The relationship between blood lactate and survival following the use of adrenaline in the treatment of septic shock.
Adrenaline is a strong agonist for the [alpha], [beta]1 and [beta] receptors with metabolic effects related to [beta] stimulation (11). Its use has been associated with a significant but transient increase in blood lactate concentration, but no attributable mortality difference when compared with noradrenaline (12, 13). Modern theory suggests that the lactate rise may be due the effect of adrenaline on [Na.sup.+]/[K.sup.+] -ATPase activity (14). Experimental data supports the role of adrenaline in inducing hyperlactataemia by binding to muscle [beta]2 receptors and raising AMP production. This leads to the co-ordinated stimulation of both [Na.sup.+]/[K.sup.+] -ATPase and glycogenolysis. ADP is generated, accelerating aerobic glycolysis via phosphofructokinase activation. The glucose substrate required for this is provided by the induced glycogenolysis. In a human septic model, over-production of skeletal muscle lactate is correspondingly blocked by ouabain inhibition of [Na.sup.+]/[K.sup.+] -ATPase (7).
Given our hypothesis that a 'lactate stress test' may reflect underlying metabolic reserve, we conducted a prospective observational study to evaluate the relationship between adrenaline, blood lactate and survival among critically ill adult patients suffering from vasopressor-dependent septic shock.
MATERIALS AND METHODS
Approval for the study was granted by the Human Research Ethics Committee of the University of Witwatersrand, South Africa. Informed consent was obtained from the patient or legal surrogate. The setting was a university affiliated mixed medical-surgical intensive care unit (ICU) in Johannesburg, South Africa.
Inclusion and exclusion criteria
All patients admitted to the ICU over a total period of six months were considered for enrolment. Patients were eligible for the study if they were 18 years and older and had adrenaline therapy initiated or escalated for the management of new onset septic shock more than 24 hours after ICU admission. The diagnostic criteria for sepsis and septic shock used definitions by the American College of Chest Physicians/Society of Critical Care Medicine Consensus Conference (15). Patients with known adrenal disease or secondary hypertension were excluded. No participants were known to be taking monoamine oxidase inhibitors prior to enrolment. Patients in whom dobutamine was used were excluded.
Baseline data collection and fluid therapy
Acute Physiology and Chronic Health Evaluation (APACHE) II scores were recorded for the 24 hours prior to study enrolment (16). Baseline APACHE II scores at ICU admission were used to predict hospital mortality. Fluid therapy received during the observation period was recorded for all but the first 16 participants. The standard crystalloid used in our ICU is Balsol[R] (Fresenius Kabi, Bad Homburg, Germany) which contains no lactate. The standard colloids used are Gelofusine[R] (B. Braun, Melsungen, Germany) and Voluven[R] (Fresenius Kabi, Bad Homburg, Germany). Both contain no lactate.
Adrenaline was the inotrope of choice for septic shock in our ICU. Noradrenaline is not registered with the Medicines Control Council in South Africa. A mean arterial pressure (MAP) target was set by the intensivist with a default target of above 65 mmHg (17). Indications for initiating adrenaline were a MAP below the target that was unresponsive to a 500 ml colloid challenge. If the patient was on adrenaline and the MAP was below the target, the adrenaline dose was escalated, with or without further colloid infusion depending on assessment of fluid responsiveness in that patient. Crystalloid infusion, enteral nutrition and/or parenteral nutrition were continued as usual.
Procedure at adrenaline initiation
A baseline blood sample was collected for initial lactate measurement (LAC1) at initiation of adrenaline as defined above. The adrenaline dose at this point (ADR1) was 0, except for patients already receiving adrenaline. An adrenaline infusion was then commenced or escalated. The dose of adrenaline that achieved the target MAP (ADR2) was then recorded in [micro]g.[kg.sup.-1].[minute.sup.-1]. Blood lactate was then measured two-hourly over the next 24 hours with peak lactate occurring within eight hours in all participants. The peak lactate during this period was recorded as LAC2.
Calculation of lactate index
Lactate index (LI) is an index termed by the authors in an attempt to quantify the increase in lactate over eight hours per dose increase in adrenaline. It is the ratio of the change in whole blood lactate concentration (in mmol x [l.sup.-1]) to the increase in adrenaline dosage (in [micro]g x [kg.sup.-1] x [minute.sup.-1]), represented mathematically as follows:
Ultimately, we postulate that LI is a measure of the ability of the cells enzyme ([Na.sup.+]/[K.sup.+] -ATPase) and metabolic (glycogenolysis) systems to respond to an exogenous stimulus (adrenaline).
Follow-up of patients
Patient survival was followed up to discharge from the ICU. Survival status at this point was recorded.
