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Microcirculatory dysfunction in critically ill patients: prevalence and significance from abedside perspective

Vellinga, N.A.R.

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Citation for published version (APA):Vellinga, N. A. R. (2014). Microcirculatory dysfunction in critically ill patients: prevalence and significance from abedside perspective.

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Download date: 11 Aug 2020

CHAPTER 5Mildly elevated lactate levels are associated with microcirculatory abnormalities, organ dysfunction and increased mortalityA microSOAP substudy; in preparation

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ABSTRACT

IntroductionMildly elevated lactate levels, i.e. arterial lactate levels below 2 mmol/L, are increasingly recognized as an important prognostic finding in critically ill patients. One of several possible underlying mechanisms, microcirculatory dysfunction, can be assessed at the bedside by direct observation of the sublingual microcirculation using direct in vivo microscopy.

MethodsThis study is a post-hoc analysis of the Microcirculatory Shock Occurrence in Acutely ill Patients (microSOAP) study, a multicenter international point prevalence study on microcirculatory alterations as assessed with Sidestream Dark Field imaging (SDF). An abnormal microcirculation was predefined as a capillary microcirculatory flow index (MFI) < 2.6. Associations between microcirculatory abnormalities, lactate levels, mortality and organ dysfunction were examined using descriptive statistics and logistic regression analysis.

Results Arterial lactate levels were available for 338 patients, with median APACHE of 16 [11-23] and median SOFA of 5 [3-8] [interquartile range]. Median arterial lactate levels were 1.21 [0.90-2.00] mmol/L. Significant predictors for an abnormal MFI were an arterial lactate level >1.5 mmol/L (OR 2.10, 95%-CI 1.16-3.82, P = 0.015) and a stay in ICU < 24 hours prior to SDF (OR 1.88, 95% CI 1.03-3.44, P = 0.040); the optimal cut-off value for arterial lactate for predicting an abnormal microcirculation was 1.47 mmol/L (sensitivity 58%, specificity 61%). No one-to-one association between an abnormal microcirculation and relative hyperlactatemia was observed. Increases in ICU mortality were observed for every lactate quartile (<0.90 mmol/L: 12.9%; 0.90-1.22 mmol/L: 17.6%; 1.23-2.00 mmol/L: 29.4%; >2.00 mmol/L: 33.7%; P = 0.004). The optimal cut-off value of arterial lactate was 1.42 mmol/L for predicting ICU mortality (sensitivity 65%, specificity 64%). For hospital mortality, similar trends were observed. A higher lactate level was accompanied by a higher SOFA score as well as a higher cumulative vasopressor index (both P < 0.001).

ConclusionsIn a heterogeneous ICU population, mildly elevated arterial lactate levels were associated with decreased microcirculatory perfusion as well as increased mortality and organ dysfunction. Although an abnormal MFI was associated with relative hyperlactatemia, a higher lactate level was not necessarily associated with an abnormal microcirculation or vice versa for individual patients.

Trial registration: NCT01179243

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INTRODUCTION

An elevated lactate level, classically defined as an arterial lactate level > 2 mmol/L, is a well-known predictor of adverse outcome in terms of organ dysfunction and mortality in different subgroups of critically ill patients [1-4]. Surviving Sepsis Campaign guidelines consider a threshold of 1 mmol/L as an indicator of tissue hypoperfusion, but suggest resuscitation to normalize arterial lactate levels in patients with arterial lactate levels > 4 mmol/L in order to improve outcome, based on the principles of early goal directed therapy [5-7]. Similarly, in non-septic patients, the value of lactate levels in goal directed resuscitation is recognized [8-10]. Recent studies indicate that small increases in lactate levels are already associated with an unfavorable clinical course. This association has been demonstrated for “relative hyperlactatemia” with thresholds as low as 0.75 mmol/L [11-15]. Although lactate is easily measured in daily practice, unraveling the underlying causative mechanism is often much more difficult. Organ hypoperfusion is regarded as an important cause of hyperlactatemia, although several other mechanisms also play a significant role, ranging from accelerated aerobic glycolysis to decreased lactate metabolism and mitochondrial and microcirculatory dysfunction [16]. Sublingual direct in vivo microscopy is a suitable method to detect microcirculatory derangement at the bedside [17]. Several studies have reported an association between lactate levels and microcirculatory alterations in subgroups of critically ill patients as well as in experimental settings [18-26]. We previously demonstrated that both microcirculatory derangements and arterial lactate levels were independent predictors of mortality in selected high risk patients. Aforementioned studies have primarily focused on the early phase of ICU admission. The significance of minimally elevated lactate levels as well as concomitant microcirculatory dysfunction at a later time point is unclear. Therefore, we aimed to investigate the significance of a randomly timed arterial lactate measurement and simultaneous in vivo microscopy in a heterogeneous ICU population, recruited from 36 ICU’s worldwide.

