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Critical Care

Open Access

Central venous-to-arterial carbon dioxide difference as a prognostic tool in high-risk surgical patients

  • Emmanuel Robin1Email author,
  • Emmanuel Futier2,
  • Oscar Pires1,
  • Maher Fleyfel1,
  • Benoit Tavernier1,
  • Gilles Lebuffe1 and
  • Benoit Vallet1
Critical Care201519:227

https://doi.org/10.1186/s13054-015-0917-6

Received: 18 November 2014

Accepted: 13 April 2015

Published: 13 May 2015

Abstract

Introduction

The purpose of this study was to evaluate the clinical relevance of high values of central venous-to-arterial carbon dioxide difference (PCO2 gap) in high-risk surgical patients admitted to a postoperative ICU. We hypothesized that PCO2 gap could serve as a useful tool to identify patients still requiring hemodynamic optimization at ICU admission.

Methods

One hundred and fifteen patients were included in this prospective single-center observational study during a 1-year period. High-risk surgical inclusion criteria were adapted from Schoemaker and colleagues. Demographic and biological data, PCO2 gap, central venous oxygen saturation, lactate level and postoperative complications were recorded for all patients at ICU admission, and 6 hours and 12 hours after admission.

Results

A total of 78 (68%) patients developed postoperative complications, of whom 54 (47%) developed organ failure. From admission to 12 hours after admission, there was a significant difference in mean PCO2 gap (8.7 ± 2.8 mmHg versus 5.1 ± 2.6 mmHg; P = 0.001) and median lactate values (1.54 (1.1-3.2) mmol/l versus 1.06 (0.8-1.8) mmol/l; P = 0.003) between patients who developed postoperative complications and those who did not. These differences were maximal at admission to the ICU. At ICU admission, the area under the receiver operating characteristic curve for occurrence of postoperative complications was 0.86 for the PCO2 gap compared to Sequential Organ Failure Assessment score (0.82), Simplified Acute Physiology Score II score (0.67), and lactate level (0.67). The threshold value for PCO2 gap was 5.8 mmHg. Multivariate analysis showed that only a high PCO2 gap and a high Sequential Organ Failure Assessment score were independently associated with the occurrence of postoperative complications. A high PCO2 gap (≥6 mmHg) was associated with more organ failure, an increase in duration of mechanical ventilation and length of hospital stay.

Conclusion

A high PCO2 gap at admission in the postoperative ICU was significantly associated with increased postoperative complications in high-risk surgical patients. If the increase in PCO2 gap is secondary to tissue hypoperfusion then the PCO2 gap might be a useful tool complementary to central venous oxygen saturation as a therapeutic target.

Keywords

Postoperative ComplicationLactate LevelSequential Organ Failure Assessment ScoreSimplify Acute Physiology ScoreCentral Venous Oxygen Saturation

Introduction

There is increasing evidence that individually optimized hemodynamic therapy oriented on goals to maintain and improve tissue perfusion and/or oxygenation improves patient outcome [1]. The development of tissue hypoxia is a leading cause of postoperative organ failure and mortality following major surgery [2,3]. Early recognition and correction of warning signals of persistent inadequacy of tissue perfusion is therefore of particular importance, especially in patients with a reduced physiological reserve [1,4].

The inability to meet an increase in oxygen (O2) demand with surgical trauma either by an increase in O2 delivery or an increase in O2 extraction can lead to tissue hypoxia [5,6]. Several markers of impaired tissue oxygenation have been explored to help identify patients at increased risk of complications. Postoperative organ failure has been shown to be associated with reduced central venous O2 saturation (ScvO2), which explores the balance of O2 delivery and tissue O2 consumption [7]. However, there is evidence that O2-derived variables are poorly correlated with anaerobic metabolism [8-11]. Indeed, both normal and high values (that is, ≥75%) for ScvO2 do not preclude the presence of tissue hypoxia in case of impaired O2 extraction capabilities, which may therefore limit the usefulness of ScvO2 monitoring [12,13]. In contrast, it has also been shown that strategies aimed at reducing high serum lactate levels, as a warning signal of a persistent tissue hypoxia at ICU admission, could reduce length of stay and mortality [14,15]. However, a rise in lactate level may be delayed compared with markers of tissue oxygenation adequacy, such as oxygen extraction [16], and could be not sensitive enough to reflect tissue hypoperfusion [14].

