CHAPTER SIX
Systematic Assessment of the Hemolysis Index: Pros and Cons Giuseppe Lippi1 Laboratory of Clinical Chemistry and Hematology, Academic Hospital of Parma, Parma, Italy 1 Corresponding author: e-mail address: [email protected]; [email protected]
Contents 1. Introduction 2. The Hemolysis Index 3. Pros and Cons 3.1 Increased Rejection Rate 3.2 Harmonization and Standardization 3.3 Instrument-Specific Cutoffs 3.4 Impact on Laboratory Efficiency 3.5 Impact on Laboratory Economics 3.6 Quality Control 4. Conclusions References
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Abstract Preanalytical quality is as important as the analytical and postanalytical quality in laboratory diagnostics. After decades of visual inspection to establish whether or not a diagnostic sample may be suitable for testing, automated assessment of hemolysis index (HI) has now become available in a large number of laboratory analyzers. Although most national and international guidelines support systematic assessment of sample quality via HI, there is widespread perception that this indication has not been thoughtfully acknowledged. Potential explanations include concern of increased specimen rejection rate, poor harmonization of analytical techniques, lack of standardized units of measure, differences in instrument-specific cutoff, negative impact on throughput, organization and laboratory economics, and lack of a reliable quality control system. Many of these concerns have been addressed. Evidence now supports automated HI in improving quality and patient safety. These will be discussed.
Advances in Clinical Chemistry, Volume 71 ISSN 0065-2423 http://dx.doi.org/10.1016/bs.acc.2015.05.002
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ABBREVIATIONS AST aspartate aminotransferase CK creatine kinase ED emergency department EQA external quality assessment HI hemolysis index HIL hemolysis index level ICSH International Council for Standardization in Haematology IQC internal quality control LDH lactate dehydrogenase RBC red blood cells
1. INTRODUCTION Preanalytical quality is as important as the analytical and postanalytical quality in laboratory diagnostics [1]. Several lines of evidence gathered over the past decades convincingly suggest that the vast majority of diagnostic errors emerge from the manually intensive activities of the preanalytical phase, especially those related to sample collection and handling [2,3]. Hemolysis, which is conventionally defined as rupture of red blood cells (RBC), mirrors a more generalized process of blood cell injury involving damage to leukocytes and platelets [4]. Hemolysis can typically occur in vivo, as a results of a number of conditions and diseases (inherited or acquired hemolytic anemias), but can also be provoked by inappropriate or mishandled procedures during specimen collection. These usually entail patient-dependent variables (fragile or difficult veins), operator-dependent variables (skill level, multiple attempts), blood collection material variables (small-gauge needles, collection from intravenous routes, use of syringes), as well as inappropriate sample management after collection (excessive shaking, freezing of whole blood, traumatic transportation) [5]. Although in vivo hemolysis (hemolytic anemia) is a life-threatening disease which requires rapid diagnosis and appropriate therapeutic management, spurious (in vitro) hemolysis is a preventable condition that may impair the quality of testing and ultimately jeopardize patient safety, especially when overlooked [6]. RBC injury, often accompanied by leukocyte and platelet injury, generates two major problems in clinical laboratory testing. The former is related to spurious modification of the complete blood count, wherein enumeration and classification of blood cells are substantially impaired [7], and a number of blood cell parameters (hematocrit, volume,
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hemoglobin content, RBC distribution width) may be biased. On the other hand, loss of plasma membrane integrity results in release of intracellular substances into blood (serum and plasma) thus spuriously increasing their concentration. These include hemoglobin, potassium, and enzymes such as lactate dehydrogenase (LDH) and aspartate aminotransferase (AST) among others [6]. The presence of these compounds may also generate analytical and biological interference. For example, cell-free hemoglobin is especially problematic for analytical techniques using optical readings at 415 nm wavelength, i.e., the “Soret peak.” Release of adenylate kinase interferes with enzymatic assessment of creatine kinase (CK). The increased presence of prothrombotic substances (thromboplastin or phospholipids) released by leukocytes and platelets which may impair results of hemostasis testing [6]. For certain analytes such as glucose, the bias may also results from an overlap of different types of interference (Fig. 1). A major drawback regarding spurious hemolysis is that a universally accepted classification does not exist. A recent study showed that the reference range of cell-free hemoglobin in ostensibly healthy subjects is different between serum and plasma [8]. More specifically, the upper limit of the reference range of cell-free hemoglobin has been defined as 0.10–0.13 g/L in lithium-heparin plasma and 0.22–0.25 g/L in serum. Interestingly, the
CK Potassium LDH AST
Chemical
Glucose
Optical
Biological
Troponins Hemostasis testing
Figure 1 Sources of hemolysis interference in some conventional laboratory tests.
