean recovery of <30%) for the three analytes. Using the internal quality control performance data (two quality control levels per each assay) the mean CVs at two standard deviations for each of the assays were: a) gentamicin 15.2%, b) vancomicin 12.6% and c) valproate 17.8%. Hence, the ideal recovery for each assay should have been: a) gentamicin 84.8-115.2%, b) vancomicin 87.4-112.6% and c) valproate 82.3-117.8%.  


Table 1a. The Passing Bablok regression analysis of concentration ranges and recovery results for the Beckman calibrators treated by 100% ethanol precipitation versus stated concentrations.


Table 1b. Comparison of drug concentrations (Passing Bablok regression analysis) measured in native patient samples and samples treated by 100% ethanol precipitation, N = 10.




From our searches, no interference has ever been reported with gentamicin or valproate turbidimetric assays by a paraprotein. Availability of absorbance curves is a powerful tool to highlighting potential assay problems. What the absorbance curves indicated was the precipitation/turbidity was occurring in the latter part of the reaction process, the non-blanking phase, upon addition of the reactive reagents hence for the high absorbance errors. As King et al. also highlight, the reverse would occur if the precipitation/turbidity is occurring in the blanking stage, and would lead to low absorbance errors, low results. This has been reported with vancomicin by previous publications (5,17,18). 

Closer scrutiny of the proteins results, globulins specifically on presentation along with the age of the patient provided a trigger for further investigation, potential presence of a paraprotein. Although IgG is the most common paraprotein (~59-70%), followed by IgM (~17%) and IgA (~11-17%) (19,20). These paraprotein producing disorders increase with age rising from 3.2% in people < 50 years of age to 5.3% in people > 70 years of age (19), 4.5% in the population in the 45-75 years of age (20). Hence the reported paraprotein interference problems are in older patients as is the case here and from review of literature IgM is most frequently reported to be the cause of interference by turbidity or precipitation. This in turn was the reason we initiated testing of all the turbidimetric assays for potential interference.

The Beckman method inserts state gentamicin, vancomicin and valproate were tested with IgM concentration up to 5 g/L without effect. In our experience the IgM concentration level is not the sole determinant for precipitation and subsequent interference. Precipitation occurs as a result of physicochemical conditions (pH, ionic strength, presence of surfactants and other chemicals in the reagents) being in the right balance, where the pH and the isoelectric point being the same and the protein charges being neutralised. This balance or uniqueness to achieve precipitation can be due to the IgM type (lambda or kappa), assay reagents or they can be influenced by other compounds like heparin (14). Ideally manufacturers should test for IgM interference with much higher concentration levels e.g. > 15 g/L, specifically with turbidimetric assays in order to better challenge the method. 

Review of the Beckman method inserts of the tested turbidimetric assays does not provide ability to try and extrapolate as to why only three of the assays exhibited interference. The inserts do not contain data on the reaction buffer used (reagent A), its type or the pH and only minimal data, antibody type only on the reactive reagent(s) (reagent B or C, or B and C) being used. It is assumed the pH of the reactive reagents in these assays was sufficient to achieve the appropriate pI and cause the precipitation. The Roche gentamicin method showed no interference and this was most likely due to the analytical method difference, fluorescence polarization type rather than turbidimetric as is the Beckman method.

The available option for laboratories in obtaining an accurately representative result is predominantly to analyse samples on an alternative system/method which is not always easily accessible. Precipitation of proteins along with the interfering protein while retaining the analyte of interest in the supernatant is an alternative option. Precipitation can depend on the analyte chemical composition, and choice of precipitant and its availability. In general precipitation is most successful with inorganic compounds e.g. digoxin (21). With gentamicin and vancomicin containing amino acids ethanol was shown to be a suitable precipitant to obtain desirable recoveries with the three analytes affected in this case. The use of filtration methods is another option but they are only readily available in a few large laboratories.

Incidences or encounters like this can be a trigger to identifying the presence of unidentified pathological abnormalities and there is a need to immediately communicate to clinical staff for best patient care as was done in this case. A limitation of this study was that due to insufficient patient samples the type of IgM was not determined and neither was precipitation performed for the gentamicin to compare results to the Roche system. A second limitation was the small number (10 patient samples) tested without paraprotein interference, and the larger number of samples could also lead to improvement in the recovery.

Not just gentamicin but vancomicin and valproate are also associated with potential toxicity and the plasma levels need to be monitored. Being able to measure analytes’ concentrations and provide results both timely and accurately is the key to the existence of pathology. Having options or tools to overcome adversity, namely interferences, in house goes a long way to ensuring laboratory services are prompt and subsequent patient care decisions are optimised. When interference is detected with one analyte it is always valuable to run such sample on assays using same analytical techniques as the minimum, specifically for immunoassay based techniques.  

In summary, the findings from this case showed for the first time IgM interference with gentamicin, valproate and vancomicin where the interference led to high absorbance which has never been reported with these analytes. Equally, it was shown ethanol can be used to precipitate proteins and produce acceptable recovery results. This allows all laboratories to use this technique to overcome such interferences.


Potential conflict of interest

None declared.




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Case report:

Şerif Ercan*1, Mustafa Çalışkan2, Erhan Koptur3. 70-year old female patient with mismatch between hematocrit and hemoglobin values: the effects of cold agglutinin on complete blood count. Biochemia Medica 2014;24(3):391-5.

1Department of Clinical Biochemistry, Lüleburgaz State Hospital, Kırklareli, Turkey

2Departments of Clinical Microbiology, Lüleburgaz State Hospital, Kırklareli, Turkey

3Home Health Services, Lüleburgaz State Hospital, Kırklareli, Turkey

*Corresponding author: serifercan [at] yahoo [dot] com [dot] tr




Introduction: There are a number of pre-analytical and analytical factors, which cause false results in the complete blood count. The present case identifies cold agglutinins as the cause for the mismatch between hematocrit and hemoglobin values.

Materials and methods: 70-year old female patient had a history of cerebrovascular diseases and rheumatoid arthritis. During routine laboratory examination, the patient had normal leukocyte and platelet counts; however, the hemoglobin (Hb: 105 g/L) and hematocrit (HCT: 0.214 L/L) results were discordant. Hemolysis, lipemia and cold agglutinin were evaluated as possible reasons for the mismatch between hematocrit and hemoglobin values.

Results: First blood sample was slightly hemolysed. Redrawn sample without hemolysis or lipemia was analyzed but the mismatch became even more distinct (Hb: 104 g/L and HCT: 0.08 L/L). In this sample, the titration of the cold agglutinin was determined and found to be positive at 1:64 dilution ratios. After an incubation of the sample at 37°C for 2 hours, reversibility of agglutination was observed.

Conclusion: We conclude that cold agglutinins may interfere with the analysis of erythrocyte and erythrocyte-related parameters (HCT, MCV, MCH and MCHC); however, Hb, leukocyte and platelet counts are not affected.


Key words: complete blood count; cold agglutinin; hematocrit; hemoglobin; interference

Received: February 11, 2014                                                                                                                                              Accepted: June 29,2014




The use of automated hematology analyzers to examine complete blood count (CBC) is very common. The CBC is applied to diagnose anemia, to identify acute and chronic illness, bleeding tendencies and white blood cell disorders by both general practitioners and other medical specialties. There are a number of pre-analytical and analytical factors that cause false CBC results. Red blood cell (RBC) counts, hemoglobin (Hb), mean cell volume (MCV), white blood cell (WBC) count and platelet (PLT) count are parameters measured by hematology analyzers that are affected by spurious values in several situations. These situations commonly include the agglutination in the presence of ethylenediamine tetra-acetic acid (EDTA), insufficiently lysed RBC, erythroblast, platelet aggregates, cryoglobulins, agglutinins, lipids, hemolysis, and elevated WBC counts (1).

In the present case, we evaluated cold agglutinins as a reason for the mismatch between hematocrit and hemoglobin values. There are several case studies associated with cold agglutinins; however, these studies have been generally presented in a clinical perspective. Laboratory findings were also not sufficiently available in these studies. Only few cases have recently drawn attention to the importance of pre-analytical affect of cold agglutinins on CBC results (2,3). To our knowledge, the present study is also a unique case report of spurious CBC results associated with cold agglutinins using the ABX Pentra 80 (Horiba Medical, Montpellier, France) hematology analyzer.


Materials and methods


Case history

An anticoagulated blood sample (K3EDTA, 2 mL, Golden Vac-Tube, GongDong Medical Technology Co., Zhejiang, China) drawn from a 70-year old female patient was analyzed during routine laboratory examination. Patient had WBC 7.1 x 109/L and PLT count 327 x 109/L; however, hemoglobin (Hb: 105 g/L) and hematocrit (HCT: 0.214 L/L) results were discordant [if Hb value (mg/dL) is multiplied by three, it gives ± 3 HCT value (%)], as shown in Table 1 (Sample 1). Blood samples have been transferred from patient’s home to our laboratory after routine examination by a family physician. Patient had a history of cerebrovascular diseases and rheumatoid arthritis.

We first suspected hemolysis. When the tube with K3EDTA was centrifuged at 500 x g for 3 minutes, slight hemolysis appeared. Thus, to rule out problems with blood sample drawing, the physician and phlebotomist were informed to redraw the tube with K3EDTA. One tube with K3EDTA was drawn by home health services in non-fasting state and a CBC was run, but the results were not corrected; in fact, the mismatch became even more distinct (Hb: 104 g/L and HCT: 0.08 L/L) (Sample 2 in Table 1). Moreover, the sample had not hemolysis or lipemia. We then suspected cold agglutinin. In this sample, the titer of cold agglutinin was determined and a peripheral blood smear was also prepared.


The determination of cold agglutinin titer

The titer of cold agglutinin was determined according to a previously described method (4). Ten tubes were prepared to determine the titration of cold agglutinins. 1.5 mL of physiologic saline was placed in tube 1 and 1.0 mL of physiologic saline in tubes 2-10. 0.5 mL of patient’s serum was added to tube 1, mixed and 1 mL of the mix was transferred to tube 2, from which 1.0 mL was then transferred to tube 3; the process was reiterated until tube 9 (tube 10 served as a cell control). By this method, dilutions from 1:4 to 1:1024 were obtained. 0.1 mL of patient’s own erythrocyte suspension (2-5%) was added to each tube, and the contents were mixed by vigorously shaking and then placed in racks at 4 °C overnight. Tubes were removed from the refrigerator and read immediately. Readings were made by shaking the tube 3-5 times, firmly enough to make a silk-like suspension in negative tests. The agglutination degree was recorded as 1+ to 5+, 1+ representing just visible agglutination and 5+, a solid clump of cells. After reading, tubes were placed at 37 °C for 2 hours and re-visualized.




The titration of the cold agglutinin was found to be 4+ at 1:4 dilution ratio and 1+ at 1:64 dilution ratios. After incubation at 37 °C for 2 hours, reversibility of agglutination was observed. Thus, agglutination was confirmed as cold agglutinin.

As shown in Figure 1A, when the blood smear was examined under the microscope, clusters of erythrocytes were observed in each field.

