Development and validation of a mathematical algorithm for quantifying preoperative blood volume by means of the...

Area of Science:

• Physiology
• Medical Technology
• Surgical Research

Background:

• Interindividual variability in blood volume (BV) is significant.
• Accurate preoperative BV estimation is crucial for patient management.
• Existing methods for BV assessment can be complex or invasive.

Purpose of the Study:

• To develop and validate a method for estimating preoperative blood volume (BV).
• To utilize the decrease in large-vessel hematocrit (HK(LV)) during acute normovolemic hemodilution (ANH) as an estimation tool.
• To provide a practical bedside method for BV assessment.

Main Methods:

• Acute normovolemic hemodilution (ANH) was performed in 39 patients (Group 1) and 10 patients (Group 2).
• Measurements included plasma volume, red cell volume, and large-vessel hematocrit (HK(LV)) before and after ANH.
• A mathematical algorithm was developed to estimate preoperative BV based on HK(LV) changes and blood removed.

Main Results:

• In Group 1, estimated BV showed a mean difference of 5.14% (p > 0.05) compared to measured BV.
• In Group 2, estimated BV was -0.53% (p > 0.05) different from measured BV, with high correlation (r = 0.94).
• The algorithm correctly identified patients with exceptionally low and high preoperative BV.

Conclusions:

• Changes in large-vessel hematocrit (HK(LV)) during ANH provide a reliable estimation of preoperative blood volume (BV).
• This method serves as a valuable and accurate "bedside" tool for assessing preoperative BV.
• The developed algorithm demonstrates clinical utility in diverse patient BV ranges.