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5.0 g/L
Gross hemolysis
Figure 2 Conventional classification of hemolyzed specimens.
cutoff for clinically meaningful interference has instead been arbitrarily fixed at 0.5 g/L for cell-free hemoglobin [6,9,10]. As such, serum containing cellfree hemoglobin may now be classified as “mildly” (0.5–3.0 g/L), “modestly” (3.0–5.0 g/L), or “grossly” hemolyzed (>5.0 g/L) (Fig. 2) [6,9,10]. This operative classification has a rational clinical background based on the degree of interference that cell-free hemoglobin may exert on clinical laboratory testing. Highly hemolysis-sensitive tests, such as potassium, LDH, and AST, are strongly biased and therefore clinically unreliable in mildly hemolyzed specimens. Intermediate hemolysis-sensitive tests such as troponin, CK, and clotting assays begin to show a significant bias in mildly hemolyzed specimens, wherein virtually all tests are biased in grossly hemolyzed specimens [11]. Universal agreement concurs that results should be suppressed whenever the bias due to an interfering substance exceeds established limits conventionally derived from biologic variation [12] or reference change value (RCV) [13].
2. THE HEMOLYSIS INDEX The assessment of sample quality has been historically based on visual inspection of the specimen before and after centrifugation. Macroscopic abnormalities, i.e., insufficient volume, the presence of clots, abnormal color, and turbidity, can commonly be assessed [6]. For many years, this approach represented the only available means of establishing sample quality. However, advances in sensor technology have provided a more robust and efficient means to automatically detect insufficient volume or the presence of small clots. By the end of the 1980s, it became clear that visual assessment of hemolysis was unreliable for objective assessment of specimen suitability for testing [14].
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This premise was subsequently confirmed in a series of elegant studies which demonstrated that skilled laboratory professionals were unable to accurately classify the degree of hemolysis despite the use of a photographic aid portraying plasma/serum specimens containing known concentrations of cell-free hemoglobin [15–17]. This compelling evidence persuaded the laboratory community and laboratory instrument manufacturers to introduce an automated system for specimen quality assessment. This approach was based on optical readings at different wavelengths to generate a series of indices comparable to sample conditions of icterus (hyperbilirubinemia), hemolysis (increased cell-free hemoglobin), and turbidity (hyperlipidemia). A large number of clinical chemistry platforms, along with several preanalytical workstations and some coagulation analyzers, can now assess the hemolysis index (HI). Although a reference method for measurement of hemoglobin does exist (i.e., the photometric determination of hemoglobin-cyanide (HiCN)) [18], linearity (0–1.0 g/L) is suboptimal for routine use in clinical laboratories. Furthermore, cyanide is highly toxic and extremely hazardous [19]. As such, the International Council for Standardization in Haematology (ICSH) recommends that this technique be made available only to national standards committees for hematological methods or official government-nominated holders [18]. Because of these limitations, manufacturers have developed a variety of approaches for automated assessment of HI. Although this topic has been comprehensively addressed [20,21], a brief overview will be provided below.
3. PROS AND CONS Despite the fact that most national and international guidelines support the systematic preanalytic assessment of sample quality by means of serum indices including HI [20,22,23], there is widespread perception that this indication has not been thoroughly assessed. A recent online international survey (388 respondents) showed that the majority (56%) of clinical laboratories continue to assess hemolysis by visual inspection [6]. Automated HI quantification is only performed in 43% of labs. The remaining 1% did not perform any preanalytic check. These data clearly indicate that some major hurdles remain for translating the theoretical advantages of automatic HI assessment into routine clinical laboratory practice. In this article, we discuss the pros and cons of systematic evaluation of sample quality by means of the HI.
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3.1 Increased Rejection Rate A leading concern of laboratory professionals with respect to systematic assessment of HI is the potential impact on specimen rejection rate. Overall, hemolysis accounts for 1–10% of rejections with the highest rates (8–12%) in specimens collected in the emergency department (ED) [4,6]. The implementation of an objective quality measure, as the HI would inherently permit, would ultimately lead to outright rejection (or test suppression) of all samples that exceed a predefined (local or instrument-based) cell-free hemoglobin concentration. Furthermore, the HI is captured at the instrument level and may be subsequently transmitted to the laboratory information system (LIS) and potentially included in laboratory reports. As such, it is no longer possible for laboratory professionals to simply ignore these results. Moreover, subjectivity associated with visual inspection is replaced by an absolute objective measure, i.e., specimens previously considered “suspicious” by visual inspection could no longer undergo analysis. These specimens would be considered “unsuitable” based on the relative hemolysis index level (HIL). It is likely that implementation of this automated strategy would result in increased rejection rate and test suppression. Consequently, disputes regarding specimen acceptability may arise with clinicians in acute care settings such as the ED and intensive care units (ICU) or pediatrics. There is widespread consensus, however, that when the degree of interference is sufficiently high that the sample be reasonably considered unsuitable, hemolysis-sensitive results should be suppressed [20,22,23]. The fear that the systematic assessment of HI may increase the rejection rate, although understandable, is therefore analytically and clinically unjustified.
