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Time Course of CD64, a Leukocyte Activation Marker, During Cardiopulmonary Bypass Surgery

Djebara, Sarah; Biston, Patrick; Fossé, Emmanuel; Daper, Anne; Joris, Marc; Boudjeltia, Karim Zouaoui; Lelubre, Christophe; Cauchie, Philippe; Piagnerelli, Michael

doi: 10.1097/SHK.0000000000000751
Clinical Aspects
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ABSTRACT Distinction between inflammation secondary to surgery, especially coronary artery bypass graft with cardiopulmonary bypass (CPB), and inflammation due to infection is difficult in surgical intensive care unit (ICU) patients. Development of biomarkers of infection could help clinicians in the early identification and thus treatment of sepsis in these patients. We compared the time course of the neutrophil CD64 index, a high affinity immunoglobulin FC γ receptor I whose expression is increased in bacterial infection, in 39 patients undergoing cardiac surgery with CPB and 11 patients admitted to the ICU with severe sepsis or septic shock. The CD64 index was significantly more elevated in septic patients than in patients who had CPB except at day 5. The CD64 index increased moderately on day 1 after cardiac surgery but the value remained lower than in septic patients. The duration for which the CD64 index was greater than 1.0 was longer in septic than in CPB patients. Receiver operating curves to differentiate CPB from sepsis on day 1 were not significantly different between C-reactive protein (CRP) concentrations and CD 64 index. Nevertheless, combination of low CD64 index with low CRP concentrations on day 1 ruled out sepsis except in three patients. There were no correlations between the CD64 index and cytokine levels (tumor necrosis factor [TNF]-α, interferon [IFN]γ, interleukin [IL]-6, IL-10, IL-8, IL-12) measured in subpopulations. In conclusion, CD64 index only in combination with CRP concentrations could be used to discriminate inflammation due to surgery from that due to infection in this particular population.

*Intensive Care, CHU-Charleroi, Université Libre de Bruxelles, Charleroi, Belgium

Clinical Laboratory, CHU-Charleroi, Université Libre de Bruxelles, Charleroi, Belgium

Anesthesiology, CHU-Charleroi, Université Libre de Bruxelles, Charleroi, Belgium

§Department of Cardiac Surgery, CHU-Charleroi, Université Libre de, Bruxelles, Charleroi, Belgium

||Experimental Medicine Laboratory, ULB 222 Unit, CHU-Charleroi, Université Libre de Bruxelles, Charleroi, Belgium

Address reprint requests to Michael Piagnerelli, MD, PhD, Intensive Care, CHU-Charleroi Marie Curie, Université Libre de Bruxelles, 140, chaussée de Bruxelles, 6042 Charleroi, Belgium. E-mail: michael.piagnerelli@chu-charleroi.be

Received 13 May, 2016

Revised 15 June, 2016

Accepted 6 September, 2016

This work is supported by a grant of the “Commission Scientifique” of CHU-Charleroi.

The authors report no conflicts of interest.

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INTRODUCTION

Cardiac surgery involving cardiopulmonary bypass (CPB) is known to be associated with perioperative inflammatory reactions (1–3), which may be responsible for significant postoperative organ dysfunction and secondary mortality (2). During surgery with CPB, various factors, including some that are material-dependent, can trigger the associated systemic inflammatory response syndrome (SIRS) (1–3). This complex inflammatory response is induced in part by complement activation, release of pro- and anti-inflammatory cytokines (tumor necrosis factor [TNF]-α, interleukin [IL]-1β, IL-2, IL-6, IL-8, and IL-10), leukocyte activation, and expression of adhesion molecules, circulating arachidonic acid metabolites, platelet-activating factors, nitric oxide, and endothelins (1–3). This SIRS is followed by a state of immune hyporesponsiveness with the release of anti-inflammatory mediators, such as IL-10, soluble TNF-α receptors, and IL-1 receptor antagonist (1–3). In addition, perioperative release of endogenous stress mediators, such as corticosteroids and catecholamines, contributes to immunosuppression, which increases the susceptibility to infectious complications in the postoperative course (1). Indeed, infections are among the most common causes of postoperative complications after surgery with CPB but their diagnosis remains challenging, largely because the clinical signs and conventional laboratory biomarkers of infection (white blood cell count, polymorphonuclear neutrophil [PMN] percentage, C-reactive protein [CRP] concentrations, etc.) are poorly specific and thus difficult to interpret in the inflammatory CPB context. Thus, developing specific biomarkers of infection rather than inflammation may be interesting to help diagnose sepsis early and hopefully reduce sepsis-related morbidity and mortality.

