LMP299Y1 Lecture Notes - Urine Test Strip, Blood Sugar, Hyperlipidemia

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Published on 12 Apr 2013
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LECTURE TWO: LAB TESTS AND THEIR INTERPRETATION
CASE ONE
A blood specimen was taken from a 55-year old woman to check her serum potassium
The patient is on diuretics to control her hypertension but she is otherwise feeling well and the check-up did
not reveal any problems
The result came back 35mmol/L. (Normal is 3.5 5.0)
The physician was not worried. Why? Because there could have been a range of lab testing errors that could
have occurred
ANALYTICAL FACTORS
Methods ( or assays) for chemicals analysis may affect the final result
The appropriate choice is determined by the Laboratory Professionals
For example: sodium can be measured by flame photometry, electrodes or colorimetrically
Some methods measure sodium concentration and others sodium ion activity which depends on sodium in
solution and therefore water content
IDEAL METHODS
o Need little or no sample
o The sample must be easily obtained
o Give results instantly
o Cost nothing to do
o Accurate
o Precise
o Free from interference
o Appropriate range for measurement
o Sensitive for low concentrations
ANALYTICAL ERRORS
The methods in the clinical laboratory have some uncertainty in them
Not the “best” methods (due to expense and time) but are cheap, give results quickly and on small samples
Random Errors (or imprecision): small variations in ambient temperature, viscosity of fluids, electrical surges,
operator technique, etc
Systematic Errors (or bias): due to differences in standardization and calibration of the methods
PRECISION VS. ACCURACY
Precision: how well repeated measurements on the same sample agree with one another
- “Can you keep telling the same lies?”
Accuracy: how close a measurement is to the true value
- “Can you tell the truth?”
STATISTICAL QUALITY CONTROL
Laboratory staff uses Quality Control (QC) to define and monitor for error
A significant portion of tests in a North American laboratory are to do with Quality Assurance
In many clinical situations it is more important for a test to be precise than accurate
The best informed physicians are cognizant (fully informed) of the analytical performance of the laboratories
that they use
INTERFERENCES
Are constituents in the sample that alter the measurement of the desired analyte and lead to an erroneous
result
May be due to cross-reactivity (where molecules that are similar in structure react together), light interference
(optical interference), consumption of reagent, non-specific effects, etc.
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Common ones that can lead to false results:
- Hemolysis (where cells break open)
- Lipemia (a lot of lipid production)
- Bilirubinemia (icteria) (break down product of RBC metabolism)
- Drugs (invitro can affect your endogenous compounds)
Affect depends on the nature of assay
POST-ANALYTICAL FACTORS
A patient is either healthy or sick. The test should be able to help you tell these populations apart
In the management of disease and in prognostication we use the laboratory test to assess if the disease is
getting worse or better
Reference Interval (reference or “normal” range): is the range of values in health or disease though its usually
for healthy population in order to establish reference intervals
To perform a study:
- usually a healthy (or diseased) population is recruited
- laboratory test measurements are made
Interval defined by the central 95% of the values derived from the population
Usually the bottom 2.5% and the top 2.5 % are excluded
Not all measurements that are taken are not symmetric, they are skewed
IS THE NORMAL REALLY HEALTHY?
o Not all populations are the same
o Range of results may not have a Gaussian distribution
o No apparent disease does not mean healthy (e.g. serum cholesterol (don’t use reference intervals for
cholesterol) or body weight)
o Statistical requirement is 120 people (minimum)
o May be influenced by pre-analytical factors (age, sex, etc.); if different subgroup need to created
o The best reference range in health is the patient’s own when healthy!
RESULTS OUTSIDE NORMAL RANGE
This could mean:
1) The patient is sick
2) Patient is well but is a statistical outlier
3) Patient is well but is not of the age, sex, race group, etc. of the reference range population
4) Patient is well but is carrying out a proscribed activity such as jogging or eating before the sampling was
made (influences the result)
Note that the population’s reference range may not be the healthy reference range
CHANGE OR VARIATION?
Need to distinguish between health and disease
But how much imprecision in the analysis?
WHAT IS A REAL CHANGE?
When two tests are done, how much difference between the results can there be before the change is
significant?
- (total variance)2 = (analytical variance)2 + (biological variance)2
- 95% probability limit = 2.80 x total variance
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