Previous relatively small studies have proposed central venous-to-arterial carbon dioxide gradient (PCO2 gap), a global index of tissue perfusion, as a useful measurement to characterize the insufficient flow state in spite of apparently normal macrocirculatory parameters [17,18]. Tissue partial pressure of carbon dioxide (PCO2) reflects metabolic alterations due to inadequate perfusion in actively metabolized tissues [19]. The PCO2 gap, which has been shown to be inversely related to cardiac output (CO) [20], is considered as a marker of the ability of the venous blood flow to remove the CO2 excess produced in tissues [21]. Thus, an impaired tissue perfusion during a reduced blood flow is the main determinant of a rise of the PCO2 gap [22]. However, despite promising findings from both experimental and clinical data, the prognostic significance of the PCO2 gap has only been examined to a small extent in the context of major surgical trauma. The purpose of this study was to evaluate the clinical relevance of high values of the PCO2 gap, and their relationships to other markers of impaired tissue perfusion and oxygenation (that is, blood lactate and ScvO2). We hypothesized that the PCO2 gap could serve as a useful tool to help identify patients at high risk of postoperative complications at ICU admission following major surgery.

Methods

Patients

This was a prospective single-center observational study of patients scheduled for major abdominal and vascular surgery and admitted to the ICU of a University Hospital over a 1-year period. The study was approved by local Research Ethics Committee of the University Hospital of Lille, France, which permitted anonymous data analysis. The requirement for written inform consent was waived due to the strict observational design of this study.

Inclusion criteria adapted from Schoemaker and colleagues [23] are summarized in Table 1 and are divided into demographic, surgical and intensive care criteria. All patients undergoing abdominal or vascular surgery were included if they had one of the following criteria: 1) one demographic criterion and one surgical criterion; 2) three or more demographic criteria; 3) three or more surgical criteria; 4) one intensive care criterion.
Table 1

Demographic, surgical and intensive care inclusion criteria

High-risk criteria

Values

Demographic criteria

 

 Age ≥70 years

42 (37)

 ASA class ≥3

70 (61)

 Severe nutritional problems

11 (10)

 Previous severe respiratory illness

24 (11)

 Chronic renal failure

6 (5)

 Chronic liver failure

7 (6)

 Ischemic heart disease (infarction or angina)

51 (44)

 Malignant neoplasia

67 (58)

Surgical criteria

 

 Major abdominal surgery

82 (71)

 Prolonged surgery ≥8 hours

9 (8)

 Urgent surgery

22 (19)

 Septic surgery

24 (21)

 Vascular clamping ≥1 hour

4 (4)

 Surgical procedures

 

  Esophagectomy

22 (19)

  Gastrectomy

9 (8)

  Small bowel resection

17 (15)

  Large bowel resection

20 (17)

  Hepatectomy

21 (18)

  Pancreatectomy

16 (14)

  Intra-abdominal vascular surgery

24 (21)

  Other

2 (2)

Intensive care criteria

 

 Shock

38 (33)

 Acute respiratory failure

32 (28)

 Hemorrhage (hemoglobin <7 g/dl)

10 (9)

 Acute coronary syndrome

7 (6)

Data are presented as absolute value (%). Severe nutritional problems: body mass index ≤17 kg/m2 or weight loss >10% in 6 months. Chronic renal failure: creatinine clearance <60 ml/min per 1.73 m2 or creatinine >176 μmol/l. Chronic liver failure: bilirubin >78 μmol/l or prothrombin time <55% or well-documented cirrhosis.

ASA, American Society of Anesthesiology physical status.

Study protocol

As part of our routine hemodynamic monitoring during major surgery, all patients were monitored with central venous (standard two-lumen catheter, Arrow, Wayne, Pennsylvania, USA; or PreSep catheter with oximetry, Edwards Lifesciences, Irvine, California, USA) and arterial (Seldicath, Plastimed, Le Plessis Bouchard, France) catheters placed before the beginning of surgery. The central venous line was positioned with the tip within the superior vena cava, and correct positioning was verified by chest radiograph. Until admission to the ICU, anesthesia and surgical procedures were performed according to the local standards. No specific hemodynamic protocol was used during surgery. All patients were admitted to the ICU immediately after surgery and were all managed according to our local standards of care.