After obtaining these findings, an expert phlebotomist and specialist of medical biochemistry visited the patient to draw blood at her home. The drawn specimen in non-fasting state was immediately transferred to the laboratory. During transfer, the specimen had not been exposed to the cold. The flat plastic container (500 mL) had been filled with water warmed to approximately 40 °C. The specimen had been placed in this hot plastic container and transferred inside the Styrofoam box. The K3EDTA tube was immediately run on the hematology analyzer. It seemed that all the CBC results were valid (Sample 3 in Table 1). Clusters of erythrocyte were not observed in the blood smear prepared from this sample (Figure 1B). Subsequently, this specimen was placed at 4 °C for 30 min, and re-analyzed. Although leukocyte and platelet values were not changed, a mismatch between HCT and Hb was again observed (Sample 3a in Table 1). The specimen was then stored at room temperature for 1-hour and re-analyzed, but the results remained the same (Sample 3b in Table 1).


Table 1. The results of CBC analysis in different samples.






Figure 1. Peripheral blood smear, May-Grunwald-Giemsa stain, 1000x. A: Redrawn first sample with clusters of erythrocyte, B: Sample transferred without exposition to cold.ples.





Cold agglutinins are antibodies that are usually specific for I antigen, an erythrocyte surface carbohydrate macromolecule. Cold agglutinins bind to the erythrocyte surface antigen at a temperature optimum of 0-4 °C, which causes agglutination of erythrocytes and, thereby, impaired microcirculation ranging from moderate acrocyanosis to severe Raynaud’s phenomenon (5). The antigen-antibody complex also induces the classical complement pathway, resulting in extravascular hemolysis. The physiologic cooling of blood in peripheral vessels is usually sufficient to cause hemolysis and circulatory symptoms in patients with high thermal amplitude of cold agglutinins (6). The clinical effects of cold agglutinins are dependent on both the titer and the thermal amplitude of antibody (7).

Cold agglutinins are rare and only low titers can be found in the serum of healthy individuals. Cold agglutinins may be monoclonal or polyclonal. Monoclonal antibodies are usually found in patients with idiopathic forms of cold agglutinin disease or lymphoproliferative disorders. Polyclonal antibodies usually appear after infection, most often with Mycoplasma pneumonia, Ebstein-Barr virus or cytomegalovirus (7).

Cold agglutinins can cause hemolysis in patients undergoing cardiac surgery during a hypothermic cardiopulmonary bypass. Screening for cold agglutinin in all patients is not recommended; however, it can be useful in specific patient groups (8).

In the presence of cold agglutinins, we found decreased HCT and elevated MCV values. Hemoglobin concentration was unaffected by cold agglutinins, thereby, calculated MCH and MCHC values were prominently elevated. Leukocyte and platelet counts were also found to be unaffected by cold agglutinins. In the present case, the analysis of CBC was performed on ABX Pentra 80 hematology analyzer. RBC is measured by an electronic impedance variation principle on ABX Pentra 80. MCV and HCT are calculated directly from the RBC histogram. The impedance method of counting and sizing cells is based on measurable changes in electrical resistance produced by non-conductive cells suspended in conductive isotonic electrolyte solution. This electrical resistance is manifested as a pulse that has a height directly proportional to the cell size. Red blood cells, platelets and leukocytes are counted and sized according to the total number and heights of produced pulses (9). Cells between 30 to 300 fL are considered and counted as red blood cells on Horiba ABX Pentra. The microaggregates of erythrocyte are counted as single cells and large clumps of cells are excluded from the count, which lead to decreased RBC count (9). These abnormal RBC values will lead to abnormal MCV and HCT results.

We met with the present case in winter. Therefore, the cold agglutinin forming might be the result of the fact that blood samples were exposed to cold weather during transfer from patient’s home to our laboratory. When the patient’s previous results were reviewed, CBC results were found to be valid. This is most likely due to drawing the blood samples at the hospital, without exposure to cold. In addition, we found that CBC results were valid if the blood drawn from the patient was immediately transferred to the laboratory without being exposed to cold.

The interference of cold agglutinin on RBC and HCT results has previously been reported using an older automated hematology analyzer (10,11). It is seems that cold agglutinins can still cause artifactual changes on RBC and related parameters. This might be due to the counting of RBC by the impedance method, which is widespread among hematology analyzers produced different manufactures. In accordance with our case report, Kakkar (2) revealed spurious CBC results due to cold agglutinins on Advia 60 (Bayer diagnostics) hematology analyzer. In his report of two cases, he reported HCT to be spuriously low and discordant with Hb. MCV, MCH and MCHC values have also been found to be elevated.

Similarly, Breuer et al. (3) reported four patients with cold agglutinins whose RBC parameters described were incompatible and spurious. They showed that cold agglutinins caused artificially decreased red blood cell counts and increased MCV and MCHC in the automated Coulter STKS hematology analyzer. It was also noted that leukocyte and platelet counts remained unchanged. In a more recent case, Reddy et al. (12) reported elevated MCHC and MCV in a 12-year-old girl with mixed autoimmune hemolytic anemia.

The in vitro phenomenon of cold agglutination results in a spurious increase in MCV and MCHC and a decrease in the RBC count given by automated hematology analyzer; however, different findings have been reported in some clinical case reports.

In a 55-year old woman with a history of rheumatoid arthritis, Bizzaro et al. (13) presented in vitro platelet clumping due to EDTA-dependent autoantibodies and RBC agglutination due to cold agglutinins. Although they observed elevated MCHC in laboratory examination, the MCV value was reported as normal. In another study, Lee et al. (14) identified cold agglutinin in a case of 75-year old woman patient with non-Hodgkin’s lymphoma. They identified RBC agglutination related to cold agglutinins; however, a normal MCHC value was reported. Laboratory methodology and findings were, unfortunately, not obtained from these studies. Therefore, a satisfactory comparison could not be done.

In conclusion, cold agglutinins interfere with the analysis of RBC and RBC-related parameters (HCT, MCV, MCH and MCHC); however, Hb, WBC and PLT counts are not affected. In addition, the presence of cold agglutinins is easily displayed by the cold agglutinin titer test. It is also visible in a blood smear. Also, the effect of cold agglutinin on CBC results may be prevented if the blood drawn from the patient is immediately transferred to the laboratory without exposure to cold. Lastly, clinicians should be aware of the fact that anemia diagnosis based on low HCT alone may be misleading.




We thank Ercan Güneş, Adem Taka, and Pervin Köksal for their technical assistance. We thank Deniz İnci for helping to take the images of blood smears.


Potential conflict of interest

None declared.