3.2 Harmonization and Standardization The harmonization of the HI is important (Table 1). In brief, the HI can be estimated by variety of methods including optical assessment at double Table 1 Unresolved Issues in Harmonization of the Hemolysis Index (HI)
• • • • •
Different technical approaches (i.e., different wavelengths) Instrument-specific algorithms and correction factors Heterogeneous diluent Expression in quantitative or semi-quantitative data Results provided as concentration units of cell-free hemoglobin or absolute numbers • Use of different and often poorly comparable categorical scales
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(405/700 nm, 570/600 nm, and 522/750 nm) and multiple wavelengths (340, 410, 470, 600, and 670 nm), or even by peak absorbance at paired wavelengths (572/604 and 628/660 nm; 410/480 and 600/800 nm) [20,21]. Predefined algorithms for converting absorbance measurements into hemoglobin concentration or HIL as well as the correction factors used for eliminating overlapping interference spectra also differ depending on the reference wavelengths used. In addition, the type of diluent (water, saline, Tris buffer) differs among procedures. Furthermore, data expression is highly variable because instruments may provide quantitative results or semiquantitative indices with some reported as arbitrary units of cell-free hemoglobin [20,21]. Data reporting may then span from a minimum of five-unit categorical scale to a continuous range of hemoglobin concentration. Disappointingly, the upper limit of linearity of automated methods range from 5 g/L in some instruments to 20 g/L in others. Understandably, this large variation has important implications for achieving worldwide harmonization of HI (Table 2). In fact, early data attested that the ability of different analyzers to correctly identify and classify reference material was unsatisfactory [24]. In a recent multicenter study employing five different clinical chemistry analyzers, agreement was generally poor, being as low as 62% under some cases [25]. Different systems may independently correlate with the reference method (cyanmethemoglobin-based Harboe or Fairbanks assays) for hemoglobin [24,26]. Unfortunately, these can exhibit substantial bias and thus have poor interinstrument comparability. This may be especially troublesome at the analytically relevant cutoff, i.e., one sample considered unsuitable at one laboratory may be considered as suitable in
Table 2 Major Hurdles and Concerns for Introduction of Systematic Hemolysis Index (HI) Assessment Concern Justified
Increased rejection rate
No
Poor harmonization of techniques
Yes
No standardization of measure unit
Yes
Heterogeneity of instrument-specific cutoffs
Yes
Impact on laboratory efficiency
No
Impact on laboratory economics
No
Lack of a reliable quality control system
Yes
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another. Hemolysis is now considered an indicator of collection quality [27]. The percentage of hemolyzed samples has recently been included as a measured quality indicator in laboratory medicine, i.e., number of samples with free hemoglobin >0.5 g/L/total number of samples [28]. Harmonization is a necessary step to compare performance worldwide. A large consensus is needed to identify a standard reference optical method for assessing HI or for harmonizing hemoglobin detection across laboratory platforms. Result reporting should also be standardized, preferably in concentration units of cell-free hemoglobin. Adoption of this approach would allow direct comparison of instrument-specific HI.
3.3 Instrument-Specific Cutoffs Although some clinical chemistry analytes such as potassium, LDH, and AST are more sensitive to hemolysis interference, the situation becomes almost critical for immunochemistry and coagulation testing due to their reagent complexity. As such, manufacturers have developed instrument-, method-, and analyte-specific alert values to assess acceptability in order to perform or omit tests in hemolyzed specimens. Unfortunately, thresholds for acceptability vary widely among instruments. A Catalonian Health Institute workgroup conducted a multicenter investigation to assess hemolysis detection methods and quantification thereof on eight clinical chemistry analyzers produced by three manufacturers [29]. This study reported substantial method- and instrument-dependent variance in hemolysis interference cutoff obtained for the majority of tests. Furthermore, there was considerable disagreement with the classification of a reference material containing 0.57 g/L cell-free hemoglobin, a concentration close to theoretical cutoff. Another paradigmatic case is that of cardiospecific troponins. Controversial evidence has been generated on reliability of cardiac troponin testing in the presence of hemolysis [30]. Negative, positive, and negligible biases have all been reported. This heterogeneity has been attributed to the target molecule itself (troponin I or T) and to the combination of specific monoclonal antibodies used in the various immunoassays. Similar findings were reported for a large number of immunoassays in general [31,32] and specifically for insulin [33], D-dimer [34], and serologic markers [35]. Interestingly, a recent study confirmed that the lipemic index, another measure of sample quality, shares similar problems [36]. Manufacturers tend to use arbitrary limits for predicting interference. In fact, observed interference may be substantially different from manufacturer specifications.
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3.4 Impact on Laboratory Efficiency It is undeniable that the inclusion of additional measures will impact instrument efficiency. Immunochemical assays have a much longer turnaround time than clinical chemistry or routine coagulation tests. HI is a simple photometric assay which entails sample dilution and peak absorbance reading. Concerns that the systematic assessment of the HI may negatively impact laboratory organization, throughput, and turnaround time are theoretically unjustified. Furthermore, a multicenter study that included five different clinical chemistry analyzers convincingly demonstrated that turnaround time of routine testing was virtually unaffected ( 0.2% to 5.0%) [25].
