Dilemmas of Adopting Goal-Directed Perfusion in Extracorporeal Circulation: A Narrative Review

Abstract

Objective:

Extracorporeal circulation (ECC) is generally based on standards established in the last decade. In recent years, a concept of perfusion management during ECC, goal-directed perfusion (GDP), has emerged to create optimal conditions for oxygen delivery and extraction, initiated by Rannuci et al. The aim of the present work was to determine whether the ECC procedure can truly be optimized with the current state of knowledge and understanding of human physiology.

Methods:

Discussed articles from 2017 to 2022 were selected from the MEDLINE (PubMed) database using the keywords “cardiopulmonary bypass” AND “cardiac surgery” AND “oxygen delivery” with the conditions of “clinical trial” OR “randomized controlled trial.”

Results:

The concept of GDP is an attempt to reproduce the physiological conditions of tissue respiration during ECC. Published articles, also due to their retrospective nature, are based on standards and recommendations that do not fully fit the field of physiological circulation. There are still insufficient tools to assess the relationship between volemia, perfusion pressure, and pump performance. Limitations include indications for vasoactive drugs. Methodology has rarely taken into account the period of starting and stopping the heart-lung machine, the most pronounced periods of circulatory destabilization with reduced oxygen delivery.

Conclusions:

Problems associated with ECC such as acute kidney injury, liver failure, vasoplegic syndrome, and others must await its resolution. The use of advanced monitoring technology and data engineering may allow the development of baseline hemodynamic models, which may make the ECC procedure more physiologic and thus improve the safety of the procedure.

Visual abstract

Keywords

extracorporeal circulation goal-directed perfusion perfusion pressure systemic vascular resistance oxygen delivery

Central Message

The use of advanced monitoring technology and data engineering may allow the development of baseline hemodynamic models, which may make the extracorporeal circulation procedure more physiologic and thus improve the safety of the procedure.

Introduction

The widely accepted extracorporeal circulation (ECC) procedure is based on specific guidelines and standards for perfusion management established by the American Society of Extracorporeal Technology (AmSECT). Perfusion management according to the last published edition of the 2013 recommendations remains unchanged despite updates in 2015 and 2017, with all attention focused on pump design and its adjustable parameter, pump flow.^1,2 During the ECC period, the patient remains under the care of cardiac surgeons and anesthetists, who have common, but sometimes conflicting, therapeutic goals. The main point of contention is the level of blood pressure. For cardiac surgeons, blood pressure that is too high complicates the procedure by increasing bleeding in the surgical field or making it difficult to perform invasive vascular access. However, for anesthetists, the overriding goal is to maintain a sufficiently high tissue perfusion. In contrast, perfusion pressure, the stabilization of which is the primary goal of therapy in the treatment of intensive care unit (ICU) patients, becomes a secondary, poorly-defined parameter during ECC.^3–5 Unlike the ICU, where cardiovascular therapy is based on extensive diagnostic capabilities, hemodynamic monitoring during EEC is very limited. Therefore, it is very difficult to determine the relationship between adequate pump output, systemic vascular resistance, and blood pressure. As a result, the pump flow rate is often not adapted to the actual hemodynamic conditions, and vasoconstrictors are overused to increase blood pressure.^1,2,6,7

In recent years, a concept of perfusion management during ECC, goal-directed perfusion (GDP), has emerged to create optimal conditions for oxygen delivery (DO₂) and extraction, initiated by Rannuci et al.⁸ Based on his observations of renal function and DO₂ during ECC, the model of adequate tissue perfusion and optimal DO₂ during ECC is proposed. There are many doubts as to whether the new GDP methodology is based on a solid foundation for understanding and restoring human physiology in the newly created hemodynamic system, the patient-heart-lung machine model. The aim of the present work was to determine whether the ECC procedure can be truly optimized with the current state of knowledge and understanding of human physiology. The key question is whether modern methods of patient monitoring during ECC and data science methodology can be used to create more physiological hemodynamic algorithms adapted to the physiology of each individual patient.