The efficient recognition and binding of microorganisms by the host's immune system relies on soluble opsonins bound to the surface of targets. The main opsonins in serum are immunoglobulin (Ig) G and complement fragments (C3b and C3bi), which once attached can be recognized by specific surface receptors of phagocytes and initiate a cascade of biochemical reactions resulting in activation of the phagocyte and killing of the pathogen (4).

Three different types of these receptors—FcγRI (CD64), FcγRII (CD32), and FcγRIII (CD16)—are located on the membranes of PMNs and monocytes and comprise the “Ig superfamily.” Interactions between these receptors and the Fc portion of Ig molecules trigger important biological functions in the cell, such as phagocytosis, activation of the respiratory burst, degranulation, and antibody-dependent cell cytotoxicity (5).

CD64 is a high-affinity receptor for the Fc portion of IgG, which means that it can bind monomeric IgG-1 and IgG-3. CD64 is expressed constitutively in monocytes and macrophages but its expression in PMNs occurs only upon activation (6, 7) induced by inflammatory cytokines, such as IL-12, interferon gamma (IFN-γ), and granulocyte colony stimulating factor (G-CSF), which are produced during infection (6, 7). Therefore, it is expected that the cellular immune response to bacterial infection would involve increased expression of Fc gamma receptors on PMN cells at an early stage of infection (6).

We designed this study to compare the time course of CD64 expression on PMNs in patients undergoing elective cardiac surgery with CPB, a real inflammatory model, and patients with severe sepsis or septic shock. In some of these patients, we investigated the relationship between cytokine levels and CD64 expressed on PMNs. Our hypothesis was that the CD64 index would remain lower in the inflammatory process observed after CPB compared to the inflammation due to infection, as observed in sepsis. If this hypothesis were verified, CD64 expression on PMN cells may be a useful marker to discriminate infectious and non-infectious inflammation.

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PATIENTS AND METHODS

Patients

After approval by the local ethical committee, we conducted a prospective study in the 24-bed medico-surgical intensive care unit (ICU) of the CHU-Charleroi (Charleroi, Belgium). During a 2-year period, we enrolled patients scheduled for cardiac surgery with CPB (CPB group) and patients admitted to the ICU for severe sepsis or septic shock (septic group). This study was divided into two steps and cytokine levels were measured in the second part of the study.

Inclusion criteria for both groups included an age of minimum 18 years and informed written consent by the patient or next of kin. The CPB group included patients undergoing scheduled cardiac surgery with CPB, including coronary artery bypass grafting, valvular, or mixed surgery. The septic group included patients with severe sepsis or septic shock as defined using the international sepsis definitions conference criteria (8). Exclusion criteria for both groups were treatment with recombinant G-CSF or IFN-γ during the month before ICU admission; all hematologic diseases other than neutropenia due to sepsis, including white blood cell, red blood cell, and platelet pathologies; prior corticotherapy of any dose; and a minimum of 7 days free of infection.

Management of the patients in the CPB group was the same throughout the study period: patients received prophylactic perioperative antibiotic treatment (cefazolin) that did not exceed 48 h and was started with the induction of anesthesia. Analgesia after surgery was provided with paracetamol and tramadol. The details of the anesthetic technique are described elsewhere (2) except that sufentanil was used instead of remifentanyl. Corticoids were not used during perioperative management.

During the ICU stay, no routine culture screening was performed, except when the criteria for sepsis were met, in agreement with the Surviving Sepsis Guidelines (9). Patients in the sepsis group were managed according to the Surviving Sepsis Campaign guidelines (9). Patients were excluded if they received hydrocortisone for persistent hemodynamic instability despite adequate fluids resuscitation and vasopressors (9).

We collected demographic data including age, sex, admission diagnosis, APACHE II, and sequential organ failure assessment scores (10, 11). For the CPB group, we additionally collected the European System for Cardiac Operative Risk Evaluation (12), duration of aortic clamp and length of CPB. The length of ICU stay and mortality rates were recorded for both groups.

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Blood sampling and analysis

For all patients, blood samples were taken from an arterial catheter or by venipuncture. Measurements included CD64 expression on PMNs (EDTA tubes: 2.5 mL of blood in 0.06 mL of 0.235 mol/L EDTA, Terumo, Venoject), cytokine measurements (TNF α, IL-1β, IL-6, IL-8, IL-12, IFNγ), and blood inflammatory markers (white blood cell count, PMN percentage, platelet count, CRP, and lactate concentrations).

