Clinical Chemistry I Week 07 Quiz

Clinical Chemistry I - 0202304

• Course instructor: Mohammad QABAJAH
• Email address: [email protected]

Week 07 - Reference Values

• Objectives:
  • Explain the need for reference intervals in clinical tests.
  • Identify conditions crucial for valid comparisons of lab results with reference values.
  • Understand exclusion criteria used for creating health-related reference values.
  • Detail the criteria used to categorize reference groups.
  • Describe parametric and nonparametric statistical methods for determining interpercentile intervals.
  • Discuss issues with the transferability of reference values and their solutions.
  • Compare reference values and reference intervals.

Decision Making: Comparison

• Medical interviews, clinical examinations, and supplementary investigations help determine diagnoses.
• Laboratory results are compared to reference values to aid in diagnosis.
• If the result doesn't match a typical disease, the diagnosis is excluded.
• If the result resembles a typical disease, the diagnosis is considered.

In Laboratory: Decision Making by Comparison

• Reference values:
  • Healthy individuals
  • Patients with specific diseases
• Reference values (Obtained from):
  • A single individual (subject-based reference)
  • A group of individuals (population-based reference)
• Reference values must be clearly defined and available to others.

Comparing Observed Data

• Reference values come from multiple sources:
  • Healthy individuals
  • Individuals with unspecified illnesses
  • Individuals with specific diseases

Conditions to Ensure Proper Comparison

• Ensure all reference individual groups are clearly defined.
• Patients being tested should have similar characteristics.
• Test conditions (e.g., environment, procedures) should be known.
• Measured values must use consistent units.
• Standardized methods are needed for all results.
• The clinical sensitivity, clinical specificity, and prevalence are relevant.

Selection of Reference Individuals

• Ideally, the entire population is sampled.
• Large-scale random sampling (as large as possible, with ~120+ individuals) is used.

Exclusion Criteria

• Diseases: Specific diseases to exclude from the reference group.
• Risk factors: Factors like obesity, high blood pressure, occupational risks, genetic risks.
• Intake of pharmacologically active agents: Medicines and supplements.
• Specific physiological states: Pregnancy, stress, excessive exercise.

Subgrouping of the Reference Group

• Factors used to subgroup:
  • Age
  • Gender
• Physiological factors:
  • Stage in menstrual cycle
  • Stage of pregnancy
  • General physical condition

Specimen Collection

• Preanalytical standardization:
  • Subject preparation before specimen collection
  • Specimen collection procedure
  • Sample handling before analysis

Analytical Procedures and Quality Control

• Components to define:
  • Analytical methods (detailed information needed)
  • Laboratory equipment
  • Reagents used
  • Calibration standards (calibrators)
  • Data types and formats of raw data
  • Calculation methodologies
  • Details of quality checks

Statistical Treatment of Reference Values

• Processes:
  • Group the results into appropriate categories
  • Evaluate data distribution for each group
  • Determine reference limits
  • Identify outliers in the data

Inspection of Distribution

• Graph presentation (frequency distribution)
  • Uni-, bi-, or polymodal distribution patterns
  • Overall shape of the distribution
  • Locate and evaluate significant values (outliers)

Determination of Reference Limits

• Reference interval:
  • Upper and lower reference limits (defining a range)
  • Reflect a specified proportion (e.g., 95%) of the reference population.
• Range: (Higher Value - Lower Value)
• Clinical decision limits: Improve the differentiation between categories (healthy vs. disease).

Identification of Outliers

• Assumption of Gaussian distribution for data.
• Outliers are any data point outside 1.5 times the interquartile range (IQR) from lower or upper quartile.

Quartile Formula

• Formulas to calculate lower quartile (Q1), middle quartile (Q2, or median), and upper quartile (Q3) using number of observations (N).

Interquartile Range Formula

• Describes the central spread of the dataset.
• Mathematically defined as difference between the 75th (Q3) and 25th (Q1) percentiles.

Outliers Formula

• Calculation of lower and upper outlier values.
• Using quartile values (Q1, Q3) and interquartile range (IQR).

Determination of Reference Limits

• Reference limit: A single boundary value.
• Clinical decision limit: Values to distinguish between categories of healthy and diseased subjects.
• Reference range: A range of values versus a reference interval, which is an interpercentile range of data.
• Reference interval: Tolerance intervals, Interpercentile Intervals. Prediction intervals

Interpercentile Interval

• A method to measure the tolerance range of a specific percentile.
• Two types: Parametric (mean and standard deviation-based) and non-parametric (observation-based).

Transferability/Transference of Reference Values

• Use of reference values from other labs, population-level considerations
• Considerations include:
  • Comparability of populations
  • Ethnic homogeneity
  • Social characteristics
  • Environmental variables across populations

Further Considerations on Transferability

• Preanalytical procedures must match.
• Analytical methodology must be the same.
• Standardization of methods is required.
• Verification methods (using 20 individuals) are essential.

This quiz focuses on the importance of reference values in clinical chemistry. It covers objectives such as understanding exclusion criteria, statistical methods for reference intervals, and the transferability of these values. Prepare to test your knowledge on these critical concepts in laboratory diagnostics.