3.5 Impact on Laboratory Economics In an era of shrinking reimbursement and increased utilization, public health care funding remains a major issue [37]. As a major player in healthcare decision making, clinical laboratories are not exempt to this continuing issue. As such, it is not surprising that the introduction of novel tests is frequently viewed with skepticism by policymakers, health care providers, and laboratory professionals themselves. As such, it is noteworthy that a major strength of the HI is its minimal cost and minimal impact to shrinking laboratory budgets.
3.6 Quality Control The development and maintenance of a quality management system is essential for generating reliable laboratory data and detecting, reducing or correcting deficiencies throughout the total testing process [38]. It is undeniable that the large effort placed on analytic quality has substantially contributed to increased accuracy, performance, and efficiency [39]. It is unquestionable that the vast majority of diagnostic errors emerge from the preanalytic phase with hemolyzed samples the leading source of error [6]. As such, the development and introduction of quality control and quality assurance methods in the preanalytical phase is required to foster quality improvement. Automated assessment of the HI is based on spectrophotometric measurements and, like any other laboratory test, is amenable to a quality control system, either internal quality control (IQC) or external quality assessment (EQA) to monitor performance and correct inaccuracy, bias, or deviations from acceptable standards. Unfortunately, no reliable quality system has been developed for the HI or other serum indices to date. This is especially concerning if one considers the large methodologic differences between laboratory instruments.
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There are, however, some potential approaches for developing an EQA. In one multicenter study, serum containing different amount of cell-free hemoglobin (0.1–2.0 g/L), as measured by the cyanmethemoglobin reference method, was prepared, aliquoted, frozen, and shipped to the participating facilities [24]. The HI was then assessed thus allowing direct comparison of results between laboratories. Findings included no significant variation of hemoglobin concentration after freezing and shipment, thereby confirming the feasibility of frozen serum as a reference material. Petrova et al. [26] also confirmed that self-made controls may be suited for quality assessment of the HI. Unfortunately, poor recovery was noted and subsequently attributed to an unidentified matrix issue in commercially available controls. These findings, while preliminary, provide an important starting point for the development of a large international quality control system. This system would entail a discrete number of steps that span from identification of reference material with clinically relevant hemoglobin concentration (i.e., degree of hemolysis), to the generation of quantitative data (i.e., expression of HI in concentration units of cell-free hemoglobin), and ultimately interpretative comments (i.e., sample suitability, test suppression) (Fig. 3). This would Quality control assessment
Identify reference serum samples (cyanmethemoglobin method) Level 1 ~0.5 g/L Level 2 ~3.0 g/L Level 3 ~5.0 g/L Level 4 ~10.0 g/L
Freeze samples Ship samples to the participating laboratories Measure HI on local instrumentation • Convert results in concentration units of cell-free hemoglobin (g/L) • Provide comments on sample quality and test suppression
Figure 3 Tentative approach for developing an external quality assessment (EQA) scheme for the hemolysis index (HI).
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allow individual performance benchmarking and establish an effective and continuous quality monitoring system. It is likely that the establishment of standardized criteria for accepting or rejecting samples would improve long-term consistency. A similar approach may be implemented for IQC in local facilities. Specimens representing appropriate reference standards may be selected and subsequently stored [40]. These materials would be treated as traditional quality control and tested according to conventional indications.
4. CONCLUSIONS Although evidence-based recommendations strongly support systematic HI assessment, this accurate and objective measure of specimen quality remains underutilized in most clinical laboratories. As discussed above, poor adoption of this quality measure is likely attributed to a perceived threat to laboratory productivity as well as to the real lack of standardization across instrument platforms. Several lines of evidence attest that automated assessment of the HI offers distinct advantages to improve quality and patient safety. First, the automated HI assessment should be mandatory in those laboratories where the preanalytical workstations are physically connected to analytic platforms [41]. Under these conditions, visual inspection is only possible following conclusion of testing. The use of HI is also advocated in newborns and infants due to increased probability of hemolysis in these patients [42]. Consideration should also be given to include the HIL in laboratory reports. Comments justifying test suppression or sample rejection provide valuable information. Despite the lack of clinical studies to date, the use of HI could be regarded as an appealing alternative for screening and monitoring hemolytic anemias [4]. Indeed, analytic technique harmonization and unit measurement standardization remain the biggest unresolved issues. Organizations such as the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) [43] or the ICSH [44] should take the lead in the development of universal recommendations for this important specimen quality measure. In the meantime, verification of local assay performance including linearity, precision, and correlation to a reference method is advisable. A reliable quality control system is required. As can be seen, no insurmountable hurdles exist, so that strict cooperation between scientific organizations and manufacturers of quality control materials could be established. One final concern involves false-positive HIL results as been occasionally described for
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samples with monoclonal gammopathy [45] and hemoglobin-based oxygen carrier [46]. Under these circumstances, communication between the laboratory and the clinic is vital to accurately identify source of error [4]. Hemolysis is a common finding in clinical laboratory specimens occurring at a much higher rate than lipemia and icterus. In this review, we presented the pros and cons in the systematic assessment of the HI. Despite its usefulness, it is clear that further work is clearly needed across the scientific community before this valuable measure of specimen quality is universally adopted.
