What is the importance of biochemistry in health and disease? Flashcards
Biochemistry helps in understanding disease mechanisms, diagnosing conditions, and developing treatments.
What are biochemical markers?
Biochemical markers are molecules found in body fluids that indicate normal or pathological processes.
What is the importance of biochemistry in health and disease?
Biochemistry helps in understanding disease mechanisms, diagnosing conditions, and developing treatments.
What is the first step in the diagnostic process in medicine?
History-taking.
What comes after history-taking in the medical diagnostic process?
A: Clinical examination.
What are the two main branches of diagnostic services?
Imaging and physiological tests (ECG, EEG, lung function).
What are the different types of laboratory services?
Haematology, histopathology, genetics, immunology, screening, and microbiology.
What is the role of clinical biochemistry in medicine?
It provides biochemical analysis for emergency services, core biochemistry, and specialized tests.
Name three physiological tests under diagnostic services.
ECG, EEG, lung function tests.
What are the three main categories of clinical biochemistry services?
Emergency services, core biochemistry, and specialized tests.
Definition of SGOT(ALT), SGPT(AST) and GGT
Alanine aminotransferase, aspartate aminotransferase and gamma glutamyl transpeptidase
How are the test results used?
1) diagnosis
2) screening
3) prognosis-
the likely course of a medical condition
4) treatment
5) forensic- drug testing and legal investigations
How many different tests can be done on an individual to measure conc of molecule in the body?
400 different tests
How important is clinical biochemistry?
1/3 importance
What is an example of a clinical biochemistry test used to confirm a diagnosis?
Serum free T4 and TSH for suspected hyperthyroidism.
How can clinical biochemistry aid differential diagnosis?
It helps distinguish between different forms of jaundice.
What test is used to refine the diagnosis of Cushing’s syndrome?
Adrenocorticotropic hormone (ACTH) test.
Which biochemical marker is used to assess the severity of renal disease?
Serum creatinine or urea.
How is the progress of diabetic ketoacidosis (DKA) monitored?
By measuring plasma glucose and serum potassium (K⁺).
What clinical biochemistry test is used to detect complications of hepatotoxic drugs?
Alanine aminotransferase (ALT) measurements.
Which test is used to monitor therapy in patients taking anti-epileptic drugs?
Serum drug concentration measurements.
Properties of ideal biomarkers
1) safe and high reproducibility
2) most sensitive and specific
3) cost effective
4) reliable and feasible
Sources of
variation in
test results
- Analytical sources of variation
- Biological causes of variation
What is accuracy in an analytical method?
The degree to which an experimental result approaches the true or accepted answer.
How can accuracy be described in an analytical method?
Accuracy can be described using error, which is the difference between the obtained result and the true value.
What are the formulas for absolute and relative error?
Absolute Error = (X – μ)
Relative Error (%) = 100(X – μ)/μ
where:
X = The experimental result
μ = The true result
What are the two types of error in analytical methods?
Random
Systematic
Random Error:
Results in a scatter of results centered on the true value
for repeated measurements on a single sample.
Systematic Error:
Results in all measurements exhibiting a definite
difference from the true value
What is precision in analytical methods?
The reproducibility of results. The degree to which an
experimental result varies from one determination to
the next.
How is precision related to random and systematic errors?
Precision is related to random error (scattering of results).
Accuracy is related to systematic error (consistent deviation from the true value).
What are some ways to describe precision?
Range: Difference between the highest and lowest values in a repeated experiment.
Standard Deviation (SD): Measures the spread of results around the mean.
Coefficient of Variation (CV): Relative standard deviation expressed as a percentage.
Standard Deviation:
Describes the distribution of the measured results about
the mean or average value.
Absolute Standard Deviation (SD):
Relative Standard Deviation (RSD) or
Coefficient of Variation (CV):
where: n = total number of measurements
Xi = measurement made for the ith trial
= mean result for the data sample
How do you calculate Coefficient of Variation (CV)?
CV (%) = (Standard Deviation / Mean) × 100
What is the response of an analytical method?
The way in which the result or signal of a method
varies with the amount of compound or property being
measured.
What is a calibration curve?
A plot of the result or signal vs. the known amount of a known compound or property (standard) being measured.
What are the parameters used to describe a Calibration Curve and what equation represents a calibration curve?
S – measured signal
c – analyte concentration
Sbl – instrument signal for blank
S = mc + Sbl
What is sensitivity in an analytical method?
Sensitivity refers to the ability of a method to detect small differences in analyte concentration.
How is analytical sensitivity calculated?
Analytical sensitivity (g) = slope (m) / standard deviation (Ss)
Sensitivity:
calibration sensitivity = slope (m) of calibration curve.
analytical sensitivity (g) = slope (m)/standard deviation (Ss)
ability to discriminate between small differences in analyte concentration.
Slope and reproducibility of the
calibration curve.
What is selectivity in an analytical method?
Degree to which the method is free from interference by other species in the sample
How is selectivity represented mathematically?
Using the selectivity coefficient (kB,A):
kB,A = mB / mA, where mB and mA are the slopes of calibration curves for interfering and target analytes, respectively.
What are the main specimen types collected for clinical biochemical analysis?
Blood, urine, feces, and other body fluids.
How do scientists establish a reference range?
By conducting a screening test in a healthy population across different age groups.
List the disadvantages of using reference ranges in diagnostics.
Physiological variability
Population variability
Arbitrary cutoffs
Overlap with disease states
What is population variability in the context of reference ranges?
