Central and Mixed Venous O₂ Saturation

Abstract

Mixed and central venous oxygen saturations are commonly used to ascertain the degree of systemic oxygenation in critically ill patients. This review examines the physiological basis for the use of these variables to determine systemic extraction ration, oxygen consumption and tissue oxygenation, and also understand the role they may play in the early treatment of septic individuals.

Introduction

The quest for mixed venous oxygenation (S_mvO₂).

In the latter part of the 19^th Century, Adolf Fick (1821–1901) proposed his famous Fick’s Principle, whereby cardiac output could be estimated by calculating the ratio of systemic O₂ consumption (VO₂)_sys, measured from the expired gases, to the arterio-venous O₂ content difference.

$$\text{Cardiac\hspace{0.17em}Output}={({\text{VO}}_2)}_{\text{sys}}/({[{\text{O}}_2]}_{\text{a}}-{[{\text{O}}_2]}_{\text{mv}})$$ (1)

This formula requires blood samples from both arterial and pulmonary artery to calculate the O₂ content as:

$${[{\text{O}}_2]}_{\text{mv}}=13.9\times {\text{S}}_{\text{mv}}{\text{O}}_2\times [\text{Hb}]+0.031\times {\text{PO}}_2\hspace{0.17em}\text{mL\hspace{0.17em}}{\text{L}}^{-1}$$ (2)

Where [Hb] indicates the haemoglobin concentration (gram dL⁻¹).

Since, at the time, there was no safe way to obtain access to pulmonary artery blood in humans, the cardiac output could not be calculated by Fick’s Principle. This situation changed in 1929 when Werner Forssman (1904–1979) demonstrated that a catheter could be passed safely into the right atrium. One year later, Otto Klein (1881–1968) became the first individual to use Forssman’s technique to measure cardiac output by Fick’s Principle. A decade later, André Cournand (1895–1988) and Dickinson Richards (1895–1973) perfected the technique of right heart catheterisation and reported that they were able to leave a pulmonary artery catheter in place for a length of time with no harm to the patient. In 1970, Jeremy Swan (1922–2005) and William Ganz (1919–2009) developed a flow-directed pulmonary artery catheter (PAC) that could be inserted into the pulmonary artery without fluoroscopic guidance, allowing for ready and safe access to mixed venous blood in the ICU (1).

Paradoxically, the PAC also eliminated the need to measure S_mvO₂, since cardiac output now could be measured accurately by thermo-dilution. On the other hand, the unhindered access to pulmonary artery blood resulted in S_mvO₂ becoming one of the most commonly monitored physiological measures in the ICU, although its clinical utility remains a topic of intense and continuing debate. This review will discuss the utility, or lack thereof, of S_mvO₂ and of central venous blood O₂ saturation (S_cvO₂) in the care of the critically ill patient.

Clinical and Research Consequences

S_mvO₂ is a measure of O₂ extraction ratio

Systemic O₂ consumption is nowadays estimated by the ‘reverse’ Fick’s Method, as the product of cardiac output (Q) (measured by thermo-dilution) and the O₂ content difference.

$${({\text{VO}}_2)}_{\text{Sys}}=\text{Q}({[{\text{O}}_2]}_{\text{a}}-{[{\text{O}}_2]}_{\text{mv}})\hspace{0.17em}\text{mL\hspace{0.17em}}{\text{min}}^{-1}$$ (3)

It should be noted that the above expression does not account for pulmonary O₂ consumption, since the deep bronchial veins drain on the left side of the circulatory system, either via the pulmonary vein or directly into the left atrium. Therefore, the reverse Fick’s Method can underestimate (O₂)_Sys in conditions associated with substantial pulmonary O₂ consumption, such as acute lung injury (2).

Defining the rate of O₂ delivered to the tissues per unit time (O₂) _Sys as,

$${({\text{DO}}_2)}_{\text{Sys}}=\text{Q}\times {[{\text{O}}_2]}_{\text{a}}\text{\hspace{0.17em}mL\hspace{0.17em}}{\text{min}}^{-1}$$ (4)

One can calculate the efficiency of O₂ uptake by the tissues, i.e., the O₂ extraction ratio (ERO₂)_Sys, as:

$${({\text{ERO}}_2)}_{\text{Sys}}={({\text{VO}}_2)}_{\text{Sys}}/{({\text{DO}}_2)}_{\text{Sys}}$$ (5)

The clinical interpretation of (ERO₂)_Sys requires detailed knowledge of the physiological conditions prevailing at the time of its measurement. (ERO₂)_Sys at rest is approximately 20–30%, but increases to 60% or higher with high intensity exercise (3). Conversely, in a critically ill individual, an (ERO₂) _Sys of 60% is associated with severe and perhaps irreversible anaerobic metabolism (4).