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Systematic Assessment of the Hemolysis Index: Pros and Cons Giuseppe Lippi1 Laboratory of Clinical Chemistry and Hematology, Academic Hospital of Parma, Parma, Italy 1 Corresponding author: e-mail address: [email protected]; [email protected]
Contents 1. Introduction 2. The Hemolysis Index 3. Pros and Cons 3.1 Increased Rejection Rate 3.2 Harmonization and Standardization 3.3 Instrument-Specific Cutoffs 3.4 Impact on Laboratory Efficiency 3.5 Impact on Laboratory Economics 3.6 Quality Control 4. Conclusions References
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Abstract Preanalytical quality is as important as the analytical and postanalytical quality in laboratory diagnostics. After decades of visual inspection to establish whether or not a diagnostic sample may be suitable for testing, automated assessment of hemolysis index (HI) has now become available in a large number of laboratory analyzers. Although most national and international guidelines support systematic assessment of sample quality via HI, there is widespread perception that this indication has not been thoughtfully acknowledged. Potential explanations include concern of increased specimen rejection rate, poor harmonization of analytical techniques, lack of standardized units of measure, differences in instrument-specific cutoff, negative impact on throughput, organization and laboratory economics, and lack of a reliable quality control system. Many of these concerns have been addressed. Evidence now supports automated HI in improving quality and patient safety. These will be discussed.
Advances in Clinical Chemistry, Volume 71 ISSN 0065-2423 http://dx.doi.org/10.1016/bs.acc.2015.05.002
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2015 Elsevier Inc. All rights reserved.
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ABBREVIATIONS AST aspartate aminotransferase CK creatine kinase ED emergency department EQA external quality assessment HI hemolysis index HIL hemolysis index level ICSH International Council for Standardization in Haematology IQC internal quality control LDH lactate dehydrogenase RBC red blood cells
1. INTRODUCTION Preanalytical quality is as important as the analytical and postanalytical quality in laboratory diagnostics [1]. Several lines of evidence gathered over the past decades convincingly suggest that the vast majority of diagnostic errors emerge from the manually intensive activities of the preanalytical phase, especially those related to sample collection and handling [2,3]. Hemolysis, which is conventionally defined as rupture of red blood cells (RBC), mirrors a more generalized process of blood cell injury involving damage to leukocytes and platelets [4]. Hemolysis can typically occur in vivo, as a results of a number of conditions and diseases (inherited or acquired hemolytic anemias), but can also be provoked by inappropriate or mishandled procedures during specimen collection. These usually entail patient-dependent variables (fragile or difficult veins), operator-dependent variables (skill level, multiple attempts), blood collection material variables (small-gauge needles, collection from intravenous routes, use of syringes), as well as inappropriate sample management after collection (excessive shaking, freezing of whole blood, traumatic transportation) [5]. Although in vivo hemolysis (hemolytic anemia) is a life-threatening disease which requires rapid diagnosis and appropriate therapeutic management, spurious (in vitro) hemolysis is a preventable condition that may impair the quality of testing and ultimately jeopardize patient safety, especially when overlooked [6]. RBC injury, often accompanied by leukocyte and platelet injury, generates two major problems in clinical laboratory testing. The former is related to spurious modification of the complete blood count, wherein enumeration and classification of blood cells are substantially impaired [7], and a number of blood cell parameters (hematocrit, volume,
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hemoglobin content, RBC distribution width) may be biased. On the other hand, loss of plasma membrane integrity results in release of intracellular substances into blood (serum and plasma) thus spuriously increasing their concentration. These include hemoglobin, potassium, and enzymes such as lactate dehydrogenase (LDH) and aspartate aminotransferase (AST) among others [6]. The presence of these compounds may also generate analytical and biological interference. For example, cell-free hemoglobin is especially problematic for analytical techniques using optical readings at 415 nm wavelength, i.e., the “Soret peak.” Release of adenylate kinase interferes with enzymatic assessment of creatine kinase (CK). The increased presence of prothrombotic substances (thromboplastin or phospholipids) released by leukocytes and platelets which may impair results of hemostasis testing [6]. For certain analytes such as glucose, the bias may also results from an overlap of different types of interference (Fig. 1). A major drawback regarding spurious hemolysis is that a universally accepted classification does not exist. A recent study showed that the reference range of cell-free hemoglobin in ostensibly healthy subjects is different between serum and plasma [8]. More specifically, the upper limit of the reference range of cell-free hemoglobin has been defined as 0.10–0.13 g/L in lithium-heparin plasma and 0.22–0.25 g/L in serum. Interestingly, the
CK Potassium LDH AST
Chemical
Glucose
Optical
Biological
Troponins Hemostasis testing
Figure 1 Sources of hemolysis interference in some conventional laboratory tests.
