- Email: [email protected]
What is in that sample ? A pertinent question when assessing quality for patient laboratory results and beyond
Clinical Biochemistry 48 (2015) 465–466
Contents lists available at ScienceDirect
Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
Editorial
What is in that sample ? A pertinent question when assessing quality for patient laboratory results and beyond Keywords: Quality Pre-analytical Analytical Interferences Sample colour Biobank
In laboratory medicine a major emphasis has been placed on quality [1]. This extends beyond the traditional clinical chemistry analytical methods and into the very techniques used in diagnostic pathology [2]. This latter aspect has been thoroughly addressed in O'Hurley and colleagues review article which highlights important quality barriers for immunohistochemistry (IHC) testing [2]. Factors such as tissue handling (e.g., duration, fixation, processing), storage, and epitope retrieval [2] not only affect IHC testing, but are also important variables for other laboratory testing and for biorepositories as well [3]. In fact, when assessing the overall question of “How good is that sample?” with respect to biobanks [3], a leading inquiry may well be “What is in that sample?”. Otherwise, the expended effort, resources, and data produced could yield artefacts and/or non-reproducible results that could hinder test development, derail the research in a specific clinical area or disease, or in the case of clinical testing could adversely impact patient care. Clinical Biochemistry over the last few years has published articles that have addressed important pre-analytical issues, from collection tubes [4,5], to sample handling and transport [6–10], and even articles assessing approaches for minimizing inferences [11–14]. The latter mainly focusing on known sample/colour interferences (i.e., lipaemia, haemolysis and icterus); however, samples received in the core laboratory can come in many different colours; and when odd colours are observed they garner much attention, especially when they are green [15]. Green serum or plasma is such a rare occurrence, that an investigation usually ensues to identify the underlying cause. Personally, I recall the day a medical laboratory technologist approached me with a green plasma sample. The first response was to recollect a blood sample from the patient; however the repeat sample also yielded green plasma. The next step was to obtain and compare all samples from the patient. Only three plasma samples were obtained, all on the same day; however and importantly, the first plasma sample had normal appearance and was not green. A time-course was constructed and communication with the ordering physician suggested that the most likely cause of the green plasma was due to the administration of Patent Blue V during the procedure (first sample was obtained prior to surgery and the first green plasma post surgery, see Fig. 1). Only sodium, potassium and chloride were clinically ordered on these
samples and the results were within the reference intervals. The dye causing the green plasma colour is consistent with a previous report on green serum where the cause was attributed to a fluorescent dye [15]. Despite the resolution in this case, lingering questions from that day have persisted: What else can result in green serum/plasma? Is the appearance of green serum/plasma pathologic? Is green serum/plasma an acceptable sample type for clinical chemistry testing? In this issue of Clinical Biochemistry, a case report details the appearance of green serum in a pregnant woman and provides additional information into this unusual sample colour appearance [16]. There is still much to be known on this subject matter; however, in this particular case the appearance of green serum did not portend any adverse effects to mother or baby [16]. Another article in this issue coupling pregnancy and childbirth with biobanking and biomarker discovery details the effect of haemolysis on the metabolomic profile in umbilical cord blood [17]. Denihan and colleagues provide compelling evidence that haemolysis may alter specific metabolites and care should be taken to record and possibly avoid these samples [17]. This is important information, that is seldom reported in studies derived from biobanks which may have profound implications in biomarker discovery, especially in the metabolomic field. Unfortunately, not all interferences are visible by the naked eye. Common drugs may adversely affect an analyte's concentration. Specifically, Luna-Záizar and colleagues' article in this issue raise two important aspects with respect to common drugs and creatinine measurement [18]. First, what is a “common drug” will vary from country to country, and international studies measuring creatinine may wish to record this information. Second, these “common drugs” may lead to either a positive bias or negative bias for creatinine depending on their concentration and the method for creatinine measurement (Kinetic Jaffe versus Enyzmatic) [18]. Providing a clinical laboratory service with high quality is an on-going pursuit. Where it begins and where it ends is open to debate. What is non-debatable is that pre-analytical factors play an important role [19, 20]. Ignoring questions related to “What is in that sample?” and “How good is that sample?” may further compromise quality and lead to a “Garbage in, garbage out” approach [2]. Disclosures None to declare. Funding None to declare.
http://dx.doi.org/10.1016/j.clinbiochem.2015.04.010 0009-9120/© 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
466
Editorial
Repeat Draw 3 hours after surgery
ii Post-op 2 hours after surgery
i Pre-op 2 hours before surgery
Fig. 1. Colour of patient plasma sample 2 h prior to surgery (i); colour of patient plasma sample 2 h post surgery (ii); and repeat plasma sample requested by laboratory after noticing green colour.