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Raffick A.R. Bowen*1, Alan T. Remaley2. Interferences from blood collection tube components on clinical chemistry assays. Biochemia Medica 2014;24(1):31-44.
1Department of Pathology, Stanford University, Stanford, CA 94305, USA
2Department of Laboratory Medicine, National Institutes of Health, Bethesda, MD 20892, USA
*Corresponding author: rbowen [at] stanfordmed [dot] org
Improper design or use of blood collection devices can adversely affect the accuracy of laboratory test results. Vascular access devices, such as catheters and needles, exert shear forces during blood flow, which creates a predisposition to cell lysis. Components from blood collection tubes, such as stoppers, lubricants, surfactants, and separator gels, can leach into specimens and/or adsorb analytes from a specimen; special tube additives may also alter analyte stability. Because of these interactions with blood specimens, blood collection devices are a potential source of pre-analytical error in laboratory testing. Accurate laboratory testing requires an understanding of the complex interactions between collection devices and blood specimens. Manufacturers, vendors, and clinical laboratorians must consider the pre-analytical challenges in laboratory testing. Although other authors have described the effects of endogenous substances on clinical assay results, the effects/impact of blood collection tube additives and components have not been well systematically described or explained. This review aims to identify and describe blood collection tube additives and their components and the strategies used to minimize their effects on clinical chemistry assays.
Key words: blood collection devices; blood collection sample tube; clinical assays; clinical chemistry; interference; pre-analytical; surfactant
Received: October 22, 2013                                                                                                                                                    Accepted: January 03, 2014
Proper blood collection and timely processing are critical pre-analytical steps required for the integrity of laboratory results. Although the influence of blood collection devices on laboratory tests is often overlooked, correct pre-analytical handling is essential. However, many laboratorians do not carefully evaluate the suitability of new devices or monitor ongoing performance. In this review, we discuss how blood collection materials and devices can alter chemistry test results, with an emphasis on blood collection tube (BCT) additives.
Blood collection device history
Reusable glass syringes with steel hypodermic needles and a hard rubber hub were the first devices used to collect blood (1). Early modifications included a refined needle, replacement of the rubber hub with glass, and the Luer-Lok syringe, which modified the needle tip for a more secure attachment to the syringe and ensuring a more reliable and safer drug delivery (1). Glass syringes were expensive to manufacture and were susceptible to breakage (2); nevertheless, what ultimately prompted their replacement with sterile disposable syringes (1) were the multiple hepatitis outbreaks that resulted from their use (1). Modern chemical sterilization techniques and radiation allowed the replacement of glass syringes by plastic syringes.
Since the 1940s, evacuated BCTs have been the most commonly used blood collection devices, since they automatically draw a predetermined blood volume and switching between tubes for additional samples poses a lower risk of spillage and needle-stick injury (3). Thus, the evolution of blood collection tubes have improved specimen quality and workflow efficiency as well as the safety of patients and health care workers.
Glass evacuated tubes containing anticoagulants were commonly used from the 1950s to the 1990s (4). Presently, plastic has replaced glass, and polymer gels and clot activators are common additives (5). Despite their similarity, evacuated tubes supplied by different manufacturers vary in the materials and additives used, which can potentially affect test performance (6). In the United States, there are two major manufacturers of evacuated tubes: Becton Dickinson (BD) (Franklin Lakes, NJ, USA) and Greiner Bio-One (Monroe, NC, USA).
Because BCTs function properly under most circumstances, many laboratorians are unaware of their complexity and limitations. A widespread surfactant (SF) problem revealed how these devices can adversely affect laboratory test results (7,8) and emphasized the importance of understanding device limitations.
Blood collection tubes
BCTs consist of tube walls, rubber stoppers, lubricants, anticoagulants, separator gels, clot activators, and SFs, all of which can affect the quality of the specimens, accuracy and precision of laboratory tests (Figure 1).
Figure 1. Components of an evacuated blood collection tube.
Reprinted from Clinical Biochemistry, 43 (1-2), Bowen RAR, Hortin GL, Csako G, Otanez O, Remaley AT. Impact of blood collection devices on clinical chemistry assays, pages 4-25, 2010, with permission from Elsevier.
Tube walls
Evacuated BCTs are generally cylindrical, measuring 50 mm to 150 mm in length and 10 mm to 20 mm in diameter (9). Most tubes for adult clinical specimens are 75 mm to 100 mm in length and 13 mm in diameter, and collect 2 to 10 mL of whole blood (9,10). Micro-collection tubes for pediatric specimens are 40 to 50 mm in length and 5 to 10 mm in diameter (11). Evacuated tubes were originally made from soda-lime or borosilicate glass, but soda-lime tubes were found to release calcium and magnesium into blood specimens (12). Glass evacuated tubes are manufactured to be airtight, waterproof, and thermally resistant, which allows for vacuum preservation and long shelf lives (13). The contact of blood coagulation factors, such as Factor XII (Hagemann Factor), with hydrophilic glass surfaces activates the clotting cascade leading to the conversion of fibrinogen to fibrin, thus enabling the separation of the non-adherent clot from blood plasma by centrifugation (14). However, clot re-suspension into plasma during handling or transport can interfere with assays attributable to the effects of hemolysis on test results (15,16).
Plastic tubes recently replaced most glass tubes following the establishment of the Occupational Safety and Health Administration (OSHA) guidelines to improve safety and reduce exposure to blood-borne pathogens (15). Plastic tubes are manufactured through injection-molding, using polyesters (e.g. polyethylene terephthalate (PET)), polyolefins (e.g. polyethylene and polypropylene (PP)), polyacrylic, polytetrafluoroethylene, polysiloxane, polyvinyl chloride, polyacrylonnitrile, and polystyrene (9,10). Compared to glass, plastic minimizes exposure to biohazardous material following breakage, has a greater shock resistance, tolerates higher centrifugation speeds, weighs less, has excellent dimensional precision, and is more easily disposed of by incineration at a lower cost (4,17). However, plastic has greater gas permeability compared to glass tubes (18). There have been numerous studies comparing glass and plastic tubes for use in chemistry (4,19), endocrinology (19), molecular testing (20), serology (21), and coagulation testing (10,19). Despite small statistically significant differences between plastic and glass tube analyte determinations, none is considered clinically significant. PET, a commonly used plastic in the manufacture of BCTs is unbreakable and maintains a vacuum for a prolonged time (22). PP, another commonly used plastic, has a lower water permeability, allowing it to retain liquid anticoagulant volume and concentration (22). Thus, PET tubes have double-walls to minimize evaporation, especially for coagulation-based tests (22); the internal PP layer protects against citrate solution evaporation, whereas the outer PET layer is more transparent, allowing easier visualization of tube fill levels. The PP plus PET combination improves shelf life and anticoagulant volume retention (22).
Plastic tubes generally have a hydrophobic surface and do not efficiently activate the coagulation process (23); clots formed on the plastic surfaces of tubes are gelatinous compared to clots formed in glass tubes (23). Further, blood does not flow smoothly over hydrophobic plastic surfaces, which can result in the adherence of platelets, fibrin, or clotted blood on the tube walls (23). This can make it difficult to cleanly separate serum from the blood clot by centrifugation, especially for micro-collection tubes or during centrifugation of vacuum tubes. The hydrophilicity of plastic surfaces can be increased by using plasma-enhanced chemical vapor deposition to introduce polar functional groups (24). Alternatively, the interior plastic surfaces can be coated with SFs, water-soluble polymers, or hydrophilic-hydrophobic copolymers (23), although SFs may dissolve in blood and interfere with clinical tests (8). There are ongoing efforts to incorporate SFs into plastic tubes to prevent exudation into blood specimens (9,10).
Rubber stoppers
Rubber stoppers are routinely color-coded according to anticoagulant type and the presence of a separator gel. The stopper should be readily penetrated by a needle and self-seal upon needle removal (23), maintaining the internal pressure differential (23). Suitable materials include polychloroprene, silicone, styrene butadiene, isobutylene-isopropene, chlorinated ethylene-propylene copolymers, and isobutylene-isoprene rubber (23,25,26). Butyl rubber, a copolymer of isobutylene and isoprene, and halogenated butyl rubber are commonly used materials (23,25,26); butyl rubber exhibits superior air and moisture impermeability, superior resistance to chemical attack and heat resistance, and good processability (25,26). To reduce the potential for splatter from the blood specimen when the rubber stoppers are removed from the collection tube, a stopper shield is used (e.g. Hemogard™). The stopper shield can be made from thermoplastic materials, such as polyethylene, polypropylene, and polyvinylchloride (8,26). Discrepancies in the bioavailability and bioequivalence of tests for blood specimens collected into tubes whose rubber stoppers containing the plasticizer tris-(2-butoxyethyl)-phosphate (TBEP) have been reported (27). TBEP, which is used to make stoppers soft, displaces certain drugs from plasma-protein binding sites, such as the α1-acid glycoprotein (28), resulting in increased drug uptake by red blood cells (RBCs), thus artificially lowering serum or plasma levels. TBEP has been reported to alter the drug distribution of quinidine, propranolol, lidocaine, tricyclic antidepressants, and several phenothiazine drugs, including fluphenazine and chlorpromazine (29). Therefore, tube manufacturers have decreased or eliminated production of rubber stoppers containing TBEP (27). Janknegt et al. (30) have demonstrated that rubber stoppers made without TBEP do not interfere with therapeutic drug monitoring. However, other stopper components can also pose problems. Curry et al. (31) reviewed how materials from elastomeric closures, including butyl rubber stoppers, can contaminate specimens with these container closures. Metals such as calcium, aluminum, magnesium, and zinc are used to manufacture rubber stoppers; it is essential that these metals are not extracted upon contact with blood (32); specially formulated rubber stoppers have been made to limit divalent cation leaching (33). Sulfur, sulfur-containing vulcanization accelerators, fatty acids, and peroxides in stoppers can also potentially affect lab tests; therefore, most stoppers are manufactured with low-extractable rubber or have been modified to minimize leaching into the blood specimens (29). The complete filling of BCTs dilutes any leached material and helps reduce the effects (34). Further, specimens in tubes with rubber stoppers should be stored at low temperatures (2 °C to 8 °C) and in the upright position to minimize leaching (34).
Stopper lubricants
Lubricants, such as silicone oils, fluids, and glycerol, facilitate the insertion and removal of stoppers (6,9,10). Lubricants minimize red blood cell and clot adherence to stoppers in order to prevent serum or plasma contamination (6,9,10). However, glycerol should not be used to lubricate stoppers used for specimens measuring glycerol or triglyceride when a non-glycerol blank assay is used (35). Siliconized stoppers are generally preferred because they are less likely to interfere with assays, although silicone may falsely elevate ionized magnesium and total triiodothyronine levels (7) and may confound peaks during mass spectrometry (MS) analysis and peak interpretation (36).
Although serum is used for most assays, plasma is a useful alternative due to its rapid processing time. Plasma, which contains fibrinogen and other clotting factors, has a higher viscosity and total protein content than serum (37). Serum has a higher concentration of thromboglobulins, potassium, activation peptides for coagulation factors, platelet factor 4, and platelet components released during platelet activation (37). Anticoagulants used to preserve analytes may interfere with other analyte determinations when using plasma (38). Ethylenediaminetetraacetic acid (EDTA), heparin, and citrate are the most commonly used anticoagulants (39-41).
