Zubair Khalid

Virologist/Molecular Biologist | Veterinarian | Bioinformatician

Conventional & Molecular Virology • Vaccine Development • Computational Biology

Dr. Zubair Khalid is a veterinarian and virologist specializing in conventional and molecular virology, vaccine development, and computational biology. Dedicated to advancing animal health through innovative research and multi-omics approaches.

Dr. Zubair Khalid - Veterinarian, Virologist, and Vaccine Development Researcher specializing in Computational Biology, Multi-omics, Animal Health, and Infectious Disease Research

Section: Clinical Pathology

Clinical Chemistry Interference Studies: Design and Interpretation

Interference studies in clinical chemistry determine how endogenous and exogenous substances alter measured analyte concentrations and whether those alterations are clinically meaningful. This article provides laboratory students, technicians, researchers, and diagnostic professionals with a practical framework for designing, executing, and interpreting interference studies, including a template for study documentation and guidance on when to escalate findings to instrument manufacturers or regulatory bodies.

Scope and Purpose of Interference Testing

Interference testing evaluates the effect of a specific substance on the analytical measurement of a target analyte. The goal is to identify whether a potentially interfering substance produces a bias that exceeds acceptable limits and could lead to incorrect clinical decisions. Interference can be endogenous, arising from substances naturally present in patient samples such as bilirubin, hemoglobin, lipids, or paraproteins, or exogenous, arising from medications, intravenous fluids, contrast media, or sample additives.

The Clinical and Laboratory Standards Institute document EP7-A2, titled "Interference testing in clinical chemistry," provides the foundational protocol for designing these experiments. This protocol describes methods for preparing interference solutions, spiking samples, and analyzing dose-response relationships. Laboratories that follow this protocol generate data that can be compared across institutions and over time.

Interference studies serve multiple purposes. They characterize assay limitations for the laboratory's own quality management system, they provide data for interpreting unexpected patient results, and they support decisions about sample rejection or dilution protocols. The World Health Organization Laboratory Quality Management System Handbook emphasizes that quality control extends beyond internal and external quality assessment to include method validation and verification activities such as interference testing.

Endogenous Interferents

Endogenous interferents originate within the patient's own biological system. The most frequently encountered endogenous interferents in clinical chemistry are hemolysis, icterus, and lipemia, collectively referred to as HIL.

Hemolysis

Hemolysis releases hemoglobin and intracellular contents from red blood cells into serum or plasma. The released hemoglobin can interfere with spectrophotometric measurements by absorbing light at wavelengths that overlap with assay detection wavelengths. Additionally, intracellular analytes such as potassium, lactate dehydrogenase, and aspartate aminotransferase are released into the sample, causing falsely elevated results for these analytes.

A retrospective study at an academic medical center evaluated interference indices in 2752 body fluid specimens and found that hemolysis of specimens submitted for lactate dehydrogenase represented the most common interference for body fluid chemistries. The study also noted that false elevations in pleural fluid lactate dehydrogenase induced by hemolysis can lead to misclassification of transudative effusions as exudative using Light's criteria. This finding demonstrates that hemolysis interference has direct clinical consequences beyond simple sample rejection.

Icterus

Icterus refers to elevated bilirubin concentrations in the sample. Bilirubin can interfere with assays through spectral absorption and through chemical reactivity with assay reagents. A retrospective study of 414,502 specimens analyzed over a 12-month period found that specimen icteric index exceeded package insert icteric index thresholds in 0.14% of clinical chemistry assays. The highest number of instances occurred for creatinine, total protein, and ammonia. The study identified alcohol-related liver disease, biliary tract disease, and neoplasms as the most common etiologies among patients with severe icterus.

The same study found that 57 patients with an icteric index of 40 or higher accounted for 49.7% of all instances where the icteric index exceeded the specific assay package insert limit. This concentration of interference in a small patient cohort has practical implications for laboratory workflow. Laboratories serving hepatology or gastroenterology services should expect higher rates of icteric interference and may need to establish specific protocols for these patient populations.

Lipemia

Lipemia results from elevated concentrations of triglycerides and other lipids in the sample. Lipemic samples appear turbid or milky, and the turbidity can scatter light, affecting spectrophotometric measurements. A retrospective study of 552,029 specimens analyzed over a 16-month period found that the most frequent suspected causes of very high lipemic index were lipid-containing intravenous infusions, accounting for 54.4% of total cases, and diabetes mellitus, accounting for 25% of total cases. Among the lipid-containing infusions, fat emulsions for parenteral nutrition accounted for 47% and propofol accounted for 7.4%.