Differences in biological markers due to genetic, environmental, and lifestyle factors among different populations.
Why might an arbitrary cutoff be a disadvantage in reference ranges?
Some healthy individuals may fall outside the defined range, leading to misclassification.
How can reference ranges overlap with disease states?
Some diseases may have biomarker levels similar to those of healthy individuals, causing diagnostic uncertainty.
What is a “reference range”?
A range of values for healthy individuals of the appropriate age and sex.
What does “values to be expected” refer to in diagnostics?
Expected biomarker levels for patients with a disease under consideration.
What is the “prevalence of disease”?
The proportion of a population affected by a specific disease.
Why is quality control important in clinical biochemistry?
It ensures accurate and reliable test results for proper diagnosis and treatment.
How does Quality Assurance ensure accurate patient results?
It ensures that the final results reported by the laboratory are correct, the right test is carried out on the right specimen, and the correct interpretation is delivered to the right person at the right time.
What are some factors that affect the quality of a patient’s results?
The condition of specimens (lysis, jaundice)
reagents & equipment (e.g., expired reagents, maintenance)
Internal quality control programs
participation in external quality programs
Interpretation & reporting of results.
What are three potential consequences of unreliable QA performance?
Patient misdiagnosis
Delays in treatment
Increased costs.
What are examples of pre-analytical errors in QA performance failure?
Mislabeling, hemolyzed sample, wrong tube for test, inadequate volume, and contaminated sample.
What are some common analytical errors in QA performance failure?
Expired reagent, improperly calibrated instruments, and sampling errors.
What are post-analytical errors in QA performance failure?
Wrong interpretation of results, incorrect transcription of results, and reporting errors.
What are the common pre-analytical issues in sample collection?
Sample Hemolysis*
Incorrect specimen container
Delay in sample delivery
Temperature issues during transport
Incorrect specimen storage (sample left overnight at room temp or stored long-term at 4°C)
What issues can sample hemolysis cause in blood sample analysis?
LDH (Lactate dehydrogenase), potassium, or inorganic phosphate levels may be falsely elevated.
What is one effect of exercise on blood sample analysis?
Creatine kinase* and CRP (C-reactive protein) levels may be elevated due to muscle stress or inflammation from exercise.
What is the importance of collection timing in blood sample analysis?
Timing affects the accuracy of certain measurements. For example, a 24-hour urine collection is necessary for accurate analysis of urinary compounds like creatinine and protein.
How can incorrect specimen storage affect blood sample analysis?
Storing the sample at incorrect temperatures, such as leaving it at room temperature overnight or storing it at 4°C for too long, can alter the levels of certain analytes and compromise test results.
What impact can delayed sample delivery have on plasma or serum analysis?
Delays in transport can cause degradation of analytes, leading to inaccurate or altered results.
Why is it important to use the correct specimen container for blood samples?
Using the wrong container can cause contamination or changes in the chemical composition of the sample, affecting the test accuracy.
How does haemolysis specifically affect laboratory results?
Hemolysis releases intracellular components, such as potassium, LDH, and phosphate, into the plasma, which can lead to falsely elevated levels of these substances.
What can be caused by incorrect storage of samples during transport?
Temperature-related issues (such as freezing or overheating) can alter enzyme activity and metabolite levels, which can compromise the accuracy of test results.
What should be considered for 24-hour urine collection?
It is important to collect urine over a full 24-hour period to ensure the accuracy of tests measuring total urine output and analyte concentrations over time.
What is the issue with using serum or plasma containers for certain tests?
Serum or plasma* is not suitable for testing PTH (parathyroid hormone) and ACTH (adrenocorticotropic hormone).
Why are fluoride tubes used for glucose testing?
Fluoride tubes* are used to inhibit glycolysis (the breakdown of glucose), which helps prevent false results in glucose analysis.
Why are EDTA tubes unsuitable for certain tests?
EDTA tubes* are unsuitable for calcium assays because EDTA chelates calcium, interfering with accurate measurement.
What is the consequence of leaving a blood sample overnight at room temperature?
Leaving the sample at room temperature can cause falsely elevated levels of potassium (K), phosphate (Pi), and red blood cell enzymes.
What is the effect of short-term refrigeration on blood sample storage?
Short-term refrigeration* may lead to changes in analyte stability, though it does not cause significant degradation.
What happens when a sample is frozen medium-term at -20°C?
Medium-term freezing at -20°C* may lead to degradation or changes in the analyte levels, impacting test results.
What effect does long-term freezing at -80°C have on a sample?
Long-term freezing at -80°C* preserves the sample for extended periods but can still affect certain unstable analytes, leading to altered results.
How does delay in sample delivery affect the analysis?
Delay in delivery* can cause falsely lowered levels of unstable analytes, affecting the accuracy of the test results.
What are the key steps in internal quality control for laboratory testing?
The key steps include daily running of two control sera
Calculating their mean and standard deviation, Plotting them on control charts, and daily checking
Interpretation of the graphs.
What is proficiency testing in the context of external quality assurance?
Proficiency testing is a system designed to objectively assess the quality of results obtained by laboratories through an external agency.
What are the benefits of External Quality Assurance (EQA)?
Provide an inter-laboratory comparison
Allow participants to identify problems with their testing process (accuracy)
Investigate factors in test performance (methods, instruments, reagents, etc.)
Supplementing internal quality control procedures
Identify improvement opportunities.