Methods

Articles were selected from the MEDLINE (PubMed) database at the time of the search using the keywords “cardiopulmonary bypass” AND “cardiac surgery” AND “oxygen delivery” with the conditions of “clinical trial” OR “randomized controlled trial” (Table 1). All articles published between 2017 and 2022 were considered for inclusion. Only articles published in English were included. A brief overview of ECC, clinical issues, and changes introduced by GDP is provided.^1,2,9

Table 1.

Publications Found in the PubMed Database Using Keywords “Cardiopulmonary Bypass” AND “Cardiac Surgery” AND “Oxygen Delivery.”

Data	Ranucci et al. (2018)⁸	Oshita et al. (2020)¹⁰	Rasmussen et al. (2019)¹¹	Newland et al. (2019)¹²	Smoor et al. (2022)¹³
Number of patients	326	202	1,968	19,410	432
Study design	Prospective	Retrospective	Retrospective	Retrospective	Retrospective
Measurement period	ECC (first 120)	ECC	ECC	ECC	ECC
Nadir DO₂, mL/min/m²	280	300	272	270	270
Organ evaluated	AKI	AKI	AKI	AKI	AKI
MAP (perfusion pressure), mm Hg	Not evaluated	>50	44.6 ± 6.9	Not evaluated	>50
Catecholamines	—	Phenylephrine	—	—	—
Heart-lung machine output	Adjustable	Fixed	Fixed	Adjustable	Fixed
Machine output, L/min/m²	GDP compliant	2.5	2.4	1.6–2.4	2–2.4
Measurement method	Average of measurements collected in 10 min intervals	AUC from measurements taken every 20 s Largest AUC below DO₂ <300 mL/min/m²	Nadir DO₂ measured in time intervals 1 to 5, 10, 15, and 30 min	Minimum DO₂ over entire observation period	At least 2 consecutive DO₂ values (2 min) were below threshold

Abbreviations: AKI, acute kidney injury; AUC, area under the curve; DO₂, oxygen delivery; ECC, extracorporeal circulation; GDP, goal-directed perfusion; MAP, mean arterial pressure.

ECC Protocols

Current ECC protocols are mainly based on guidelines from the 1990s, and their latest update has not changed the basic concepts.^1,2,9 It is still recommended to calculate the pump flow from body surface area (BSA) for all patients, regardless of age or sex. The latest European recommendations also support the concept of determining heart-lung machine performance based on BSA but allow the pump flow, previously kept constant at 2.4 to 2.5 L/min/m², to be adjusted to ensure adequate organ perfusion and optimize DO₂ and extraction.^1,2,9 However, recommendations still do not define the appropriate values for optimal perfusion pressure or DO₂. Other methods of assessing ECC are the results of biochemical and diagnostic tests with assessment of lactate levels and cerebral oximetry.^1,2,9,14 The definition of adequate perfusion pressure during ECC remains undefined. This appears to be difficult to determine as the minimum perfusion pressure varies from organ to organ as well as from person to person and depends on the underlying disease.^4,5,14

What Is GDP?

GDP is an ECC concept in which the target for tissue perfusion is defined as a minimum DO₂ threshold to ensure proper tissue respiration and maintain organ function during the perioperative period. This concept is based on modern in-line monitoring methods that continuously collect data on oxygen transport in the body and also facilitate the estimation of the difference in gas content between the ECC venous system and the arterial system.

Results

There are methodological and computational limitations in determining normal tissue perfusion and DO₂.