The study also found that the frequency of hemolysis increased with increasing lipemic index. This association between lipemia and hemolysis is important because the combined effect of multiple interferents may differ from the effect of each interferent alone. The study concluded that iatrogenic factors are the most common cause of severe lipemia, suggesting that education and intervention may help reduce the frequency of severe lipemia in patient specimens.

Cross-Interference Among HIL Parameters

Recent evidence indicates that hemolysis, icterus, and lipemia can interfere with the measurement of each other's indices. A study following the CLSI-EP07 guideline prepared high-concentration icterus and lipemia pools from leftover clinical samples and a hemolysate pool, then serially diluted these pools with low-index serum to obtain defined combinations. The study found that hemolysis in the range of 2.5 to 10.0 g/L caused a 20% to 150% false increase in lipemia index and a 10% to 60% false decrease in icterus index. Conversely, lipemia in the range of 25 to 100 index led to a 20% to 150% false increase in icterus index and reduced low levels of hemolysis by 10% to 30%. Icterus at 42.75 to 171 µmol/L resulted in a 15% to 45% false reduction in low levels of hemolysis.

These findings demonstrate that assessing HIL indices independently can lead to misinterpretation. The study proposed a rule-based, threshold-dependent algorithm incorporating these interactions to enhance accuracy in sample rejection decisions. Laboratories should consider whether their current sample rejection protocols account for cross-interference among HIL parameters.

Exogenous Interferents

Exogenous interferents enter the sample from sources outside the patient's biological system. These include medications, intravenous fluids, contrast media, anticoagulants, and other substances administered during patient care.

Hemoglobin-Based Oxygen Carriers

Hemoglobin-based oxygen carriers are artificial oxygen transport solutions developed as red blood cell substitutes. These products can interfere with clinical chemistry assays because the hemoglobin they contain absorbs light and participates in chemical reactions similar to endogenous hemoglobin.

A study evaluating the hemoglobin-based oxygen carrier Hemospan found that it did not interfere with 20 of 35 analytes tested. Hemospan produced negative interference in serum creatinine, amylase, alkaline phosphatase, uric acid, and gamma-glutamyltransferase assays. It produced positive interference in serum phosphate, lactate dehydrogenase, iron, triglycerides, total protein, aspartate aminotransferase, cholesterol, magnesium, and albumin assays. The study also found that Hemospan appeared to positively bias the serum cardiac troponin I assay only when troponin I was present in the sample.

Another study evaluated the red cell substitute pyridoxalated hemoglobin-polyoxyethylene and found interference with blood compatibility, coagulation, and clinical chemistry testing. These findings highlight the importance of understanding the specific interference profile of each oxygen carrier product, as the effects vary by product formulation and by assay methodology.

Medications and Therapeutic Agents

Many medications can interfere with clinical chemistry assays. The interference may occur through spectral properties of the drug, chemical reactivity with assay reagents, or effects on the patient's physiology that alter analyte concentrations.

A study on the interference of high dose ascorbate in blood gas, point-of-care, and automated clinical chemistry assays documented the analytical effects of this commonly used medication. Ascorbate can interfere with assays that rely on oxidation-reduction reactions, including glucose and uric acid measurements.

Ethamsylate, a hemostatic agent, has been shown to interfere with different methods for testing serum creatinine. The nature and magnitude of the interference depend on the specific creatinine method used, demonstrating that interference studies must be performed for each assay method instead of for each analyte.

Traditional medicine preparations can also interfere with clinical chemistry assays. A study of Salviae Miltiorrhizae Compound Injection documented its interference in common clinical biochemical tests. Laboratories serving patient populations that use traditional or herbal medicines should be aware of potential interference from these products.

Oligonucleotide Therapeutics

Oligonucleotide-based therapeutics represent an emerging class of medications that may interfere with clinical chemistry assays. These agents include antisense oligonucleotides, small interfering RNAs, and aptamers. A review of therapeutic oligonucleotides noted that these agents can interfere with biomolecules representing the entire extended central dogma, and their delivery systems include lipid nanoparticles and ligand-conjugated formulations.

The clinical translation of small interfering RNA therapeutics has depended on chemical modifications and sophisticated delivery platforms to improve stability, limit immune activation, facilitate internalization, and increase target affinity. These delivery platforms may themselves interfere with laboratory assays. Laboratories should monitor the literature for reports of interference from new therapeutic classes as they enter clinical use.