Data collection and outcome measures

Standard postoperative monitoring included: electrocardiograph (heart rate), invasive mean arterial pressure, pulse oxymetry and urine output. In all patients, the PCO2 gap, calculated as the difference between central venous partial pressure of carbon dioxide and arterial partial pressure of carbon dioxide, ScvO2, serum lactate level, blood gas analysis, troponin I and routine laboratory tests were obtained by intermittent blood sampling immediately after admission (H0) and repeated 6 (H6) and 12 hours (H12) later. At ICU admission, data on demographics (age, sex, weight), type of surgical procedure, American Society of Anesthesiology Physical Status score, Simplified Acute Physiology Score (SAPS) II [24], presence of catecholamine and the need for mechanical ventilation were recorded in all patients. Postoperative organ failure was assessed using the Sequential Organ Failure Assessment (SOFA) score recorded daily until ICU discharge.

Briefly, the organ failure criteria are:
  • Circulatory failure: use of catecholamine to maintain a mean arterial pressure ≥65 mmHg after a suitable fluid loading.

  • Acute respiratory failure: need for mechanical ventilation or noninvasive ventilation.

  • Acute kidney injury: 1.5-times increase in creatinine serum level or increased creatinine >0.3 mg/dl or urine output <0.5 ml/kg per hour for 6 hours.

  • Neurological impairment: stroke with focal deficit or coma (Glasgow score ≤8) or delirium.

Postoperative complications were assessed in accordance with previously defined criteria [25,26] until hospital discharge or death as follows: postoperative sepsis (pneumonia, intraperitoneal abscess, wound infection, peritonitis and urinary tract infection), acute respiratory failure, acute renal and cardiac failures, postoperative hemorrhage, ischemic events, and postoperative mortality. Patients were followed-up until hospital discharge or death.

Statistical analysis

The study population was divided into two groups according to the occurrence of postoperative complications. Normal distribution of all variables was accessed by graphical methods and the Kolmogorov-Smirnov test. All data are presented as absolute value (%), as mean ± standard deviation or as median (interquartile range) when necessary. Differences between the two groups at baseline were analyzed using the Student’s t test or Mann-Whitney U test for continuous variables, and chi-square test or Fisher’s exact test for categorical variables. A repeated-measure analysis of variance was used to compare variables over time. When the sphericity assumption has been violated as assessed by Mauchly’s test, the degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity. A Bonferroni correction was used for post hoc tests. Univariate analysis was performed to test associations with postoperative complications. A logistic regression was performed for multivariate analysis for all univariate relevant covariates that discriminate between the two groups (P value <0.05 was set as the limit for inclusion). A hierarchical entry method in two blocks was used. In the first block, variables usually known to influence prognosis were entered. In the second block, all other variables were entered. Receiver operating characteristic (ROC) curves were generated to identify optimal cut-off values for outcome associations, and the area under the ROC curve, sensitivity and specificity were calculated. The optimal threshold value from the ROC curves was assessed to obtain the highest Youden index and positive likelihood ratio. A P value less than 0.05 was considered statistically significant. Statistical analysis was performed using the SPSS 17.0 software (Chicago, IL, USA).

Results

Between May 2008 and May 2009, 115 patients who fulfilled the entry criteria were included in the study. Baseline characteristics of the study population are given in Table 1. The median American Society of Anesthesiology Physical Status score was 3.0 (2.0-3.0), mean age was 65 ± 12 years, and 75% were male. At the time of inclusion (T0), the median SAPS II score was 19.5 (15.0-28.7) and the mean ScvO2 and PCO2 gap were 77.3 ± 6.3% and 7.2 ± 3.3 mmHg, respectively. A total of 43% of patients were mechanically ventilated, and 36% received catecholamine infusion. The median duration of mechanical ventilation was 0.0 (0.0-3.0) days. The SOFA scores were 4.0 (1.0-10.0), 4.0 (1.0-8.0), and 4.0 (1.0-8.0) at postoperative days 1, 2 and 3, respectively. The median ICU and hospital length of stays were 6.0 (4.0-8.0) days and 21.0 (15.0-29.0) days, respectively. The 28-day mortality rate was 8% (septic shock, n = 4; acute mesenteric ischemia, n = 2; myocardial infarction, n = 2; massive acute blood loss, n = 1).

