Kleihauer–Betke test

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Revision as of 13:10, 16 November 2021 by Mikael Häggström (talk | contribs) (Quantification: format)
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Author: Mikael Häggström [note 1]
The Kleihauer–Betke test stains fetal red blood cells (cells containing HbF) dark reddish-pink, while adult red blood cells will be white to light pink.

Collection

EDTA-containing-tube.

Criteria for fetal cells

KB stain with green marks at cells counted as fetal (HbF) cells, and red marks at incompletely colored cells at top and a too small cell at right.

A fetal blood cell should be:

  • Stained more than approximately half of what is seen in control.
  • Not be nucleated or too big (white blood cell are generally also stained).
  • Not be too small.

Semi-quantification

This is done for Rh-negative mothers, with the following main indications:

  • Fetal demise
  • Bleeding due to placenta previa
  • Placental abruption

10HPFs (in 40x) are scanned, and fetal RBCs are counted (cells per 10 HPFs, not average per HPF), and classified as:

  • 0 - Negative
  • 1 - Rare
  • 2-5 - Few
  • 6-10 - Moderate
  • >10 - Abundant

Quantification

This is done for Rh-negative mothers to estimate the number of Rho(D) immune globulin vials to administer.

2000 cells are counted, in order to give a percentage calculated as:

  • Fetal RBCs (given in%) = (Fetal RBC count) / (Total cell count) *100

Alternatively, an acceptable estimation can be done by using a micrograph (or a microscopy grid) to estimate the mean number of cells in a certain area, and using the same mean to estimate the number of cells in equally sized areas:
1. Count cells (both adult and fetal) until reaching 100 cells (including each cell in square by square if using a microscopy grid). Take note of how large micrograph area (or how many grid squares) were counted (here designated as x amount), and how many fetal RBCs were counted.
2. Pick another random location (you may randomize again if it is of a significantly different cell density, but do not let the number of positive cells influence your decision). Count the total number of cells in the same area size (or same x number of squares), and how many of them are fetal RBCs.
3. Pick another location again, and count the number of cells in the same area size, and how many of them are fetal RBCs.

  • If a count of 200-300 cells only shows 0 or 1 stained cell, there only needs to be 1 vial of 300 micrograms Rho(D) immune globulin, and the rest of the steps in this section can be skipped.
Standard
deviation
Count cells
in following
number of areas
Up to 6 3
7 4
8 5
9 6-7
10 8
11 10
12 12
  • Calculate how much the count for the second and third areas deviated from 100, and take the average thereof, which is the standard deviation. If the standard deviation is higher than 12, count a total of 2000 cells regardless of areas and calculate as per formula above, and the rest of the steps can be skipped.
  • Use the table at right to estimate how many areas in total you need to count in order to have a mean number of cells per area with an acceptable confidence interval.

3. Calculate the average of the number of cells per area (or per x number of squares), and assume that number for the rest of the counting.
4. In additional areas, only count the number of fetal cells per area (or x number of squares), until presumably exceeding a total of 2000 cells counted.

Fetal RBCs (given in%) = (Fetal RBC count) / (Presumable total cell count) *100

Example:

Calculation of number of vials

Assuming that a vial of 300 micrograms of Rho(D) immune globulin will protect against 30 mL of fetal blood, the number of vials needed to compensate for the fetal-maternal transfusion is calculated as following, rounded up,[1] or rounded to the closest full number and then adding 1.[2]

Number of vials = Fetal RBCs in% * 1.7

Notes

  1. For a full list of contributors, see article history. Creators of images are attributed at the image description pages, seen by clicking on the images. See Patholines:Authorship for details.

Main page

References

  1. Diann M. Krywko. Kleihauer Betke Test. StatPearls, National Center for Biotechnology Information. Last update: Last Update: January 20, 2020.
  2. Practice at Danbury Hospital, Danbury, Connecticut, New England.

Image sources