References [1] Plebani M, Lippi G. To err is human. To misdiagnose might be deadly. Clin Biochem 2010;43:1–3. [2] G, Sjöstedt E, Rahman A, Li B, Kampf C, Pontén F, et al. Garbage in, garbage out: a critical evaluation of strategies used for validation of immunohistochemical biomarkers. Mol Oncol 2014;8:783–98. [3] Hammett-Stabler CA. How good is that sample?. Verifying the integrity of biobanked samples. Clin Biochem 2015;48:363. [4] Bowen RA, Hortin GL, Csako G, Otañez OH, Remaley AT. Impact of blood collection devices on clinical chemistry assays. Clin Biochem 2010;43:4–25. [5] Bowen RA, Sattayapiwat A, Gounden V, Remaley AT. Blood collection tube-related alterations in analyte concentrations in quality control material and serum specimens. Clin Biochem 2014;47:150–7. [6] Kavsak PA. Quality control material testing and the importance of “treating it like a patient's sample”. Clin Biochem 2014;47:147–9. [7] Nikolac N, Omazic J, Simundic AM. The evidence based practice for optimal sample quality for ammonia measurement. Clin Biochem 2014;47:991–5. [8] Kittanakom S, Kavsak PA. Metrics for identifying errors related to pre-analytical sample handling. Clin Biochem 2014;47:989–90.
[9] Norton SE, Lechner JM, Williams T, Fernando MR. A stabilizing reagent prevents cellfree DNA contamination by cellular DNA in plasma during blood sample storage and shipping as determined by digital PCR. Clin Biochem 2013;46:1561–5. [10] Wong D, Moturi S, Angkachatchai V, Mueller R, DeSantis G, van den Boom D. Optimizing blood collection, transport and storage conditions for cell free DNA increases access to prenatal testing. Clin Biochem 2013;46:1099–104. [11] Lippi G, Avanzini P, Cervellin G. Prevention of hemolysis in blood samples collected from intravenous catheters. Clin Biochem 2013;46:561–4. [12] Kavsak PA. A step closer in reducing hemolysis in blood samples collected in the emergency department. Clin Biochem 2013;46:565. [13] Heiligers-Duckers C, Peters NA, van Dijck JJ, Hoeijmakers JM, Janssen MJ. Low vacuum and discard tubes reduce hemolysis in samples drawn from intravenous catheters. Clin Biochem 2013;46:1142–4. [14] Saracevic A, Nikolac N, Simundic AM. The evaluation and comparison of consecutive high speed centrifugation and LipoClear® reagent for lipemia removal. Clin Biochem 2014;47:309–14. [15] Bailey H, Wu AH. Images in clinical medicine. Bright green serum. N Engl J Med 2007;356:e10. [16] Karaca RE, Ulubay M, Fıratlıgil FB, Fidan U, Keskin U, Pehlivan H. Green serum and pregnancy: case report. Clin Biochem 2015;48:550–1. [17] Denihan NM, Walsh BH, Reinke SN, Sykes BD, Mandal R, Wishart DS, et al. The effect of haemolysis on the metabolomic profile of umbilical cord blood. Clin Biochem 2015;48:534–7. [18] Luna-Záizar H, Virgen-Montelongo M, Cortez-Álvarez CR, Ruiz-Quezada SL, EscutiaGutiérrez R, García-Lemus CR, et al. In vitro interference by acetaminophen, aspirin, and metamizole in serum measurements of glucose, urea, and creatinine. Clin Biochem 2015;48:538–41. [19] Plebani M, Sciacovelli L, Marinova M, Marcuccitti J, Chiozza ML. Quality indicators in laboratory medicine: a fundamental tool for quality and patient safety. Clin Biochem 2013;46:1170–4. [20] Green SF. The cost of poor blood specimen quality and errors in preanalytical processes. Clin Biochem 2013;46:1175–9.
Peter A. Kavsak Department of Pathology & Molecular Medicine, McMaster University, Hamilton, Ontario, Canada Juravinski Hospital and Cancer Centre (Core Lab Section) 711 Concession Street Hamilton, ON L8V 1C3, Canada. Fax: 905 575 2581. E-mail address: [email protected].