For the CPB group, blood samples for CD64 expression and cytokine measurements were obtained before cardiac surgery (T-1), at ICU admission (T0) and postoperatively on day 1 (T1) and day 5 (T2). For the septic group, blood was taken during the first 12 h of ICU admission (T0), on ICU day 1 (T1) and on day 5 (T2). Depending on the patient's evolution, T2 could be in the ICU or on the general hospital floor for both groups.

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Measurement of CD64 expression

Expressions of CD64 on PMNs, monocytes, and lymphocytes were measured using quantitative flow cytometry with a flow cytometer (Cell Dyn Sapphire Abbott, Chicago, Ill) using the Leuko 64 assay (Trillium Diagnostics, LLC, Brewer, Maine) within 3 h after blood sampling. This assay is composed of three antibodies (Ab) with specificity for CD64 (clones 22 and 32.2, both fluorescein isothiocyanate [FITC] conjugated) and CD163 (clone Mac2-148, phycoerytrin [PE] conjugated), and a fluorescence bead suspension with three fluorescence signals (green fluorescence due to FITC, orange fluorescence similar to PE, and red fluorescence of starfire red) for unique identification of beads, and used for instrument calibration and standardization to leukocyte CD64 in human blood. Briefly, 50 μL of whole blood, or diluted whole blood to adjust the leukocyte concentration to less than 25 × 109/L, was incubated for 10 min at room temperature with a mixture of murine monoclonal Ab followed by red cell lysis with an ammonium-chloride-based red cell lysis solution (Trillium Lyse). Fluorescence beads were then added and flow cytometer analysis was performed on a minimum of 50,000 leukocytes. PMNs were distinguished from other leukocytes (monocytes and lymphocytes) by their characteristic side scatter. The mean fluorescence intensity (MFI) was measured as a linearized log scale value on lymphocytes (red, negative control, measuring CD64 expression), monocytes (green, positive control, measuring CD64, and CD163 expression), PMN (blue, measuring CD64 expression), and beads (aqua blue, measuring FITC and PE expression). PMNs were distinguished from other leukocytes by their characteristic side scatter.

CD64 index measurements (Leuko 64 Quanti Calc software by Trillium Diagnostics) were derived by the ratio of linearized MFI of the neutrophils to the FITC signal from the beads. Internal negative (lymphocytes with a CD64 index <1.0) and positive (monocytes with a CD64 index >3.0) assay controls were used to validate each sample.

The CD 64 index was measured by two biologists (EF and PC) who were blinded to the clinical data, and the results were provided after the end of the study period.

As the best CD64 index value varies among studies (13–16), we chose as our reference the median value of the CD64 index calculated in the CPB group before surgery (T-1): 0.83 [0.67–1.08].

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Cytokines

In the second part of the study, we measured cytokine levels in CPB (n = 18) and septic (n = 6) patients at each time point. Measurements included IL-6 (Human IL-6 Elisa Set, Bd Biosciences Pharmingen, San Diego Calif; detection limit 7.8 pg/mL), IL-8 (Human IL-8 Elisa Set, Bd Biosciences Pharmingen; detection limit 3.1 pg/mL), IL-10 (Human IL-10 Elisa Set, Bd Biosciences Pharmingen; detection limit 3.9 pg/mL), IL-1β (Human IL-1 β Elisa Set II, Bd Biosciences Pharmingen; detection limit 3.1 pg/mL), TNF-α (Human TNF Elisa Set, Bd Biosciences Pharmingen; detection limit 3.1 pg/mL), IL-12 (Human IL-12 (p70) Elisa Set, Bd Biosciences Pharmingen; detection limit 7.8 pg/mL), IFN-γ (Human IFN-γ Elisa Kit II, Bd Biosciences Pharmingen; detection limit 2.3 pg/mL).

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STATISTICAL ANALYSIS

Values are expressed as median and (25th–75th) percentiles. Pairwise comparisons were made using Mann–Whitney U tests for continuous distributions or chi square tests for categorical distributions. To study inflammation due to CPB or infection, we compared T0 values in both groups. The time course of CD64 was studied using ANOVA on ranks for repeated measures (Friedman test) with post hoc correction for multiple comparisons (Dunn test). Correlation analyses were performed using a Spearman rho test. The diagnostic performance of CD64, CRP, white blood cells, and neutrophils was assessed using receiver operating curve (ROC) analyses. Areas under the ROC curves (AUCs) were evaluated using the trapezoid method (17). Standard errors of AUCs were calculated using the procedure of DeLong et al. (18). Exact confidence intervals for the AUCs were determined using a binomial approach. Using this methodology, we computed AUCs above the reference levels for CD64 index (1) and CRP concentrations (1 mg/dL). All analyses were performed using SigmaPlot version 12.5 (Systat Software, Inc, San Jose, Calif) for Microsoft Windows, and MedCalc Statistical Software version 16.2.0 (MedCalc Software bvba, Ostend, Belgium). A value of P <0.05 was considered significant.