Potassium EDTA (Table 1), an anticoagulant and chelating agent, interferes with calcium assays and clot generation (42), but it is preferred for hematology testing. EDTA binds the metallic ions europium (immunoassay reagent), zinc, and magnesium (enzyme cofactors for immunoassay reagents such as alkaline phosphatase) (43). Insufficient sample volumes produce relatively elevated EDTA levels, which can increase the chelation of magnesium and zinc, and can then affect reagent enzymes used for signal generation, such as alkaline phosphatase (43). Reagent antibodies recognize divalent cation complex binding sites on proteins; thus, decreased calcium and magnesium levels may induce conformational changes that decrease antibody binding (43).
Table 1. Evacuated blood collection tube stopper color and additives.
Heparin salts (typically from porcine intestinal mucosa) are also extensively used as anticoagulants in BCTs (Table 1) (44). Heparin complexes with and induces a conformational change of antithrombin III to accelerate the inhibition of thrombin and Factor Xa (35), which prevents thrombin activation and the generation of fibrin from fibrinogen. Since heparin binds electrolytes and changes the concentration of bound and free ions (45), manufacturers have created electrolyte-balanced formulations (45). However, heparin can interfere with a variety of clinical assays. Specimens assayed with Dimension™ Vista 1500 (Siemens Healthcare Diagnostic, Newark, DE, USA) may produce negative anion gaps due to heparin interference with chloride electrode membranes (unpublished observation). Heparin also slows some antibody-antigen reaction rates (46), particularly during the precipitation step in second-antibody systems, although this problem can be avoided with the use of solid-phase systems (47). Heparin should also be avoided in cryoprotein investigations since it precipitates cryofibrinogen (43,47). Exogenously administered heparin alters serum thyroid hormone levels (43,47). Falsely low albumin levels have been observed when heparinized tubes have been used on hemodialysis patients (48). It is has been proposed that heparin inhibits the binding of bromocresol green to albumin, leading to less colorimetric complex formation (48). Proteomic studies show that heparinized plasma causes non-specific protein binding, which influences the separation and MS of peptides (49). Recently, Lippi et al. (50) demonstrated that incomplete filling of lithium heparin tubes produced significantly higher creatine kinase and γ-glutamyltransferase activity on a Unicel DxC 800 analyzer.
Trisodium citrate in a 3.2% (109 mmol/L) or 3.8% (129 mmol/L) solution is preferred for coagulation testing (Table 1) (51). It can inhibit both aspartate aminotransferase and alkaline phosphatase by the chelation of cations (51). Sodium citrate, which is used in acid citrate dextrose and citrate theophylline adenosine dipyrridamole (51), inhibits platelet activation and is used to measure plasma levels of platelet-derived components.
Potassium oxalate, another calcium-chelating anticoagulant (Table 1) often combined with antiglycolyitc agents (sodium fluoride and sodium iodoacetate) can actually decrease hematocrits by as much as 10% by drawing water from cells into plasma (51). Oxalate can also inhibit several enzymes, such an amylase, lactate dehydrogenase, and acid and alkaline phosphatase (51).
Sodium fluoride (Table 1) inhibits the glycolytic enzyme enolase and is used to limit the ex vivo consumption of glucose by cells in a collected blood specimen (51). However, in fluoridated, non-separated blood samples, glucose is still metabolized at approximately 5% to 7% per hour at room temperature because upstream enzymes continue to convert it to glucose-6-phosphate (52). Hence, complete inhibition of glycolysis in fluoride-containing tubes can take up to 4 hours at room temperature with a normal blood cell count (53). Fluoridated tubes can affect diabetes diagnosis, which uses fixed plasma glucose levels established using blood that was iced, centrifuged, and had the plasma removed (54). In fact, the American Diabetes Association no longer recommends using sodium fluoride only to inhibit in vitro glycolysis (54). A BCT with EDTA and fluoride in a citrate buffer (pH < 5.9) has been proposed to preserve glucose concentrations due to its immediate inhibition of glycolysis (53). Sodium fluoride may be unsuitable for enzymatic immunoassays because of its enzyme inhibitory activity (51). Fluoride may also interfere with electrolyte measurements by altering cell membrane permeability (51) and promoting hemolysis by red blood cell ATP with subsequent potassium efflux (51). Iodoacetate preserves glucose concentrations by inhibiting glyceraldehyde-3-phosphosphate dehydrogenase, but it can interfere with the measurement of glucose, sodium, potassium, chloride, and lactate dehydrogenase measurements and can cause hemolysis (51).
Although anticoagulants and antiglycolytics can be unsuitable for certain assays, assay manufacturers do not always specify the plasma sources used to validate their tests. Consequently, it is important that clinical laboratories assess tube performance with their particular assays, instruments, and platforms. Tube manufacturers’ fill-volume recommendations should be followed to ensure proper additive to blood ratios and minimize assay interference and resultant laboratory errors, repeat testing, and unnecessary troubleshooting.
Separator gels
Separator gels are used to separate serum from clotted whole blood or plasma from cells (55). In this regard, serum separator tubes (SST) are easy to use, require short processing times, yield higher serum levels, limit hazardous aerosolization, require only one centrifugation step, allow primary tube sampling, and require a single label (55).
During centrifugation, the thixotropic gel used in these tubes lodges between packed cells and the top serum layer (56). The position of the gel after centrifugation is influenced by many tube characteristics, such as specific gravity, yield stress, viscosity, density, and tube material. It can also be affected by temperature, centrifugation speed, acceleration and deceleration, storage, and patient factors, such as heparin therapy, low hematocrit, elevated plasma protein, and serum/plasma specific gravity (57). Polymeric gels affect viscosity,density, and other physical properties. Separator gels are typically made from viscous liquids, fillers, or tackifiers with substances like dibenzylidene sorbitol as a gelling agent (23). The inner tube surface may have a hydrophobic coating to ensure separator gel adherence and a complete barrier to prevent mixing between RBCs and serum/plasma (9,10). Because the serum/plasma specific gravity ranges from 1.026 to 1.031 g/cm3, and the clot specific gravity ranges from 1.092 to 1.095 g/cm3, the separator gel specific gravity should ideally be within 1.03 to 1.09 g/cm3 (58). If the serum/plasma specific gravity is elevated due to hyperproteinemia or radio-contrast dye, the serum may not float above the gel (57). Fatas et al. (58) showed that the specific gravity is a more important factor than viscosity affecting improper BCT gel separation. In addition, Faught et al. (59) showed differences in separator gel specific gravity in different BCTs and between some tube lots.
Several reports of gels affecting analyte concentrations have been published. Hydrophobic drugs, such as phenytoin, phenobarbitol, carbamazepine, quinidine, and lidocaine, can adsorb onto hydrophobic separator gels and lead to a decrease in serum drug concentrations by as much as 20% to 50% after 24 hours at 4 °C (60,61). Organochlorine, polychlorinated biphenyl, and progesterone levels may also be significantly reduced (47). A small but statistically significant difference in myoglobin and CK-MB levels has been reported between tubes with and without separator gels (5). Interestingly, newer separator gels (e.g. polydimethylsiloxane-polyethylene oxide copolymers) that minimize drug and analyte adsorption have been developed (e.g., the BD SST II™ tube) (9,10,62). Recently, RBCs have been observed to surpass the separator gel barrier in plasma and serum tubes increasing the plasma/serum potassium levels (63). Separator gels may also release materials (e.g., gel pieces and silicone oil) into the specimens and spuriously interfere with assays, sample probes, tubes and cuvettes, solid-phase immunoassay systems, and electrode surfaces (47,64); the rate of degradation and release may be increased by improper storage or extreme temperatures (47). Recently, Shi et al. (65) demonstrated that the separator gel components in some types of BCTs (i.e., SST and lithium heparin plasma separator tubes) from a specific tube manufacturer were the source of interference in the quantitation of serum testosterone levels using liquid chromatography-tandem MS. The interference increased according to the length of storage of serum in the tubes and was more pronounced with specimens containing low testosterone levels (65). Modifications of the assay and liquid chromatography-tandem MS parameters did not resolve the tube interference problem with the quantitation of serum testosterone levels (65). Thus, new technologies applied in the clinical laboratory to determine analyte concentrations can be significantly affected by BCTs components such as the separator gel. Ideally, separator gels should maintain uniform chemical and physical properties for the intended period of use and be inert to the specimens collected in BCTs.
Clot activators and water-soluble agents
Plastic tubes require clot activators that use either intrinsic or extrinsic pathways to ensure rapid and dense clot formation (10). Clot activation by the intrinsic pathway is surface-dependent and a greater density of activating surface sites speeds clotting time. Siliceous substances (e.g., glass, silica, kaolin, bentonite, diatomaceous earth) accelerate clot formation through contact activation (23), but particulate clot activators work relatively slowly (30 to 60 minutes) (10). The amount of clot activator varies by manufacturer (23). Clot activators also diminish latent fibrin formation in the separated serum (47).
Clot activation by the extrinsic pathway, coagulation initiated by adding substances extrinsic to blood, is biochemical (e.g., ellagic acid, thrombin, snake venoms, thromboplastin) and concentration-dependent (10). Although these clot activators produce rapid clotting (10 to 20 minutes), the clots formed are gelatinous and do not easily separate from serum (10). Clot activators can be added to tubes by adding small beads or paper coated discs, or they can be sprayed on interior tube surfaces with a carrier (e.g., polyvinylpyrrolidone (PVP), carboxymethyl cellulose, polyvinyl alcohol, and polyethylene oxide) (10,23). These carriers allow rapid clot activator suspension into blood so that the carriers dissolve into both serum and clots as the clotting is initiated (23). PVP and water-soluble SFs also release clot activators into blood specimens to reduce the need for mixing (23). BD has recently released a serum tube containing thrombin (rapid serum tubes (RSTTM); Table 1, orange stopper) for rapid clot activation (within 5 minutes) (42). Dimeski et al. (66)demonstrated that the use of RST tubes would not be appropriate for patients on high-dose heparin or warfarin therapy since latent clot formation in the tube may clog instrument probes and produce erroneous test results. Based on these findings, it is clear that additional studies are needed to ensure that the RST tubes give clinically equivalent results to other commercially available serum tubes, especially for partially filled tubes of blood.
Some clot activators are problematic in that they must be thoroughly mixed to allow complete pelleting with the clot. If soluble fibrin clots form, they can interfere with pipetting device accuracy or in solid-phase binding in immunoassays (67). To limit these problems, plasma gas may be used to introduce heteroatoms (non-carbon and hydrogen atoms in the backbone of the molecular structure) to the tube wall surface to accelerate clotting without contaminating the serum or clot with binders or activators (24).
Various studies have revealed the impact of clot activators on laboratory test performance. Sampson et al. (68) showed that silica and silicone SF are associated with elevated lithium concentrations when using the Lytening 2Z (Lytening West Peabody, MA, USA) ion-specific electrode analyzer. The clot activators or silicone SFs can interact with ion-specific analyzer membranes, which increase the measured voltage and falsely elevate serum lithium ion concentration. Clot activators can also falsely elevate serum testosterone measurements (69), but changing the ion pair eliminates this problem (69). Proteome analysis by MS may also be altered by clot activators (70). Silica and silicate clot activators, when sprayed onto plastic tubes, induces the release of pro-, active, and complexed matrix metalloproteinases (71). Recently, it was shown that ficolin-1 and ficolin-2 levels, a group of proteins that can activate the complement pathway, and their binding capacities were significantly affected, presumably, by the silicate material in SST tubes (72). Thus, it is critical that the optimal amounts and composition of clot activators and water-soluble agents be determined and consistently added to different types and sizes of BCTs in order for these substances to function properly without adversely affecting the quality of the blood specimens and test results.