Contents lists available at ScienceDirect
Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
Editorial
What is in that sample ? A pertinent question when assessing quality for patient laboratory results and beyond Keywords: Quality Pre-analytical Analytical Interferences Sample colour Biobank
In laboratory medicine a major emphasis has been placed on quality [1]. This extends beyond the traditional clinical chemistry analytical methods and into the very techniques used in diagnostic pathology [2]. This latter aspect has been thoroughly addressed in O'Hurley and colleagues review article which highlights important quality barriers for immunohistochemistry (IHC) testing [2]. Factors such as tissue handling (e.g., duration, fixation, processing), storage, and epitope retrieval [2] not only affect IHC testing, but are also important variables for other laboratory testing and for biorepositories as well [3]. In fact, when assessing the overall question of “How good is that sample?” with respect to biobanks [3], a leading inquiry may well be “What is in that sample?”. Otherwise, the expended effort, resources, and data produced could yield artefacts and/or non-reproducible results that could hinder test development, derail the research in a specific clinical area or disease, or in the case of clinical testing could adversely impact patient care. Clinical Biochemistry over the last few years has published articles that have addressed important pre-analytical issues, from collection tubes [4,5], to sample handling and transport [6–10], and even articles assessing approaches for minimizing inferences [11–14]. The latter mainly focusing on known sample/colour interferences (i.e., lipaemia, haemolysis and icterus); however, samples received in the core laboratory can come in many different colours; and when odd colours are observed they garner much attention, especially when they are green [15]. Green serum or plasma is such a rare occurrence, that an investigation usually ensues to identify the underlying cause. Personally, I recall the day a medical laboratory technologist approached me with a green plasma sample. The first response was to recollect a blood sample from the patient; however the repeat sample also yielded green plasma. The next step was to obtain and compare all samples from the patient. Only three plasma samples were obtained, all on the same day; however and importantly, the first plasma sample had normal appearance and was not green. A time-course was constructed and communication with the ordering physician suggested that the most likely cause of the green plasma was due to the administration of Patent Blue V during the procedure (first sample was obtained prior to surgery and the first green plasma post surgery, see Fig. 1). Only sodium, potassium and chloride were clinically ordered on these
samples and the results were within the reference intervals. The dye causing the green plasma colour is consistent with a previous report on green serum where the cause was attributed to a fluorescent dye [15]. Despite the resolution in this case, lingering questions from that day have persisted: What else can result in green serum/plasma? Is the appearance of green serum/plasma pathologic? Is green serum/plasma an acceptable sample type for clinical chemistry testing? In this issue of Clinical Biochemistry, a case report details the appearance of green serum in a pregnant woman and provides additional information into this unusual sample colour appearance [16]. There is still much to be known on this subject matter; however, in this particular case the appearance of green serum did not portend any adverse effects to mother or baby [16]. Another article in this issue coupling pregnancy and childbirth with biobanking and biomarker discovery details the effect of haemolysis on the metabolomic profile in umbilical cord blood [17]. Denihan and colleagues provide compelling evidence that haemolysis may alter specific metabolites and care should be taken to record and possibly avoid these samples [17]. This is important information, that is seldom reported in studies derived from biobanks which may have profound implications in biomarker discovery, especially in the metabolomic field. Unfortunately, not all interferences are visible by the naked eye. Common drugs may adversely affect an analyte's concentration. Specifically, Luna-Záizar and colleagues' article in this issue raise two important aspects with respect to common drugs and creatinine measurement [18]. First, what is a “common drug” will vary from country to country, and international studies measuring creatinine may wish to record this information. Second, these “common drugs” may lead to either a positive bias or negative bias for creatinine depending on their concentration and the method for creatinine measurement (Kinetic Jaffe versus Enyzmatic) [18]. Providing a clinical laboratory service with high quality is an on-going pursuit. Where it begins and where it ends is open to debate. What is non-debatable is that pre-analytical factors play an important role [19, 20]. Ignoring questions related to “What is in that sample?” and “How good is that sample?” may further compromise quality and lead to a “Garbage in, garbage out” approach [2]. Disclosures None to declare. Funding None to declare.
http://dx.doi.org/10.1016/j.clinbiochem.2015.04.010 0009-9120/© 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
466
Editorial
Repeat Draw 3 hours after surgery
ii Post-op 2 hours after surgery
i Pre-op 2 hours before surgery
Fig. 1. Colour of patient plasma sample 2 h prior to surgery (i); colour of patient plasma sample 2 h post surgery (ii); and repeat plasma sample requested by laboratory after noticing green colour.