Neglecting the contribution of plasma PO₂ to blood O₂ content yields an expression for (ERO₂)_Sys in terms of S_mvO₂ and S_aO₂, as:

$${({\text{ERO}}_2)}_{\text{Sys}}=(1-{\text{S}}_{\text{mv}}{\text{O}}_2/{\text{S}}_{\text{a}}{\text{O}}_2)$$ (6)

Figure 1 illustrates the close relationship between (ERO₂) _Sys and S_mvO₂. The graph was developed using data from a cohort of critically ill patients (n=53) (5).

Figure 1.

Systemic O₂ extraction ratio (ERO₂) as a function of mixed venous O₂ saturation (SmvO₂) for a heterogeneous cohort of critically ill patients (n=53). The solid line represents the linear correlation (R2= 0.99; p<0.01)

Since S_aO₂ in critically ill patients is usually constrained to the narrow range of 90–100%, for all practical purposes, as illustrated by Figure 1, (ERO₂) _Sys becomes a complementary function of S_mvO₂, as:

$${({\text{ERO}}_2)}_{\text{Sys}}\approx (100-{\text{S}}_{\text{mv}}{\text{O}}_2\%).$$ (7)

The foregoing analysis shows that S_mvO₂ is a reliable indicator of (ERO₂)_Sys, thus providing a useful insight on the balance between (DO₂)_Sys and (VO₂)_Sys. The clinical significance of changes in (ERO₂)_Sys depends on prevalent physiological conditions. Low (ERO₂)_Sys values may result from either a decrease in (DO₂)_Sys or an increase in (VO₂)_Sys, although in resting ICU patients it is the former that is usually prevalent. It should be emphasised that central venous O₂ saturation (S_cvO₂) cannot be used to calculate (ERO₂)_Sys, since the resulting value would apply exclusively to organs located in the upper body.

S_mvO₂ as a measure of cardiac output

Further manipulation of equations (1) and (2) shows the complex relationship that exists between cardiac output and S_mvO₂. This relationship must also take into account other physiological variables, namely, the haemoglobin concentration and (O₂)_Sys.

$$\text{Q}={({\text{VO}}_2)}_{\text{Sys}}/[13.9·[\text{Hb}]·({\text{S}}_{\text{a}}{\text{O}}_2-{\text{S}}_{\text{mv}}{\text{O}}_2)]$$ (8)

This relationship is a source of considerable uncertainty when using S_mvO₂ as an estimate of Q, as exemplified by Figure 2, where we again used the data from the patient cohort portrayed in Figure 1. Clearly, there is a positive relationship between Q and S_mvO₂, but this correlation is weak (R²=0.24), making it difficult to predict one from the other. For example, according to Figure 2, a value of 70% for S_mvO₂ may correspond to cardiac output values between 3 L minute⁻¹ and 12 L minute⁻¹.

Figure 2.

Cardiac output (Q) as a function of mixed venous O₂ saturation (S_mvO₂) for the patient cohort shown in Figure 1 (n=53). The solid line represents the linear correlation (R2=0.24; p<0.01)

The poor correlation between S_mvO₂ and Q has been noted in studies performed under diverse clinical conditions, including the induction of anaesthesia (6), congestive heart failure (7), and septic shock (8). Using continuous measures of S_mvO₂ that were obtained by reflectance spectrophotometry to calculate Q has also proven disappointing, because it was found to accurately predict changes in cardiac output only 50% of the time (9).

From a practical standpoint, however, as long as (VO₂)_Sys, [Hb], and S_aO₂ remain relatively constant, a decrease in S_mvO₂ in a critically ill individual is likely to reflect a lower cardiac output, rather than indicate increases in tissue O₂ requirements.