Association with outcome

A total of 78 (68%) patients developed postoperative complications during their ICU stay, of whom 57 (50%) patients developed postoperative sepsis and 54 (47%) patients developed organ failure (Table 2). At the time of surgery, patients with postoperative complications were more likely to undergo urgent surgery (Table 3). There were no other statistically significant differences in baseline high-risk criteria between the two patient groups. Patients with postoperative complications were more severely ill on ICU admission (SOFA score: 7.0 (3.0-12.0) versus 1.0 (1.0-2.5), P < 0.001; SAPS II score: 23.0 (16.5-31.2) versus 15.5 (12.0-24.2), P = 0.008), had longer durations of mechanical ventilation (2.0 (0.0-3.0) days versus 0.0 (0.0-0.0) days, P < 0.001) and longer durations of hospital stay (25.0 (20.0-34.0) days versus 14.0 (12.0-160), P < 0.001). On the day of ICU admission, there were statistically significant differences in lactate level (P = 0.006), but not in ScvO2 values (P = 0.17) between patients who did and did not develop postoperative complications. Univariate analysis identified nine variables on ICU admission associated with the occurrence of postoperative complications on ICU admission: lactate level (P = 0.006), troponin level (P = 0.025), bicarbonate level (P = 0.008), arterial O2 saturation (P = 0.026), urine output (P = 0.023), PCO2 gap value (P < 0.001), SAPS II (P = 0.008), SOFA score (P < 0.001) and emergency surgery (P = 0.04). Multivariate analysis showed that a high PCO2 gap (odds ratio = 1.93, 95% confidence interval (CI) 1.36 to 2.75, P < 0.001) and a high SOFA score (odds ratio = 1.52 95% CI 1.14 to 2.02, P = 0.004) at H0 were independently associated with the occurrence of postoperative complications (Table 4). The same results were observed at H6 (data not shown). The area under the ROC curve for the occurrence of postoperative complications was 0.86 (95% CI 0.77 to 0.95) for the PCO2 gap. The area under the ROC curve for organ failure for SOFA score, SAPS II score, lactate level and troponin value were 0.82, 0.67, 0.67 and 0.57, respectively (Figure 1). The optimal PCO2 gap value on ICU admission was 5.8 mmHg (sensitivity 90.7%, specificity 70.0%, positive predictive value 86.6%, and negative predictive value 78.8%) for discriminating between patients who did and patients who did not develop postoperative complications. Of the 54 patients who developed organ failure, 46 had a PCO2 gap ≥6 mmHg. A high PCO2 gap (>6 mmHg) was observed in 68% of the patients upon admission to the ICU after surgery. Compared with patients with a low PCO2 gap on ICU admission, a high PCO2 gap was associated with more organ failure (P < 0.001), and an increase in duration of mechanical ventilation (P = 0.002) and length of hospital stay (P < 0.001) (Table 5). In addition, a high PCO2 gap was associated with a higher 28-day mortality rate (11.5% versus 0%, P = 0.056).
Table 2

Postoperative complications

Variables

 

Sepsis

57 (49.6)

 Pneumonia

37 (32.2)

 Peritonitis

17 (14.8)

 Wound infection

2 (1.7)

 Urinary tract infection

1 (0.8)

Acute renal failure

18 (15.7)

Acute cardiac failure

10 (8.7)

Acute myocardial infarction

5 (6.1)

Pulmonary embolism

3 (2.6)

Hemorrhage

14 (12.2)

Lower limb ischemia

11 (9.6)

Data are presented as absolute values (%).