Perfusion Pressure

Studies evaluating oxygen transport in the ECC neglect the issue of perfusion pressure. The problem arises from the lack of strict standards and a universally accepted minimum mean arterial pressure (MAP) of 50 mm Hg.^1,2,9 It would seem that if we know the pump flow rate and the arterial blood gas results, we have all the necessary data to calculate DO₂ and extraction. However, the driving force for the blood to overcome the systemic vascular resistance that is the determinant of adequate tissue respiration is the perfusion pressure.^3–6 In addition, because of the lack of knowledge about the relationship between pump flow, blood rheological properties, and systemic vascular resistance, catecholamine therapy is often used during ECC to achieve the desired blood pressure. The risk of microcirculatory occlusion and even counterproductive effects such as worsening of DO₂ is associated with the overuse of vasoconstrictors.^3–6 Although there are no well-defined standards for the appropriate minimum perfusion pressure for ECC, it is increasingly recognized that a level of 50 mm Hg is still too low to maintain renal function.⁵ Therefore, the accepted perfusion pressure is more likely to correspond to the experience of normal renal perfusion and should be greater than 65 mm Hg.^5,15,12 It is inexplicable that the articles describing tissue DO₂ omit perfusion pressure from their basic assumptions (Table 1).^8,10–14 The microcirculation is not taken into account; only the correct DO₂ and extraction rate are determined. In the case of hypotension or excessive use of vasoconstrictors, the microcirculation may remain occluded, giving an apparently normal oxygen extraction. In this case, neither the pump flow rate nor the venous blood saturation (oxygen extraction rate) can fully describe the adequacy of tissue perfusion.^4,16

According to the equation, DO₂ in GDP depends on the oxygen content of the blood—the hemoglobin level—and also on the pump flow rate. An increase in blood volume and viscosity, as well as an increase in blood flow, leads directly to an increase in perfusion pressure. However, MAP is either not considered at all in the clinical observations performed, or it is considered in advance to be of no importance for proper oxygen transport and delivery (Table 1).^8,10–14

Cardiac Surgery Procedure

Advances in cardiac surgery require the perfusionist to reduce or even temporarily stop blood flow to the heart-lung machine. As a result of such surgical manipulations, the inevitable pharmacologic effects cause temporary destabilization and pressure drops. The beginning and end of ECC appear to be the most critical for hemodynamics and oxygen transport. These momentary drops in blood flow may cause organ dysfunction in the mechanism of hypoperfusion, regardless of the concept of perfusion pursued. The widely reported results of various studies usually do not cover the entire period of connection to the heart-lung machine but only the ECC period during aortic cross-clamping (Table 1).

Figure 1 shows the measurements taken at 10 s intervals to determine DO₂ in relation to hemoglobin level and cardiac index during 270 ECC procedures.⁷ Each point on the graph is described by 3 parameters: DO₂, hemoglobin level, and pump flow. These inseparable parameters occupy the entire graph, even in the areas of nonphysiological low DO₂, because there are expected decreases in all ECC procedures, as previously mentioned.⁷ These decreases are mainly due to the reduction in pump flow, as other factors such as hemoglobin level, saturation, and oxygen content are usually kept constant during ECC.

Fig. 1.

A full set of the cardiac index data during extracorporeal circulation, in the function of hemoglobin density and tissue oxygen delivery for patients with mixed venous oxygen saturation above 68% and mean arterial pressure above 60 mm Hg. Oxygen delivery has been illustrated with color, where the darker shades correspond with lower values. Image reprinted with no modifications from Lukaszewski et al., “The use of data science to analyse physiology of oxygen delivery in the extracorporeal circulation,” BMC Cardiovasc Disord, 2019, under the terms of the CC BY 4.0 license.⁷

Calculation Limitations

The calculation method based on averaging the ECC periods of oxygen transport to the tissues is a serious limitation of the sensitivity of the tests and the assessment of GDP efficiency. As a result, data analysis is limited and can lead to errors. Even a very short period of hypoperfusion, which is not taken into account by averaging, can lead to organ dysfunction (Fig. 2). It should be noted that visceral perfusion is characterized by a certain inherent organ resistance to transient disturbances in blood flow. Restoration of blood flow then allows visceral function to be restored, with possible periods of transient dysfunction. On the other hand, the brain is extremely sensitive to hypoperfusion, which can be a much greater problem during the ECC procedure. For this reason, the averaging method may not be a suitable tool for calculating and evaluating DO₂.¹⁷

Fig. 2.

