RELATIONSHIP BETWEEN EXTENDED INFLAMMATORY PARAMETERS OF HEMATOLOGIC ANALYSIS (NEUT-RI, NEUT-GI, RE-LYMP, AS-LYMP) WITH RISK OF INFECTION IN POLYTRAUMA Ustyantseva I.M., Kulagina E.A., Aliev A.R., Agadzhanyan V.V.
Regional Clinical Center of Miners’ Health Protection, Leninsk-Kuznetsky, Russia
Multiple organ failure is the main cause of mortality in polytrauma [1]. Tissue injury and ischemia/reperfusion initiate the cascade of proinflammatory processes in patients with polytrauma – systemic inflammatory response syndrome (SIRS) [2, 3]. Currently it is known that the systemic inflammatory response is required as a part of the initial response to the injury. It often plays the compensatory role and does not allow development of the pathologic process and systemic organic injuries, but uncontrolled SIRS can lead to a subsequent organ injury and multiple organ dysfunction syndrome [4, 5].
Currently, there are a lot of new evidence-based findings, and nobody rejects the presence of the phenomenon of progressing systemic inflammation, but it is only one of possible responses of the macroorganism to infection development. Moreover, the various stages of interaction between the infectious agent and the macroorganism are accompanied by multivariant responses of the mediatory response, and by difficult characterization of the patient’s status at a time [6].
Polytrauma causes the strong destabilization of homeostasis with changes in soluble inflammatory mediators, disordered function of phagocytes, and pathologic responses of hemostasis system. They contribute to immune suppression in severe trauma [1].
Our previous studies showed the high diagnostic sensitivity and specificity of some laboratory tests (increasing blood levels of lactate [7, 8], lipopolysaccharide-binding protein (LPSBP), interleukins-6-8 (IL-6, IL-8), C-reactive protein (CRP), procalcitonin (PCT) [9], and high decrease in apolipoprotein B (ApoB) [10]. It allowed recommending these values as the markers of generalization of the infectious process and development of septic complications.
In our recent study, we published a possibility of new diagnostic extended inflammatory parameters of hematologic analysis (activated neutrophils and lymphocytes) for diagnosis of septic complications in critically ill patients [11].
Currently, there are not any studies estimating the changes in extended inflammatory parameters and their relationship with the risk of infection.
Objective – to estimate the clinical and predictive value of levels of extended inflammatory parameters of hematologic analysis (activated neutrophils and lymphocytes) in development of infection in patients with polytrauma.
The study was conducted in compliance with Helsinki Declare, 2013, and the Rules for Clinical Practice in the Russian Federation (the Order by Russian Health Ministry, 19 June 2003, No.266), with the written consent of patients (or their relatives), and the approval of the ethical committee of Regional Clinical Center of Miners’ Health Protection, Leninsk-Kuznetsky.
The prospective nested study (case-control) was carried out. All required variables for each critically ill patient were extracted from the medical information system (MIS) database of the clinical center.
In clinical conditions, 40 patients with polytrauma were examined. The patients were admitted to the clinic within 2 hours from trauma in January, 2018 to March, 2019 (the table 1).
At admission, all patients showed the traumatic shock of degrees 2-3 (APACHE-III ≥ 80, approximate blood loss – 1,200-1,500 ml, 20-50 % of circulating blood). The individual estimation of blood loss was conducted with summing the external and regional blood loss with consideration of approximate blood loss in fractures.
The inclusion criteria for the study: the age of 18-65, severe associated or multiple injuries, ISS (Injury Severity Score [16]) ≥ 30, absence of lethal outcomes within 21 days.
The study did not include patients who were transferred to other hospital or patients with lethal outcomes within 21 days after admission.
The data on microbiological and clinical infections, and the use of antibiotics were registered daily within 21 days after admission.
SOFA was used for clinical description of patients and for organ dysfunction. Glasgow Coma Scale (GCS) was used for estimation of consciousness disorder. Sepsis-1 [12] and Sepsis-3 [13] criteria were used for identification of sepsis signs.
The duration of stay in the intensive care unit (ICU) was estimated with consideration of days of artificial lung ventilation (ALV) and days in the clinic.
