Tabuk University

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Tabuk University

• Faculty of Applied Medical Sciences
• Department Of Medical Lab. Technology
• 3rd Year Level 5 AY 1434-1435

Hematology 2, MLT 307
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Quality Assurance and Automation in Hematology

• By/
• Dr WalidZAMMITI Phd M.Sc MLT

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Objectives

• Describe the electrical impedance and light
  scatter principles for performing cell counts.
• Utilize quality control procedures to determine
  if patient results are acceptable.
• Explain histograms and their indications.
• Concentrate on some parameters and indices.
• Identify the major components of a quality
  assurance program.
• Be able to distinguish between quality assurance
  quality control.
• Define and give examples of each of the following
  terms Accuracy-Calibration-Control-Standard-Prec
  ision.
• Understand the concepts of internal external
  control.

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Quality system begins and ends with the patient
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Quality Assurance vs. Quality Control
Quality Assurance
Quality Control
An overall management plan to guarantee
the integrity of data (The system)
A series of analytical measurements used to
assess the quality of the analytical data (The
tools)
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Quality Assurance in Hematology

• QA includes all aspects of laboratory activities
  that affects the results produced, from the
  choice of methods, to the education of personnel,
  to the handling of specimens and reporting
  results.
• The real purpose of QA activities is to determine
  how correct or incorrect the results emanating
  from the lab are, and to allow those managing the
  lab to determine whether or not the lab is
  fulfilling its functions satisfactorily.

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QA in Haematology Laboratory

• QA in haematology lab is intended to ensure the
  reliability of the lab tests.
• The objective is to achieve precision and
  accuracy
• 4 components of QA programme
• 1 ) Internal Quality Control ( IQC )
• 2 ) External Quality Control ( EQC )
• 3 ) Standardization
• 4 ) Proficiency surveillance

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Accuracy vs. Precision

• Precision
• How well a series of measurements agree with each
  other Is the closeness of agreement between
  independent test results obtained under
  stipulated conditions.

• Accuracy
• How well a easurement agrees with an accepted
  value is the closeness of the agreement between
  the result of a measurement and a true value of
  the measurand.

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Accuracy vs. Precision
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Internal Quality Control

• Internal Quality Control Internal quality control
  is set up within a laboratory to monitor and
  ensure the reliability of test results from that
  laboratory.
• The primary tool for internal quality control is
  called a control. A control is a specimen with a
  predetermined range of result values, called
  control values, that is processed in the same
  manner as a patient sample.
• Control samples are processed with each series or
  run of patient samples.
• If the result of a test on a control sample is
  different from its known value, this indicates a
  problem in the equipment or the methods being
  used.

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External Quality Control ( EQC )

• is the objective evaluation by an outside agency
  of the performance by a number of laboratories on
  material which is supplied specially for the
  purpose
• is usually organized on a national or regional
  basis
• analysis of performance is retrospective
• the objective is to achieve comparability with
  results of other labs.

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Standardization

• Refers to both materials and methods.
• A material standard or reference preparation is
  used to calibrate analytic instruments and to
  assign a quantitative value to calibrators.
• A reference method is an exactly defined
  technique which provides sufficiently accurate
  and precise data for it to be used to assess the
  validity of other methods

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Proficiency surveillance

• Implies critical supervision of all aspects of
  laboratory tests collection, labelling,
  delivery, storage of specimens before the tests
  are preformed and of reading and reporting of
  results.
• Also includes maintenance and control of
  equipment and apparatus.