METHODS

Patients and settingThis study is a post-hoc analysis of a prospective observational point prevalence study, investigating the prevalence and significance of microcirculatory alterations in a heterogeneous ICU population (Microcirculatory Shock Occurrence in Acutely ill Patients (microSOAP), NCT01179243) [27]. Thirty-six ICUs worldwide participated in this study. Being a point prevalence study, data collection on patient characteristics and laboratory values as well as simultaneous sublingual Sidestream Dark Field (SDF) imaging was performed on a single day for all patients in a given ICU or ICU subunit.

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Sidestream Dark Field (SDF) imaging SDF imaging is a noninvasive technique consisting of a camera incorporated in a handheld device that emits stroboscopic green light with a wavelength within the absorption spectrum of hemoglobin [17]. The light emitted by the SDF camera (MicroScan, Microvision Medical, Amsterdam, the Netherlands) is absorbed by hemoglobin, visualizing erythrocytes as black cells on the screen [28-30]. Offline software-assisted analysis of SDF images (AVA 3.0, Microvision Medical, Amsterdam, the Netherlands) yields information on convective oxygen transport and diffusion distance: the semi-quantitative microvascular flow index (MFI), ranging from 0 (no flow) to 3 (continuous flow), and percentage of perfused vessels (PPV) provide information on convection, whereas total vessel density (TVD) and perfused vessel density (PVD) provide information on diffusion [31]. A single measurement consisting of three sublingual SDF image sequences of 10-20 seconds was obtained for every patient. SDF imaging as well as subsequent image analysis were performed in line with international consensus [28,29].

Statistical analysisAnalysis was focused on associations between lactate levels, mortality, organ dysfunction and microcirculatory alterations. An abnormal microcirculation was predefined as a sublingual microcirculatory flow index (MFI) < 2.6 for vessels < 20 mm, being the lowest reported lower bound of the 95%-confidence interval of healthy volunteers [27,32-35]. This cut-off value has been validated as clinically relevant [36]. Backwards stepwise logistic regression was employed to detect determinants of a capillary MFI < 2.6. Predictors with P<0.25 in univariable logistic regression were used for multivariable modeling. Tested predictors included SOFA score, APACHE II score, length of stay (LOS) in the ICU prior to SDF imaging, hemoglobin, arterial lactate level, heart rate, mean arterial pressure (MAP), fluid balance and vasopressor use. In case of non-linearity of the logit, variables were dichotomized. The resulting models were tested for multicollinearity. Hosmer and Lemeshow goodness-of-fit was used to test the fit of the model. Furthermore, the associations between lactate levels, microcirculatory dysfunction, mortality and organ dysfunction (SOFA, cumulative vasopressor index (CVI [37]) were described by dividing the lactate measurements in quartiles. To determine cut-off values for lactate levels for both abnormal MFI and mortality, area under the curve (AUC) was calculated. To test for differences between normally distributed variables, Student’s t-test or the Mann-Whitney U test was performed. To compare dichotomous variables, Fisher’s exact test was applied. Distributions across more than two groups were tested using the non-parametric Kruskal-Wallis test. The data were analyzed using SPSS 21.0 (IBM, New York, USA) and GraphPad Prism 5.04 (GraphPad Software, Inc., La Jolla, USA) and are presented as the median [interquartile range] or mean ± standard deviation, unless indicated otherwise. A P<0.05 was considered statistically significant.