S_mvO₂ and right-to-left pulmonary shunt fraction

The right-to-left pulmonary shunt fraction (Q_Shunt/Q_Total) is estimated with the patient breathing 100% F_IO₂ as:

$$\frac{{\text{Q}}_{\text{S}}}{{\text{Q}}_{\text{T}}}=\frac{{[{\text{O}}_2]}_{\text{c}}-{[{\text{O}}_2]}_{\text{a}}}{{[{\text{O}}_2]}_{\text{c}}-{[{\text{O}}_2]}_{\text{mv}}}$$ (9)

where [O₂]_c represents the idealised pulmonary capillary O₂ content and is calculated from the alveolar air equation. Some researchers have proposed substituting O₂ saturations for O₂ contents in eq. 10 as a bedside estimate of Q_S/Q_T (10), as:

$$\frac{Q_S}{Q_T}=\frac{1-S_a{O}_2}{1-S_{mv}{O}_2}$$ (10)

This equation will underestimate Q_S/Q_T and its use should be discouraged.

S_mvO₂ as a measure of tissue oxygenation

In 1919, August Krogh (1874–1949) developed a model of microcirculation to quantify the process of O₂ transfer from capillaries to tissue parenchyma (11), with tissues represented by a cylinder surrounding a single, non-branched capillary (Figure 3). The red blood cells (RBC) release O₂ into the capillary plasma and from there it diffuses radially into the tissues. Among the variables that determine plasma PO₂ are the rate of O₂ dissociation from haemoglobin, the O₂ solubility in plasma, and the capillary transit time, with the latter being defined as the ratio of capillary length to RBC velocity. The transit time increases with greater capillary cross-sectional area and decreases with faster blood flow.

Figure 3.

Krogh’s cylinder model of capillary-tissue oxygenation

Tissue O₂ uptake, or O₂ flux, is driven primarily by plasma PO₂. As RBCs traverse the length of the capillary, haemoglobin-bound O₂ and plasma PO₂ are depleted. According to Krogh’s model, the capillary plasma PO₂ and O₂ flux reach a nadir at the venous end, giving rise to a region labelled the ‘lethal corner’, where tissues are at risk of hypoxia.

An important assumption of Krogh’s model is the equivalence between end-capillary and venous blood PO₂. This assumption provides the physiological basis for the notion that venous SO₂ is a marker of tissue oxygenation. Extension of the Kroghian theory to the body as a whole provides the foundation for assuming that S_mvO₂ is a marker of global tissue oxygenation. This is a precarious and often incorrect assumption, since it fails to consider the intricate macro- and microcirculatory adjustments that are attendant to sepsis and hypoxaemia.

The elegant simplicity of Krogh’s model provides a lucid physiological construct for the process of tissue oxygenation, but fails to account for the spatial and temporal heterogeneity of the microcirculation. Second order processes, including capillary recruitment, O₂ diffusion between adjacent capillaries, time-dependent haemoglobin O₂ unloading, and perpendicular and counter-current flow combine to produce a remarkably homogeneous distribution of tissue, one lacking ‘lethal corners’. It is possible that the intestinal villi and the renal medulla, organs characterised by a peculiar vascular arrangement of counter-current flow, may have regions akin to the ‘lethal corner’, where cells exist on the edge of hypoxia, vulnerable to even mild ischaemic or hypoxic insults (12).

Another factor conflicting with the use of S_mvO₂ as a marker of peripheral organ oxygenation is that S_mvO₂ results from mixing the venous effluents of all organs in the right heart chambers. As such, it can be defined as the flow-weighted average of all venous effluents SO₂ as:

$${\text{S}}_{\text{mv}}{\text{O}}_2{=}_{\mathrm{\Sigma }}{[{\text{S}}_{\text{v}}{\text{O}}_2]}_{\text{i}}\times {\text{Q}}_{\text{i}}/\text{Q.}$$ (11)

Where [S_vO₂]_i and Q_i represent venous SO₂ and flow from various organs. According to equation 11, organs having the greatest venous outflow are the primary determinants of S_mvO₂. As a result, under certain pathological conditions such as sepsis, patients could have normal or even elevated S_mvO₂ values, along with simultaneously experiencing tissue hypoxia.