Example of DO₂ measurements collected at 10 s intervals. On the y axis is DO₂, on the x axis is elapsed time, and the red line in the graph is the recognized lowest DO₂ level for renal dysfunction. DO₂ measurements collected by in-line noninvasive real-time monitoring System M (Spectrum Medical, Gloucester, UK) during extracorporeal circulation procedure. DO₂, oxygen delivery.

Discussion

This article has attempted to show that the physiology of ECC is misunderstood. There is no other circulation and its physiology, whether the driving force is the heart or a mechanical device. Scientific observational papers report information randomly and show superficial correlations, as in the case of the cited publications (Table 1). The main problem in estimating which parameter is more important comes from the physiological relationships between them. For example, increasing pump output increases perfusion pressure; increasing hemoglobin level increases blood viscosity, systemic resistance, and perfusion pressure. There is no way to determine whether the physiological state is being maintained by adequate DO₂ or by adequate blood viscosity and blood flow, which translates into systemic pressure.

From the formula for DO₂, it is easy to deduce that we could calculate a recognized minimum level of DO₂ of 280 mL/min/m²:

280 mL/min/m² = 2.4 L/min/m² (average cardiac output) × 1.3 × (average hemoglobin level during ECC – 90 g/L)

Such averaged parameters during ECC give a statistically correct perfusion pressure also during ECC. Therefore, statistics on very large groups of patients will report this value of DO₂ as the most physiological. Similarly, in the Magruder et al. publication, this most optimal and near-average physiological state will provide the statistical effect.¹⁸ But to return to the large study under physiological conditions, the basis for proper cellular respiration is proper perfusion; in the case of the kidney, the perfusion pressure should be above 65 mm Hg.⁵

The assumptions of the GDP concept are logical and based on the physiological basis of tissue respiration and oxygen transport. However, failure to include the correct perfusion pressure in the calculations reduces the specificity of the observations presented (Table 1). Low perfusion pressure occludes the microcirculation, and the use of vasoconstrictors in the presence of inadequate blood volume and cardiac output may further increase tissue damage.^3,5,19–21 Table 1 lists publications assessing oxygen transport and its impact on postoperative kidney function. The methodological limitations described above were repeated in all publications that were found. The authors present the perfusion pressure value as an average over the whole observation, not as an instantaneous value. In addition, the exact period of DO₂ measurements is not specified (whether it concerns the entire ECC procedure or only the aortic cross-clamp period) and the use of vasoconstrictive drugs is not taken into account. Finally, the authors analyze the arithmetic mean of measurements taken at different time intervals.^8,10
–13

The concept of GDP is an attempt to reproduce the physiological conditions of tissue respiration during ECC. However, to apply this concept in practice, it is necessary to know the correct hemodynamic relationships in the patient-heart-lung machine model. This is a very difficult task when we compare ECC therapy with the possibility of hemodynamic diagnosis and treatment of ICU patients in hemodynamic shock. We still do not have sufficient tools to assess the correlation between volemia, cardiac output, and systemic vascular resistance.³ Therefore, the goal of cardiovascular therapy in hemodynamic shock according to the Surviving Sepsis Campaign guidelines is to maintain MAP (i.e., perfusion pressure) with fluid therapy, improved cardiac output, and the use of catecholamines.^3,5,7,22,23 However, ultimately the validity of the applied cardiovascular therapy is confirmed by the basic clinical indicators of normal organ function, such as renal excretory function and correct arterial blood gas results, including lactate levels.