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RESULTS

General characteristicsOut of 501 patients, arterial lactate levels were available for 338 (67%) of patients. These patients, with median APACHE of 16 [11-23] and median SOFA of 5 [3-8], were included for further analysis (table 1). Surgery (35%) and sepsis (20%) were the main reasons for ICU admission. Median arterial lactate levels were 1.21 [0.90-2.00] mmol/L. ICU and hospital mortality were 23.4% and 31.5%, respectively.

Lactate levels and microcirculatory abnormalities Patients with a capillary MFI<2.6 had significantly higher lactate levels as compared to patients with a higher MFI (1.6 [1.0-2.7] vs. 1.2 [0.9-2.0] mmol/L, P=0.017). AUC was 0.60 (95% CI 0.52-0.69, P = 0.018) with a cut off value for arterial lactate of 1.47 mmol/L (sensitivity 58%, specificity 61%) for predicting an abnormal microcirculation. A non-significant trend towards a higher prevalence of an abnormal microcirculation in higher lactate quartiles was observed (Fig.1, P=0.151). No significant differences with respect to illness severity scores, hemodynamics, vasopressor dose and use, or time in ICU prior to SDF imaging were observed. In multivariable logistic regression analysis the only remaining significant predictors for an abnormal MFI were an arterial lactate level >1.5 mmol/L (OR 2.14, 95%-CI 1.18-3.86, P = 0.012) and a stay in ICU < 24 hours prior to SDF (OR 1.88, 95% CI 1.03-3.44, P = 0.040). AUC for this two-variable model was 0.63 (95% CI 0.54-0.71, P = 0.003). Hosmer and Lemeshow Chi square was 0.106, P =0.0948. Small vessel TVD was higher in patients with arterial lactate level > 1.5 mmol/L (19.54±3.73 vs. 18.53±3.92 mm/mm2, P = 0.037). Small vessel PPV was slightly, but significantly, lower in patients with a higher lactate level (0.97 [0.94-0.99] vs. 0.98 [0.96-1.00], P = 0.022). Values for small vessel PVD and heterogeneity index did not differ significantly between both lactate groups (PVD: 18.78±3.75 vs. 17.89±3.81 mm/mm2, P = 0.059; heterogeneity index: 0.34 [0.00-0.37] vs. 0.34 [0.00-0.37], P = 0.618).

Table 1. Patient characteristics

Age (years) 64 [53-74]

Male sex – no. (%) 198 (59)

APACHE IIa 16 [11-23]

SOFAb 5 [3-8]

ICU mortality – no. (%) 79 (23.4)

In-hospital mortality – no. (%) 106 (31.4)

Reason for ICU admission

Surgery – no. (%) 117 (35)

Sepsis – no. (%) 67 (20)

Cardiac disease – no. (%) 26 (8)

Neurological disorders – no. (%) 35 (10)

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Trauma – no. (%) 32 (10)

Respiratory insufficiency – no. (%) 27 (8)

Other – no. (%) 34 (10)

Arterial lactate (mmol/L) 1.21 [0.90-2.00]

Vasopressive drugs

Patients treated – no. (%) 130 (38)

Cumulative vasopressor indexc 3.4±1.6

Abnormal microcirculation (n, %) 53 (15.7)

MFI small vessels (AU) 2.93 [2.69-3.00]

MFI large vessels (AU) 3.00 [2.93-3.00]

TVD, mm/mm2 (small vessels) 18.93±3.87

PVD, mm/mm2 (small vessels) 18.24±3.80

PPV (small vessels) 0.98 [0.95-0.98]

De Backer score (small vessels) 11.55±2.44

De Backer score (perfused small vessels) 11.12±2.38

Heterogeneity Index (small vessels) 0.34 [0.00-0.37]

Values are mean ± standard deviation or median [interquartile range] unless specified otherwise. aScores on the Acute Physiologic and Chronic Health Evaluation II (APACHE II) scale range from 0 to 71, with higher values indicating more severe disease. bScores on the Sequential Organ Failure Assessment (SOFA) scale range from 0 to 4 for each organ system, with higher scores indicating more severe organ dysfunction.c Trzeciak et al. Intensive Care Med 2008;34:2210-7Abnormal micrcirculation, small vessel MFI < 2.6. MFI, microvascular flow index. Cutoff value for small vessels: < 20 μm. TVD, total vessel density. PVD, perfused vessel density. PPV, proportion of perfused vessels.