Table 3

Baseline characteristics of patients who did and did not develop postoperative complications

Variables

Patients with postoperative complications

Patients without postoperative complications

P value

(n = 78)

(n = 37)

Severity scores

   

ASA class

3.0 (2.0-3.0)

3.0 (2.0-3.0)

0.16

 ASA class ≥3 (%)

51 (65)

19 (51)

0.150

SOFA

7.0 (3.0-12.0)

1.0 (1.0-2.5)

<0.001

SAPS II

23.0 (16.5-31.2)

15.5 (12.0-24.2)

0.008

High-risk criteria (%)

   

Age, years

64 ± 13

65 ± 10

0.84

Age ≥70 years

30 (38)

12 (32)

0.53

Severe nutritional problems

8 (10)

3 (8)

1.00

Previous respiratory illness

20 (26)

4 (11)

0.07

Chronic renal failure

5 (6)

1 (3)

0.66

Chronic liver failure

6 (8)

1 (3)

0.43

Ischemic heart disease

32 (41)

19 (51)

0.30

Malignant neoplasia

46 (59)

21 (57)

0.82

Major abdominal surgery

52 (67)

30 (81)

0.11

Prolonged surgery ≥8 hours

6 (8)

3 (8)

1.00

Urgent surgery

19 (24)

3 (8)

0.04

Septic surgery

19 (24)

5 (13)

0.18

Vascular clamping ≥1 hour

4 (5)

0 (0)

0.30

Physiological parameters

   

Mean arterial pressure, mmHg

82 ± 16

85 ± 14

0.30

Urine output, ml/3 hours

266 ± 228

345 ± 258

0.023

Biologic parameters

   

 Serum lactate, mmol/l

1.54(1.1-3.2)

1.06 ± (0.8-1.8)

0.006

 Serum bicarbonate, mmol/l

19.6 ± 4.2

21.4 ± 2.7

0.008

 Hemoglobin, g/dl

10.4 ± 1.8

10.8 ± 1.7

0.39

 Troponin I, ng/ml

0.03 (0.01-0.11)

0.01 (0.00-0.04)

0.025

 Arterial pH

7.33 ± 0.08

7.35 ± 0.07

0.47

 Venous pH

7.28 ± 0.09

7.30 ± 0.06

0.06

 PCO2 gap, mmHg

8.7 ± 2.8

5.1 ± 2.6

<0.001

 PcvCO2, mmHg

46.1 ± 6.7

45.9 ± 6.0

0.92

 PaCO2, mmHg

37.4 ± 6.5

40.7 ± 6.2

0.09

 ScvO2, %

76.3 ± 6.3

78.0 ± 5.2

0.17

 SaO2, %

99.2 (98.4-99.5)

98.8 (98.1-99.2)

0.026

 PaO2, mmHg

145 (116–175)

135 (110–156)

0.05

 PcvO2, mmHg

46.0 (41.7-54.0)

48,0 (40.5-52.0)

0.77

Data are presented as absolute values (%), mean ± standard deviation, or median (interquartile range). Comparison between groups were assessed by Student’s t test or Mann-Whitney U test when necessary. Significant P values are indicated in bold text. ASA, American Society of Anesthesiology physiological status; PaCO2, arterial partial pressure of carbon dioxide; PaO2, arterial partial pressure of oxygen; PCO2 gap, central venous-to-arterial carbon dioxide gradient; PcvCO2, central venous partial pressure of carbon dioxide; PcvO2, central venous partial pressure of oxygen; SaO2, arterial oxygen saturation; SAPS, Simplified Acute Physiology Score; SOFA, Sequential Organ Failure Assessment; ScvO2, central venous oxygen saturation.

Table 4

Logistic regression results: variables associated with the occurrence of postoperative complications

 

B (SE)

Odds ratio

95% confidence interval

P

Constant

−5.61 (3.50)

   

PCO2 gap

0.66 (0.18)

1.93

1.36-2.75

<0.001

SOFA score

0.42 (0.15)

1.52

1.14-2.02

0.004

Lactate

0.38 (0.37)

1.47

0.71-3.02

0.300

SAPS II score

0.04 (0.04)

1.04

0.96-1.13

0.347

Emergency surgery

0.09 (1.17)

1.10

0.11-10.80

0.937

Bicarbonate

−0.07 (0.11)

0.931

0.75-1.16

0.931

Troponin

1.87 (1.47)

6.50

0.36-117.06

0.204

diuresis

0.0003 (0.002)

1.00

0.997-1.003

0.825

Model χ2 = 54.96, P < 0.001, R2 = 0.50 (Hosmer and Lemeshow), R2 = 0.48 (Cox and Snell), R2 = 0.66 (Nagelkerke). Significant P values are indicated in bold text. PCO2 gap, central venous-to-arterial difference in carbon dioxide; SAPS II, Simplified Acute Physiology Score II; SE, standard error; SOFA, Sequential Organ Failure Assessment.