Values are reported as mean [+ or -] SD for normally distributed data (APACHE II score and LI) with median (IQR [range]) reported for the predominantly non-normal dataset. Non parametric statistical methods were used in bivariate analysis. A Mann-Whitney U test was used to determine differences between survivors and non-survivors (P values from a Student's t-test are also reported for normally distributed variables). Wilcoxon signed rank sum test was used to test the change in lactate and adrenaline dose between time periods. Spearman's rank correlation coefficient (rho) was used to determine the association between lactate and adrenaline dose. A two-tailed P value <0.05 was considered statistically significant. A multivariate model was used to test the association of LAC1, LAC2, [DELTA]LAC, ADR1, ADR2, [DELTA]ADR and LI with hospital mortality. Logistic regression analysis with backward elimination was used with forced entry of age and APACHE II score into the model; variables with P >0.05 were eliminated. To confirm model choice, individual LAC/ADR parameters were entered into a logistic regression model with age and APACHE II score and the likelihood ratio was used to evaluate the overall model fit compared with an intercept-only model. Non-normal variables were log-transformed prior to entry into the model; [DELTA]LAC and ADR1 were not log-transformed due to zero/negative values. The Hosmer-Lemeshow test was used to evaluate goodness of fit; a model with P >0.05 was considered to fit the data well; Nagelkerke's [R.sup.2] is also reported. Data analysis was conducted using SPSS 15.0 (SPSS Inc., Chicago, IL, USA).
Forty-three patients with new onset ICU-acquired septic shock were included in the study with three patients excluded from the analysis due to missing ADR2 data. Patients were initially admitted from trauma (17), general surgery (11), obstetrics and gynaecology (7), internal medicine (3), oncology (1) and vascular surgery (1) services. Admission source and site of infection by ICU survival status are displayed in Table 1. All patients had a minimum of two organ systems requiring support, i.e. respiratory support in the form of positive pressure ventilation and cardiac support in the form of vasopressors. The median age was 32 (21 to 52 [19 to 80]) years and the mean APACHE II score was 24 [+ or -] 7.5. Gender was approximately equivalent; 22 (55%) were male. The mortality at ICU discharge in this study was 52.5% (21/40). Predicted hospital mortality at ICU admission was 44%.
Lactate and adrenaline
The median lactate level before shock treatment with adrenaline (LAC1) was 2.3 (1.5 to 3.9 [0.6 to 10.7]) mmol.l-1. The median dose of adrenaline at this initial point (ADR1) was 0 (0 to 0.10 [0 to 0.63]) [micro]g x [kg.sup.-1] x minute-1.
The median adrenaline dose increased significantly after treatment of shock from 0 (ADR1) to 0.14 (0.08 to 0.36 [0.05 to 0.71]) [micro]g x [kg.sup.-1] x [minute.sup.-1] (ADR2) after the target MAP was achieved (P <0.001). A similar increase in lactate occurred after adrenaline treatment of shock. The median blood lactate concentration increased 26% from 2.3 mmol x [l.sup.-1] (LAC1) to 2.9 mmol x [l.sup.-1] (2.2 to 4.5 [0.8 to10.1]) (LAC2) (P=0.024). The peak lactate (LAC2) correlated with peak adrenaline (ADR2) (rho=0.34, P=0.032). Total fluid received during the data collection period in a subgroup analysis was not statistically different between patients whose lactate increased compared with patients whose lactate decreased or stayed the same (1300 ml vs 1500 ml, respectively, in 24/40 patients, P=0.58).
Age, APACHE II score, [DELTA]LAC and LI were associated with ICU mortality in bivariate analysis (Table 2). Neither initial lactate (LAC1) nor peak lactate (LAC2) was significantly associated with survival. The mean APACHE II values for survivors and non survivors were 21 [+ or -] 6.4 and 27 [+ or -] 7.5, respectively (Student's t-test: P=0.015). Figure 1 shows LI by survival status. The mean LI of survivors was 11.8 [+ or -] 12.4 compared to -2.11 [+ or -] 11.4 for non survivors (Student's t-test: P=0.001). LI was not associated with age (P=0.94) or APACHE II score (P=0.30).
[FIGURE 1 OMITTED]
In multivariate analysis, LI was the only study parameter to remain significantly associated with ICU survival after controlling for age and APACHE II score (Table 3). The Hosmer-Lemeshow statistic for the model is 7.98 (P=0.44) suggesting that the model fitted the data well. When compared with other models containing individual LAC/ADR parameters, the model which included lactate index had the best fit with a likelihood ratio chi-square of 23.63 (P <0.001).
We conducted this study to evaluate the relationship between adrenaline and blood lactate concentration in ICU-associated septic shock. We found a significant positive relationship between peak adrenaline dose and maximum blood lactate concentration. Increases in lactate followed increases in adrenaline with a peak observed within eight hours of therapy initiation or escalation. The variable increase in lactate in comparison to adrenaline dose escalation, as determined by the LI, was significantly associated with survival.