Lactate levels and mortalityIncreases in ICU mortality were observed for every lactate quartile (<0.90 mmol/L: 12.9%; 0.90-1.22 mmol/L: 17.6%; 1.23-2.00 mmol/L: 29.4%; >2.00 mmol/L: 33.7%; P = 0.004), see figure 1. AUC was 0.65 (95% CI 0.58-0.72, P<0.001) with a cut off value of 1.42 mmol/L for ICU mortality (sensitivity 65%, specificity 64%). For hospital mortality, similar trends were observed (figure 1). The same cut-off value was seen for hospital mortality with a sensitivity of 60% and a specificity of 65% (AUC 0.63 (95% CI 0.56-0.70), P<0.001). Mortality was at least twice as high for patients with an arterial lactate level >1.5 mmol/L as compared to patients with a lower lactate level: for ICU mortality 35.6% vs. 15.5% and for hospital mortality 44.7% vs. 22.9% (both P<0.001).

Table 1. Patient characteristics. Continued

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Figure 1. Arterial lactate levels (quartiles) and distribution of ICU/hospital mortality and abnormal MFI. P=0.004 for ICU mortality, P=0.003 for hospital mortality, P = 0.151 for abnormal MFI.

Lactate levels and organ dysfunctionA higher lactate level was accompanied by a higher SOFA score (P < 0.001, figure 2). For patients using vasopressors, a higher lactate level was accompanied by a higher CVI (P<0.001, figure 3).

Figure 2. SOFA scores per arterial lactate quartile (P<0.001).

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Figure 3. Cumulative vasopressor index (CVI) per arterial lactate quartile, P<0.001 for distributions over quartiles.

Different phenotypesAlthough an abnormal MFI and elevated lactate levels appear to be associated, several different phenotypes exist. For individual patients, a higher lactate level was not necessarily associated with adverse outcome or an abnormal microcirculation or vice versa, pointing towards a multifactorial etiology and significance of both hyperlactatemia and microvascular derangements (figure 4).

Figure 4. Venndiagram depicting overlap between an abnormal microcirculation and lactate groups.

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DISCUSSION

In the present study, a randomly measured arterial lactate level > 1.5 mmol/L is associated with increased mortality as well as microcirculatory abnormalities and organ dysfunction. This relative hyperlactatemia (i.e. lactate levels < 2 mmol/L) is an emergent concept [11-15]. Lactate levels on admission as low as 0.75 mmol/L appear already associated with adverse outcome [15]. In this respect, it is noticeable that we were able to demonstrate an association between randomly measured lactate levels and increased mortality, albeit for slightly higher lactate levels (> 1.5 mmol/L). The two-fold increase in mortality in patients with a lactate level > 1.5 mmol/L, fits in with previous studies focusing on the first day of ICU admission [13,14]. Only several studies report on lactate levels and its association with outcome during the later phase of ICU stay, showing contradictory results. Hyperlactatemia de novo after initial stabilization has been linked to higher mortality rates, whereas other researchers found that not lactate after initial stabilization but impaired lactate clearance was associated with adverse outcome [38,39]. Not only mortality, but also organ dysfunction in terms of SOFA score appeared to be more severe for increasing lactate levels. A previous study was able to detect associations between incremental lactate levels above 2 mmol/L and SOFA scores [4]. However, this study evaluated the time course of lactate measurements, whereas the present study evaluates the implications of a single lactate measurement. Inotropes have different effects on lactate levels: adrenaline is known for increasing lactate levels, whereas dobutamine is linked to decreases in lactate levels [40,41]. In our analysis CVI did not appear to be associated with an abnormal MFI.