For example, the loss of regional microcirculatory control could apportion a greater Q_i to some tissue beds, such as resting skeletal muscle with its enormous capacity for auto-regulation. Skeletal muscle is an organ capable of inducing a 7-fold increase in blood flow by trebling the number of open capillaries by capillary recruitment (13). This is a beneficial response during exercise, as it directs the bulk of the cardiac output towards the working skeletal muscles. During critical illness, however, a misdirected increase in blood flow to resting skeletal muscle would result in a muscle venous effluent of high SO₂, potentially overwhelming the hypoxic signals emanating from under-perfused organs, such as the gut and kidneys. This is a condition termed as ‘covert tissue hypoxia’ (14), and is defined by a normal or even elevated S_mvO₂ in conjunction with regional tissue hypoxia, as it may occur in patients with sepsis or septic shock.

Alternatively, low S_mvO₂ values may occur in the absence of tissue hypoxia during aerobic exercise. Trained athletes are known to experience very low S_mvO₂, as low as 40%, prior to reaching the anaerobic threshold (15). Far from signalling tissue hypoxia, these low S_mvO₂ values reflect the ability of trained skeletal muscles to maintain aerobic metabolism by extracting O₂ maximally from capillaries.

Another confounder in the interpretation of S_mvO₂ vis-à-vis tissue oxygenation is the manner by which O₂ is lowered. Animals subjected to decreases in O₂ by hypoxaemia or by isovolaemic anaemia reach a state of anaerobiasis at similar (O₂)_sys levels, which is defined as the critical O₂ delivery level (O₂)_critical. Remarkably, S_mvO₂ is much lower in hypoxemia than in isovolaemic anaemia at (O₂)_critical (16), a phenomenon that has also been noted at the organ level (17). This is because resting skeletal muscle preparations that are exposed to hypoxaemia and isovolaemic anaemia show similar tissue PO₂ distributions and O_2critical, but significantly different S_vO₂ values.

To summarise, the relationship of S_mvO₂ to tissue PO₂ is tenuous at best, and the values for S_mvO₂ being ≥70% do not guarantee adequate tissue oxygenation. The fundamental issue in caring for critically ill patients is to discern the level of regional O₂ required to sustain aerobic ATP turnover rate by all cells, in all organs, at all times. This information, however, cannot be gained from measuring the S_mvO₂.

Can we use central venous SO₂ in place of mixed venous SO₂?

S_cvO₂ has been proposed as a surrogate for S_mvO₂ (18), which begs the question of how reliable S_cvO₂ is as an estimate of S_mvO₂. The right atrium (RA) is a complex hydrodynamic chamber where venous blood of different provenances mix together. The resulting S_mvO₂ is the flow-weighted average of blood SO₂ from the inferior vena cava (IVC), the superior vena cava (SVC), and the coronary sinus (CS).

Studies in children with heart defects gave an impetus to the development of formulas to estimate S_mvO₂ based on SVC and IVC blood samples drawn nearly simultaneously. The expression (19) gaining the widest acceptance is:

$${\text{S}}_{\text{mv}}{\text{O}}_2=\frac{3{\text{S}}_{\text{svc}}{\text{O}}_2+{\text{S}}_{\text{IVC}}{\text{O}}_2}{4}$$ (12)

This expression was derived empirically and does not imply a physiological model of RA blood mixing. Its utility is constrained to the range of measured SO₂ values and the clinical conditions present at the time of blood sampling. It, however, does point to the large influence of S_cvO₂ on S_mvO₂, further suggesting these variables may be closely correlated. It should be noted that Eq. 13 does not account for the contribution of CS blood towards the development of S_mvO₂. The O₂ saturation of CS blood (S_CSO₂) is usually low, nearly 40% (20), but given its low flow relative to cardiac output, the effect of S_CSO₂ on S_mvO₂ is likely to be modest at best. On the other hand, S_CSO₂ may play a role in determining the direction (or sign) of the SO₂ gradient, defined here as the difference between S_cvO₂ and S_mvO₂, as:

$$\mathrm{\Delta }{\text{SO}}_2={\text{S}}_{\text{cv}}{\text{O}}_2-{\text{S}}_{\text{mv}}{\text{O}}_2$$ (13)

Some have proposed that subtracting 5% from S_cvO₂ may help to obtain an accurate estimate of S_mvO₂ (21), but the notion that S_cvO₂ and S_mvO₂ are separated by a fixed SO₂ % value is not supported by clinical data (5).