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5.0 g/L
Gross hemolysis
Figure 2 Conventional classification of hemolyzed specimens.
cutoff for clinically meaningful interference has instead been arbitrarily fixed at 0.5 g/L for cell-free hemoglobin [6,9,10]. As such, serum containing cellfree hemoglobin may now be classified as “mildly” (0.5–3.0 g/L), “modestly” (3.0–5.0 g/L), or “grossly” hemolyzed (>5.0 g/L) (Fig. 2) [6,9,10]. This operative classification has a rational clinical background based on the degree of interference that cell-free hemoglobin may exert on clinical laboratory testing. Highly hemolysis-sensitive tests, such as potassium, LDH, and AST, are strongly biased and therefore clinically unreliable in mildly hemolyzed specimens. Intermediate hemolysis-sensitive tests such as troponin, CK, and clotting assays begin to show a significant bias in mildly hemolyzed specimens, wherein virtually all tests are biased in grossly hemolyzed specimens [11]. Universal agreement concurs that results should be suppressed whenever the bias due to an interfering substance exceeds established limits conventionally derived from biologic variation [12] or reference change value (RCV) [13].
2. THE HEMOLYSIS INDEX The assessment of sample quality has been historically based on visual inspection of the specimen before and after centrifugation. Macroscopic abnormalities, i.e., insufficient volume, the presence of clots, abnormal color, and turbidity, can commonly be assessed [6]. For many years, this approach represented the only available means of establishing sample quality. However, advances in sensor technology have provided a more robust and efficient means to automatically detect insufficient volume or the presence of small clots. By the end of the 1980s, it became clear that visual assessment of hemolysis was unreliable for objective assessment of specimen suitability for testing [14].
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This premise was subsequently confirmed in a series of elegant studies which demonstrated that skilled laboratory professionals were unable to accurately classify the degree of hemolysis despite the use of a photographic aid portraying plasma/serum specimens containing known concentrations of cell-free hemoglobin [15–17]. This compelling evidence persuaded the laboratory community and laboratory instrument manufacturers to introduce an automated system for specimen quality assessment. This approach was based on optical readings at different wavelengths to generate a series of indices comparable to sample conditions of icterus (hyperbilirubinemia), hemolysis (increased cell-free hemoglobin), and turbidity (hyperlipidemia). A large number of clinical chemistry platforms, along with several preanalytical workstations and some coagulation analyzers, can now assess the hemolysis index (HI). Although a reference method for measurement of hemoglobin does exist (i.e., the photometric determination of hemoglobin-cyanide (HiCN)) [18], linearity (0–1.0 g/L) is suboptimal for routine use in clinical laboratories. Furthermore, cyanide is highly toxic and extremely hazardous [19]. As such, the International Council for Standardization in Haematology (ICSH) recommends that this technique be made available only to national standards committees for hematological methods or official government-nominated holders [18]. Because of these limitations, manufacturers have developed a variety of approaches for automated assessment of HI. Although this topic has been comprehensively addressed [20,21], a brief overview will be provided below.
3. PROS AND CONS Despite the fact that most national and international guidelines support the systematic preanalytic assessment of sample quality by means of serum indices including HI [20,22,23], there is widespread perception that this indication has not been thoroughly assessed. A recent online international survey (388 respondents) showed that the majority (56%) of clinical laboratories continue to assess hemolysis by visual inspection [6]. Automated HI quantification is only performed in 43% of labs. The remaining 1% did not perform any preanalytic check. These data clearly indicate that some major hurdles remain for translating the theoretical advantages of automatic HI assessment into routine clinical laboratory practice. In this article, we discuss the pros and cons of systematic evaluation of sample quality by means of the HI.
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3.1 Increased Rejection Rate A leading concern of laboratory professionals with respect to systematic assessment of HI is the potential impact on specimen rejection rate. Overall, hemolysis accounts for 1–10% of rejections with the highest rates (8–12%) in specimens collected in the emergency department (ED) [4,6]. The implementation of an objective quality measure, as the HI would inherently permit, would ultimately lead to outright rejection (or test suppression) of all samples that exceed a predefined (local or instrument-based) cell-free hemoglobin concentration. Furthermore, the HI is captured at the instrument level and may be subsequently transmitted to the laboratory information system (LIS) and potentially included in laboratory reports. As such, it is no longer possible for laboratory professionals to simply ignore these results. Moreover, subjectivity associated with visual inspection is replaced by an absolute objective measure, i.e., specimens previously considered “suspicious” by visual inspection could no longer undergo analysis. These specimens would be considered “unsuitable” based on the relative hemolysis index level (HIL). It is likely that implementation of this automated strategy would result in increased rejection rate and test suppression. Consequently, disputes regarding specimen acceptability may arise with clinicians in acute care settings such as the ED and intensive care units (ICU) or pediatrics. There is widespread consensus, however, that when the degree of interference is sufficiently high that the sample be reasonably considered unsuitable, hemolysis-sensitive results should be suppressed [20,22,23]. The fear that the systematic assessment of HI may increase the rejection rate, although understandable, is therefore analytically and clinically unjustified.