The mortality rate in our study was 52.5%, which is close to the expected mortality of 50% in a group characterised by septic shock (18). Unlike the relationship of APACHE II score with mortality, we could not convincingly show a similar mortality relationship with peak lactate. There was a trend towards a higher initial lactate (LAC1) in nonsurvivors compared to survivors (P=0.072).
The most interesting finding, however, was the relationship between LI and survival. Taking advantage of a potential strong mechanistic link between adrenaline and lactate led us to coin the term 'lactate index' for the ratio of the increase in lactate to the increase in adrenaline. We found that survivors had a significantly higher LI than nonsurvivors. This may suggest that lactate response to [beta]2 stimulation, as opposed to an elevated lactate from cellular hypoxia, is predictive of survival in a critically ill population.
An experimental study using an animal model has shown that adrenaline, but not noradrenaline, increases lactate without a change in lactate to pyruvate ratio. ATP concentrations in the heart, muscle, liver and gut were unchanged, suggesting a non-hypoxic mechanism (19). Sair et al found increased muscle P[O.sub.2] in human septic shock compared to controls, also negating a hypoxic mechanism (20). Similarly, Myburgh et al suggested that the adrenaline-induced hyperlactatemia in human subjects was probably not due to hypoxia, but rather to [beta]2 stimulation12. More recently, Mikkelsen et al showed that initial serum lactate is associated with mortality independent of shock and organ dysfunction (21).
Probably the most daring hypothesis to support our findings is the cell-to-cell lactate shuttle (22). This hypothesis highlights the role of lactate as a fuel. Highly oxidative muscle like the heart may be net consumers of lactate. Although hotly disputed, there is evidence that mitochondria may directly take up and oxidise lactate, without cytosolic conversion to pyruvate. Lactate may therefore compete with glucose as a fuel, and its increase may have physiological benefit. In another animal model, Levy et al have shown how systemic lactate deprivation by selective [beta]2-antagonism and pyruvate dehydrogenase stimulation with dichloracetate resulted in cardiovascular collapse (23). This myocardial energy failure was blunted by lactate infusion.
Several authors have postulated that the human response to sepsis is nonlinear, i.e. the 'whole' is more than the sum of its parts (24-26). Nonlinear systems are composed of many interconnected (mutually dependent) variables. The quantity of these variables may be constantly changing. This results in a complex and dynamic web of interactions. A change in one variable will result in changes in other components and in the interaction between variables. An important property of this system is its ability, through these complex interactions, to generate less disorder. Therefore a small perturbation can cause a large change (the 'butterfly effect'). The properties are called emergent as they materialise at increasing levels of connectivity.
[FIGURE 2 OMITTED]
Consider lactate as a case in point. Over a thousand mmol are produced in an average adult daily, yet the mean blood concentration is less than 2 mmol/l. Lactate depends on numerous factors relating to its production and also its clearance (Figure 2). To look at the lactate concentration and relate it to clinical outcome is simplistic and does not consider lactate in relation to its environment. If we consider that lactate is continuously produced and metabolised depending on a myriad of biological processes including metabolic control mechanisms, oxygen carrier capacity, acid base status, autonomic balance, adequate cardiac output and normal enzyme systems, we see lactate as part of a complex interdependent system.
Lactate index is an attempt to evaluate lactate in terms of some of these inter-relationships. Could LI be one such emergent property? Our study suggests that the ability of lactate production to increase in response to an appropriate stimulus may represent the variability and responsiveness indicative of health reserve. On the other hand, failure to do so may herald disease. As a further hypothesis, could the early lactate clearance associated with survival shown by Nguyen et al (27) represent the ability to utilise lactate as a fuel? Whether a physiological role of lactate can explain the association of endogenous production with survival in our study, or is merely a marker of survival, requires further investigation.
Our study has three important limitations which need to be taken into consideration. First, our survival endpoint was at ICU discharge and whether LI is predictive of 28-day mortality was not determined. Second, this was a small study and further testing of the prognostic ability of the LI in a larger sample is warranted. Utility of the index in all cases of septic shock, not just ICU-associated sepsis, requires further evaluation. Third, this study was observational and all potential confounders were unable to be controlled or adjusted for. In particular, only 24 patients had fluid therapy recorded during the observation period and fluid resuscitation prior to study enrolment was not accounted for. Whether depleted glycogen stores or circulatory insufficiency amongst poor responders could contribute to our findings was unable to be determined.
We have shown that the relationship of lactate to adrenaline is more important than the peak lactate concentration in terms of prognosis for patients with ICU-associated septic shock. We have provided evidence that lactate responsiveness to adrenaline administration is associated with survival, and may be a beneficial and appropriate response in human septic shock. We have also defined an emergent property, the LI, which may serve as a prognostic marker in a critically ill population.