Figure 1

Discriminant factors of postoperative complications. Receiver operating characteristic curve comparing the ability of central venous-to-arterial difference in carbon dioxide (PCO2 gap), Sequential Organ Failure Assessment (SOFA) score, Simplified Acute Physiology Score (SAPS) II score, lactate level and troponin level at baseline to discriminate between patients who did (n = 78) and did not (n = 37) develop postoperative complications. Areas under the curve are 0.86; 0.82; 0.67; 0.67 and 0.57, respectively.

Table 5

Outcome of patients with high and low values of PCO 2 gap on ICU admission

Variables

PCO2 gap ≥6 mmHg

PCO2 gap <6 mmHg

P value

(n = 78)

(n = 37)

Total duration of MV, days

2.0 (0.0-3.2)

0.0 (0.0-0.0)

<0.001

Length of ICU stay, days

6.0 (4.0-8.2)

5.0 (4.0-7.5)

0.287

Length of hospital stay, days

22.5 (17.0-32.2)

16.0 (13.0-23.5)

0.002

Organ failure

46 (59.0%)

8 (21.6%)

< 0.001

28-day mortality

9 (11.5%)

0

0.056

Areas under the curve are 0.86; 0.82; 0.67; 0.67 and 0.57, respectively. Data are presented as medians (interquartile range) or absolute value (%). Significant P values are indicated in bold text. MV, mechanical ventilation; PCO2 gap, central venous-to-arterial difference in carbon dioxide.

Trends in PCO2 gap

Changes in the PCO2 gap and lactate values during the first 12 hours are shown in Figure 2. From H0 to H12, there was a significant difference for mean PCO2 gap (P = 0.001) and mean lactate values (P = 0.003) between patients who did or did not develop postoperative complications. Maximal difference was present immediately after inclusion just after surgery (8.7 ± 2.8 mmHg versus 5.1 ± 2.6 mmHg, P < 0.001). There was a trend towards a decreased PCO2 gap all along the first 12 hours of medical support in the ICU for patients with postoperative complications (P = 0.064). Similar trends were present for the lactate level. There was also a significant difference for mean PCO2 gap (P = 0.003) between patients who developed organ failure and those who did not (Figure 3).
Figure 2

Trends in PCO2 gap and lactate level. (A) Trends in PCO2 gap (mmHg) and (B) trends in lactate level (mmol/l) in patients who did (n = 78; square markers) and did not (n = 37; circle markers) develop postoperative complications. PCO2 gap, central venous-to-arterial difference in carbon dioxide.

Figure 3

Trends in PCO2 gap and organ failure. Trends in PCO2 gap (mmHg) in patients who developed organ failure (n = 54; square markers) and those who did not (n = 61; circle markers). Results are expressed as means ± 95% confidence interval. PCO2 gap, central venous-to-arterial difference in carbon dioxide.

Discussion

The main finding of our study is that a PCO2 gap >6 mmHg at ICU admission following major surgery is predictive of postoperative complications in high-risk surgical patients. Patients with an enlarged PCO2 gap had more organ failure, increased durations of mechanical ventilation as well as length of hospital stay, and a trend towards higher mortality rates, although the latter did not reach statistical significance.

To the best our knowledge, this study is the first to evidence the prognostic significance of an enlarged PCO2 gap at ICU admission in high-risk surgical patients. In patients who developed postoperative complications, the increase in PCO2 gap was maximal immediately after ICU admission and gradually decreased thereafter as a result of medical support. The diagnostic performance of the PCO2 gap is quite similar to the SOFA score with the huge advantage of being measurable at patient admission. In addition, the measurement of the PCO2 gap is much more responsive than the SOFA score and easy to implement at the bedside. These results are supported by the results of a previous study by our group in which an enlarged PCO2 gap was associated with an increased rate of postoperative complications in patients who remained inadequately managed by volume loading during an individualized goal-directed therapy [17]. These results also echo those of previous studies in patients with severe sepsis or septic shock in which a large PCO2 gap was associated with higher rates of organ failure and greater mortality [18,21,27]. In all these studies, the thresholds for PCO2 gap values were around 5 to 6 mmHg, as in our study.

