Estimating intraoperative blood loss is a crucial element of surgery, minimizing chances of anemia, preventing hemodynamic instability or dangerously low organ perfusion, and maximizing donor blood reserves. Not only does this avoid tapping into the tightly limited blood bank supplies in the United States ¹, but this also greatly reduces the risk of severe adverse clinical outcomes ². To this end, a slew of methods have been developed for intraoperative patient blood loss estimation.

First, a series of rather crude, easy-to-implement methods can be used to assess blood loss. Simple visual assessment methods are the least invasive and most frequently used of these ^3,4. However, despite the development of pictorial guides, the visual assessment of blood loss remains relatively inaccurate across surgical spheres ^5,6 and is particularly prone to human bias and errors. In contrast, gravimetric methods rely on subtracting instruments’ dry weights from the weights of surgical material contaminated with blood, thereafter using a conversion rate of 1 gram = 1 mL of blood to estimate the volume of blood lost to the instruments. While more accurate than visual assessment methods, such techniques remain inconsistently effective. In particular, in obstetric surgical contexts, the loss of amniotic fluid may confound results ⁷. A more precise variation of gravimetric methods mostly used in the field of obstetrics, direct methods rely on a calibrated collection bag harboring all mixed liquids lost during surgery. While easy to implement, of particular relevance in resource-poor settings, this method remains rather approximative as well ⁸.

A number of more advanced algorithmic methods can also be used, including, first, various mathematical approaches. Currently, three main formulas are used to calculate total blood loss, incorporating patient height, weight and sex ^9,10. However, these methods have been shown to reproducibly overestimate blood loss. More recently, Gauss Surgical Inc. ¹¹ developed a smartphone application based on a Triton system to estimate blood loss based on a colorimetric analysis of photographs of surgical sponges or gauze ¹². The technique filters out the effects of non-blood components to assess the hemoglobin mass in the surgical sponge; blood loss can be deduced by comparing postoperative to preoperative hemoglobin levels. Overall, this system has been demonstrated to work against a broad spectrum of sponge saturations, resulting in accurate blood loss estimation.

Finally, a slew of other techniques have also been fleetingly attempted in recent years. These include ultrasound of the inferior vena cava, contrast-enhanced ultrasound, and near-infrared spectroscopy – to no avail ¹³. Overall, a large, recent meta-analysis confirmed substantial case-by-cases variation across all assessed blood loss estimation techniques and very little consistency across methods ¹⁴.

Peri- and intraoperative patient treatment and transfusion decisions are critically dependent on the precise monitoring of blood loss. While visual and gravimetric blood loss estimation techniques tend to be quite inaccurate, colorimetric methods are precise and enable real-time assessment. However, given the importance of estimated blood loss in a variety of contexts, including for the generation of perioperative prognostication models, research should continue to support, and clinicians should eventually strive for, the ubiquitous adoption of practical and reproducible methods for blood loss estimation.

References

1. Nation confronts severe blood shortage: Blood donations urgently needed. https://www.redcross.org/about-us/news-and-events/press-release/2021/nation-confronts-severe-blood-shortage-blood-donations-urgently-needed.html.
2. Manjuladevi M, Vasudeva Upadhyaya KS. Perioperative blood management. Indian J Anaesth. 2014. doi:10.4103/0019-5049.144658
3. Kollberg SE, Häggström ACE, Lingehall HC, Olofsson B. Accuracy of visually estimated blood loss in surgical sponges by members of the surgical team. AANA J. 2019.
4. Schorn MN. Measurement of Blood Loss: Review of the Literature. J Midwifery Women’s Heal. 2010. doi:10.1016/j.jmwh.2009.02.014
5. Homcha BE, Mets EJ, Goldenberg MDF, Kong L, Vaida SJ. Development and Assessment of Pictorial Guide for Improved Accuracy of Visual Blood Loss Estimation in Cesarean Delivery. Simul Healthc. 2017. doi:10.1097/SIH.0000000000000246
6. Yoong W, Karavolos S, Damodaram M, et al. Observer accuracy and reproducibility of visual estimation of blood loss in obstetrics: How accurate and consistent are health-care professionals? Arch Gynecol Obstet. 2010. doi:10.1007/s00404-009-1099-8
7. Ambardekar S, Shochet T, Bracken H, Coyaji K, Winikoff B. Calibrated delivery drape versus indirect gravimetric technique for the measurement of blood loss after delivery: A randomized trial. BMC Pregnancy Childbirth. 2014. doi:10.1186/1471-2393-14-276
8. Legendre G, Richard M, Brun S, Chancerel M, Matuszewski S, Sentilhes L. Evaluation by obstetric care providers of simulated postpartum blood loss using a collector bag: a French prospective study. J Matern Neonatal Med. 2016. doi:10.3109/14767058.2016.1139569
9. Jaramillo S, Montane-Muntane M, Capitan D, et al. Agreement of surgical blood loss estimation methods. Transfusion. 2019. doi:10.1111/trf.15052
10. Kahr MK, Brun R, Zimmermann R, Franke D, Haslinger C. Validation of a quantitative system for real-time measurement of postpartum blood loss. Arch Gynecol Obstet. 2018. doi:10.1007/s00404-018-4896-0
11. Home – Gauss Surgical. https://www.gausssurgical.com/. Accessed July 9, 2021.
12. Konig G, Holmes AA, Garcia R, et al. In vitro evaluation of a novel system for monitoring surgical hemoglobin loss. Anesth Analg. 2014. doi:10.1213/ANE.0000000000000198
13. Gerdessen L, Meybohm P, Choorapoikayil S, et al. Comparison of common perioperative blood loss estimation techniques: a systematic review and meta-analysis. J Clin Monit Comput. 2021. doi:10.1007/s10877-020-00579-8
14. Tran A, Heuser J, Ramsay T, McIsaac DI, Martel G. Techniques for blood loss estimation in major non-cardiac surgery: a systematic review and meta-analysis. Can J Anesth. 2021. doi:10.1007/s12630-020-01857-4