Learn the importance of auto diff analysis to diagnose diseases accurately and efficiently. Learn more here.

Learn the importance of auto diff analysis to diagnose diseases accurately and efficiently. Learn more here.

The complete blood count (CBC) with autodifferential (Auto Diff) is a fundamental test used in medical practice to evaluate a patient’s overall health and diagnose a number of medical conditions. This comprehensive blood test provides valuable information about the different types and numbers of blood cells present in a person’s bloodstream.

The Auto Diff CBC measures several key blood components, including

  1. Red blood cells (RBCs): These cells carry oxygen throughout the body and help determine whether a patient has anemia or other blood disorders.
  2. White blood cells (WBCs): Responsible for fighting infections and maintaining a healthy immune system, white blood cell counts can indicate the presence of infections or diseases.
  3. Platelets: Fragments of cells involved in blood clotting, platelet levels may be indicative of bleeding disorders or clotting abnormalities.
  4. Hemoglobin (Hb): It is the protein in red blood cells that transports oxygen. Hemoglobin levels help evaluate a patient’s oxygen-carrying capacity.
  5. Hematocrit (Hct): Proportion of red blood cells in total blood volume. Measuring hematocrit helps diagnose diseases such as anemia and dehydration.

Note: The Auto Diff CBC also includes a differential white blood cell count, which analyzes the different types of white blood cells present, such as neutrophils, lymphocytes, monocytes, eosinophils, and basophils. This breakdown helps healthcare professionals identify specific infections, inflammatory responses, and other underlying conditions.

Understanding the Complete Blood Count (CBC)

An automatic differential blood count refers to a complete blood count test that includes an automatic differential, which counts and analyzes different types of white blood cells. This information is crucial for diagnosing and managing infections, inflammations, and immune system disorders. The CBC with Automatic Differential report typically provides a comprehensive breakdown of specific blood cell counts and related parameters.

Key components of an autodif blood count:

  • Red blood cells (RBC): They are responsible for transporting oxygen throughout the body. Abnormalities in the red blood cell count may indicate anemia or other blood disorders.
  • White blood cells (GB): They play a crucial role in the fight against infections and the defense of the organism against foreign substances. A high or decreased count of white blood cells can mean infection, allergies or even certain types of leukemia.
  • Platelets: They are essential for blood coagulation and excessive hemorrhages prevention. A low platelet count can cause an increase in bleeding, while a high count can increase the risk of blood clots.

The results of the hemogram with sel f-defusion are usually shown in the form of a table, which provides a global vision of the different types of blood cells and their counts. It is important that health professionals analyze these results together with the medical history and patient’s symptoms to perform a precise diagnosis and determine the proper treatment.

The periodic monitoring of the hemogram with Auto DIFF can help monitor the changes in blood cell counts over time and help evaluate the effectiveness of certain treatments or interventions. By understanding and interpreting the results of a hemogram, health professionals can obtain valuable information about the patient’s general health status and identify any underlying medical condition that may require more research or treatment.

Component Normal range Interpretation
Red Bloods (GR) 4. 5-5. 5 million cells/mcl (men) 4. 0-5. 0 million cells/mcl (women) Anomalies in the GR count can indicate anemia or blood disorders.
White blood cells (WBC) 4, 500-11, 000 cells/mcl A high or reduced count of white blood cells may indicate infections, allergies or certain types of leukemia.
Platelets 150, 000-450, 000 cells/mcl A low platelet count can cause an increase in bleeding, while a high count can increase the risk of blood clots.

The Role of Automated Differential Analysis

The automated differential analysis allows a more precise and effective evaluation of the patient’s white blood cell count compared to the manual differentiation carried out by laboratory technicians. The automated process uses advanced technologies and algorithms to classify and count the different types of white blood cells, such as neutrophils, lymphocytes, monocytes, eosinophils and basophils.

Automated differential analysis uses specialized instruments, such as flow cytometers or automated hematological analyzers, to detect and differentiate the different types of white blood cells. These instruments incorporate lase r-based technology and fluorescent dyes to measure and analyze the characteristics of individual cells.

The results of automated differential analysis are usually presented in tabular format, allowing for a clear and organized representation of the different types of WBC and their corresponding figures. This table usually includes columns for each type of white blood cell and their respective percentages and absolute counts.

In addition to providing valuable information about the types and numbers of white blood cells, automated differential analysis can also help in the diagnosis and monitoring of various medical conditions. Abnormalities in white blood cell differential values may indicate underlying infections, inflammation, autoimmune disorders, or even certain types of cancer.

  1. Greater accuracy and efficiency compared to manual differentiation
  2. Uses advanced technologies and algorithms for accurate classification and counting
  3. Results presented in tabular format for ease of interpretation
Type of white blood cells Percentage absolute count
Neutrophils fifty% 5, 000 cells/µL
Lymphocytes 40% 4, 000 cells/µL
Monocytes 6% 600 cells/µL
Eosinophils 3% 300 cells/µL
Basophils 1% 100 cells/µL

Author of the article
Dr.Greenblatt M.
Dr.Greenblatt M.
Medical oncologist at the Robert Larner College of Medicine, MD, at the University of Vermont

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