The increase in venous PCO2 would reflect a state of insufficient flow relative to CO2 production [28,29]. Indeed, in an in situ, vascularly isolated, innervated dog hindlimb model, Vallet and colleagues evidenced that the PCO2 gap increased during low blood flow-induced tissue hypoxia (ischemic hypoxia) while it remained unchanged during hypoxemia-induced hypoxia (hypoxic hypoxia) [22]. These results were confirmed in a mathematical analysis model [30] and in in vivo conditions in pig [31] and in sheep [9]. These results are also in agreement with those of Bakker and colleagues [21] who showed that, in patients with septic shock, the PCO2 gap was smaller in survivors than in non-survivors, despite quite similar CO, O2 delivery (DO2) and O2 consumption (VO2) values. In septic shock patients, characterized by an increased PCO2 gap and a low flow state, fluid challenge was found to lower the PCO2 gap while increasing CO [32]. In contrast, no significant changes in CO and PCO2 gap were found in patients with normal PCO2, thus confirming the relationship between an increased PCO2 gap and insufficient flow [32].

In our study, ScvO2 did not allow us to discriminate between patients with and without postoperative complications. These results seem to contradict previous studies. Indeed, recently published data clearly demonstrate that low ScvO2 during and after major abdominal surgery is associated with an increased risk of postoperative complications [7,16,33]. In addition, ScvO2 was part of early goal-directed therapy protocol algorithms that have proven their effectiveness in improving the prognosis of patients [16,34]. As the use of ScvO2 has become increasingly popular in the management of high-risk surgical patients, one part of our patients (at the convenience of the anesthetist in charge of the patient) had already been treated using ScvO2 during surgery before inclusion in the study. The hemodynamics of our patients were in part optimized, as evidenced by ScvO2 values above 70% in both groups. Another point to consider is that sepsis was the main cause of postoperative complications in our study (47%). In this situation where microcirculation failure is frequent, a normal or high ScvO2 value does not preclude tissue hypoperfusion [12,13,35]. According to the modified Fick equation applied to CO2, the PCO2 gap is linearly related to CO2 production (VCO2) and inversely related to CO [29]. In situations where the VO2/DO2 relationship is satisfied, the flow is sufficient to wash out the CO2 produced by the tissue even if there is an additional anaerobic VCO2 [22]. Conversely, when blood flow is low, the PCO2 gap may increase even if there is no increase in VCO2 [31]. Taken together, these factors may explain why, in some of our patients, the PCO2 gap was increased while ScvO2 was normal and ScvO2 failed to predict postoperative complications [36].

Similarly, lactate levels were not an independent factor associated with postoperative complications, unlike the PCO2 gap. This difference is not entirely a surprise since our surgical patients benefited from immediate hemodynamic support in the operating room and intensive care. Therefore, these patients were not necessarily in a decompensated state as evidenced by the small increase in lactate levels (<2.5 mmol/l on average) and ScvO2 > 70% including patients who present with postoperative complications. The increase in PCO2 gap seems only to suggest that there is a hemodynamic optimization margin for these patients. Moreover, the PCO2 gap and lactate levels may reflect different events since lactate clearance is slower than the dynamic and rapid change in PCO2 gap; the lactate level could reflect the hemodynamic state in the last hours of surgery. If there was a significant relationship between the rate of lactate at H0 and intraoperative variables, such as intravenous fluids, blood loss, episodes of low mean blood pressure ≤60 mmHg for more than 10 minutes, and duration of surgery (data not shown), the strength of this association is quite relative, since the correlation coefficients ranged from 0.273 to 0.359. If intraoperative events influenced the lactate levels at postoperative ICU admission, they were not the only explanation.