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RESULTS

Patients

Fifty patients (39 in the CPB and 11 in the sepsis groups) were included. Cytokine measurements were made in 18 patients in the CPB group (46%) and 6 patients in the septic group (55%). The clinical and biochemical characteristics of patients are shown in Table 1.

Table 1

Table 1

In the CPB group, 9 patients were admitted for valvular surgery, 20 for coronary artery bypass grafting, and 10 for mixed surgery. Because surgery was scheduled and not emergency, severity scores were low (Table 1).

Among the septic patients, eight had septic shock and three had severe sepsis according to the international sepsis definitions conference criteria (8). All except three of the septic patients were directly admitted from the emergency department. Causes of sepsis were peritonitis and pneumonia each in three patients, pyelonephritis in two patients, septicemia with unknown origin in one patient, urinary infection in one and gastroenteritis in one patient. All the septic patients had microbiologically-proven infection except three, one with gastroenteritis, one with urinary infection (with leukocyturia but negative culture under antibiotic therapy), and the last with peritonitis without positive cultures. Six patients (54%) had bacteremia.

At T0, as expected, the ICU severity scores and the inflammatory parameters (white blood cell count, percentage of PMNs, CRP concentrations, temperature) were significantly increased in septic patients compared with CBP patients. More septic patients had acute renal failure as assessed by the creatinine concentrations (Table 1). Nevertheless, ICU mortality was very low in both groups. All patients except one were on the general floor by T2 in the CPB group and 5 (45%) of the 11 patients in the septic group (Table 1).

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Measurement of the CD64 index

The median value of the CD64 index at T-1 in the CPB group was 0.83 [0.67–1.08]. At T0, the CD64 index was significantly lower in CPB patients than in septic patients (0.92 [0.71–1.14] vs. 3.24 [1.89–8.76]; P <0.001) (Fig. 1).

Fig. 1

Fig. 1

The time course of the CD64 index was different between groups. In the CPB group, the CD64 index increased slightly, with the highest median value measured at T1 (1.31 [0.70–1.79], P <0.001) (Fig. 1). In the septic group, the CD64 index did not significantly increase over time (P <0.05) (Fig. 1) but at T1, the values were significantly higher than those in the CPB group (4.41 [2.48–7.82] vs. 1.31 [0.70–1.79], P <0.001. At T2 the differences were no longer significant (1.32 [1.00–2.72] vs. 1.04 [0.69–1.37], P = 0.09).

In the CPB group, we also compared the distribution of the CD64 index and CRP concentrations during the study period. At T0, T1, and T2, respectively, 5.1%, 23.1%, and 10.3% of the patients had a CD64 index ≥2. By contrast, 25.6% and 51.3% of patients had a CRP value ≥10 mg/dL at T1 and T2, respectively (this value was chosen as the cutoff with the best sensitivity for infection in critically ill patients) (19). If we combined a CRP ≥10 mg/dL and a CD64 index ≥2, no patients met these criteria at T0 and only three (7.7%) at T1 and T2.

We also compared the AUC of ROC curves between CD 64 index and routine laboratory measurements (CRP concentrations, WBC and neutrophils counts) to differentiate CPB from sepsis at T1 (Fig. 2). ROC curves for CD 64 index and CRP concentrations were not significantly different (CD 64 index: 0.906 [0.783–0.972] and CRP concentrations: 0.944 [0.834–0.990]; P = 0.45) but was better than WBC (0.567 [0.413–0.713]; P = 0.04) and neutrophil counts (0.518 [0.366–0.668]; P = 0.009) (Fig. 2).

Fig. 2

Fig. 2

We also measured the duration that the CD64 index was >1.0 (75th percentile of the value measured in CPB patients at T-1) in both groups. This duration was longer in septic than in CPB patients (65.7 ± 16.0 vs. 20.9 ± 2.5 hours; P = 0.001). The same calculation was made for CRP measurements (normal range at our reference laboratory 1.0 mg/dL), with similar findings: duration for septic patients 127.5 ± 62.4 vs. 67.1 ± 36.6 h for the CPB group, P = 0.044.