Study Design Principles

Designing an interference study requires careful attention to sample selection, interferent preparation, concentration ranges, and analytical methods.

Baseline Sample Selection

The baseline sample is the matrix into which the interferent is added. For most clinical chemistry assays, pooled serum or plasma from healthy donors serves as the baseline. The baseline sample should have analyte concentrations within the reference interval or at clinically relevant decision points.

For assays where the interferent effect depends on analyte concentration, multiple baseline pools with different analyte concentrations may be needed. For example, an immunoassay for a cardiac marker may show different interference patterns at low and high analyte concentrations. A study of the hemoglobin-based oxygen carrier Hemospan found that the positive bias in the cardiac troponin I assay occurred only when troponin I was present in the sample, demonstrating the importance of testing at multiple analyte concentrations.

Interferent Preparation

Endogenous interferents such as bilirubin, hemoglobin, and lipids can be prepared from patient samples or from commercial sources. Hemolysate is typically prepared by lysing red blood cells, and bilirubin solutions are prepared by dissolving bilirubin in an appropriate solvent. Lipemic samples can be obtained from patients with elevated triglycerides or from commercial lipid emulsions.

A comprehensive dataset comparing endogenous and exogenous HIL interference across diverse clinical immunoassays found significant analytical discrepancies between artificially simulated and genuine clinical samples, particularly in lipemic samples. This finding suggests that exogenous interference models may not accurately reflect the effects of endogenous interferents. Laboratories should validate their interference findings using genuine clinical samples whenever possible.

Concentration Ranges

The interferent concentration range should extend from below the expected physiological range to above the concentration where interference becomes clinically significant. For bilirubin, this range should include concentrations seen in severe jaundice. For hemoglobin, the range should include concentrations seen in grossly hemolyzed specimens.

The study of cross-interference among HIL parameters used serial dilutions of high-concentration pools to obtain defined combinations across a range of concentrations. This approach allows the laboratory to determine the concentration at which interference first becomes detectable and the concentration at which the bias exceeds acceptable limits.

Analytical Methods

Interference studies should be performed using the same analytical methods and instruments used for patient testing. The studies should include appropriate quality control samples to verify instrument performance during the experiment. The World Health Organization Laboratory Quality Management System Handbook provides guidance on quality control practices that apply to interference studies.

Statistical Analysis and Interpretation

The statistical analysis of interference data focuses on determining whether the observed bias exceeds acceptable limits and whether the bias is clinically significant.

Calculating Bias

Bias is calculated as the difference between the measured analyte concentration in the presence of the interferent and the measured concentration in the baseline sample. Bias can be expressed as an absolute difference or as a percentage of the baseline concentration.

The percentage bias is calculated by dividing the difference between the interfered and baseline measurements by the baseline measurement and multiplying by 100. For example, if a baseline sample measures 100 mg/dL and the interfered sample measures 110 mg/dL, the bias is 10%.

Acceptable Limits

The acceptable bias for an analyte depends on the clinical use of the test. For analytes with narrow therapeutic ranges or critical decision points, smaller biases may be clinically significant. For analytes with wide reference intervals, larger biases may be acceptable.

The CLSI EP7-A2 protocol provides guidance on defining acceptable interference limits. Laboratories should establish these limits before conducting the study, based on the analyte's clinical utility and the laboratory's quality goals.

Dose-Response Analysis

Interference studies typically evaluate multiple interferent concentrations to establish a dose-response relationship. The data can be plotted with interferent concentration on the x-axis and measured analyte concentration or percentage bias on the y-axis. This plot allows the laboratory to identify the interferent concentration at which the bias exceeds acceptable limits.

The study of cross-interference among HIL parameters found no concentration-dependent systematic bias for lipemia and icterus, whereas hemolysis showed level-dependent effects. This finding illustrates that different interferents may show different dose-response patterns, and the analysis should account for these differences.

Statistical Significance Versus Clinical Significance

A statistically significant bias may not be clinically significant if the magnitude of the bias is small relative to the analyte's reference interval or clinical decision limits. Conversely, a bias that is not statistically significant in a small study may become clinically significant when applied to a large patient population.

The interpretation of interference data should focus on clinical significance instead of statistical significance alone. The laboratory should document the rationale for the acceptable bias limits and apply these limits consistently across studies.