In this context, when early goal-directed therapy has reached its objectives including ScvO2 > 70%, the PCO2 gap could be a useful additional tool to continue processing hemodynamic optimization. In several studies using a goal-directed therapy in sepsis, it was demonstrated that either lactate clearance or PCO2 gap could be useful for identifying a persistent tissue hypoperfusion even when ScvO2 goals had been achieved [15,18]. In surgical patients, it has been shown that an individualized preload-targeted fluid loading to maintain tissue perfusion was not sufficient to prevent significant differences in outcome [37]. Interestingly, the mean PCO2 gap was larger in patients with complications with a “normalized” DO2/VO2 ratio (ScvO2 ≥ 71%) than in patients without complications, with 5 mmHg as the best threshold value. Associated with these previous studies, our results confirm that the PCO2 gap is a useful and additional tool to detect persistent tissue hypoperfusion. Moreover, the increase in lactate level, another marker of inadequate VO2/DO2 relationship, is often delayed compared to other markers such as ScvO2 [16]. In our study the elevation of the PCO2 gap was very early, starting at patient inclusion. Part of this increase was probably secondary to the intraoperative hemodynamic situation. The PCO2 gap at H0 was significantly higher in patients undergoing intraoperative catecholamine (6.88 ± 3.16 versus 3.02 ± 8.7, P = 0.006), but this effect appears to be limited to the most seriously ill patients (those receiving catecholamines) since there was no correlation between PCO2 gap at H0 and other intraoperative macrocirculatory variables (mean arterial pressure, heart rate, blood loss, fluid loading, blood transfusions, dieresis; data not shown).

Our study has several limitations. First, this was a single-center study involving patients undergoing major abdominal surgery. It is therefore uncertain whether our findings can be extrapolated to other non-abdominal surgery. Second, we are aware that the number of patients was relatively small which could limit the external validity of the study, and that complementary data are needed to confirm the result. Nevertheless, when we considered that one measurement of PCO2 ≥ 6 mmHg at inclusion was associated with the occurrence of postoperative complications, we found a post-hoc power >90%. Third, the use of central venous-to-arterial PCO2 difference as a surrogate for mixed venous PCO2 gap might be a further limitation. Nevertheless, it has been found that central venous PCO2, obtained from a simple central blood sample instead of a pulmonary arterial blood sample, is a valuable alternative to mixed PCO2 and that correlation with CO still exists in this context [38].

Conclusion

This is the first study concerning the usefulness of PCO2 gap in high-risk surgical patients at admission in postoperative ICU confirming previous results established during a surgical period or in septic patients. There is strong support for the use of goal-directed therapy, particularly for fluid resuscitation, with ScvO2 as the cornerstone of these algorithms. However, once these objectives are achieved, the PCO2 gap might be a useful and complementary tool to detect persistent tissue hypoperfusion that could be included as an additional step in the algorithms of early goal-directed therapy protocols. As the design of our study did not formally link the changes in PCO2 gap with tissue hypoperfusion or therapeutic change, further studies are needed to confirm these findings and be extended to other forms of surgery.

Key messages

  • High PCO2 gap values were associated with a higher rate of postoperative complications in high-risk surgical patients.

  • Threshold value is 6 mmHg.

  • In further studies, PCO2 gap could be integrated as an additional step in the algorithms of goal-directed therapy.

Abbreviations

CI: 

confidence interval

CO: 

cardiac output

CO2

carbon dioxide

DO2

oxygen delivery

H: 

hours

O2

oxygen

PCO2

partial pressure of carbon dioxide

PCO2 gap: 

central venous-to-arterial difference in carbon dioxide

ROC: 

receiver operating characteristic

SAPS: 

Simplified Acute Physiology Score

ScvO2

central venous oxygen saturation

SOFA: 

Sequential Organ Failure Assessment

VCO2

carbon dioxide production

VO2

oxygen consumption

Declarations

Authors’ Affiliations

(1)
Department of Anaesthesiology and Intensive Care Medicine, University Hospital of Lille, Lille, France
(2)
Department of Anaesthesiology and Intensive Care Medicine, Hospital Estaing, University Hospital of Clermont-Ferrand, Clermont-Ferrand, France

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Copyright

© Robin et al. 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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