In all patients combined, CRP concentrations were significantly correlated with the CD64 index at T0: r = 0.65, P <0.00001. There were no other significant correlations with the CD64 index at T0 except for the APACHE II score (r = 0.39, P = 0.007) and the creatinine concentration (r = 0.31, P = 0.03). There were no significant correlations between the CD64 index and other parameters in the two separate patient groups (data not shown).

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Cytokines

At ICU admission

As expected, IL-6, IL-8, and IFNγ concentrations were significantly higher in septic patients than in the CPB group at T0. By contrast, IL-12 concentrations were significantly lower in septic patients (Table 2).

Table 2

Table 2

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Time course of cytokines

The time course of cytokine concentrations is shown in Table 2. For the CPB patients, IL-6, IL-10, IL-8, TNF-α, and IFN-γ concentrations decreased significantly from T0 to T2. IL-1β and IL-12 concentrations did not change over time (Table 2). For the septic patients, all the studied cytokine concentrations remained stable except for IFN-γ concentrations, which increased over time (Table 2).

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Relationship between cytokine concentrations and CD64 index

In the CPB patients, the CD64 index was inversely correlated with IFN-γ concentrations at T-1 (r = −0.57, P = 0.02), with TNF-α at T2 (r = 0.57, P = 0.02) and with IL-6 at T2 (r = 0.68, P = 0.003). There were no other correlations between TNF-α, IL-1, IL-8, IL-10, and IL-12 concentrations and the CD64 index at any time points in either group.

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DISCUSSION

In this study, the CD64 index was significantly higher in the septic group compared with the CPB group except at T2, but at this time point the majority of patients in both groups had been discharged from the ICU to the general floor with a satisfactory evolution (Fig. 1). Interestingly, and in contrast to the majority of studies (14–16, 20), we studied the time course of CD64 index in both groups. We observed a very moderate increase in the CD64 index in the CPB group over time (Fig. 1) but it remained elevated in the septic group during the critical phase of sepsis (T0 and T1) (Fig. 1). These data were confirmed by the duration for which the CD64 index was >1.0. This duration was significantly longer in the septic patients. Interestingly, the mean duration of elevated CD64 index for the CPB group was short (only 20.9 ± 2.5 h), suggesting that not only the absolute value at one moment but also the time course of the CD64 index could be used as a marker of infection. Although the CD64 index had increased moderately in the CPB group at T1, the majority of patients of this group had a CD64 index <2. At T 1, AUCs between CD 64 index and CRP concentrations were not significantly different (0.906 [0.783–0.972] and CRP concentrations: 0.944 [0.834–0.990]; P = 0.45) to discriminate infection. That suggests a low usefulness of CD 64 index measurements alone compared with an inflammatory parameter measured routinely as CRP concentrations. Nevertheless, CRP concentrations were elevated (>10 mg/dL) in approximately 25% of these patients. Combining the CD64 index with CRP concentrations could improve the sensitivity for infection as only 7.7% of patients in the CPB group had elevated values of both markers at this time point.

By T2, the CD64 index was not significantly different between groups. In contrast, CRP concentrations were always elevated in the majority of patients in the CPB group although these patients were not severely ill because a majority of them had left the ICU.

A combination of several biomarkers to diagnose sepsis was already reported in a study by Gibot et al. (13). In this study including 300 patients, these authors created a “bioscore” combining several biomarkers and validated it in a prospective cohort of 79 critically ill patients (13). The biomarkers included the CD64 index, soluble triggering receptor expressed on myeloid cell-1 (sTREM-1), and procalcitonin concentrations. In this cohort of patients suspected of sepsis, the CD64 index, with a cutoff of 1.62, had the highest sensitivity and specificity for a diagnosis of sepsis. However, it was the combination of at least two of the three markers that was able to identify at least 90% of infected patients.