The data presented in Table 1 use statistical averaging to define circulatory parameters in ECC based on DO₂. However, it is not the average result that is important for patient management but rather the optimization of treatment, which is more like a Gaussian curve. A more flexible approach to machine performance is needed; even in human physiology, the range of normal cardiac output is twice as wide, blood viscosity and hemoglobin levels need to be taken into account, higher perfusion pressure is required, and vasoconstrictors need to be used much more carefully.

The introduction of modern monitoring methods and the ability to analyze a huge medical database using data science tools has revealed new limitations of current therapeutic standards (Fig. 1, Fig. 2). The monitoring of hemodynamics and oxygen transport during ECC is an excellent example of technical excellence introduced into medical practice. In contrast to the intensive care patient, the performance of ECC with the use of extensive in-line monitoring allows a more precise determination of hemodynamic dependencies.²² In the case of patients connected to the heart-lung machine, thanks to structural data (oxygen supply and extraction, CO₂ production, cardiac output, perfusion pressure) and nonstructural data (age, sex, body mass index, additional diseases), taking into account the use of modern data analysis possibilities with large databases, including data science, it is possible to create basic hemodynamic models on the basis of which it will be possible to perform the ECC procedure in a more physiological way.⁶ We believe that the goal of GDP should be to create such optimal hemodynamic conditions in which it will be possible to maintain correct perfusion through the microcirculation by adjusting the optimal projection to the volemia and the pressors used.^6,7,24–27 Currently, the generally accepted pump flow rate is 2.4 L/min/m², irrespective of the patient’s sex, age, anthropometric characteristics, and disease burden. The lack of consideration of perfusion pressure, indicators of systemic vascular resistance, and indications for the use of catecholamines seems to be an extreme medical archetype in the GDP concept. With data science, an analysis of the relationship between machine output, perfusion pressure achieved, hemoglobin and blood viscosity levels, and microperfusion assessment, performed on a sufficiently large group of matched patients, can generate physiological patterns. Based on these patterns, the creation of hemodynamic models of ECC could be performed in a more physiological manner by adapting the appropriate machine output to cardiovascular physiology and reducing the often-abused toxic use of vasoconstrictor doses.

Footnotes

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Marceli Lukaszewski

References

Baker

Bronson

Dickinson

, et al. Report from AmSECT’s International Consortium for Evidence-Based Perfusion: American Society of Extracorporeal Technology standards and guidelines for perfusion practice: 2013. J Extra Corpor Technol 2013; 45: 156–166.

American Society of ExtraCorporeal Technology. Standards and guidelines for perfusion practice, https://www.amsect.org/Portals/0/2017%20Standards%20and%20Guidelines%20for%20Perfusion%20Practice%20AmSECT.pdf (2017, accessed 28 August 2023).

Dunser

Takala

Ulmer

, et al. Arterial blood pressure during early sepsis and outcome. Intensive Care Med 2009; 35: 1225–1233.

De Backer

and Foulon

. Minimizing catecholamines and optimizing perfusion. Crit Care 2019; 23(Suppl 1): 149.

Suarez

and Busse

. New strategies to optimize renal haemodynamics. Curr Opin Crit Care 2020; 26: 536–542.

Lukaszewski

and Kosiorowska

. The importance of perfusion pressure in estimating oxygen delivery and extraction. Comment on Br J Anaesth 2020; 124: 395–402. Br J Anaesth 2021; 126: e97–e99.

Lukaszewski

Kosiorowska

, et al. The use of data science to analyse physiology of oxygen delivery in the extracorporeal circulation. BMC Cardiovasc Disord 2019; 19: 292.

Ranucci

Johnson

Willcox

, et al. Goal-directed perfusion to reduce acute kidney injury: a randomized trial. J Thorac Cardiovasc Surg 2018; 156: 1918–1927.

Wahba

Milojevic

Boer

, et al. 2019 EACTS/EACTA/EBCP guidelines on cardiopulmonary bypass in adult cardiac surgery. Eur J Cardiothorac Surg 2020; 57: 210–251.

