1. Platelet Counts Dr Kunal Sehgal, M.D. Associate Consultant
PGIMER, Chandigarh
Tata memorial Hospital
PD Hinduja Hospital
Platelet Counts
Dr Kunal Sehgal, M.D.
Associate Consultant
Hematology Laboratory
Department of Lab Medicine
PD Hinduja National Hospital and MRC

2. Platelets – Historical Perspective
1882- Platelets recognised as distinct corpuscles – Italian pathologist
Giulio Bizzozero
Manual Phase Contrast Microscopic Method using Neubauer chamber - ICSH - Gold Standard
Semi- Automated and Fully Automated Counters
1981- Hydrodynamically focused whole blood aperture IMPEDANCE counter
1985- OPTICAL Platelet Counts
Early 1990s- Flow cytometric methods based on CD41/61
2001- Flow Cytometric RBC platelet Ratio – the new International reference Method (IRM)
Briggs et al. Continuing developments with the automated platelet count. Int. Jnl. Lab. Hem.2007,29,77-91.

3. Manual Platelet Counts- The Old Gold Standard
Laborious
Time Intensive
Subjective
High Inter- observer CVs of %
Briggs et al. Continuing developments with the automated platelet count. Int. Jnl. Lab. Hem.2007,29,77-91.

4. International Flow Reference Method The New Gold Standard
RBC/Platelet Ratio Method
Dual Platform Method
Absolute Platelet Count=
Platelet events X RBC count
RBC events (Automated Cell Analyzer)
Platelets
CD 41/61
RBC
ISLH Task Force, Am J Clin Pathol 115, (2001)

5. Peripheral Blood Smear (Platelet count check only)
Platelets to be counted in a region where RBCs and platelets are well dispersed.
Atleast 10 oil immersion fields to be counted (more in lower counts)
Average no. of platelets in a field multiplied by is the approximate platelet count

6. Problems of Peripheral Smear Platelet Check
Platelet Clumps
Platelet Satellitism on WBCs
Poor Smearing
Highly subjective

9. Peripheral Blood Smear (Platelet count check only)
Eg :
a) 10 fields – 45 platelets
Avg. plt per field is 4.5
Approximate Platelet count=4.5x10000=45000
b) 20 fields – 40 platelets
Avg. plt per field is 2
Approximate Plt count=2x10000=20000

12. ARTEFACTS

13. Automated CBC Analysers
Impedance principle
Optical Principle
Counters count many more cells and hence more reproducible results
Improved C.V. - typically less than 5%

14. Impedance Principle Coulter Principle or Resistance detection method
Cells suspended in an elecrolyte solution
Change in electric impedance impedance signal
Impedance signal Directly proportional to the volume of the cell

15. CBC Histograms

16. Normal Platelets histogram
Giant Platelets histogram

17. Problems with Impedance Counts

18. Optical Principle Two dimensional Light Scatter
Two angles of laser ight scatter are measured
Light Scatter- 2-3°C- volume (plt size)
Light Scatter- 5-15°C- refractive index (plt density)
Rbc fragments have a different RI as compared to platelets and hence can be separated
Optical Fluorescence platelet counting
Size vs. Fluorescence plot (Polymethine Dye)
RBC fragments do not contain RNA while giant platelets and immature forms contain RNA and are called reticulated platelets
These are easily separated from microcytic RBCs and fragments

19. Advantages of Optical Platelet Counting
Jaldeep Bhansali 19

20. Optical Platelet Enumeration
Giant PLT
Microcytic RBC

21. CASE STUDIES

22. Case Study 1 Automated CBC -Platelet count – 1.05lacs
PS- many large platelet clumps
What do you do?
Peripheral Smear – comment –
Platelets are seen in many clumps. Platelets are adequate on smear (>1lac). Kindly repeat CBC for accurate platelet count if clinically indicated.

23. Case Study 2 Automated CBC -Platelet count – 2.35lacs
PS- many platelet clumps
What do you do?
Peripheral Smear – comment –
Platelets are adequate on smear. Platelets are also seen in clumps.

24. Case Study 3 - 31/F,Blood Donor, East Indian Origin,
Normal Hb and WBC, Impedance Plt- 134, Platelet O –162, Morphologically- Many Giant platelets

25. Case Study 4- CBC Histogram

26. Case Study 4- continued…

27. Platelet Clumps in WBC Ghost Area
Ghost area in a case of platelet clumps
Ghost area in a normal CBC

28. Case Study 5 72 year old male
Hemogram revealed thrombocytopenia (54,000/cmm)

31. Based on platelet histogram findings, a
peripheral smear examination was done
Giant platelets were seen
Platelet clumps seen
The sample contained adequate platelets,
however we got spurious results on
automated analyzer

32. EDTA induced Pseudothrombocytopenia
Citrated PB Sample –Platelet count lacs
Peripheral smear showing many
platelet clumps (10x).

33. Case Study 6 Peripheral smear check- Rule out micro clots in sample
55/M A know case of Acute Leukemia
Hb -7.5g% WBC x103 /ul Platelet count- 18 x103 /ul
What do you do next?
Peripheral smear check-
Rule out micro clots in sample
Look for fibrin strands and platelet clumps on slide
Do a peripheral smear estimation of platelet counts
Be aware of the clinical decisions that depends on your result- i.e know the transfusion threshold levels
Discuss case with clinician if required

34. Case study 7- Acceptable C.V.
Case Scenario 1
First run, platelet count
Second run, platelet count –
A difference of Is this Acceptable? Yes- the difference is only 4%
Case Scenario 2
First run platelet count
Second run platelet count – 16000
A difference of Is this Acceptable?
NO- the difference is of 33% and will have a huge clinical impact!

35. Any Questions ?