Endogenous Versus Exogenous Interference Models

The choice between endogenous and exogenous interference models has important implications for the validity of study findings.

Exogenous Models

Exogenous interference models involve adding the interferent to a baseline sample. This approach offers several advantages. The interferent concentration can be precisely controlled, the baseline sample can be characterized before interference is added, and multiple interferent concentrations can be tested using a single baseline pool.

However, exogenous models have limitations. The interferent added to the sample may not behave identically to the endogenous interferent in patient samples. For example, bilirubin added to a sample may differ in its binding to albumin and its spectral properties compared to endogenous bilirubin. The comprehensive dataset comparing endogenous and exogenous HIL interference found significant analytical discrepancies between artificially simulated and genuine clinical samples, particularly in lipemic samples.

Endogenous Models

Endogenous models use patient samples that naturally contain the interferent. These samples can be obtained from patients with elevated bilirubin, hemoglobin, or lipids. The endogenous model more accurately reflects the clinical situation because the interferent is present in its natural form and concentration.

The study of cross-interference among HIL parameters used endogenous patient-derived samples to ensure clinically relevant conditions. The study prepared high-concentration icterus and lipemia pools from leftover clinical samples and a hemolysate pool, then serially diluted these pools with low-index serum to obtain defined combinations.

Practical Considerations

Laboratories should use both models when feasible. Exogenous models are useful for initial screening and for establishing dose-response relationships. Endogenous models are useful for confirming findings and for assessing the combined effects of multiple interferents.

The dataset comparing endogenous and exogenous HIL interference provides derived reference charts and correction formulas for hemolysis-sensitive analytes. These resources can help laboratories refine interference validation protocols and minimize unnecessary sample rejections.

At a Glance: Interference Study Design Decision Table

Study Element Endogenous Model Exogenous Model Hybrid Approach
Sample source Patient samples with naturally elevated interferent Pooled baseline samples spiked with interferent Both patient samples and spiked pools
Interferent control Limited control over concentration range Precise control over concentration range Control over spiked pools plus confirmation in patient samples
Clinical relevance High relevance to actual patient conditions May not reflect endogenous interferent behavior High relevance with controlled dose-response data
Resource requirements Requires access to patient samples with elevated interferents Requires interferent preparation and characterization Higher resource requirements for both sample types
Best use case Confirming findings and assessing combined effects Initial screening and dose-response establishment Comprehensive validation for critical assays

Practical Workflow for Conducting an Interference Study

The following workflow provides a structured approach to conducting an interference study in a clinical chemistry laboratory.

Step 1: Define the Study Question

Identify the analyte, the interferent, and the assay method to be studied. Document the clinical context that motivates the study, such as a suspected interference from a new medication or a high rate of sample rejection due to hemolysis.

Step 2: Establish Acceptable Bias Limits

Define the acceptable bias for the analyte based on its clinical use. Document the rationale for the chosen limits. For analytes with established quality specifications, use these specifications as the basis for acceptable bias.

Step 3: Prepare Baseline Samples

Obtain pooled serum or plasma from healthy donors. Verify that the baseline pool has analyte concentrations within the desired range. For assays where the interferent effect depends on analyte concentration, prepare multiple baseline pools.

Step 4: Prepare Interferent Solutions

Prepare the interferent at the desired concentrations. For endogenous interferents, use patient samples or commercial preparations. For exogenous interferents, use pharmaceutical preparations or purified compounds. Document the preparation method and verify the interferent concentration.

Step 5: Prepare Test Samples

Combine the baseline sample with the interferent solution to achieve the desired interferent concentrations. Include a baseline sample without interferent as the control. Prepare samples in duplicate or triplicate to assess analytical variation.

Step 6: Analyze Samples

Analyze all samples in a single run using the same instrument and reagent lot. Include quality control samples to verify instrument performance. Record all results, including any instrument flags or error messages.

Step 7: Calculate Bias

Calculate the bias for each interferent concentration by comparing the measured analyte concentration to the baseline concentration. Express the bias as a percentage of the baseline concentration.

Step 8: Interpret Results

Compare the calculated bias to the acceptable bias limits. Identify the interferent concentration at which the bias first exceeds the acceptable limit. Document the findings and their implications for patient testing.

Step 9: Document and Report

Document the study design, results, and interpretation in a format that can be reviewed by laboratory leadership and shared with instrument manufacturers if needed. Include the study date, reagent lot numbers, instrument identification, and personnel involved.