References [1] Plebani M, Lippi G. To err is human. To misdiagnose might be deadly. Clin Biochem 2010;43:1–3. [2] G, Sjöstedt E, Rahman A, Li B, Kampf C, Pontén F, et al. Garbage in, garbage out: a critical evaluation of strategies used for validation of immunohistochemical biomarkers. Mol Oncol 2014;8:783–98. [3] Hammett-Stabler CA. How good is that sample?. Verifying the integrity of biobanked samples. Clin Biochem 2015;48:363. [4] Bowen RA, Hortin GL, Csako G, Otañez OH, Remaley AT. Impact of blood collection devices on clinical chemistry assays. Clin Biochem 2010;43:4–25. [5] Bowen RA, Sattayapiwat A, Gounden V, Remaley AT. Blood collection tube-related alterations in analyte concentrations in quality control material and serum specimens. Clin Biochem 2014;47:150–7. [6] Kavsak PA. Quality control material testing and the importance of “treating it like a patient's sample”. Clin Biochem 2014;47:147–9. [7] Nikolac N, Omazic J, Simundic AM. The evidence based practice for optimal sample quality for ammonia measurement. Clin Biochem 2014;47:991–5. [8] Kittanakom S, Kavsak PA. Metrics for identifying errors related to pre-analytical sample handling. Clin Biochem 2014;47:989–90.
[9] Norton SE, Lechner JM, Williams T, Fernando MR. A stabilizing reagent prevents cellfree DNA contamination by cellular DNA in plasma during blood sample storage and shipping as determined by digital PCR. Clin Biochem 2013;46:1561–5. [10] Wong D, Moturi S, Angkachatchai V, Mueller R, DeSantis G, van den Boom D. Optimizing blood collection, transport and storage conditions for cell free DNA increases access to prenatal testing. Clin Biochem 2013;46:1099–104. [11] Lippi G, Avanzini P, Cervellin G. Prevention of hemolysis in blood samples collected from intravenous catheters. Clin Biochem 2013;46:561–4. [12] Kavsak PA. A step closer in reducing hemolysis in blood samples collected in the emergency department. Clin Biochem 2013;46:565. [13] Heiligers-Duckers C, Peters NA, van Dijck JJ, Hoeijmakers JM, Janssen MJ. Low vacuum and discard tubes reduce hemolysis in samples drawn from intravenous catheters. Clin Biochem 2013;46:1142–4. [14] Saracevic A, Nikolac N, Simundic AM. The evaluation and comparison of consecutive high speed centrifugation and LipoClear® reagent for lipemia removal. Clin Biochem 2014;47:309–14. [15] Bailey H, Wu AH. Images in clinical medicine. Bright green serum. N Engl J Med 2007;356:e10. [16] Karaca RE, Ulubay M, Fıratlıgil FB, Fidan U, Keskin U, Pehlivan H. Green serum and pregnancy: case report. Clin Biochem 2015;48:550–1. [17] Denihan NM, Walsh BH, Reinke SN, Sykes BD, Mandal R, Wishart DS, et al. The effect of haemolysis on the metabolomic profile of umbilical cord blood. Clin Biochem 2015;48:534–7. [18] Luna-Záizar H, Virgen-Montelongo M, Cortez-Álvarez CR, Ruiz-Quezada SL, EscutiaGutiérrez R, García-Lemus CR, et al. In vitro interference by acetaminophen, aspirin, and metamizole in serum measurements of glucose, urea, and creatinine. Clin Biochem 2015;48:538–41. [19] Plebani M, Sciacovelli L, Marinova M, Marcuccitti J, Chiozza ML. Quality indicators in laboratory medicine: a fundamental tool for quality and patient safety. Clin Biochem 2013;46:1170–4. [20] Green SF. The cost of poor blood specimen quality and errors in preanalytical processes. Clin Biochem 2013;46:1175–9.
Peter A. Kavsak Department of Pathology & Molecular Medicine, McMaster University, Hamilton, Ontario, Canada Juravinski Hospital and Cancer Centre (Core Lab Section) 711 Concession Street Hamilton, ON L8V 1C3, Canada. Fax: 905 575 2581. E-mail address: [email protected].