Much has been written about the pre-analytical challenges facing clinical labs. Pre-analytical issues are the largest source of diagnostic errors and can result in serious impact to patients. Due to the consolidation of laboratories, the growth of typical operational size, and the implementation of total laboratory automation (TLA), the examination of samples before testing has undergone a transformation from visual to automated. This, too, may have a significant impact on test reliability.
This article outlines the well-known serum indices interference and how technological advances in automated instrument testing have created new challenges. Importantly, this will include an overview of how serum index determinations are made, detected and responded to – and how that system needs a quality process. Also provided is information on the latest international guidance documents and recommendations.
Background
The quality and integrity of biological samples collected by venipuncture is essential to generate reliable test results. The presence of hemolysis (H), icterus (I) and lipemia (L) in diagnostic samples are important and common interferences in many chemistry assays.
Hemolysis can affect the measurement results of specific analytes significantly, since even very low concentrations of interferences can cause clinically relevant deviation of the true value. Test issues can arise from either photometric interference at selected wavelengths or from RBC contents altering the sample composition. Hemolysis is usually an artifact of collection, transportation, or storage issues. More rarely it is an indicator of a true in vivo hemolysis.
Icterus is the increased concentration of bilirubin, which can be caused by underlying liver disease. High serum/plasma bilirubin concentrations can cause photometric interference with assays or can act as a chemical interference with reagent components.
Lipemia is the increased concentration of lipid and lipoprotein particles, creating a milky or turbid appearance that interferes photometrically with multiple biochemical tests. In elevated cases, lipemia can also interfere in some electrolyte assays via a pseudohyponatremia effect.
Automated versus visual assessment
Most clinical laboratories have adopted the assessment of sample quality before testing as an essential part of their routine practice. In the past, HIL detection was mainly done by visual checks. However, it has been well documented that visual checks have disadvantages and are unreliable, displaying poor accuracy and high person-to-person variability.1,2
According to the CLSI C56-A guideline Hemolysis, Icterus, and Lipemia/Turbidity Indices as Indicators of Interference in Clinical Laboratory Analysis (clsi.org), “The use of automated HIL indices overcomes the inherent limitations of visual estimation that have been used in the clinical laboratory for decades.”3
Most modern high-throughput automated chemistry analyzers today offer an automated HIL index testing feature, and it has become widely accepted that automated HIL detection should replace visual checks. Moreover, in high test-volume TLA laboratories, visual checking by lab staff slows down workflow and high-throughput capabilities when compared with automated detection. Labs have come to rely on the automated features of such analyzers.
Challenges in automated serum index detection
No standard exists today to specify a recommended methodology for HIL measurement, or any recommended reporting system or standardized units. While some analyzer systems may be similar, others use very different mechanisms. CLSI C56-A catalogued several such system differences.3 The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group for Preanalytical Phase also outlined such challenges in its 2018 paper and proposed solutions that may be adopted by analyzer manufacturers for increasing worldwide harmonization of serum index detection and reporting.4
Some HIL-capable chemistry analyzers use detection systems that can run HIL tests without impacting analyzer throughput. Others do impact throughput when HIL detection is enabled, though often not greatly.
Some systems report the interferences only in an ordinal scale, for example: 0, +1, +2, +3 – similar to older procedures for visual interpretation. For optimal interpretation of specific samples, this representation could bring some challenges. The system’s continuous values are, in these cases, not available. In other systems, the result reporting is on an arbitrary scale, such as 0-10 or 0-50. The actual photometric absorbance responses also are not usually available.
Since HIL index determinations are approximate for purposes of sample assessment, system operators should not confuse such determinations with exact reports of interferent concentration (e.g.: gm/dL of hemoglobin or mg/dL of bilirubin), as this can lead to inaccurate reporting of test results.
HIL detection is not influenced by the analyzer assay reagents, though it is crucial that the HIL detection performance is stable and accurate over time. The HIL module may be subject to drift; sample pipetting may have a bias that is calibrated out in most assays but not in the HIL detection; or HIL sample carryover in cuvettes can be an issue if the cuvette washer is misaligned. This may not be evident for most chemistry assays, but some HIL assessments (e.g.: very high levels of hemoglobin) may be affected. Most laboratories do not consider periodic maintenance, inspection, or performance-checking for their HIL determinations as part of the routine quality processes. Taking all of this into consideration, it is important to consider a quality process approach to HIL testing.