The ΔSO₂ gradient develops as blood from the SVC mixes with IVC and CS blood. This gradient is not constant, but may vary widely from patient to patient, and in the same patient at different times, in response to changes in the clinical condition. A complete understanding of the relative influences on ΔSO₂ of IVC and CS blood is hindered by a lack of clinical data. A study on patients with pulmonary hypertension (22) showed similar S_IVCO₂ and S_cvO₂, with a ΔSO₂ of 4.4%, suggesting that mixing with CS blood of lower SO₂ is the likely mechanism that results in positive ΔSO₂ gradients.

Studies measuring both SO₂ and lactate concentrations in SVC and PA blood report positive ΔSO₂ gradients accompanied by a step-down in lactate concentration from SVC to PA (23). Lactate is a preferred myocardial substrate and its concentration in CS blood is usually low, giving further credence to the role played by CS blood in generating ΔSO₂. This observation raises the interesting possibility of ΔSO₂ being capable of providing useful insight into myocardial O₂ utilisation in some patients.

The clinical significance ΔSO₂ is not clear. A multicentre study of post-operative and medical ICU patients measured ΔSO₂ at 6-hour intervals (24) and found a strong association between survival and a positive ΔSO₂. Conversely, studies in cardiac surgery patients suggest that a negative ΔSO₂ gradient is associated with better outcomes and less inotropic support requirements (25).

In summary, measures of S_cvO₂ are not reliable surrogates for S_mvO₂, especially with regards to septic patients, where the influence of IVC and CS blood on S_mvO₂ may predominate. Further, the notion that S_mvO₂ may be estimated by subtracting 5% from S_cvO₂ is not supported by clinical data. However, in certain conditions in which the pathophysiology is well understood, it may be possible to ascertain alterations in systemic O₂ extraction from measures of S_cvO₂, particularly if it is measured continuously (26).

S_mvO₂ and S_cvO₂ as predictors of morbidity and mortality

Studies in critically ill patients relating morbidity and mortality to measures of S_mvO₂ or S_cvO₂ are remarkably few in number. Moreover, the nature of the data is ambiguous, given that poor ICU outcomes may occur with either high or low S_mvO₂ or S_cvO₂ values.

There appears to be consensus that mortality is greater in patients with S_mvO₂ or S_cvO₂ values of <70%, although the boundary between decedents and survivors varies according to the study. A study in patients with septic shock (n=20), in which S_mvO₂ was measured continuously with fiberoptic PACs, noted increased mortality for patients with a preponderance of S_mvO₂ readings <65% (27). A retrospective case-control analysis (28) of septic patients with pre-existing left ventricular dysfunction (n=166) showed decedents with a lower initial mean S_mvO₂ than survivors (61% vs. 70%). This was somewhat confusing, as the control group (n=168) showed decedents with similar S_mvO₂ as survivors (70% vs. 71%). Greater mortality rate (29% vs. 17%) was also noted in patients with S_cvO₂ <60%, who had been admitted to a multidisciplinary ICU (n=98) (29). Similarly, patients with septic shock (n=363) were found to experience greater mortality rates when the ICU admission occurred at an S_cvO₂ <70% (38% vs. 27%) (30).

To complicate matters further, high S_cvO₂ values are also have been associated with greater ICU mortality. In a secondary analysis of septic patients (31), using data culled from prospectively collected registries (n=619) showed patients with both low and high S_cvO₂ (<70% or >89%) having greater mortality rates than patients with a ‘normal’ range of S_cvO₂ (70% to 89%). A retrospective study of 169 septic patients revealed that patients with ‘high’ or ‘low’ admission S_cvO₂ values (78.8% and 51.1%, respectively) experienced significantly higher mortalities than those with ‘normal’ S_cvO₂ (70.9%) (32).

Perhaps the time during which a patient is exposed to a low S_mvO₂ or S_cvO₂ carries more weight regarding the outcome than sporadic decreases in saturation. A retrospective analysis of septic shock patients (n=111) found that decreases in S_mvO₂ <70% for a significant amount of time during their first 24 ICU hours was associated with greater mortality (33%) (33).