SFs are commonly used to decrease non-specific adsorption, but they must be carefully selected and optimized for immunoassays since, at high concentrations, they may cause the loss of antibodies passively adsorbed onto the solid support beads used in immunoassays (73). Commercially available tubes contain a variety of SFs (7,8,10) that improve blood flow, distribute clot activator, and prevent proteins, RBCs, and platelets from adsorbing to tube walls (10).
Silicone SF-coated tubes have been shown to interfere with ion-specific electrode measurementof ionized magnesium and lithium (7,68). Silicone SFs seems to interact with ion-specific electrode membranes to increase the measured voltage during magnesium and lithium determinations (7,68). In addition, water-solublesilicone polymer coatings in separator tubes canphysically mask antibodies and alter avidin-biotin binding reactionsin immunoradiometric assays (74).
Bowen et al. (7) demonstrated that the nonionic polydimethylsiloxane-polyethylene oxide and polypropylene oxide graft copolymer SF, Silwet™ L-720 (Figure 2; OSI Specialities, Danbury, CT, USA; 75), in BD SST™ tubes falsely elevates triiodothyronine in a dose-dependent manner by causing the desorption of captured antibodies from the solid phase used in immunoassays (7,8). Competitive immunoassays (e.g., vitamin B12) and non-competitive immunoassays (e.g., cancer antigen 15-3) are also affected by Silwet L-720, but the mechanism is unclear (7).
Figure 2. Silwet™ silicone surfactant. A) general molecular structure and B) schematic structure with polyether (polyethylene oxide and polypropylene oxide) attached (via hydrosilation reaction) to the polydimethylsiloxane backbone; x, y, m, n are integers independently greater than zero; z can be hydrogen or alkyl radical (75).
Due to immunoassay interference, BD reformulated their tubes to reduce SF levels (7). Morovat et al. (76) have shown statistically significant but clinically insignificant biases in immunoassay results using these reformulated tubes. Yet, in this study, the control tubes were coated with the problematic SF. Wang et al. (77) reported that the reformulated tubes produced clinically significant biased results for free triiodothyronine and free thyroxine. Interestingly, Silwet L-720 and other types of Silwet surfactants can be used in separator gel formulations, which may account for the clinically significant biased thyroid hormone test results with the reformulated tubes stated above (75).
Further studies have examined whether additives supply molecules that may interfere with MS peaks. Drake et al. (36) showed that seven of the eleven tubes tested contained various components, such as SF and polyvinylpyrrolidone, which produced multiple MS signals in the m/z range of 1,000 to 3,000. These tube additive peaks complicate and compromise mass spectra interpretation in the low molecular mass range, particularly for MALDI or SELDI techniques (36). Tube additives may also affect the ionization process during liquid chromatography-MS analysis, thereby suppressing metabolite ionization. Yin et al. (78) recently reported that five different S-Monovettes™ (Sarstedt Newton, NC, USA) BCT additives produced chemical noise in the mass spectra that interfered with metabolic profiling. Thus, an initial step in MS investigations should be the examination of BCTs.
SF detergent properties can also alter cell membrane permeability and lipophilic structures. A study showed that SFs in tubes affected free fatty acid concentrations in specimens rather than interfere with their analytical detection (79). Thus, producing BCTs with SF that do not contaminate the blood specimens and cause assay interferences would be ideal.
Order of draw
The importance of the order of draw in obtaining accurate laboratory tests has been known for many decades. Calam and Cooper (80) demonstrated that the initial drawing of blood into potassium-EDTA tubes falsely decreased and increased the calcium and potassium values, respectively, in blood collected into subsequent tubes containing no anticoagulants (80). These findings prompted the development of Clinical and Laboratory Standards Institute (CLSI) guidelines to standardize tube sequence and syringe use for blood collection to minimize carryover of tube additives (81). When laboratories switched from glass to plastic tubes, the CLSI order of draw guideline changed because plastic serum tubes were considered equivalent to gel separator tubes with clot activators (81). The current CLSI guideline for glass and plastic tubes order of draw is as follows: blood culture tubes; sodium citrate tubes; serum tubes with and without clot activator and with or without gel separator; heparin tubes with or without gel separator; EDTA tubes; acid citrate dextrose containing tubes; and glycolytic inhibitor (fluoride, iodoacetate) tubes (81). However, the use of order of draw has recently been questioned and studies by Salvagno et al. (82) have demonstrated negligible effects of the order of draw on sample quality for some routine chemistry tests. Nevertheless, an extensive study with more analytes is warranted. Tube manufacturers color-code tube closures for easy identification of tube additives. Laboratorians must understand associated additives, proper order of draw, and carryover effects of additives on clinical assays.
Protease inhibitors
Protease inhibitors are among the most abundant plasma protein components (83), far outnumbering active proteases except where activation occurs by surfaces or other stimuli. Chelating agents, such as EDTA and citrate, do not directly inhibit serine proteases, but they do limit the activation of proteases in the coagulation system by interfering with calcium-mediated surface binding and by allowing inhibitors to dominate. Direct inhibitors of thrombin or coagulation factor Xa serve as alternative anticoagulants, but they have not achieved widespread use because of cost (84). Such products, however, can increase protein stability and allow chemistry and hematology tests on a single specimen. Small bioactive peptides such as parathyroid hormone and insulin are more stable in EDTA-anticoagulated plasma compared to citrate-anticoagulated plasma or serum (85). Aprotinin increases the stability of brain-type natriuretic peptides (86); some reference laboratories recommend the collection of specimens for bioactive peptide analysis in tubes containing aprotinin or other protease inhibitors. Many peptides, such as glucagon-like peptide 1, undergo rapid cleavage by the exopeptidase dipeptidyl peptidase IV (87), and thus collection tubes must contain exopeptidase inhibitors to recover the intact peptide. EDTA-containing tubes are generally recommended for proteomic analyses to minimize protein component changes (88); small peptide components can also undergo rapid degradation by exopeptidases (89). However, addition of chemically reactive protease inhibitors, such as sulfonyl halides, can covalently modify proteins (89). An alternative approach is to inhibit protease activity by decreasing pH (89). In general, small peptides are frequently less stable than proteins since proteases sequestered in an α2-macroglobulin inhibitor retain peptidolytic activity even though they are sterically hindered from cleaving full-size proteins (90); further, peptides lack a globular structure and are more accessible to exopeptidase action. Although endogenous protease inhibitors are quite abundant in plasma, most are mainly against serine dependent endoproteases and exhibit relatively little activity against exopeptidases. Therefore, the addition of exogenous, low molecular weight protein inhibitors or small synthetic compounds to a blood specimen is often used to stabilize samples.
Protease activity may be accentuated by the release of intracellular proteases from white or RBCs. For example, insulin is substantially less stable in hemolyzed blood because of the thiol proteases from RBCs (91). The use of protease inhibitors has a limited effect on the recovery of chemokines and cytokines from plasma, but the rapid processing of blood can limit this problem because most cytokines and chemokines are degraded by intracellular protease (92).
The addition of exogenous protease inhibitors depends on the intended use of specimens. Because there is wide variability in protein and peptide stability, each laboratory should analyze the stability of components of interest; where protein or peptide stability problems are identified, protease inhibitors should be considered. Blood collection systems (e.g., BD P100™) containing a cocktail of protease inhibitors that enable preservation of plasma proteins for proteomic investigation have been developed (42).
Prevention of pre-analytical errors from BCT additives remains an ongoing problem for tube and assay manufacturers and ultimately affects the ability of clinical laboratories to produce accurate results. Any new or modified blood collection product should ideally be thoroughly evaluated for any potential problems inherently caused in the downstream processing and analysis of specimens. BCT manufacturers should also consider evaluating their products under conditions of reduced specimen volumes, extended contact times, and long-term storage. Because it is not possible for manufacturers to assess the impact of their tubes on all assay platforms, it is important that they establish close working relationships with their customers and should consider developing a surveillance program to quickly identify problems. Similarly, manufacturers of assays and instrument platforms should ideally verify the performance of their assays with a wide variety of BCTs on the market and on different lots of the same tube type. Reference interval studies performed on older instruments or tubes no longer in use should be repeated using materials and conditions that are consistent with current use.
Blood collection device problems may go unnoticed by laboratorians since routine quality control (QC) practice typically does not assess all aspects of laboratory testing from blood collection, including specimen processing, analytical testing, and test reporting (7,8). Proficiency testing programs, which do not require blood collection, also fail to detect blood collection device problems (7,8). Hence, QC and proficiency testing specimens in clinical laboratories are analyzed but not processed as patient specimens are. Although QC specimens are typically non-commutable with native patient specimens because the QC matrices are usually altered by manufacturing processes from that of native specimens, the comparison of control sera results from specimens exposed and non-exposed to BCTs could potentially reveal the adverse effects of additives (7,8,93). This could be done by clinical laboratories or perhaps by tube manufacturersby exposing QC sera to BCTs on a lot-by-lotbasis. When laboratorians change the tubes they use, they should also perform a comparative tube evaluation (94); this tube comparison study should be similar to the one described for method comparison studies, using the CLSI EP9-A guideline (95). In addition to contacting tube manufacturers, tube-related issues should also be reported to regulatory agencies (i.e., Food and Drug Administration) via MedWatch in the United States and the Medicines Healthcare Products Authority in the United Kingdom. Finally, the routine evaluation of BCTs by clinical laboratories should be incorporated into QC plans based on risk management to help prevent or detect tube-related errors and enhance the quality of the test results (96).
The BD Diagnostics preanalytical division has developed a program through an Instrument Company Liaison to work with assay manufacturers to identify and eliminate and/or reduce tube-related assay problems prior to products being commercialized (97, 98, 99). A CLSI guideline is available for tube manufacturers, in vitro diagnostic manufacturers, and clinical laboratories for verification and validation of venous and capillary BCTs for chemistry, immunochemistry, hematology, and coagulation (99,100).
Although current BCTs largely work as designed and are therefore often taken for granted, it is important that laboratorians become aware of the potential problems that they can cause in the analysis of specimens. BCTs are medical devices and, as such, have inherent limitations. When improperly used or because of problems related to their manufacturing, BCT-related interferences in test results can adversely influence patient outcomes, decrease laboratory efficiency, delay test results, and increase the cost per test due to recollection and retesting. Thus, optimization and standardization of BCTs are vital for the reliable test analysis. Because laboratory test result quality ultimately depends on specimen integrity, tube manufacturers, in vitro diagnostic companies, and laboratorians should all remain vigilant in protecting against the adverseeffects of BCT problems on clinical laboratory assays.
The authors would like to thank Ms. Krista Tanquary for editing and reviewing of the manuscript.
Potential conflict of interest
None declared.
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Original scientific paper:

