Establishment of a Linear Correlation Model of Central Venous Blood Oxygen Saturation and Lactate in Sepsis

Songchang Shi; Xiaobin Pan; Wei Lin; Chao Wu; Mei Ye; Yingfeng Zhuang; Jian Lin; Xincai Wang; Lihui Zhang; Shujuan Zhang; Hangwei Feng; Long Huang; Songjing Shi; Xingsheng Lin

doi:10.22514/sv.2020.16.0064

Signa Vitae. 2021; 17(1): 101-105. doi: 10.22514/sv.2020.16.0064

Original Research

Establishment of a Linear Correlation Model of Central Venous Blood Oxygen Saturation and Lactate in Sepsis

Songchang Shi¹, Xiaobin Pan¹, Wei Lin², Chao Wu¹, Mei Ye¹, Yingfeng Zhuang¹, Jian Lin¹, Xincai Wang¹, Lihui Zhang¹, Shujuan Zhang¹, Hangwei Feng¹, Long Huang¹, Songjing Shi³^,^*^,, Xingsheng Lin¹^,^*^,

¹Department of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital South Branch, Fuzhou, 350001, P. R. China

²Department of Endocrinolog, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, FuZhou, 350001, P. R. China

³Department of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou ,350001, P. R. China

^*Corresponding Author(s):songjingshifz@163.com (Songjing Shi))xingshenglinfz@163.com (Xingsheng Lin)

History

Submitted: 07 July 2020 | Accepted: 24 August 2020 | Published: 08 January 2021

Copyright:	©2021 The Author(s). Published by MRE Press.
	This is an open access article under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/).

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Abstract

Introduction: Studies have shown that there is a complex relationship between lactate and ScvO $_{2}$ . Methods: A retrospective study was carried out in 37 intensive care patients with sepsis or septic shock. The relationship between lactate and ScvO $_{2}$ was explored with correlation analysis and simple linear modelling. Results: Lactate and ScvO $_{2}$ were significantly correlated in patients with septic shock (r2 = 0.46, p = 0.001; y = -4.11x + 82.62), but not in sepsis. y Significant correlation between these parameters was also found in the group of patients who went on to die (r2 = 0.67, p $<$ 0.01; y = -3.70x + 78.61), but not in patients who survived. Conclusions: In sepsis, the correlation between ScvO $_{2}$ and lactate is not constant over the sepsis course and may be dynamic. In the resuscitation of sepsis and/or septic shock, changes in ScvO $_{2}$ requires further study.

Keywords:Central venous blood oxygen saturation;Lactate;Sepsis;Septic shock

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Cite this article

Songchang Shi, Xiaobin Pan, Wei Lin, Chao Wu, Mei Ye, Yingfeng Zhuang, Jian Lin, Xincai Wang, Lihui Zhang, Shujuan Zhang, Hangwei Feng, Long Huang, Songjing Shi, Xingsheng Lin. Establishment of a Linear Correlation Model of Central Venous Blood Oxygen Saturation and Lactate in Sepsis. Signa Vitae. 2021; 17(1): 101-105. doi: 10.22514/sv.2020.16.0064

1. Introduction

Sepsis and septic shock are common and potentially lethal complications of chronic illness and acute organ dysfunction secondary to infection [1, 2]. Sepsis is a leading cause of mortality and critical illness worldwide [3, 4]. The incidence of sepsis and septic shock in adults ranges from 56 to 91 per 100,000 population per year [5]. Short term mortality is 20–30%, reaching up to 50% in patients with septic shock [6]. Despite improvements in sepsis care, there has been neither a significant increase in the incidence of sepsis nor a significant improvement in outcomes between 2009 and 2014 [7]. This is despite efforts to improve methods of identifying and managing sepsis with the aim of reducing mortality [8].

Studies of the critically ill have shown that lactate can be used as a marker of tissue hypoxia [9]. Another marker is central venous oxygen saturation (ScvO $_{2}$ ), which is a surrogate marker of oxygenation of venous return and hence oxygen delivery and tissue consumption [10]. The relationship between lactate and ScvO $_{2}$ has been shown to be complex [11, 12].

As both lactate and ScvO $_{2}$ are markers of tissue oxygenation [13, 14, 15, 16], it was posited that levels of lactate and ScvO $_{2}$ may be correlated in sepsis and in septic shock. We investigated this in a cohort of patients with sepsis by building a linear correlation model to determine the existence of a correlation between these two markers in sepsis and septic shock.

2. Materials and Methods

2.1 Study population

This was a retrospective study, carried out in the Fujian Medical University teaching hospital. The study was conducted according to the ethical principles for medical research stated in the Helsinki Declaration. The study was approved by the Ethics Committee of the Fujian Provincial Hospital.