The majority of surgical and trauma studies show an association between low values for S_mvO₂ and S_cvO₂ and post-operative complications. A retrospective analysis of 488 post-operative cardiac patients found a greater incidence of both post-operative complications and mortality (9.4%) for patients with a S_mvO₂ level of <55% on arrival to the ICU (34). Patients with a cardiac index of <2.0 L.min⁻¹m⁻² following coronary artery bypass grafting (CABG; n=36), experienced low S_mvO₂ values (58.5% vs. 63.7% in control) and a prolonged course of stay in the ICU (35). Decreases in S_cvO₂ have been independently associated with post-operative complications following major surgery (n=117) (36). Patients experiencing complications had lower S_cvO₂ during surgery (63% vs. 67%).

However, as we have noted in septic and general ICU patients, the relationship of post-operative complications to low S_cvO₂ measurements is not clear cut. Greater mortality rates also have been noted in patients undergoing elective cardiac surgery (n=205) with either low (<61%) or high (>77%) S_cvO₂ values (37).

Given the uneven ability of S_cvO₂ to provide a forecast of the outcome, some researchers advocate combining early measures of S_cvO₂ with either blood lactate concentration ([Lac]) or with lactate clearance. Blood lactate concentration ([Lac]) may be more reliable as a predictor of post-surgical complications than S_cvO₂. Patients following CABG (n=629) had fewer complications when [Lac] measured <3.9 mmol/L, irrespective of S_cvO₂ values (38).

A study in septic shock patients showed no difference in mortality when therapy aimed at increasing lactate clearance to ≥10% was compared to that of raising S_cvO₂ to ≥70% (n=150 each group) (39). A subsequent study by the same investigators (40) (n=203) showed that achieving a lactate clearance of ≥10% was more strongly associated with survival than achieving a S_cvO₂ value of ≥70%.

Decreases in S_mvO₂ or S_cvO₂ levels are prone to reflect increased extraction by the respiratory muscles, therefore, monitoring these variables during the process of weaning patients from mechanical ventilation appears to be useful. A study in haemodynamically stable ICU patients undergoing weaning (n=73) found that a decrease in S_cvO₂ > 4.5% was the only independent predictor of re-intubation (41). When S_mvO₂ was monitored continuously, weaning failure (n=8) was associated with progressive declines in S_mvO₂, in contrast to weaning success (n=11), where the S_mvO₂ did not change (42).

S_cvO₂ as a guide to resuscitation in sepsis

The concept of pathologic supply dependency during sepsis arose from the confluence of two observations. The first observation is that [Lac] usually increases in sepsis, which may be interpreted as the activation of anaerobic glycolysis by tissue hypoxia. The second observation is that increasing (DO₂)_Sys in septic patients is usually associated with greater (VO₂)_Sys (43). These observations gave rise to the concept of ‘pathologic supply dependency’, implying that septic tissues experience a ‘covert’ hypoxic condition (44), which is unmasked by increases in (DO₂)_Sys accomplished either by a dobutamine-mediated rise in cardiac output (45) or by the transfusion of blood (46). A clinical trial tested this hypothesis in a heterogeneous ICU population in which one group (n=253) was targeted to achieve a high cardiac index and another (n=257) was set to maintain S_mvO₂ at ≥70%. Neither group, however, showed improved survival when compared to the control group (47).

Several years later, a study was conducted in septic shock patients (n=263) that emphasised alacrity in therapeutic response. Treatment was dictated by a resuscitation algorithm called Early Goal Directed Therapy (EGDT) implemented during the patient’s initial 6 hours in the hospital (48), in which therapy was in part guided by S_cvO₂ measured continuously with a spectrophotometric central venous catheter. Among the treatment arms of the EGDT algorithm was the maintenance of S_cvO₂ ≥70% mediated by increases in (O₂)_Sys with fluids, RBC transfusions and dobutamine. The study showed a substantially lower mortality (30.5% vs. 46.5%) in patients treated with EGDT.

Three large prospective randomised studies enrolling a total of 4,183 patients tested the hypothesis that EGDT improves ICU survival in septic patients. All three of these trials, The Protocolized Care for Early Septic Shock (ProCESS) (49), the Autralasian Resuscitation Sepsis Evaluation (ARISE) (50), and the Protocolised Management of Sepsis (ProMISe) (51) have failed to show a survival advantage by implementing EGDT.