Best practices and recommendations in HIL testing
HIL assessment and automated handling to detect deviations in sample quality are important. All other relevant parameters on laboratory instruments are regularly checked by internal and external quality control. However, HIL indices are generally not under such control.
As indicated by von Meyer, et al. on behalf of the EFLM Working Group for Preanalytical Phase, “Due to such large potential impact on diagnostic results, serum indices should be subject to regular internal and external quality control procedures.”4
While the testing of the HIL indices is an important practice for routinely monitoring sample quality in most clinical laboratories, there are few standardized practical guidelines about the quality approach to these HIL index results. Some QC strategies around HIL interference detection have been described in the literature.5
From a QC program design perspective, the goal is to have a practical approach to a quality strategy. Looking at the frequency of testing for HIL QC, the main recommendation is to approach a process in line with the lab’s routine test intervals and to handle comparably to other QCs. This should always be done in keeping with local regulations where applicable.
When starting with a QC approach in the laboratory around HIL detection, or any new assay or process, a few practical considerations arise and these include:
- QC design and handling, such as selecting key parameters to monitor, at what frequency, and with which internal or external materials.
- Management of QC, such as setting up rules and following up over time.
- Tools to Manage QC, such as the selection and use of data-management software.
- Troubleshooting steps, such as handling an “out of control” situation, reporting this to laboratory management, and possibly correcting reported results.
A detailed example of this type of quality process analysis is described in a paper by Lippi et al. on behalf of the EFLM Working Group for Preanalytical Phase.5
Third party materials are available and are intended to monitor instrument response in detecting Hemolyzed, Icteric or Lipemic samples. The use of such products is recommended as an objective assessment of the instrument’s response. Third party materials, as compared to “home brewed,” can minimize the lab staff preparation time and effort.
International guidance
ISO 15189-2012 Medical laboratories — Requirements for quality and competence is a widely recognized international standard for laboratory quality systems, and compliance is a regulatory requirement for laboratories in many countries. ISO 15189, section 4.9 states that the laboratory “…shall have a documented procedure to identify and manage nonconformities in any aspect of the quality management system, including pre-examination…processes.” Section 5.4 also more specifically describes the “pre-examination process.”6
CLSI C56-A recommends that QC material containing human sourced material (prepared following procedures as described in CLSI guidelines C56-A and EP07) is acceptable for HIL indices.3
The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) maintains a working group specifically focused on pre-analytical errors from the importance of pre-analytical follow up to background and to specific guidance for QC approaches. More background can be found at the EFLM working group on the pre-analytical phase website.7
Summary
Laboratories understand the potential of inaccurate results from certain samples and have dealt with serum index issues for many years. The introduction of high-volume, high-throughput analyzers with built-in serum-index detection capabilities has improved assessment of such samples. They have also, however, introduced their own opportunities for errors, and these need to be controlled in a laboratory quality process focused on possible errors in serum index measurements. This article has reviewed this status and offered resources that explain how labs can maintain control of their processes.
References
- Glick MR, Ryder KW, Glick SJ, Woods JR. Unreliable visual estimation of the incidence and amount of turbidity, hemolysis, and icterus in serum from hospitalized patients. Clin Chem 1989; 35:837-9.
- Luksic AH, Nikolac Gabaj N, Miler M, Dukic L, Bakliza A, Simundic AM. Visual assessment of hemolysis affects patient safety. Clin Chem Lab Med 2018; 56:574-81.
- CLSI. Hemolysis, Icterus, and Lipemia / Turbidity Indices as Indicators of Interference in Clinical Laboratory Analysis. Approved Guideline. CLSI document C56-A. Wayne, PA: Clinical and Laboratory Standards Institute; 2012.
- von Meyer A, Cadamuro J, Lippi G. Simundic AM. Call for more transparency in manufacturers declarations on serum indices: On behalf of the Working Group for Preanalytical Phase (WG-PRE), European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Clinica Chimica Acta. 2018; 484: 328-332. doi: 10.1016/j.cca.2018.03.043.
- Lippi G, Cadamuro J, von Meyer A, Simundic AM. Local quality assurance of serum or plasma (HIL) indices. Clin Biochem 2018; 54:112-8. DOI: 10.1016/j.clinbiochem.2018.02.018.
- ISO 15189. Medical laboratories - Requirements for quality and competence. Geneva, Switzerland: International Organization for Standardization; 2012.ISO 15189:2012.
- Working Group: Preanalytical Phase. European Federation of Clinical Chemistry and Laboratory Medicine. https://www.eflm.eu/site/page/a/1194. Accessed November 23, 2020.