Exclusion criteria included pregnancy and patients with advanced tumors or irreversible organ failure.

2.2 Data collection

Sepsis and septic shock were defined according to the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) [17]. Herein, sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Patients with septic shock can be identified with a clinical construct of sepsis with persisting hypotension requiring vasopressors to maintain a mean arterial pressure (MAP) of 65 mmHg and having a serum lactate level of $>$ 2 mmol/L (18 mg/dL) despite adequate volume resuscitation.

All patients were admitted to the intensive care unit (ICU). Within 1 hour of arrival, the subclavian vein was catheterised and blood samples were taken from the subclavian vein, as well as from the radial or femoral artery. Arterial blood lactic acid concentration and central venous oxygen saturation were determined using the GEM Premier 3500 system.

Patients were divided into the sepsis group (Group1_1) or the septic shock group (Group1_2), according to the Sepsis-3 definitions [17]. Patients were further divided according to outcome, into the survival (Group2_1) or the non-survival group (Group2_2).

2.3 Statistical analyses

Data analyses were conducted with SPSS 26 statistical software package (SPSS, Chicago, IL, USA).

First, we performed a missing value analysis of related variables, using the expectation-maximisation (EM) algorithm and regression. Where the Little’s MCAR test did not reach significance ( $α$ = 0.05), those missing values were replaced with the series mean.

Group differences with respect to lactate and ScvO $_{2}$ were tested. Where data were normally distributed, a two-sample t test was carried out (with p $<$ 0.05 representing statistical significance). Where data were non-normally distributed, non-parametric testing was carried out (p $<$ 0.05).

Correlation analysis was then conducted on the consecutive lactate and ScvO $_{2}$ data, by the calculation of the Pearson correlation coefficient (with p $<$ 0.05 representing statistical significance) and by linear regression analysis.

3. Results

37 patients within the sepsis population were included in this study. Patients were aged 29 – 86 years (Table 1).

Table 1.Basic information of the study population.

	Group1 (n = 37)	Group2 (n = 37)
	No shock (n = 17)	Shock (n = 20)	Survival (n = 26)	Death (n = 11)
	(Group1_1)	(Group1_2)	(Group2_1)	(Group2_2)
Ages	64.88 $\pm$ 12.55	65.20 $\pm$ 18.28	69.15 $\pm$ 12.25	55.36 $\pm$ 19.11
Sex	Male:12 (Female:5)	Male:16 (Female:4)	Male:21 (Female:5)	Male:7 (Female:4)
Chronic lung disease	5 (29.4%)	4 (20%)	8 (30.8%)	1 (9.1%)
Chronic heart disease	11 (64.7%)	9 (45%)	16 (61.5%)	4 (36.3%)
Diabetes	4 (23.5%)	6 (30%)	9 (34.6%)	1 (9.1%)
Lung infection	7 (41.2%)	14 (70%)	16 (61.5%)	5 (45.4%)
Abdominal infection	9 (52.9%)	4 (23.5%)	8 (30.8%)	5 (45.5%)
Blood system infection	1 (5.9%)	1 (5%)	1 (3.8%)	1 (9.1%)
Urinary system infection	2 (11.8%)	4 (20%)	4 (15.4%)	2 (18.2%)

3.1 Missing value analysis

There were no missing values of lactate. Six values of ScvO $_{2}$ were identified, with a deletion rate of 16.2%. Statistical analysis of missing variables, by EM and regression, yielded a Little’s MCAR test result of p = 0.799, indicating that the missing value is missing completely at random. The series mean was used to replace these missing values.

3.2 Differences between groups

Data from the sepsis and septic shock groups were found to be non-normally distributed. Two independent sample non-parametric tests were carried out, with the finding that lactate concentrations were significantly lower in the sepsis group compared to the shock group (p $<$ 0.05, one-tailed). No differences of ScvO $_{2}$ saturations were found between groups (p $>$ 0.05, one-tailed) (Fig. 1).

Fig. 1.Comparison of lactate and ScvO between the sepsis group and septic shock group.

Data from the survival and death groups did not conform to a normal distribution, and as such two independent sample non-parametric tests were carried out. Neither lactate nor ScvO $_{2}$ levels were found to be significantly different between groups (p $>$ 0.05, one-tailed) (Fig. 2).

Fig. 2.Comparison of lactate and ScvO between the survival group and death group.

3.3 Linear correlation analysis

Linear correlation analysis of all observed lactate and ScvO $_{2}$ data yielded a Pearson correlation coefficient of r $^{2}$ = 0.37 (p $<$ 0.001). Linear regression produced estimates for the slope and intercept of this linear relationship according to the equation y = -3.30x + 77.01 (Fig. 3).

Fig. 3.Correlation analysis between lactate and ScvO in the sepsis population.