Massimo Daves1*, Roberto Cemin2, Bruno Fattor3, Giovanni Cosio1, Gian Luca Salvagno4, Francesco Rizza1, Giuseppe Lippi5. Evaluation of hematocrit bias on blood glucose measurement with six different portable glucose meters. Biochemia Medica 2011;21(3):306-11.
1Clinical Biochemical Laboratory, Regional Hospital of Bolzano, Bolzano, Italy
2 Cardiology Division, Regional Hospital of Bolzano, Bolzano, Italy
3 Internal Medicine Division, Regional Hospital of Bolzano, Bolzano, Italy
4 Sezione di Chimica Clinica, Università degli Studi di Verona, Verona, Italy
5 U.O. Diagnostica Ematochimica, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
*Corresponding author: massimo [dot] daves [at] asbz [dot] it
Introduction: Measurement and monitoring of blood glucose levels in hospitalized patients with portable glucose meters (PGMs) is performed widely and is an essential part of diabetes monitoring, despite the increasing evidence of several interferences which can negatively bias the accuracy of measurements. The purpose of this study was to evaluate the effect of the hematocrit on the analytical performances of different PGMs as compared with a reference laboratory assay.
Materials and methods:The effect of various hematocrit values (~0.20, ~0.45 and ~0.63 L/L) were assessed in three whole blood specimens with different glucose concentration (~1.1, ~13.3, and ~25 mmol/L) by using six different commercial PGMs. The identical samples were also tested with the laboratory reference assay (i.e., hexokinase). The percentage difference from the laboratory assay (%Diff) was calculated as follows: % Diff = average PGM value - value from laboratory assay x 100 / value from laboratory assay.
Results: The %Diff of the six different PGMs were rather broad, and comprised between 56.5% and -34.8% in the sample with low glucose concentration (č1.1 mmol/L), between 40% and -32% in the sample with high glucose concentration (~13.3 mmol/L), and between –50% and 15% in the sample with very high glucose concentration (~25 mmol/L), respectively. It is also noteworthy that a very high hematocrit value (up to 0.63 L/L) generated a remarkable negative bias in blood glucose (-35%) as measured with the laboratory assay, when compared with the reference sample (hematocrit 0.45 L/L).
Conclusion: The results of this analytical evaluation clearly confirm that hematocrit produces a strong and almost unpredictable bias on PGMs performances, which is mainly dependent on the different type of devices. As such, the healthcare staff and the patients must be aware of this limitation, especially in the presence of extreme hematocrit levels, when plasma glucose assessment with the reference laboratory technique might be advisable.
Key words: portable glucose meters; hematocrit bias; analytic performance
Received: April 11, 2011                                                                                                                Accepted: August 18, 2011
The chronic hyperglycaemia of diabetes mellitus is associated with long-term organ dysfunction and increased risk of complications such as cardiovascular disease, renal failure, retinal and neurological diseases (1). Regular monitoring of blood glucose along with appropriate pharmacological treatment are effective to improve the glycaemic control and thereby decrease the burden of long term complications of hyperglycaemia (2). In agreement with the current position of the American Diabetes Association (ADA), self-monitoring of blood glucose (SMBG) is recommended for all patient undergoing insulin therapy (3). In particular, ADA suggests that SMBG should be used in patients on intensive insulin therapy, in patients not in pharmacological treatment but in diet therapy alone to achieve an optimal glycaemia control, and to achieve the optimal postprandial glycaemic target (4). The National Academy of Clinical Biochemistry (NACB) also recommends that SMBG should be made available to all diabetic patients on insulin therapy (5). Portable glucose meters (PGMs) are widely used by patients for home testing, and despite these devices are fast and easy to use, the patients must be trained on the correct handling. Moreover, PGMs are currently used in other clinical settings, including departments of acute and chronic care (hospital, clinics) as well as internal medical wards to monitor hypoglycaemic therapy in diabetics and patients with acute myocardial infarction. In internal medicine wards, PGMs are used directly by the healthcare staff, which should be appropriately trained to their use and maintenance, so that the risk of improper application can be eliminated or limited at least. Nevertheless, some variables can affect the efficacy of glucose monitoring by PGM also in this setting, including the hematocrit level, hypoxemia, hypotension, hypertriglyceridemia, temperature and humidity of the environment (6). The purpose of this study was to evaluate the interference of the hematocrit on the analytical performances of different PGMs as compared with the laboratory measurement.
Material and methods
To evaluate the effect of hematocrit on reliability of PGM test result, three different hematocrit levels (0.22, 0.45 and 0.62 L/L) were studied. Three levels of glucose (target ranges as č20 mg/dL, č240 mg/dL and č450 mg/dL; i.e., č1.1 mmol/L; č13.3 mmol/L and č25 mmol/L) were assessed. We obtained discarded venous blood collected in heparin tubes without separator gel (Venosafe, Terumo Europe, Leuven, Belgium) from healthy donors. Assuming that samples with very low glucose concentrations are not easily available, these were obtained by collecting the blood the day before the evaluation and maintained the whole anticoagulated blood on a rocker to allow consumption of glucose. We ensured the blood was saturated with oxygen by opening the tubes. Afterwards, a glucose stock solution (Concentration 20 g/dL) supplied by Nova Biomedical Corporation (Waltham, CA, USA)(i.e., the addition of 7.5 μL of glucose spiking solution to a 1 mL whole blood sample increases the glucose concentration by 8.3 mmol/L) was spiked into each blood collection tube to obtain the target glucose ranges andthe blood tubes were then placed on blood tubes rocker for 10 minutes to allow adequate mixing.
The initial hematocrit of the stock blood (i.e., 0.469 L/L) was assessed on a hematological analyzer (Coulter LH750 Analyser, Beckman Coulter, Fullerton, CA, USA). In our laboratory the reference interval of hematocrit values are 0.37-0.47 L/L for females and 0.42-0.52 L/L for males, respectively. Three aliquots of 1 mL samples were thereby prepared (labelled as A1, A2, A3) by adding fixed amount of packed red blood cells and plasma to achieve final hematocrit concentrations in the tubes as follows: A1: 0.22; A2: 0.45; A3: 0.62 L/L. The tubes were then placed on tube rocker for 10 minutes and glucose was tested afterwards with six PGMs and, after centrifugation of the samples (then minutes at 3500 rpm), by the reference laboratory assay (i.e., hexokinase, Olympus AU 2700, Beckman Coulter, Fullerton, CA, USA). Table 1 shows the main characteristics of the PGMs used in this study (Accu-Chek Compact Plus Roche Diagnostics GmbH, Mannheim, Germany; Breeze2 Bayer, Basel, Switzerland; One touch Vita, Life Scan Inc., Milpitas, CA, USA; Optium Xceed Abbott Diabetes Care, Oxon, UK; Ratisbonne BGM, Acon Laboratories Inc. San Diego, CA, USA; Stat-Strip Xpress Nova Biomedical, Waltham,CA, USA). Only one test strip lot was used for each PGMs. The PGMs and the laboratory assay were all calibrated according to manufacturer’s instruction. All the measurements were performed simultaneously (within 10 min) in duplicate by two skilled laboratory technologists.
Table 1. Characteristic of the GPMs used in this study.
Statistical analysis
The % difference from laboratory method (%Diff) was calculated by the average glucose measurement of each duplicate obtained from each PGM from the value obtained by the laboratory method (i.e., % Diff = average PGM value - value from the reference laboratory assay x 100 / value the reference laboratory assay).
The results of this investigation are shown in figures 1, 2 and 3 and in tables 2, 3 and 4. At low glucose concentration (~1.1 mmol/L) the %Diff from the value obtained by the laboratory method are comprised between 56.5% and -34.8%. Among the different PGMs, the Stat-Strip Xpress shows the best performance in comparison with the reference laboratory assay (%Diff between -4.3 and +8.7). It is however noteworthy that the bias of some PGMs (as compared with the reference laboratory assay) at normal hematocrit level and very low glucose concentration was broad and clinically meaningful (Figure 1).
Figure 1. %Diff from laboratory method at different hematocrit levels (0.22, 0.45 and 0.63 L/L) in the sample with very low glucose concentration (~1.1 mmol/L).
At high glucose concentration (~13.3 mmol/L) the %Diff were comprised between -32% and +40%. In such case, the modest performance by PGMs is conceivably attributable to the effect of high levels of hematocrit. Interestingly, the observed bias of PGMs was mostly negative (i.e., from -32% to -17%), with the only exception of the Ratisbonne (+40%). The Stat-Strip Xpress and the Accu-Chek showed the best performance in comparison with the laboratory assay (Figure 2).
Figure 2. %Diff from laboratory method at different hematocrit levels (0.22, 0.45 and 0.63 L/L) in the sample with high glucose concentration (~13.3 mmol/L).
At very high glucose concentration (~25 mmol/L), the %Diff was comprised between -50% and 15%. (Figure 3). As expected, the great difference from the reference laboratory assay was again attributable to the influence of extremely high hematocrit level. Even more interestingly, the sample with hematocrit value up to 0.63 also produced a remarkable bias using the laboratory technique, since the sample with a theoretically glucose concentration of 25 mmol/L yielded instead a final value of 16 mmol/L (i.e., -35%).
Figure 3. %Diff from laboratory method at different hematocrit levels (0.22, 0.45 and 0.63 L/L) in the sample with very high glucose concentration (~25 mmol/L).
Table 2. Glucose measurement (mean of two replicates) and %Diff on sample with low glucose concentration. Value from laboratory method 1.28 mmol/L (as mean of two replicate in the sample with hematocrit 0.45 L/L).
Table 3. Glucose measurement (mean of two replicates) and %Diff on sample with high glucose concentration. Value from laboratory method 13.4 mmol/L (as mean of two replicate in the sample with hematocrit = 0.45 L/L.
Table 4. Glucose measurement (mean of two replicates) and %Diff on sample with very high glucose concentration. Value from laboratory method 25.2 mmol/L (as mean of two replicate in the sample with hematocrit = 0.45 L/L.
Preanalytical variability and analytical quality both have a strong influence on the reliability of laboratory testing, on common laboratory assays (7-11) and point of care testing (POCT) (12).
The revised Clinical and Laboratory Standards Institute (CLSI, the former National Committee for Clinical Laboratory Standards) guidelines (9), and further adopted by the International Organization for Standardization (ISO), recommend that less than 5% of the samples should have a bias of ± 0.83 mmol/L (for glucose concentrations < 4.2 mmolL), or within ± 20% (for glucose concentrations > 4.2 mmol/L), when compared with the reference laboratory assay. Therefore the results of this analytical investigation confirm that the hematocrit value can substantially bias glucose measurements on PGMs and reference laboratory assay, producing a bias that largely exceed the quality requirements established by the CLSI and which can thereby be considered clinically significant. Noteworthy, the hematocrit bias appeared extremely heterogeneous and mostly unpredictable among the different PGMs, with differences as high as 40%. This finding has substantial clinical implication for both the clinical decision making and the therapeutic management, especially in subjects who are characterized by unusually high or low hematocrit values, such as newborns and critically ill patients, respectively. In particular, we have shown that this bias is also evident in samples with very low glucose levels (i.e., č1.1 mmol/L) as compared with the reference laboratory technique (Figure 1). Recently Roth-Kleiner report that before daily use in the newborn population, careful clinical evaluation of each new POCT system for glucose measurement is of utmost importance, concluding that the bench analyzer ABL 735 was the most accurate system, being however characterized by an important drawback (i.e., the blood volume needed is more than 15 times higher than for handheld PGMs) (13). So, the users of PGMs (both the healthcare personnel and the patients) must be aware of this limitation and, as recommended by Tang et al. (14), we suggest that clinicians must interpret with great caution the results obtained with PGMs in patients with abnormal (especially very high or very low) hematocrit levels. In these circumstances, the measurement of plasma glucose using the laboratory technique might be advisable.
Although the mechanism underlying the preanalytical interference of hematocrit has not been fully established, it has however been suggested that the presence of an increased number of red blood cells might (mechanically) prevent the diffusion of plasma through the layers of the test strips, thereby decreasing the volume of plasma available for the enzymatic reaction (6). This interference has been eliminated in some PGMs that measure hematocrit along with glucose in the drop of blood, operating a further correction of test results (15). Some authors have also developed a simple mathematical correction formula for some commonly used PGMs used in the United States that is effective to reduce, as claimed by the authors, the inaccuracy caused by anemia (16,17). More recently, Hoedemaekers et al. failed to observe an effect of hematocrit on the accuracy of PGMs performance in critically ill patients (18).
We would like to thank the technical staff (Maria Gabriella Groppo, Nadia Trevisan and Sara Negrisolo) for their collaborative work.
Potential conflict of interest
None declared.
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11. Simundic AM, Topic E, Nikolac N, Lippi G. Hemolysis detection and management of hemolysed specimens. Biochem Med 2010;20:154-9.
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Procjena pogreške zbog hematokrita prilikom mjerenja koncentracije glukoze u krvi primjenom šest različitih prijenosnih glukometara
Uvod: Mjerenje i praćenje koncentracije glukoze u krvi kod hospitaliziranih bolesnika prijenosnim glukometrom (engl. portable glucose meters, PGMs) u širokoj je primjeni te predstavlja ključan dio liječenja šećerne bolesti, usprkos prisustvu nekoliko vrsta interferencija koje mogu uzrokovati negativnu pogrešku prilikom mjerenja. Svrha ovog istraživanja je procijeniti utjecaj hematokrita na analitički rad različitih PGM u usporedbi s referentnom laboratorijskom metodom.
Materijali i metode: Utjecaj različitih vrijednosti hematokrita (~0,20, ~0,45 i ~0,63 L/L) procijenjen je u tri uzorka pune krvi s različitom koncentracijom glukoze (~1,1, ~13,3 i ~25,0 mmol/L) primjenom šest različitih komercijalnih PGM. Isti su uzorci ispitivani referentnom laboratorijskom metodom (heksokinazom). Postotak razlike u odnosu na laboratorijsku metodu (%Diff) izračunat je na sljedeći način: %Diff = prosječna vrijednost dobivena PGM – vrijednost dobivena laboratorijskom metodom x 100 / vrijednost dobivena laboratorijskom metodom.
Rezultati: %Diff između šest različitih PGM bila je širokog raspona i iznosila između 56,5% do -34,8% kod uzoraka s niskom koncentracijom glukoze (~1,1 mmol/L), između 40% i -32% kod uzoraka s visokom koncentracijom glukoze (~13,3 mmol/L) i između -50% i 15% kod uzoraka s vrlo visokom koncentracijom glukoze (~5,0 mmol/L). Također je značajan podatak da je vrlo visoka vrijednost hematokrita (0,63 L/L) stvorila značajno negativnu pogrešku kod određivanja koncentracije glukoze u krvi (-35%) laboratorijskom metodom u usporedbi s referentnim uzorkom (hematokrit 0,45 L/L).
Zaključak: Rezultati ovog analitičkog istraživanja jasno potvrđuju da hematokrit stvara jaku i gotovo nepredvidivu pogrešku u primjeni PGM što uglavnom ovisi o različitom tipu uređaja. Zdravstveno osoblje i bolesnici moraju biti svjesni tog ograničenja pogotovo kod pojave ekstremne razine hematokrita kada se preporuča određivanje koncentracije glukoze u plazmi referentnim laboratorijskim metodama.
Ključne riječi: prijenosni glukometar; pogreška; hematokrit; analitički rad