Several mechanisms can result in elevated lactate levels. One of these, microcirculatory flow abnormalities, was indeed associated with relative hyperlactatemia. Relative hyperlactatemia was accompanied by a higher vessel density, whereas perfused vessel density, and therefore effective diffusion distance, did not differ between patients with and without relative hyperlactatemia. Impaired convective oxygen transport, but not diffusion distance might therefore have contributed to anaerobic glycolysis. Several researchers have also observed an association between impairment of microvascular flow and elevations in arterial lactate, whereas others were able to demonstrate associations between lactate levels and PVD, PPV and/or TVD in septic patients, as well as in patients with heart failure, cardiogenic shock or in the perioperative period [18,20-26]. In our patients, capillary recruitment might have been responsible for the absence of a difference in total vessel density between lactate groups [42]. Besides a reduction in microvascular flow, changes in capillary hematocrit (plasma skimming) and capillary oxygen saturation can also exert an influence on convective oxygen transport [43]. Consequently, anaerobic metabolism is promoted, resulting in lactate production. Furthermore, several other factors can lead towards increased aerobic lactate formation under conditions of stress, by promoting conversion of glucose to lactate via pyruvate instead of pyruvate entering the citric acid cycle. Although this conversion yields little ATP (netto 2 ATP per mmol glucose), this reaction enables the cell to provide energy much faster under conditions

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of stress as compared to the aerobic metabolism via the citric acid cycle and oxidative phosphorylation [16,44]. Indeed, lactate formation in endotoxemia predominantly results from increased aerobic lactate formation [45]. On top of that, exogenous adrenergic stress resulting from adrenalin administration can also increase lactate formation [40]. Further stimulation of lactate production follows impairment of oxidative phosphorylation due to mitochondrial dysfunction and changes in pH [46,47]. Other microvascular derangements, such as an injured glycocalyx, might as well influence cellular metabolism [48]. Besides ongoing lactate formation, impaired lactate clearance has to be kept in mind as a cause of relative hyperlactatemia. Levraut and co-workers observed that in stable septic patients in whom arterial lactate levels were below 2 mmol/L after the initial resuscitation phase, impaired clearance of exogenous sodium lactate but not baseline lactate values could discriminate between survivors and non-survivors [38,49]. It is conceivable that a similar mechanism is involved in our patients.

Another finding was that an abnormal MFI was significantly more prevalent in patients with a stay in ICU < 24 hours prior to SDF imaging (22% vs. 13%, P=0.031). This fits in with previous literature indicating that microcirculatory alterations tend to attenuate over time [50-52].

Our study has several limitations. Because of the design of the study, patients with a longer length of stay in ICU before study inclusion are overrepresented. It is imaginable that the present study population is a more severely ill subset. However, in 75% of patients arterial lactate was below 2 mmol/L, so it is likely that the attending physician was not alarmed by this value. The lack of macrohemodynamic monitoring limited in depth statistical analysis of factors associated with relative hyperlactatemia. Furthermore, no detailed information on factors influencing lactate clearance or drugs influencing lactate metabolism (e.g., metformin) was available. Because of the numerous mechanisms underlying elevations in lactate levels, it is not surprising that we did not observe a one-to-one association between an abnormal microcirculation, relative hyperlactatemia and outcome. Specifically, heterogeneity in microcirculation in and between different organs may play a role as well as a multifactorial etiology of lactate formation [50]. Current SDF technology might lack sufficient discriminative ability, which may improve with newly introduced microcirculatory imaging technology [53]. However, ample research demonstrating an association between sublingual microcirculation and outcome as well as lactate levels has been published over the past years [18,20-25,52,54-56]. Serial measurements of both microcirculation and lactate could have shed more light on the time course of organ dysfunction in patients with relative hyperlactatemia [37,57,58].

Although it is clear from the present study and previous research that even lactate levels within the usual reference range are associated with an unfavorable clinical course, the question remains how the clinician has to respond to this in comparatively stable ICU patients. It is difficult to provide a clear answer: in the early phase after ICU admission, incorporating a decrease in lactate levels as a resuscitation goal could lead to better outcomes [6,8]. Which endpoints should be chosen in stable ICU patients and how direct in vivo microscopy can be of help, is a subject for future research.

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