10.

Oshita

Hiraoka

Nakajima

, et al. A better predictor of acute kidney injury after cardiac surgery: the largest area under the curve below the oxygen delivery threshold during cardiopulmonary bypass. J Am Heart Assoc 2020; 9: e015566.

11.

Rasmussen

Kandler

Nielsen

, et al. Duration of critically low oxygen delivery is associated with acute kidney injury after cardiac surgery. Acta Anaesthesiol Scand 2019; 63: 1290–1297.

12.

Newland

Baker

Woodman

, et al. Predictive capacity of oxygen delivery during cardiopulmonary bypass on acute kidney injury. Ann Thorac Surg 2019; 108: 1807–1814.

13.

Smoor

van Dongen

EPA

Verwijmeren

, et al. Critical oxygen delivery threshold during cardiopulmonary bypass in older cardiac surgery patients with increased frailty risk. Eur J Cardiothorac Surg 2022; 61: 685–692.

14.

Murphy

Hessel

II and Groom

. Optimal perfusion during cardiopulmonary bypass: an evidence-based approach. Anesth Analg 2009; 108: 1394–1417.

15.

RKY

Broad

JHT

Parker

FLM

, et al. Decreased mean perfusion pressure as an independent predictor of acute kidney injury after cardiac surgery. Heart Vessels 2020; 35: 1154–1163.

16.

Dubin

Pozo

Casabella

, et al. Increasing arterial blood pressure with norepinephrine does not improve microcirculatory blood flow: a prospective study. Crit Care 2009; 13: R92.

17.

Leenders

Overdevest

Van Straten

, et al. The influence of oxygen delivery during cardiopulmonary bypass on the incidence of delirium in CABG patients; a retrospective study. Perfusion 2018; 33: 656–662.

18.

Magruder

Weiss

DeAngelis

, et al. Correlating oxygen delivery on cardiopulmonary bypass with Society of Thoracic Surgeons outcomes following cardiac surgery. J Thorac Cardiovasc Surg 2022; 164: 997–1007.

19.

den Os

van den Brom

van Leeuwen

ALI

, et al. Microcirculatory perfusion disturbances following cardiopulmonary bypass: a systematic review. Crit Care 2020; 24: 218.

20.

Shepherd

Pawlik

Mailman

, et al. Effects of vasoconstrictors on intestinal vascular resistance and oxygen extraction. Am J Physiol 1976; 230: 298–305.

21.

Lannemyr

Bragadottir

Hjärpe

, et al. Impact of cardiopulmonary bypass flow on renal oxygenation in patients undergoing cardiac operations. Ann Thorac Surg 2019; 107: 505–511.

22.

Long

Zhou

, et al. Oxygen–flow–pressure targets for resuscitation in critical hemodynamic therapy. Shock 2018; 49: 15–23.

23.

Rhodes

Evans

Alhazzani

, et al. Surviving Sepsis Campaign: international guidelines for management of sepsis and septic shock: 2016. Intensive Care Med 2017; 43: 304–377.

24.

Hendrix

RHJ

Ganushchak

and Weerwind

. Oxygen delivery, oxygen consumption and decreased kidney function after cardiopulmonary bypass. PLoS One 2019; 14: e0225541.

25.

Yalcin

Ortiz

Williams

, et al. Perfusion pressure and blood flow determine microvascular apparent viscosity. Exp Physiol 2015; 100: 977–987.

26.

Mukaida

Matsushita

Yamamoto

, et al. Oxygen delivery-guided perfusion for the prevention of acute kidney injury: a randomized controlled trial. J Thorac Cardiovasc Surg 2023; 165: 750–760.

27.

Ranucci

Romitti

Isgrò

, et al. Oxygen delivery during cardiopulmonary bypass and acute renal failure after coronary operations. Ann Thorac Surg 2005; 80: 2213–2220.