3.2 Harmonization and Standardization The harmonization of the HI is important (Table 1). In brief, the HI can be estimated by variety of methods including optical assessment at double Table 1 Unresolved Issues in Harmonization of the Hemolysis Index (HI)
• • • • •
Different technical approaches (i.e., different wavelengths) Instrument-specific algorithms and correction factors Heterogeneous diluent Expression in quantitative or semi-quantitative data Results provided as concentration units of cell-free hemoglobin or absolute numbers • Use of different and often poorly comparable categorical scales
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(405/700 nm, 570/600 nm, and 522/750 nm) and multiple wavelengths (340, 410, 470, 600, and 670 nm), or even by peak absorbance at paired wavelengths (572/604 and 628/660 nm; 410/480 and 600/800 nm) [20,21]. Predefined algorithms for converting absorbance measurements into hemoglobin concentration or HIL as well as the correction factors used for eliminating overlapping interference spectra also differ depending on the reference wavelengths used. In addition, the type of diluent (water, saline, Tris buffer) differs among procedures. Furthermore, data expression is highly variable because instruments may provide quantitative results or semiquantitative indices with some reported as arbitrary units of cell-free hemoglobin [20,21]. Data reporting may then span from a minimum of five-unit categorical scale to a continuous range of hemoglobin concentration. Disappointingly, the upper limit of linearity of automated methods range from 5 g/L in some instruments to 20 g/L in others. Understandably, this large variation has important implications for achieving worldwide harmonization of HI (Table 2). In fact, early data attested that the ability of different analyzers to correctly identify and classify reference material was unsatisfactory [24]. In a recent multicenter study employing five different clinical chemistry analyzers, agreement was generally poor, being as low as 62% under some cases [25]. Different systems may independently correlate with the reference method (cyanmethemoglobin-based Harboe or Fairbanks assays) for hemoglobin [24,26]. Unfortunately, these can exhibit substantial bias and thus have poor interinstrument comparability. This may be especially troublesome at the analytically relevant cutoff, i.e., one sample considered unsuitable at one laboratory may be considered as suitable in
Table 2 Major Hurdles and Concerns for Introduction of Systematic Hemolysis Index (HI) Assessment Concern Justified
Increased rejection rate
No
Poor harmonization of techniques
Yes
No standardization of measure unit
Yes
Heterogeneity of instrument-specific cutoffs
Yes
Impact on laboratory efficiency
No
Impact on laboratory economics
No
Lack of a reliable quality control system
Yes
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another. Hemolysis is now considered an indicator of collection quality [27]. The percentage of hemolyzed samples has recently been included as a measured quality indicator in laboratory medicine, i.e., number of samples with free hemoglobin >0.5 g/L/total number of samples [28]. Harmonization is a necessary step to compare performance worldwide. A large consensus is needed to identify a standard reference optical method for assessing HI or for harmonizing hemoglobin detection across laboratory platforms. Result reporting should also be standardized, preferably in concentration units of cell-free hemoglobin. Adoption of this approach would allow direct comparison of instrument-specific HI.
3.3 Instrument-Specific Cutoffs Although some clinical chemistry analytes such as potassium, LDH, and AST are more sensitive to hemolysis interference, the situation becomes almost critical for immunochemistry and coagulation testing due to their reagent complexity. As such, manufacturers have developed instrument-, method-, and analyte-specific alert values to assess acceptability in order to perform or omit tests in hemolyzed specimens. Unfortunately, thresholds for acceptability vary widely among instruments. A Catalonian Health Institute workgroup conducted a multicenter investigation to assess hemolysis detection methods and quantification thereof on eight clinical chemistry analyzers produced by three manufacturers [29]. This study reported substantial method- and instrument-dependent variance in hemolysis interference cutoff obtained for the majority of tests. Furthermore, there was considerable disagreement with the classification of a reference material containing 0.57 g/L cell-free hemoglobin, a concentration close to theoretical cutoff. Another paradigmatic case is that of cardiospecific troponins. Controversial evidence has been generated on reliability of cardiac troponin testing in the presence of hemolysis [30]. Negative, positive, and negligible biases have all been reported. This heterogeneity has been attributed to the target molecule itself (troponin I or T) and to the combination of specific monoclonal antibodies used in the various immunoassays. Similar findings were reported for a large number of immunoassays in general [31,32] and specifically for insulin [33], D-dimer [34], and serologic markers [35]. Interestingly, a recent study confirmed that the lipemic index, another measure of sample quality, shares similar problems [36]. Manufacturers tend to use arbitrary limits for predicting interference. In fact, observed interference may be substantially different from manufacturer specifications.
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3.4 Impact on Laboratory Efficiency It is undeniable that the inclusion of additional measures will impact instrument efficiency. Immunochemical assays have a much longer turnaround time than clinical chemistry or routine coagulation tests. HI is a simple photometric assay which entails sample dilution and peak absorbance reading. Concerns that the systematic assessment of the HI may negatively impact laboratory organization, throughput, and turnaround time are theoretically unjustified. Furthermore, a multicenter study that included five different clinical chemistry analyzers convincingly demonstrated that turnaround time of routine testing was virtually unaffected ( 0.2% to 5.0%) [25].