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Control
 What is a Control? QC programs require the same sample to be tested every day testing is done. This type of sample is called a control. Controls, which are often purchased from manufacturers, use a human base to ensure the analyses being tested parallel human ranges. Manufacturers pool together many human blood samples to create the large volume needed for a lot number of control

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Tools for Validation of QC results Control
Charts A Control Chart depend on the use of IQC
specimens and is developed in the following manner
3 sd
2 sd
1 sd
Target value
-1 sd
-2 sd
-3 sd
Assay Run
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• Control Charts
• Samples of the control specimen are included in
  every batch of patients specimens and the
  results checked on a control chart
• Check precision it is not necessary to know the
  exact value of the control specimen
• Value has been determined reliably by a reference
  method, the same material can be used to check
  accuracy or to calibrate an instrument
• Controls with high, low and normal values should
  be used
• Advisable to use at least one control sample per
  batch even if the batch is very small
• The results obtained with the control samples can
  be plotted on a chart

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How to calculate SD

• 1. Get the Mean.
• 2. Get the deviations. (each value minus the
  mean)
• 3. Square these.
• 4. Add the squares.
• 5. Divide by total numbers less one.
• 6. Square root of result is Standard Deviation

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Types Of Errors

• An error which varies in an unpredictable manner,
  in magnitude and sign, when a large number of
  measurements of the same quantity are made under
  effectively identical conditions.

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Systematic vs.Random Errors

• Systematic Error
• Avoidable error due to controllable variables in
  a measurement.

• Random Errors
• Unavoidable errors that are always present in
  any measurement. Impossible to eliminate

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Random Error

• Random errors create a characteristic spread of
  results for any test method and cannot be
  accounted for by applying corrections. Random
  errors are difficult to eliminate but repetition
  reduces the influences of random errors.
• Examples of random errors include errors in
  pipetting and changes in incubation period.
  Random errors can be minimized by training,
  supervision and adherence to standard operating
  procedures.

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Random Errors
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Systematic Error

• An error which, in the course of a number of
  measurements of the same value of a given
  quantity, remains constant when measurements are
  made under the same conditions, or varies
  according to a definite law when conditions
  change.
• Systematic errors create a characteristic bias in
  the test results and can be accounted for by
  applying a correction.
• Systematic errors may be induced by factors such
  as variations in incubation temperature, blockage
  of plate washer, change in the reagent batch or
  modifications in testing method.

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Systematic Errors
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• Automation in Haematology

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Automated techniques of blood counting

• Semi-automated instruments
• Require some steps, as dilution of blood samples
• Often measure only a small number of variables
• Fully automated instruments
• Require only that an appropriate blood sample is
  presented to the instrument.
• They can measure 8-20 variables including some
  new parameters which do not have any equivalent
  in manual methods.

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• The accuracy of automated counters is less
  impressive than their precision.
• In general automated differential counters are
  favourable to the manual in 2 conditions
• Exam of normal blood samples
• Flagging of abnormal samples

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• CBC Complete Blood Count
• The complete blood count is performed as an
  automated procedure. A sample of blood is placed
  in an analyzer and the cells are sorted by a
  laser according to size, granularity, and shape.

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(No Transcript)
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• Parameters
• WBC Total white blood cells
• RBC Red blood cell count
• HGB Hemoglobin concentration
• HCT Hematocrit (PCV)
• MCV Mean Cell Volume
• MCH Mean Cell Hemoglobin
• MCHC Mean Cell Hemoglobin Concentration
• PLT Platelets count
• NEUT Percentage Neutrophil count
• LYMPH Percentage Lymphocyte count
• MONO Percentage Monocyte count
• EO Percentage Eosinophil count
• BASO Percentage Basophil count
• NEUT Absolute Neutrophil Count
• LYMPH Absolute Lymphocyte Count
• MONO Absolute Monocyte Count
• EO Absolute Eosinophil Count
• BASO Absolute Basophil Count

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Examples of Haematology analysers

• AcT 5diff (Beckman Coulter )
• SE 9000, KX21, XE 2100 (Sysmex)
• Advia 60 (Bayer)
• Cell-Dyn 3500 ( Abott)

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When to Calibrate

• You should calibrate your instrument
• At installation.
• After the replacement of any component that
  involves dilution characteristics or the primary
  measurements (such as the apertures).
• When advised to do so by your service
  representative.

