Diagnostic clinical chemistry Prepared By : Ikram M. Hmaid Mr.Naser Abu. Sha’ban

Remember Chemistry panel

Quality Control:- Quality Assurance:- In a medical laboratory, it is a statistical process used to monitor and evaluate the analytical process that produces patient results. The process of detecting errors Quality Assurance:- The overall program that ensures that the final results reported by the laboratory are correct i.e. It is the systems or procedures in a place to avoid errors occurring QC results are used to validate whether the instrument is operating within pre-defined specifications, inferring that patient test results are reliable. Once the test system is validated, patient results can then be used for diagnosis, prognosis, or treatment planning. For example, when a patient’s serum is assayed (tested) for potassium, the test result tells us how much potassium (concentration) is present in the blood. This result is then used by the physician to determine whether the patient has a low, normal or high potassium.

What are the potential consequences of unreliable performance ? A good laboratory will have both these complementary systems working together to ensure the reliability of the test results and ultimately to give best patient care. The results of patient testing should never be released if the Q.C. results for the test run doesn’t meet the lab target values. What are the potential consequences of unreliable performance ? The patient could be misdiagnosed There could be delays in treatment. The cost to the health care system increases as repeat or other confirmatory tests will have to be run. There are a huge variety of potential errors which can affect the quality of the laboratory results.

Regular Testing Good laboratory practice requires testing normal and abnormal controls for each test at least daily to monitor the analytical process. If the test is stable for less than 24 hours or some change has occurred which could potentially affect the test stability, controls should be assayed more frequently. Regular testing of quality control products creates a QC database that the laboratory uses to validate the test system. Validation occurs by comparing daily QC results to a laboratory-defined range of QC values.

Let’s assume the measured value of K+ in a patient’s serum is 2 Let’s assume the measured value of K+ in a patient’s serum is 2.8 mmol/L . “ This result is abnormally low and indicates an inappropriate loss of potassium “ . It could be possible that the instrument is out of calibration and the patient’s true potassium value is 4.2 mmol/L – a normal result. But how does the person performing the test know that this result is truly reliable? The question of reliability for most testing can be resolved by Regular use of quality control materials and statistical process control.

Quality Control used to monitor the accuracy and precision of the assay How correct your result is The reproducibility of your results. The lower the SD the better the Precision. Quantified by measuring the Standard Deviation (SD) of the set of results.

Which is more Precise ? Potassium SD = 0.1 mmol/L Sodium SD = 2.0 mmol/L A %CV takes into consideration the magnitude of the overall result.

Potassium %CV = (0.1 / 5.0) x 100% = 2.0% Sodium %CV = (2.0 / 140) x 100% = 1.4% Sodium has the better CV and in this example is performing better than potassium.

How can Analytical Quality be Controlled ? 1. Internal Quality Control (IQC). daily monitoring of quality control sera 2. External Quality Assessment (EQA). comparing of performance to other laboratories. Laboratories with good Quality Assurance Programmes will generally adopt two separate but complementary systems Laboratories with good Quality Assurance Programmes will generally adopt two separate but complementary systems Firstly, Internal Quality Control (IQC) where analytical performance is monitored by analysing Quality Control Sera with known values, on a daily basis.    Secondly, External Quality Assessment (EQA) where analytical performance is assessed by comparing the laboratory’s performance with that of other laboratories.

What are the Options ? 1. Unassayed serum: the cheaper option ! but the laboratory must establish its own ranges cannot be used to assess accuracy ! no externally assigned target values 2. Assayed serum: with predetermined targets and ranges established by the manufacturer. There are two types of serum that are commercially available:- Unassayed serum which is supplied with little or no information. This is a cheaper option but the laboratory must establish its own acceptable ranges and cannot be used to assess accuracy as it has no externally assigned target value. The other option is to use an assayed serum which has predetermined target values and ranges established by the manufacturer.

Levey Jennings Chart (L-J chart) A Levey Jennings Chart, is plotted with lines representing the mean and the SDs above and below, against a suitable time interval. Most laboratories will run a series of quality control sera, covering the full clinical range and not rely on a single control with only normal values. A chart will be established for each analyte and each level of control run. The values obtained are plotted on the chart allowing a rapid visual assessment of performance to be made. The laboratory needs to document that quality control materials are assayed and that the quality control results have been inspected to assure the quality of the analytical run. This documentation is accomplished by maintaining a QC Log and using the Levey-Jennings chart on a regular basis.

When the results are plotted, an assessment can be made about the quality of the run. The technologist/technician performing the test should look for systematic error and random error

1st : Random Error Note :- 2nd : Systematic Error Technically, random error is any deviation away from an expected result. For QC results, any positive or negative deviation away from the calculated mean is defined as random error. Note :- There is acceptable(or expected) random error as defined and quantified by standard deviation. There is unacceptable (unexpected) random error that is any data point outside the expected population of data (e.g., a datapoint outside the ±3s limits). 2nd : Systematic Error The change in the mean may be gradual and demonstrated as a trend in control values or it may be abrupt and demonstrated as a shift in control values.

Trend Shift Trending may include: Shifts may be caused by: Sudden failure or change in the light source Change in reagent formulation Change of reagent lot Major instrument maintenance Sudden change in incubation temperature (enzymes only) Change in room temperature or humidity Failure in the sampling system Failure in reagent dispense system Inaccurate calibration/recalibration Trending may include: Deterioration of the instrument light source Gradual accumulation of debris in sample/reagent tubing or on electrode surfaces Aging of reagents Gradual deterioration of control materials Gradual deterioration of incubation chamber temperature (enzymes only) Gradual deterioration of light filter integrity Gradual deterioration of calibration

1- Normal curve Excellent performance with a nice tight grouping of results (good precision) with a random spread of results either side of the 140mmol/L target (good accuracy) There is no evidence for bias or any type of error

2- An example of slight bias Both accuracy and precision are within acceptable limits, however there would perhaps be a tendency towards a slight positive bias over the last few results.

3- An example of positive bias Good precision but a definite positive bias – check calibration value or cuvette temperature.

4- Systematic error - Trend There is a definite downward trend – check reagent and control stability or the lamp.

5- Systematic error - Shift A distinct pattern evident – it is indicative of a change in shifts in a routine laboratory.

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