Nevertheless, results of studies evaluating CD64 alone in critically ill patients have been controversial. Indeed, Gros et al. (15) studied 293 patients admitted to the ICU with at least two signs of SIRS. The authors observed significantly higher CD64 indexes and CRP concentrations in patients with bacterial infection compared with patients without infection (for CD64 index: 3.00 [1.49–4.95] vs. 1.06 [0.86–1.62]; and for CRP concentrations: 153 [76–252] vs. 30 [7–97] mg/dL; all P <0.0001) but, as observed in our study, the ROC curves for CD64 index and CRP were not significantly different (0.80 [95% CI 0.75–0.84] vs. 0.78 [95% CI 0.73–0.83], P = 0.6). The authors concluded that the CD64 index had poor sensitivity for bacterial infection, and especially for gram-positive bacteria in their study population (meningitis and bacteremia). They suggest using the CD 64 index with another biomarker such as CRP concentrations (15). Another explanation of the poor sensitivity of the CD64 index to discriminate infection was its rapid decrease after initiation of antibiotherapy. Indeed, Icardi et al. (21) observed a low CD64 index in patients with infection already treated by antibiotics and who had limited systemic symptoms (21). Also in this study, the CD64 index decreased if antibiotherapy was adequate and may provide useful information to the clinician regarding a positive patient evolution (21).

In a larger cohort, Dimoula et al. (22) measured the neutrophil CD64 expression at ICU admission in 468 patients. In the 103 patients with sepsis, CD64 expression was significantly higher than in non-septic patients. The authors identified a cutoff of CD64 expression that identified sepsis with a sensitivity of 89% and a specificity of 87%. Moreover, an abnormal value of the combination of CD64 and CRP concentrations was associated with a 92% probability of sepsis and ruled out the diagnosis with a probability of 99% when both measurements were in the normal range (22). Our results are in agreement with those of Dimoula et al. (22) in that the combination of CRP concentration and CD64 index at a specific time point (T1) helped rule out a diagnosis of sepsis. Another important observation of this study was the increase in the CD64 expression in the 69 non-septic patients at ICU admission who developed a nosocomial infection (sensitivity 88% and specificity 65%). These results could be interesting for patients undergoing CPB who develop an infection. Nevertheless, further studies are needed to confirm the utility of the CD64 index in this particular situation. Moreover, because the authors (22) used the neutrophil expression of CD64, these results should be confirmed with the CD64 index measured using the Leuko 64 assay kit.

A recent meta-analysis that pooled results from eight studies in septic critically ill patients (23), reported a sensitivity of 0.76 (95% CI: 0.73–0.78) and a specificity of 0.85 (95% CI: 0.82–0.87) for neutrophil CD64 expression. These authors concluded that neutrophil CD64 expression could help the clinician in the early diagnosis of sepsis in critically ill patients, but also in association with other markers, medical history, and physical examination (23).

We observed a very low increase in the CD64 index in the CPB group. This result could be explained by the different cytokine concentrations between the groups. IL-12 and IFNγ have been reported as activators of CD64 expression (16, 24) but only concentrations of IL-12 were significantly higher in the CPB group than in the septic group at T0 and we observed a lower CD64 index in the CPB group. These results may perhaps be explained by the limited number of patients included in the analysis of cytokine concentrations and the fact that septic patients were included at T0 (the first 24 h of ICU admission) but the real start of infection and inflammation was unknown. Our results for IL-12 measurements agree with those of Livadati et al. (16). Moreover, Kamisoglu et al. (25) recently observed a biphasic trend in the expression of cytokines in a model of human endotoxemia.

Our study has some limitations. First, the number of patients in both groups was limited but our results for CD64 index, especially in septic patients, are in agreement with other published data (13, 15, 20, 22). In contrast with other studies, our study population was the patients with CPB and not the septic patients who acted as controls. Second, to fully answer the question of whether the CD64 index could be used as a marker for diagnosing infection in CPB patients, we would need a large population of CPB patients who develop sepsis during their evolution. Our results provide preliminary data about the time course of the CD64 index in CPB patients and we observed limited increases in this biomarker (26). Third, combinations with other biomarkers may be more sensitive than just using one biomarker (13, 25, 27).

In conclusion, we report that the CD64 index was lower and increased moderately after CPB compared with patients with severe sepsis or septic shock. The increase in the CD64 index was higher after 1 day of surgery and the mean duration of elevated CD64 index for the CPB group was only 20.9 ± 2.5 h, suggesting that not only the absolute value at one time point but also the time course of the CD64 index could be used as a marker of infection. The CD 64 index alone was not better than CRP concentrations to discriminate infection on day 1. Nevertheless, CD64 index in combination with CRP concentrations could be used to aid in diagnosis of sepsis. Further studies combining CD64 index and CRP concentrations were needed to discriminate inflammation due to surgery from that due to infection in this particular population.

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Keywords:

Biomarkers; cardiopulmonary bypass; CD 64; C-reactive protein; infection; inflammation

© 2017 by the Shock Society