Records and Measurements

Accurate record keeping is essential for interference studies. The following records should be maintained for each study.

Study Documentation

The study protocol should document the study question, acceptable bias limits, sample preparation methods, interferent concentrations, and analytical methods. Any deviations from the protocol should be recorded and explained.

Sample Records

Each sample should be identified with a unique identifier. The record should include the baseline pool used, the interferent concentration, the preparation date and time, and any observations about sample appearance or handling.

Analytical Records

The analytical record should include the instrument identification, reagent lot numbers, calibration information, quality control results, and the raw analytical data for each sample. Instrument flags or error messages should be recorded.

Interpretation Records

The interpretation record should document the calculated bias for each interferent concentration, the comparison to acceptable bias limits, and the conclusions drawn from the study. Any recommendations for changes to laboratory procedures should be documented.

Common Failure Patterns in Interference Studies

Several common problems can compromise the validity of interference studies.

Inadequate Baseline Characterization

If the baseline sample contains the interferent at measurable concentrations, the calculated bias will be underestimated. Laboratories should verify that baseline samples have low or undetectable interferent concentrations before proceeding with the study.

Interferent Instability

Some interferents are unstable in solution. Bilirubin is light-sensitive and can degrade during the study. Hemoglobin can oxidize and change its spectral properties. Laboratories should prepare interferent solutions fresh and protect them from light and heat as appropriate.

Matrix Effects

The interferent solution may contain substances other than the interferent that affect the assay. For example, bilirubin solutions may contain solvents that interfere with the assay. Laboratories should include a solvent control to distinguish the effect of the interferent from the effect of the solvent.

Incomplete Mixing

Inadequate mixing of the interferent with the baseline sample can result in variable interferent concentrations across replicate samples. Laboratories should use thorough mixing procedures and verify interferent concentrations in the test samples.

Carryover Effects

Analyzing high-interferent samples before low-interferent samples can result in carryover contamination. Laboratories should analyze samples in an order that minimizes carryover risk, such as analyzing baseline samples before interferent samples.

Ignoring Cross-Interference

The study of cross-interference among HIL parameters demonstrated that hemolysis, icterus, and lipemia can interfere with each other's measurements. Laboratories that assess only one interferent at a time may miss clinically relevant interactions.

Limitations of Interference Studies

Interference studies have inherent limitations that should be acknowledged when interpreting results.

Single-Instrument Findings

Interference findings from one instrument or reagent lot may not apply to other instruments or reagent lots. Laboratories should verify interference findings when changing instruments or reagent suppliers.

In Vitro Versus In Vivo Effects

In vitro interference studies evaluate the effect of the interferent on the analytical measurement. These studies do not capture in vivo effects, where the interferent may affect the patient's physiology and thereby alter analyte concentrations. For example, a medication may interfere with the assay and also affect the patient's renal function, producing a combined effect that differs from the in vitro finding.

Concentration Extrapolation

Interference studies typically evaluate a limited range of interferent concentrations. Extrapolating findings beyond the tested range may not be valid, particularly if the dose-response relationship is nonlinear.

Sample Matrix Differences

Interference findings from serum samples may not apply to plasma, urine, or body fluid samples. A study of interference indices in body fluid specimens found that body fluids exhibited a higher proportion of samples with severe icterus or lipemia compared to serum or plasma specimens. Laboratories should verify interference findings for each sample type they test.

Resource Constraints

Interference studies require time, personnel, and materials. In resource-constrained settings, the capacity to conduct comprehensive interference studies may be limited. A review of interferences in clinical chemistry in resource-constrained settings noted that persistent limitations in laboratory infrastructure, workforce training, and quality management systems exacerbate vulnerabilities across the total testing process. The review reported a pooled pre-analytical error prevalence of approximately 17.5% in African laboratories, substantially exceeding rates commonly reported in high-income countries.

Safety and Regulatory Context

Interference studies involve handling patient samples and chemical reagents. Laboratories should follow appropriate biosafety practices as described in the World Health Organization Laboratory Biosafety Manual. This includes using appropriate personal protective equipment, handling sharps safely, and disinfecting work surfaces.

When the interferent is a pharmaceutical product, the laboratory should follow the manufacturer's safety recommendations for handling the product. When the interferent is prepared from patient samples, the laboratory should follow standard precautions for handling potentially infectious materials.