Original scientific paper:

Giuseppe Lippi1*, Paola Avanzini1, Fernan da Pavesi1, Mirco Bardi1, Luigi Ippolito1, Rosalia Aloe1, Emmanuel J Favaloro2. Studies on in vitro hemolysis and utility of corrective formulas for reporting results on hemolyzed specimens. Biochemia Medica 2011;21(3):297-305.
1U.O. Diagnostica Ematochimica, Dipartimento di Patologia e Medicina di Laboratorio, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
2Department of Haematology, Institute of Clinical Pathology and Medical Research (ICPMR), Westmead Hospital, NSW, Australia
*Corresponding author: glippi [at] ao [dot] pr [dot] it, ulippi [at] tin [dot] it
Introduction: Spuriously hemolyzed specimens are the most common preanalytical problems in clinical laboratories. Corrective formulas have been proposed to allow the laboratory to release test results on these specimens. This study aimed to assess the influence of spurious hemolysis and reliability of corrective formulas.
Materials and methods:Blood collected into lithium heparin vacuum tubes was divided in aliquots and subjected to mechanical injury by aspiration with an insulin syringe equipped with a thin needle (30 gauge). Each aliquot (numbered from “#0” to “#5”) was subjected to a growing number of passages through the needle, from 0 to 5 times. After hematological testing, plasma was separated by centrifugation and assayed for lactate dehydrogenase (LD), aspartate aminotransferase (AST), potassium and hemolysis index (HI).
Results:Cell-free hemoglobin concentration gradually increased from aliquot #0 (HI: 0) to #5 (HI: 76±22, cell-free hemoglobin č 37.0 g/L). A highly significant inverse correlation was observed between HI and red blood cell count (RBC), hematocrit, mean corpuscular volume (MCV), LD, AST, potassium, whereas the correlation was negative with mean corpuscular hemoglobin (MCH). No correlation was found with hemoglobin, platelet count and glucose. A trend towards decrease was also observed for white blood cells count. The ANCOVA comparison of analyte-specific regression lines from the five subjects studied revealed significant differences for all parameters except potassium. In all circumstances the sy,x of these equations however exceeded the allowable clinical bias.
Conclusions:Mechanical injury of blood, as it might arise from preanalytical problems, occurs dishomogeneously, so that corrective formulas are unreliable and likely misleading.
Key words:hemolysis; hemolyzed specimens; interference; preanalytical variability
Received: July 27, 2011                                                                                                              Accepted: August 25, 2011
Laboratory diagnostics is a complex enterprise, with the ultimate aim to provide reliable and appropriate information to the key stakeholders, i.e., patients and clinicians. Although it is commonly assumed that laboratory testing is trustworthy and safe, a variety of risks might arise throughout the total testing process. Some of these problems can adversely affect the quality of results and furthermore waste precious economic healthcare resources, as well as jeopardize patient safety. The testing process is traditionally divided in three major stages, namely the preanalytical, analytical and postanalytical phases. Due to remarkable technological advances and strict internal and external control of the process, a major degree of safety has been achieved in the analytical phase, as granted by high test accuracy and precision. Accordingly, the major vulnerabilities seem to arise now from the pre- and postanalytical phases (1). In particular, considerable data has been gathered to support the notion that the manually intensive preanalytical activities are responsible for the vast majority of errors throughout the total testing process, and upwards of 70% of all errors (1-4). These activities broadly entail the collection, handling, transport, preparation and storage of the specimens that are subsequently utilized for testing.
Several individual studies and critical reviews of the literature have now clearly established that spuriously hemolyzed specimens represent the most common preanalytical problem encountered in the daily laboratory practice. Their frequency is comprised between 2 and 3% of all of routine samples, which is nearly five-time higher than the second cause (i.e., clotted samples). More importantly, only minorities of hemolyzed specimens reflect an in vivo cause of hemolysis (i.e., hemolytic anemia, occurring in č3% of all hemolyzed samples) (5). Thus, most of the hemolyzed samples referred to the laboratory for testing reflect the breakdown of erythrocytes and other blood cells during the collection, handling and/or transportation of the specimens. The multitude of factors that might generate spurious hemolysis typically begins during venipuncture and then continues downstream throughout this process, up to the time of analysis. These factors can be classified as follows (6,7):
-          Factors dependent upon patient’s conditions (e.g., fragile veins or unsuitable venous access);
-          Factors dependent upon the ability of the phlebotomist;
-          Factors dependent upon the venipuncture per se (e.g., traumatic blood draw, unsatisfactory attempts, vein missing, prolonged placement of the tourniquet);
-          Factors associated with the devices used for collecting the sample (e.g., syringes, cannulas, butterfly devices, small gauge needles);
-          Factors dependent upon the conditions for transport (e.g., prolonged transportation, unsuitable environmental conditions - excess heat or cold – as well as contact of tubes with frozen packs);
-          Factors dependent upon processing of the specimen (e.g., force, time and temperature of centrifugation, or generation of poor barrier integrity between blood cells and serum or plasma);
-          Factors dependent upon the storage of specimens (e.g., refrigerated as whole blood with poor barrier between cells and sample, freezing-thawing of samples, storage in cyclic defrost freezers).
The major problem encountered with hemolyzed specimens is represented by the varying degree of interference with some laboratory assays, which is typically dependent upon biological factors (e.g., leakage of intracellular components into serum or plasma, release of cell derived tissue factor and phospholipids), chemical and/or spectrophotometric interference of cell-free hemoglobin in certain assays (6,7).
It has been previously highlighted that whenever a laboratory test is unreliable due to the presence of an “interferent” such as cell-free hemoglobin, the results should be suppressed and blinded to the clinicians (6-8). Nevertheless, this procedure is challenging, since it might cause relational problems, especially with the emergency department where the burden of hemolyzed specimens is comparatively high (9), or with emergency physicians who need urgent results for rapid patient triage (10). The advantages of routine determination of plasma or serum cell-free hemoglobin concentration have been described (11). Corrective formulas have also been proposed, so that adjustment of the data obtained on hemolyzed specimens would permit to release test results with an appropriate accompanying post-analytical comment (e.g., “results obtained on a hemolyzed specimen, suggest repeat testing for confirmation”) (12-14), or the hemolysis index (HI) (15-18). Some caveats have however been highlighted in this policy, including the imprecise estimation of the analytes following the use of these corrective equations, due primarily to the large intra-individual variability. Therefore, to further assess whether correction of hemolysis-sensitive laboratory tests for the degree of cell-free hemoglobin might be suitable, we performed a series of studies on mechanically-induced hemolyzed samples and potential corrective formulas for reporting results on these specimens. This is of notable importance since most clinical chemistry instruments are now equipped with serum indices, including the HI, which are much more reliable than classically applied visual inspection (19,20), and would permit an instantaneously applied correction of test results by incorporating a HI-based equation within specific instrumentation, middleware software or within the laboratory information system (LIS) (21).
Materials and methods
Samples and methods
Blood was collected by a single experienced phlebotomist early in the morning into 6.0 mL siliconized vacuum tubes without gel separator and containing 18 U/L lithium heparin (Vacuette, Greiner Bio-One GmbH, Frickenhausen, Germany), by using a 20 gauge, 0.80 x 19 mm straight needle (Greiner Bio-One GmbH). Two consecutive primary tubes were drawn from each of 5 healthy volunteers recruited among the laboratory staff (3 males and 2 females, mean age 42 years; range 38-46 years). The study was carried out according to the Declaration of Helsinki and under the terms of all relevant local legislation, and all subjects provided written informed consent. The blood from the two primary tubes was pooled. Spurious hemolysis was obtained by a variation of the original method of Dimeski (22), i.e., by aspirating the blood with a 0.5 mL insulin syringe equipped with a very thin needle (30 gauge, 0.3 x 8 mm). A first aliquot (“#0”) was separated from the rest of the blood and processed without further manipulation. A second aliquot (“#1”) was obtained by a single aspiration of the pooled blood. A third aliquot (“#2”) was then obtained by a single aspiration of the blood in aliquot #1, a fourth aliquot (#3) by a single aspiration of the blood in aliquot #2, a fifth aliquot (#4) by a single aspiration of the blood in aliquot #3, and a sixth aliquot (#5) by a single aspiration of the blood in aliquot #4. This method has been validated to reliably mirror a traumatic blood collection with production of a poor quality specimen (22), and is also expected to produce injury to platelets and white blood cells (WBC), other than to red blood cells (RBCs). The anticoagulated whole blood was immediately assessed on an Advia 2120 (Siemens Healthcare Diagnostics, Tarrytown NY, USA) for hematological testing. Lithium-heparin plasma from each aliquot was also subsequently obtained by centrifugation at 2000 x g for 15 min at room temperature, separation from the cell pellet and then tested for lactate dehydrogenase (LD; DGKC method), aspartate aminotransferase (AST; IFCC method with pyridoxal phosphate activation), potassium and HI on a Beckman Coulter DxC (Beckman Coulter Inc., Brea CA, USA), following manufacturer specifications and using proprietary reagents. The HI is assessed on Beckman Coulter DxC by direct spectrophotometry. Semiquantitative values are calculated on a linear scale from 0 (0 g/L of hemoglobin) to 10 (hemoglobin from 4.5 to 5.0 g/L). The highly significant correlation between HI and cell-free hemoglobin (measured with the reference cyanmethemoglobin assay) has been reported elsewhere (23). When outside the linearity of the methods, the aliquots were further diluted in saline to obtain a definitive value. Total imprecision (i.e., CV) of all the parameters tested has been reported to be < 2.5% for both the ADVIA 2120 (24), and Beckman Coulter DxC (25). The same instruments and reagent lots were used throughout the study and all measurements were performed within a single analytical session.
Statistical analysis
The comparison of analyte-specific regression lines obtained from each of the five subjects was done by ANCOVA. Correlation was calculated between the baseline MCV (mean corpuscular volume) value and the slope of the RBCs equation. The bias of results was also compared with the quality specifications derived from biologic variation for each of the parameter analyzed (26).
Statistical analysis was carried out by using Dsaastat for Excel version 1.1 (available at:
The main results of this investigation are reported in table 1. As expected, no significant amount of cell-free hemoglobin was found in the baseline aliquot #0 (i.e., HI of 0 in all samples, cell-free hemoglbin < 0.5 g/L). Conversely a progressive amount of cell-free hemoglobin was observed in the subsequent aliquots: aliquot #1, HI of 15±6 (cell free hemoglobin č7.0 g/L); aliquot #2, HI of 29±11 (cell free hemoglobin č14.0 g/L); aliquot #3, HI of 45±14 (cell free hemoglobin č22.0 g/L); aliquot #4, HI of 59±17 (cell free hemoglobin č29.0 g/L); and aliquot #5, HI of 76±22 (cell free hemoglobin č37.0 g/L). A highly significant inverse correlation was observed between HI and RBC count, hematocrit, MCV, LD, AST and potassium, whereas a highly significant negative correlation was observed with the Mean Corpuscular Hemoglobin (MCH). No significant correlation was instead observed between HI and hemoglobin, platelet count and glucose (Table 1). A marginally significant, negative correlation was observed between the HI and WBC count. In particular, although an evident trend was observed towards decreasing values of the WBC in parallel with the increase of the HI, the overall behavior was extremely heterogeneous among the study population, as shown in figure 1. Similarly, the platelet count also exhibited an apparent and remarkable increase in grossly hemolyzed specimens (i.e., HI > 100; cell-free hemoglobin of č50 g/L). The comparison by ANCOVA of analyte-specific regression lines obtained from each of the five subjects studied revealed that the resulting individual equations significantly differed (i.e., P < 0.001) among the five subjects for all parameters tested except potassium (P = 0.090) (Figure 2). A significant correlation was also observed between the baseline MCV value and the slope of the RBCs equation (r = -0.901; P = 0.037). As regards the clinical significance of these variations, in all circumstances the sy,x calculated from the individual linear regression analysis between the HI and the parameters, largely exceeded the quality specifications for desirable bias when expressed as percentage bias (Table 1).
Table 1. Correlation and linear regression analysis between the Hemolysis Index and results of hematological and clinical chemistry parameters in mechanically hemolyzed specimens collected from five healthy volunteers.
 Figure 1. Behavior of white blood cell (WBC) (1A) and platelet (1B) count in mechanically hemolyzed specimens.
Figure 2. Linear regression analysis between hemolysis index (HI) and red blood cell count (2A), hemoglobin (2B), hematocrit (2C), MCV (2D), MCH (2E), LD (2F), AST (2G) and potassium (2H).
Hemolyzed specimens represent a crucial issue in laboratory diagnostics, both for the high frequency and for the important interference that cell-free hemoglobin, other intracellular components and cellular debris exert on a variety of clinical chemistry (28), coagulation (29), and immunochemistry assays (7), as well as on arterial blood gas analysis (30). Moreover, since hemolyzed specimens are often an important cause of relational, economical and organizational problems between laboratory professionals and physicians, especially those working in the emergency department (10), some corrective formulas have been proposed, since this might be beneficial for early triage and decision making, and further harmonizing professional relationships. At least hypothetically, when the lower bound of the predicted bias would provide a roughly acceptable value (i.e., within the reference range), the collection of a second sample might be unnecessary. In these specifically reported equations, the concentration of the analyte is multiplied by the slope obtained from a linear regression analysis between the bias observed at different cell-free hemoglobin concentrations, as assessed by either the cyanmethemoglobin assay (12,13), or the HI (15-17). Brescia et al. suggested an additional approach, where the analyte (i.e., potassium) released by lyzed RBCs is estimated from a formula including the MCHC along with cell-free hemoglobin (18). There are however several theoretical reasons proposed against the use of such formulas, which include (i) the large heterogeneity of the different formulas which prevents their interchangeability among different local conditions of instrumentation, assay and sample matrix (e.g., serum or plasma), (ii) the potentially broad interindividual variability of most intracellular constituents (e.g., potassium, LD and AST), and (iii) the misleading information about the biochemical profile in the presence of hemolytic anemia. While the last two aspects are virtually incontestable, the aim of this experiment was to verify whether also the third assumption was valid, thereby arguing definitively against the use of these equations.
Taken together, our results support the hypothesis that a dishomogenous interindividual behavior of clinical chemistry and hematological parameters exists following mechanical trauma of blood, so that the different tests could be essentially classified according to five patterns, as shown in figure 3, i.e., unaffected, homogenous interindividual variation and non clinically significant bias, heterogeneous interindividual variation and non clinically significant bias, homogenous interindividual variation and clinically significant bias, heterogeneous interindividual variation and clinically significant bias. The first and the second would reasonably reflect the ideal conditions. In the first case, the results might be safely released to the clinicians since the bias caused by blood cell lysis is virtually inappreciable. The second case might also be similarly handled, since the homogeneous interindividual variation of results and the lack of a clinically significant bias would allow the use of corrective formulas, calculated according to the concentration of cell-free hemoglobin in the sample to permit adjustment of test results accordingly. The three other conditions would instead lead to suppression of all test results and blinding of these to the clinicians since (i) one corrective formula would not be adequate for all cases in the presence of a high degree of interindividual variation of results, or (ii) the correction of results by any corrective equation would hypothetically produce an estimated value that exceeds clinical significance and would thereby be unreliable or misleading.
According to our results, hemoglobin and glucose fell within the first category, so that test results on hemolyzed specimens might be reliable regardless of the concentration of cell-free hemoglobin in the specimen (Figure 3). No parameter tested fell within the second category, i.e., displayed a homogenous interindividual variation and a non clinically significant bias that would permit the calculation of an analyte-specific, universal, corrective formula for each analyte to accurately estimate test results. Conversely, all remaining test parameters could be classified within the other three categories, where the use of an equation formula would be misleading due to the large interindividual variability of the values (RBC count, hematocrit, MCV and MCH), or the imprecise estimation since the percentage bias of the sy,x exceeded the quality specifications for desirable bias derived from biologic variation (i.e., potassium), or both aspects (platelet count, WBC count, LD and AST) (Figure 3) (26). In clinical practice, this implies that (i) the values of RBC count, hematocrit, MCV and MCH in hemolyzed specimens might be reliably predicted by a HI-based equation, which should however be individualized (i.e., separate equation for each patient); (ii) a common formula might be developed for predicting potassium values according to the HI, but the calculated value would not be sufficiently accurate to be clinically usable, and (iii) the values of platelet count, WBC count, LD and AST cannot be accurately predicted from the HI, nor can a common equation be identified. These results, at least for potassium, are in keeping with those of Shepherd et al., who correlated the bias between potassium in the hemolyzed and non-hemolyzed repeated samples with the HI (31). These workers also observed a significant linear relationship, mirrored by a 0.16 mmol/L potassium increase for each increment of the HI. Nevertheless, in agreement with our results, they observed a wide bias in potassium values calculated from the expected equation (i.e., ± 0.4 mmol/L vs. ± 0.5 mmol/L in our study), concluding that the magnitude of this variation was too excessive to recommend the use of the HI to predict potassium concentration in hemolyzed specimens.
Figure 3. Classification of hematological and clinical chemistry results in hemolyzed specimens.
WBC - white blood cells; RBC - red blood cells; Hb - hemoglobin; Ht – hematocrit; MCV - mean corpuscular volume; MCH - mean corpuscular hemoglobin; Plt – platelets; LD -lactate dehydrogenase; AST - aspartate aminotransferase.
Despite the limited number of subjects investigated, all the trends were however consistent. As such, an additional and important aspect that we observed in this study is that - although a similar pattern of RBCs lysis was observed among the study population – the slopes were statistically different one from the other, indicating that the different subjects were characterized by heterogeneous erythrocyte fragility. Interestingly, the slope of the RBCs equation was reliably predicted by the baseline MCV value (r = -0.901; P = 0.037), thereby suggesting that the differential degree of RBCs breakdown might at least partially depend upon the initial size of the erythrocytes, where the RBCs of subjects with smaller MCV tend to be more resistant to the mechanical lysis than those of subjects with a greater MCV. Unpredictable patterns were also observed for platelet count and WBC. While the results of the former parameter were dramatically unreliable, increasing progressively in parallel with the increase of the HI due to the well known interference from damaged blood cells and their cytoplasmic fragments in platelet enumeration and sizing (32), the behavior of WBC was roughly similar among the different individuals, displaying a significant inverse relationship with the HI and thereby confirming that WBCs other than RBCs might be dramatically injured in hemolyzed specimens.
In conclusion, the results of our investigation attest that the mechanical injury of the blood, as it might occur during flawed or mishandled procedures for collecting and handling blood specimens, does not occur homogeneously nor sufficiently predictably among different subjects, so that the use of corrective formulas to adjust and release test results on these samples is unreliable and likely to be even misleading.
Potential conflict of interest
None declared.
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Istraživanja o in vitro hemolizi i primjeni korektivnih formula u izvještavanju o rezultatima iz hemolitičnih uzoraka
Uvod: Lagano hemolitični uzorci predstavljaju najčešći problem u prijeanalitičkoj fazi u radu kliničkih laboratorija. Predložene su korektivne formule koje omogućuju laboratoriju izdavanje rezultata iz takvih uzoraka. Cilj ovog istraživanja je procjena utjecaja hemolize in vitro na pouzdanost korektivnih formula.
Materijali i metode: Krv sakupljena u vakuum epruvete s litij-heparinom alikvotirana je te su u njoj mehanički oštećene stanice aspiracijom inzulinskom injekcijom s tankom iglom (30 gauge). Alikvoti su označeni brojevima od “#0” do “#5”. Ovisno o oznaci uzorci krvi su nakon vađenja (uzorak #0) provučeni su kroz iglu dodatnih 1 (uzorak “#1”) do 5 (uzorak “#5”) puta. Nakon hematološkog ispitivanja plazma je odvojena centrifugiranjem i u njoj je određena aktivnost laktat-dehidrogenaze (LD), aspartat-aminotransferaze (AST), koncentracija kalija i indeks hemolize (HI).
Rezultati: Koncentracija slobodnog hemoglobina postepeno je rasla od alikvota #0 (HI = 0) do #5 (HI = 76±22, slobodni hemoglobin č37,0 g/L). Primijećena je statistički značajna inverzna korelacija između HI i broja eritrocita, hematokrita, srednjeg volumena eritrocita (MCV), aktivnosti LDH, AST i koncentracije kalija, dok je korelacija s prosječnom količinom hemoglobina u eritrocitu (MCH) bila negativna, a nije bilo korelacije s koncentracijom hemoglobina i glukoze te brojem trombocita. Primijećen je trend prema nižoj koncentraciji leukocita. ANCOVA usporedbom regresijskih pravaca specifičnih za svaki analit dobivene su statistički značajne razlike za sve parametre osim kalija. Međutim, u svim oblicima je sy,x bio iznad dopuštene kliničke pogreške.
Zaključak: Mehaničko oštećivanje stanica u krvi koje se može dogoditi u prijeanalitičkoj fazi, nije homogeno, što čini korektivne formule nepouzdanima te je vrlo vjerojatno da će navesti na pogrešan zaključak.
Ključne riječi: hemoliza, hemolitični uzorci, interferencija, prijeanalitička varijabilnost