Without delving into all possible causes leading to the divergent outcomes of the initial EGDT study and the recent trials, it may be instructive to examine one aspect of these trials heretofore ignored. It concerns the low initial S_cvO₂ values reported in the initial. EGDT study of 49±11%. By most standards these are very low S_cvO₂ values, and quite different from those found in a Dutch multicentre study that reported <1% of septic patients having S_cvO₂ <50% within 6 hours of hospital admission (52). Moreover, initial S_cvO₂ values were 71±13% in the ProCESS, 73±11 % in the ARISE, and 65±20% in the ProMISe study.

Figure 4 depicts the Gaussian functions corresponding to these initial S_cvO₂ values. Obviously, the S_cvO₂ distribution reported in the EGDT trial is substantially different from the others (p<0.001). This observation suggests that the cohort enrolled in the EGDT trial differed fundamentally from those enrolled in the subsequent negative trials.

Figure 4.

Hypothetical S_cvO₂ Gaussian population distributions derived from the mean±standard deviation values published in various Early Goal Directed Therapy (EGDT) trials

A possible explanation for this discrepancy may be found by noting the location of the catheter in the SVC where S_cvO₂ is measured. The central venous catheter should lie with its tip in the SVC, below the anterior first rib, and above the RA. This places the infrared spectrophotometer fibreoptic sensor just below the opening of the azygos vein, a unilateral vessel carrying blood from the posterior intercostal muscle and the diaphragmatic veins.

Patients in the original EGDT study experienced considerable respiratory distress, with 53% requiring invasive mechanical ventilation, compared to the values of 26%, 20%, and 22% for patients in the ProCESS, ARISE, and ProMISe trials, respectively. Increased work by the respiratory muscles, particularly by the intercostal muscles, results in blood of very low O₂ saturation being discharged by the azygos vein into the SVC, which is in close proximity to the oximeter sensor. Therefore, it is likely that the S_cvO₂ values reported in the EGDT trial reflected increased work of breathing and not global tissue hypoxia, further suggesting that the correct therapy was by way of mechanical ventilation, not RBC transfusion or dobutamine infusion. Supporting this hypothesis was a study of septic patients showing increases in S_cvO₂ from 64% to 71%, before and after applying mechanical ventilation (53).

To summarise, it appears that S_cvO₂-guided resuscitation does not improve the survival of septic patients. On the other hand, the early application of some treatment modalities, such as the early administration of antibiotics, low tidal volume mechanical ventilation, and rapid fluid infusion with the reversal of hypotension can improve survival in cases of severe sepsis or septic shock (54).

Conclusion

The ideal ICU monitored variable must meet each of the following parameters: (1) easy to measure; (2) easy to interpret; (3) amenable to treatment; and (4) measured non-invasively. Pulse oximetry is the quintessential monitoring device that meets all these criteria. S_cvO₂ monitoring, on the other hand, falls far short of this expectation.

S_cvO₂ is relatively easy to measure, either intermittently or continuously, with a fiberoptic catheter. However, due to its invasiveness, the decision to insert a central venous catheter solely for the purpose of measuring S_cvO₂ should be tempered by the risk associated with the procedure.

Changes in S_mvO₂ are inversely related to changes in systemic ERO₂. The same concept applies to S_cvO₂ regarding upper body organs. As previously reviewed, however, S_cvO₂ is not easy to interpret. Experienced clinicians might also be confused by the information conveyed by S_cvO₂. Perhaps the continuous monitoring of S_mvO₂ or S_cvO₂ is useful in selected cases where the patient’s pathophysiology is well understood, such as when there is cardiomyopathy with reduced cardiac output. This is not the case in most other conditions that affect critically ill individuals, particularly in cases of severe sepsis, in which both high and low S_mvO₂ or S_cvO₂ values carry a dire prognosis.

Lastly, not knowing the pathophysiological processes responsible for alterations in S_cvO₂ in sepsis, as well as lacking a clearly defined therapeutic response, greatly diminish the clinical utility of this monitored variable. Whether the aim is to decrease O₂ consumption by mechanical ventilation or increase O₂ delivery by transfusing RBCs or infusing dobutamine, it cannot be easily discerned from measures of S_cvO₂.