Similar analysis was conducted by subject group. In patients with sepsis, the correlation coefficient of lactate and ScvO $_{2}$ was non-significant (r $^{2}$ = 0, p $>$ 0.05). In the septic shock group, the correlation coefficient of lactate and ScvO $_{2}$ was r $^{2}$ = 0.46 (p = 0.001). The linear equation was y = -4.11x + 82.62 (Fig. 4).

Fig. 4.Correlation analysis between lactate and ScvO in the sepsis and septic shock groups.

In the survival group, linear correlation analysis between lactate and ScvO $_{2}$ was non-significant (r $^{2}$ = 010, p $>$ 0.05). In the death group, the correlation coefficient of lactate and ScvO $_{2}$ was r $^{2}$ = 0.67 (p $<$ 0.01). The linear equation was y = -3.70x + 78.61 (Fig. 5).

Fig. 5.Correlation analysis between lactate and ScvO in the survival group and death group.

4. Discussion

Persistently improving of lactate levels suggests ongoing inadequacy of oxygen delivery. High levels of ScvO $_{2}$ indicate the impaired of the cellular oxygen utilization and microcirculatory, which suggest a systemic oxygen delivery in excess of oxygen demand. Low levels of ScvO $_{2}$ suggest inadequate oxygen delivery for metabolic demands.

Lactate, which is the product of anaerobic metabolism, is considered the biomarker of choice for reflecting the presence of tissue hypoxia [18, 19]. Reduction in ScvO $_{2}$ occurs when oxygen delivery to tissues is reduced and oxygen extraction is increased [20]. Elevated ScvO $_{2}$ suggests a systemic oxygen delivery in excess of oxygen demand, impaired mitochondrial oxygen utilization, and/or microcirculatory shunting. Low ScvO $_{2}$ values imply inadequate oxygen delivery that fails to meet metabolic demands [21].

Early goal-irected therapy (EGDT) for patients with sepsis and septic shock was first implemented by Rivers et al., based on a landmark single center randomized controlled clinical trial (RCT) in which a 16% mortality reduction was achieved by treatment targeting of ScvO $_{2}$ , MAP, central venous pressure and urine output within the first 6 hours after diagnosis [22]. More recently, three multicenter RCTs showed that EGDT did not confer survival benefit compared with usual care for patients with sepsis and/or septic shock, along with suggestions that it should be excluded from the guideline [23, 24]. Interestingly, none of these trials addressed the utility of ScvO $_{2}$ as a target for resuscitation of septic shock [12], because half of the included patients had normal ScvO $_{2}$ at the time of randomization. However, studies have shown that lactate and ScvO $_{2}$ are independent predictors of mortality [25] and that normalization of either or both biomarkers is associated with improved outcomes in sepsis and septic shock [19, 26]. This is consistent with our findings, which demonstrate a complex relationship between lactate and ScvO $_{2}$ . In the implementation of ScvO $_{2}$ to assess the balance between tissue oxygen supply and consumption in sepsis, the choice of time point is crucial [11].

The present study is an analysis of the relationship between lactate and ScvO $_{2}$ in sepsis patients. To our knowledge it is the first analysis of these two markers after stratifying sepsis cases by severity. This study had several limitations, however. First, it is a single-center study including relatively few patients. Second, this study was cross-sectional, so its ability to infer causality is limited.

5. Conclusion

In sepsis, the correlation between ScvO $_{2}$ and lactate is not constant. As the disease progresses, the correlation may be dynamic. Therefore, in the resuscitation of sepsis and/or septic shock, changes in central venous blood oxygen saturation need attention.

Acknowledgments

We would like to thank the participants for providing the information used in this study and for kindly making the arrangements for data collection.

Conflict of interest

The authors declare no conflicts of interest relevant to this article.

List of abbreviations

ScvO $_{2}$ : Central Venous Oxygen Saturation; MAP: Mean Arterial Pressure; ICU: Intensive Care Unit; EGDT: Early Goal Directed Therapy; RCT: Randomized Controlled Clinical Trial

Ethical approval

The study has been approved by the Fujian Provincial Hospital Ethics Committee.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Funding

This study was supported by the Natural Science Foundation of Fujian Province (Grant No. 2019J01175), and the Young and Middle-aged Talents Training Project of Fujian Provincial Health Commission (Grant No. 2018-ZQN-1).

Authors’ contributions

Songchang Shi and Wei Lin performed the statistical analysis and were the major contributors in writing the manuscript. Xiaobin Pan, Chao Wu and Mei Ye interpreted the data. Songjing Shi and Xingsheng Lin reviewed and designed the study. All authors read and approved the final manuscript. Songjing Shi is the guarantor of this manuscript and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

References

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