Dr Dulhunty was supported by a Queensland Health clinical research registrar position (2008) and a grant from the Royal Brisbane and Women's Hospital Private Practice Trust Fund (2009) during preparation of this manuscript.
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S. OMAR *, A. T. BURCHARD ([dagger]), A. C. LUNDGREN ([double dagger]), L. R. MATHIVHA ([section]), J. M. DULHUNTY **
Intensive Care Unit, Chris Hani Baragwanath Hospital, University of Witwatersrand, Johannesburg, South Africa
([dagger]) M.B., Ch.B., F.C., Path. (SA) Chem., D.A. (SA), Critical Care (SA), Critical Care Specialist.
([double dagger]) M.B., Ch.B., F.C.A. (SA), Specialist Anaesthetist, Department of Anaesthesia.
([section]) M.B., Ch.B. (Cape Town), D.A. (SA), F.F.A. (SA), Professor of Anaesthesiology, University of Witwatersrand, Chris Hani Baragwanath Hospital. ([section]) M.B., Ch.B., F.C.Paed. (SA), Crit. Care. (SA), Professor of Critical Care,
University of Witwatersrand and Chris Hani Baragwanath Hospital.
**M.B., B.S., M.T.H., Ph.D., Research Fellow, Department of Intensive Care Medicine, Royal Brisbane and Women's Hospital and Burns, Trauma and Critical Care Research Centre, The University of Queensland, Brisbane, Queensland, Australia.
Address for correspondence: Dr S. Omar, email: email@example.com
Accepted for publication on November 25, 2010.
TABLE 1 Admission category and infection site for survivors and non-survivors of ICU admission Characteristic Survivors, Non-survivors, n=19 n=21 Admission source Trauma 7 (41) 10 (59) General surgery 4 (36) 7 (64) Obstetrics and gynaecology 6 (86) 1 (14) Internal medicine 2 (67) 1 (33) Oncology 0 1 (100) Vascular surgery 0 1 (100) Infection site Lung/pleural 7 (54) 6 (46) Abdominal 4 (31) 9 (69) Gynaecologic 5 (83) 1 (17) Central nervous system 0 2 (100) Cardiac 1 (50) 1 (50) Skin 1 (100) 0 Unknown 1 (33) 2 (67) ICU=intensive care unit. TABLE 2 Study characteristics for survivors and non-survivors of ICU admission using the first episode of septic shock after the first day of ICU admission Characteristic Survivors, n=19 Non-survivors, n=21 Median (IQR [range]) Median, (IQR [range]) Age (26 [19-80]) (45 [19-75]) APACHE II score (20 [11-36]) (25 [9-40]) LAC1 (1.8 [0.6-5.7]) (3.0 [1.3-10.7]) LAC2 (2.9 [0.8-10.1]) (2.9 [1.0-8.5]) ALAC (0.9 [-1.4-8.6]) (-0.1 [-2.2-3.1]) ADR1 (0 [0-0.55]) (0.051 [0-0.63]) ADR2 (0.10 [0.050-0.69]) (0.20 [0.050-0.71]) AADR (0.10 [0.022-0.67]) (0.080 [0.013-0.50]) LI (10 [-4.7-40]) (-1.0 [-2.3-22]) Characteristic P value Age 0.019 APACHE II score 0.010 LAC1 0.072 LAC2 0.95 ALAC 0.007 ADR1 0.11 ADR2 0.27 AADR 0.54 LI 0.001 Significance tested by Mann-Whitney U test. ICU=intensive care unit, IQR=interquartile rage, APACHE=Acute Physiological and Chronic Health Evaluation. LAC1=initial lactate ([mmol.l.sup.-1]), LAC2=peak lactate ([mmol.l.sup.-1]), ALAC=difference between initial and peak lactate ([mmol.l.sup.-1]), ADR1=initial adrenaline dose (ug.kg-1.min-1), ADR2=peak adrenaline dose ([micro]g.[kg.sup.-1]. [min.sup.-1]), AADR=difference between initial and peak adrenaline dose ([micro]g.[kg.sup.-1].[min.sup.-1]), LI=lactate index. TABLE 3 Logistic regression model predictive of ICU survival Characteristic OR (95% CI) P value Age 0.94 (0.88-1.00) 0.049 APACHE II score 0.91 (0.79-1.04) 0.17 LI 1.14 (1.04-1.26) 0.007 Nagelkerke's R2=0.60. ICU=intensive care unit, OR=odds ratio, CI=confidence interval, APACHE=Acute Physiology and Chronic Health Evaluation, LI=lactate index.
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|Author:||Omar, S.; Burchard, A.T.; Lundgren, A.C.; Mathivha, L.R.; Dulhunty, J.M.|
|Publication:||Anaesthesia and Intensive Care|
|Date:||May 1, 2011|
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