Regulatory considerations apply to interference studies conducted for regulatory submissions. The U.S. Food and Drug Administration Bioanalytical Method Validation Guidance provides recommendations for validating bioanalytical methods, including assessment of selectivity and interference. The Assay Guidance Manual from the National Center for Advancing Translational Sciences provides additional guidance on assay development and validation.

For in vitro diagnostic products, interference studies are part of the performance evaluation required for regulatory approval. The regulatory framework varies by jurisdiction, and laboratories should consult the relevant regulatory requirements for their region.

Professional Escalation Criteria

Laboratories should escalate interference findings to instrument manufacturers or regulatory bodies under specific circumstances.

Manufacturer Notification

Notify the instrument or reagent manufacturer when an interference study identifies a clinically significant bias that is not documented in the package insert. Provide the manufacturer with the study protocol, results, and interpretation. The manufacturer may be able to provide additional data or modify the package insert to reflect the new findings.

Regulatory Reporting

Report interference findings to the relevant regulatory authority when the interference poses a significant risk to patient safety. The reporting requirements vary by jurisdiction and by the type of device or test involved.

Clinical Consultation

Consult with clinical staff when an interference finding affects the interpretation of patient results. Provide the clinical team with information about the nature and magnitude of the interference and recommendations for alternative testing approaches.

Literature Publication

Consider publishing interference findings in the peer-reviewed literature when the findings are novel and have implications beyond the local laboratory. Published findings can help other laboratories recognize and manage similar interference issues.

Frequently Asked Questions

What is the difference between an endogenous and an exogenous interferent?

An endogenous interferent originates within the patient's biological system, such as bilirubin, hemoglobin, or lipids. An exogenous interferent enters the sample from outside the patient, such as medications, intravenous fluids, or sample additives. The distinction matters because endogenous interferents are present in their natural form and concentration, while exogenous interferents may behave differently when added to a sample in vitro.

How do I choose the interferent concentrations to test?

The interferent concentration range should extend from below the expected physiological range to above the concentration where interference becomes clinically significant. For bilirubin, include concentrations seen in severe jaundice. For hemoglobin, include concentrations seen in grossly hemolyzed specimens. The CLSI EP7-A2 protocol provides guidance on selecting concentration ranges.

What is the difference between statistical significance and clinical significance in interference studies?

Statistical significance indicates that the observed bias is unlikely to be due to chance. Clinical significance indicates that the bias is large enough to affect clinical decisions. A statistically significant bias may not be clinically significant if the magnitude is small relative to the analyte's reference interval. The interpretation of interference data should focus on clinical significance.

How do I determine the acceptable bias for an analyte?

The acceptable bias depends on the clinical use of the test. For analytes with narrow therapeutic ranges or critical decision points, smaller biases may be clinically significant. For analytes with wide reference intervals, larger biases may be acceptable. Laboratories should establish acceptable bias limits before conducting the study, based on the analyte's clinical utility and the laboratory's quality goals.

Why do exogenous interference models sometimes disagree with endogenous patient samples?

Exogenous models add the interferent to a baseline sample, and the added interferent may not behave identically to the endogenous interferent in patient samples. A comprehensive dataset comparing endogenous and exogenous HIL interference found significant analytical discrepancies between artificially simulated and genuine clinical samples, particularly in lipemic samples. Laboratories should validate interference findings using genuine clinical samples whenever possible.

What should I do if I find an interference that is not in the package insert?

Notify the instrument or reagent manufacturer and provide the study protocol, results, and interpretation. The manufacturer may be able to provide additional data or modify the package insert. If the interference poses a significant risk to patient safety, report the finding to the relevant regulatory authority and consult with clinical staff about the implications for patient testing.

How do hemolysis, icterus, and lipemia interfere with each other's measurements?

A study following the CLSI-EP07 guideline found that hemolysis caused false increases in lipemia index and false decreases in icterus index, while lipemia caused false increases in icterus index and reduced low levels of hemolysis. Icterus caused false reductions in low levels of hemolysis. These cross-interferences can lead to misinterpretation if indices are assessed independently.

What records should I maintain for an interference study?

Maintain the study protocol, sample records with unique identifiers and preparation details, analytical records including instrument identification and reagent lot numbers, and interpretation records documenting the calculated bias and conclusions. Include the study date, personnel involved, and any deviations from the protocol.

Related Diagnostic Guides

References and Further Reading

This article is educational and does not replace validated laboratory procedures, institutional biosafety review, manufacturer instructions, or professional interpretation.