3.5 Impact on Laboratory Economics In an era of shrinking reimbursement and increased utilization, public health care funding remains a major issue [37]. As a major player in healthcare decision making, clinical laboratories are not exempt to this continuing issue. As such, it is not surprising that the introduction of novel tests is frequently viewed with skepticism by policymakers, health care providers, and laboratory professionals themselves. As such, it is noteworthy that a major strength of the HI is its minimal cost and minimal impact to shrinking laboratory budgets.
3.6 Quality Control The development and maintenance of a quality management system is essential for generating reliable laboratory data and detecting, reducing or correcting deficiencies throughout the total testing process [38]. It is undeniable that the large effort placed on analytic quality has substantially contributed to increased accuracy, performance, and efficiency [39]. It is unquestionable that the vast majority of diagnostic errors emerge from the preanalytic phase with hemolyzed samples the leading source of error [6]. As such, the development and introduction of quality control and quality assurance methods in the preanalytical phase is required to foster quality improvement. Automated assessment of the HI is based on spectrophotometric measurements and, like any other laboratory test, is amenable to a quality control system, either internal quality control (IQC) or external quality assessment (EQA) to monitor performance and correct inaccuracy, bias, or deviations from acceptable standards. Unfortunately, no reliable quality system has been developed for the HI or other serum indices to date. This is especially concerning if one considers the large methodologic differences between laboratory instruments.
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There are, however, some potential approaches for developing an EQA. In one multicenter study, serum containing different amount of cell-free hemoglobin (0.1–2.0 g/L), as measured by the cyanmethemoglobin reference method, was prepared, aliquoted, frozen, and shipped to the participating facilities [24]. The HI was then assessed thus allowing direct comparison of results between laboratories. Findings included no significant variation of hemoglobin concentration after freezing and shipment, thereby confirming the feasibility of frozen serum as a reference material. Petrova et al. [26] also confirmed that self-made controls may be suited for quality assessment of the HI. Unfortunately, poor recovery was noted and subsequently attributed to an unidentified matrix issue in commercially available controls. These findings, while preliminary, provide an important starting point for the development of a large international quality control system. This system would entail a discrete number of steps that span from identification of reference material with clinically relevant hemoglobin concentration (i.e., degree of hemolysis), to the generation of quantitative data (i.e., expression of HI in concentration units of cell-free hemoglobin), and ultimately interpretative comments (i.e., sample suitability, test suppression) (Fig. 3). This would Quality control assessment
Identify reference serum samples (cyanmethemoglobin method) Level 1 ~0.5 g/L Level 2 ~3.0 g/L Level 3 ~5.0 g/L Level 4 ~10.0 g/L
Freeze samples Ship samples to the participating laboratories Measure HI on local instrumentation • Convert results in concentration units of cell-free hemoglobin (g/L) • Provide comments on sample quality and test suppression
Figure 3 Tentative approach for developing an external quality assessment (EQA) scheme for the hemolysis index (HI).
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allow individual performance benchmarking and establish an effective and continuous quality monitoring system. It is likely that the establishment of standardized criteria for accepting or rejecting samples would improve long-term consistency. A similar approach may be implemented for IQC in local facilities. Specimens representing appropriate reference standards may be selected and subsequently stored [40]. These materials would be treated as traditional quality control and tested according to conventional indications.
4. CONCLUSIONS Although evidence-based recommendations strongly support systematic HI assessment, this accurate and objective measure of specimen quality remains underutilized in most clinical laboratories. As discussed above, poor adoption of this quality measure is likely attributed to a perceived threat to laboratory productivity as well as to the real lack of standardization across instrument platforms. Several lines of evidence attest that automated assessment of the HI offers distinct advantages to improve quality and patient safety. First, the automated HI assessment should be mandatory in those laboratories where the preanalytical workstations are physically connected to analytic platforms [41]. Under these conditions, visual inspection is only possible following conclusion of testing. The use of HI is also advocated in newborns and infants due to increased probability of hemolysis in these patients [42]. Consideration should also be given to include the HIL in laboratory reports. Comments justifying test suppression or sample rejection provide valuable information. Despite the lack of clinical studies to date, the use of HI could be regarded as an appealing alternative for screening and monitoring hemolytic anemias [4]. Indeed, analytic technique harmonization and unit measurement standardization remain the biggest unresolved issues. Organizations such as the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) [43] or the ICSH [44] should take the lead in the development of universal recommendations for this important specimen quality measure. In the meantime, verification of local assay performance including linearity, precision, and correlation to a reference method is advisable. A reliable quality control system is required. As can be seen, no insurmountable hurdles exist, so that strict cooperation between scientific organizations and manufacturers of quality control materials could be established. One final concern involves false-positive HIL results as been occasionally described for
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samples with monoclonal gammopathy [45] and hemoglobin-based oxygen carrier [46]. Under these circumstances, communication between the laboratory and the clinic is vital to accurately identify source of error [4]. Hemolysis is a common finding in clinical laboratory specimens occurring at a much higher rate than lipemia and icterus. In this review, we presented the pros and cons in the systematic assessment of the HI. Despite its usefulness, it is clear that further work is clearly needed across the scientific community before this valuable measure of specimen quality is universally adopted.
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