Blood volume analysis can distinguish true anemia from hemodilution in critically ill patients

J Trauma. 2011 Mar;70(3):646-51. doi: 10.1097/TA.0b013e31820d5f48.


Background: Peripheral hematocrit (pHct) is traditionally used as a marker for blood loss. In critically ill patients who are fluid resuscitated, pHct may not adequately represent red blood cell volume (RBCV). We hypothesize that the use of pHct alone may overestimate anemia, potentially leading to unnecessary interventions.

Methods: Patients admitted to the intensive care unit underwent blood volume analysis. Serial blood samples were collected after injection of I-albumin. Samples were then processed by the Blood Volume Analyzer-100. RBCV and total blood volume (TBV) were calculated using the directly measured plasma volume (PV) and pHct. A computed normalized hematocrit (nHct) adjusts pHct to the patient's ideal blood volume.

Results: Thirty-six patients (21 men), aged 49.8 years ± 18.4 years, Acute Physiology And Chronic Health Evaluation II score 14.9 ± 8.1, and injury severity score 29.4 ± 12.4 had 84 blood volume analyses performed on 3 consecutive days. Using ratios of TBV compared with ideal TBV, patients were stratified into three separate groups: hypovolemic (16 of 84), normovolemic (23 of 84), and hypervolemic (45 of 84). Mean differences between pHct and nHct in each group were 4.5% ± 3.1% (p≤0.01), 0.0% ± 1.2% (p=0.85), and -6.5% ± 4.1% (p≤0.01), respectively. pHct, when compared with nHct, diagnosed anemia (Hct <30) nearly equal within the hypovolemic and normovolemic groups. However, pHct overdiagnosed anemia in 46.7% of hypervolemic patients.

Conclusion: Use of blood volume analysis in critically ill patients may help to distinguish true anemia from hemodilution, potentially preventing unnecessary interventions.

MeSH terms

  • Anemia / diagnosis*
  • Blood Volume*
  • Chi-Square Distribution
  • Critical Illness*
  • Female
  • Fluid Therapy
  • Hematocrit
  • Hemodilution
  • Humans
  • Indicator Dilution Techniques
  • Male
  • Middle Aged
  • Sensitivity and Specificity
  • Statistics, Nonparametric