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Flagging

• Condition flags
• Describes cell population
• normal
• abnormal
• WBC Suspect flags
• Blasts
• Immature Grans/Bands 1
• Immature Grans/Bands 2
• Variant lymphocytes
• Review Slide

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More Flagging

• RBC Suspect flags
• NRBCs
• Macrocytic RBCs
• Dimorphic RBC population
• Micro RBCs/RBC fragments
• RBC agglutination
• Definitive Flagging
• Based on predetermined lab limits
• Provide information for review

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Histograms

• RBC, PLT, and WBC plotted on histogram
• X-Axis
• Cell size in femtoliters (fL)
• Y-Axis
• of cells

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RBC Histogram As A Quality Control Tool
INDICATOR PROBABLE CAUSE COMMENT
Left of curve does not touch baseline Schistocytes and extremely small red cells Review smear CBC and Platelet histogram
Bimodal peak Transfused cells, therapeutic response Review Smear
Right portion of curve extended Red cell autoagglutination Review CBC Smear
Left shift of curve Microcytes Review smear CBC
Right shift of curve Macrocytes Review smear CBC
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Platelet Histogram As A Quality Control Tool
INDICATOR PROBABLE CAUSE COMMENT
Peak or spike at left end of histogram (2-8 fl) Cytoplasmic fragments Review smear
Spike towards right end of histogram Schistocytes, microcytes, giant platelets Review smear CBC (? MCV ? RDW) (? MPV ? PDW)
Bimodal peak Cytoplasmic fragments Review smear
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Histograms - WBCs

• WBC Distribution with three individual peaks and
  valleys at specific regions representing the
  lymphocytes, monocytes, and granulocytes.

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WBC Histogram As A Quality Control Tool
INDICATOR PROBABLE CAUSE COMMENT
Trail extending downward at extreme left, or lymph peak not starting at baseline NRBC, Plt clumping, unlysed RBC, cryoproteins, parasites Review smear and correct WBC for NRBC
Peak to the left of lymph peak or widening of lymph peak towards left NRBC Review smear correct WBC for NRBC
Widening of lymph peak to right Atypical lymphs, blasts, plasma cells, hairy cells, eosinophilia, basophilia Review smear
Wider mono peak Monocytosis, plasma cells, eosinophilia, basophilia, blasts Review smear
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WBC Histogram As A Quality Control Tool
INDICATOR PROBABLE CAUSE COMMENT
Elevation of left portion of granulocyte Left Shift Review smear
Elevation of right portion of granulocyte peak Neutrophilia Review smear
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RDW-SD
RDW is an actual measurement of the width of the
erythrocyte distribution curve. It is a
measurement of Anisocytosis. May increase before
MCV becomes abnormal Reference values female
36.4 46.3 fL male 35.1 43.9 fL It is
increased in many types of anemias to indicate
the variation in red cell sizes.
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RDW-CV
The coefficient of variation (CV) is defined as
the ratio of the standard deviation (x), to the
mean (µ) Cv x/µ Sometimes known as relative
standard deviation. Reference values female
11.7 14.4 male 11.6 14.4
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MCV MEAN Cell VOLUME

• M.C.V. Hematocrit X 10
• RBC in millions/µl
• Normal values Men women
• 82 97 fl (femtoliters) cubic
  microns
• Increased Macrocytes
• Decreased Microcytes

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MCH Mean Cell Hemoglobin

• M.C.V. Hemoglobin g/dl X 10
• RBC in millions/µl
• Normal values Men women
• 27 32 pg (pico grams)
• Increased Hyperchromic
• Decreased Hypochromic

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MCHC Mean Cell Hb Concentration

• M.C.V. Hemoglobin g/dl X 100
• Hematocrit
• Normal values Men women
• 30 34 g/dl
• Increased Hyperchromic
• Decreased Hypochromic

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Other Hematology Machines

• Coagulometers
• - Used in Hemostasis studies, and the Endpoint
  Detection depends on Mechanical, Optical
  (Photo-optical , Nephelometric , Chromogenic or
  Immunologic), Electrochemical principles.
• ESR machines in 30 minutes.
• Leucocytes automated Differential Counters
• Using cytochemical or image recognition methods.

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• Thank you