By the end of the follow-up (the day 21), all patients were distributed into two groups. The main group included all cases of infection (infection +) (n = 22; pneumonia, endobronchitis, purulent wounds, osteomyelitis, acute urethritis etc.). The control group included all cases with absent growth of microbial cultures (infection -) (n = 18; acute respiratory distress-syndrome (ARDS), disseminated intravascular coagulation, fat embolism and others).
The classification was performed by two doctors not dealing with treatment of patients. The clinical data was added. A case was considered as infection if its source was found or microbiological data confirmed it, or if microorganisms were found in normally sterile tissues.
The result of the study were compared between the main group (infection +, n = 22) and the controls (infection-, n = 18).
The study program was realized with use of microbiological and laboratory methods on the days 1, 2, 3 and 21 after admission to ICU.
Inoculation of various biomaterials (blood, urine, sputum) was performed for identification of bacterial contamination according to the valid order No.533, Health Ministry of USSR, 22 April 1985. Vitek 2 bacteriological analyzer (bioMerieux, France) was used for identification of microorganisms.
The samples of peripheral venous blood in test tubes with K3EDTA anticoagulant (Becton Dickinson) were studied with Sysmex XN-1000 hematological analyzer (Sysmex Co., Japan) within two hours after collection of samples.
The main parameters were estimated, including the calculation of leukocytes, absolute and relative count of neutrophils, immature granulocytes (IG), and the extended inflammatory parameters (NEUT-GI – neutrophil granulosity intensity; NEUT-RI – neutrophil reactivity intensity; RE-LYMP – count of reactive lymphocytes; AS-LYMP – anti-body synthesizing lymphocytes).
ApoB was measured in simultaneously received blood samples with use of the analytic module platform Cobas 6000 SWA (Switzerland). Serum IL-6 and IL-2R were measured with IMMULITE ONE immunochemiluminiscent analyzer with DPC reagents (USA). pH, pO2, pCO2, glucose and lactate in whole venous blood were measured with Roche Omni analyzer for critical states (Germany).
The statistical analysis was carried out with IBM SPSS Statistics 21 (Statistical Product and Service Solutions – SPSS).
The qualitative signs were presented as absolute and relative (%) values. The quantitative variables were presented as mean arithmetic (M) and quadratic deviation of mean arithmetic values (SD), as Me (LQ-UQ), where Me – median, (LQ-UQ) – interquartile range (IQR) (LQ – 25 %, UQ – 75 % quartiles). Mann-Whitney’s U-test was used for identification of differences in quantitative signs. Fisher’s exact test and χ2-test were used for comparison of qualitative values. Spearman’s rank test (ρ) was used for estimation of correlations between the signs.
Univariate logistic regression was used for analysis of each predictor (activated neutrophils and lymphocytes, interleukins, ApoB, ISS, volume of crystalloids and blood components) and a predicted value of a response variable of infection development. The primary result for inclusion of the variables into the univariate logistic regression analysis was available estimate of incidence of infections in patients with polytrauma.
The discriminative power of the model was estimated with ROC-curve. It was used for estimation of diagnostic efficiency of the tests. Prediction of the random chance creates AUC 0.50, whereas AUC 1.00 – the value of absolute recognition. AUC 0.70-0.79 presents the acceptable recognition in the model for infection prediction, within 0.80-0.89 – excellent.
The critical level of significance (α) for testing the statistical hypotheses was 0.05. If p was less than 0.05, the differences were significant.
RESULTS AND DISCUSSION
High risk of infection in patients with polytrauma
The mean age of the patients (SD) was 41 (16). There were more men (70 %), mainly with associated injuries (88 %). The patients with polytrauma showed the high incidence of registered infections (55 %) (the table 1). The infection appeared approximately 5.5 days after trauma (IQR, 3-9). 29 cultures of microorganisms in the diagnostically significant titer were found in 22 patients. The cultures were extracted from tracheal aspirate, urine, the blood and wounds. They corresponded to diagnosed pneumonia infections, urinary tract infections, and bloodstream infections. Also wound infections and meningitis were found. They were mainly presented by gram-negative bacteria, Escherichia coli and Acinetobacter baumannii (the table 1). Staphylococcus aureus was the cause of three cases of infection. In one patient, it was separated from multiple sources. For some patients, some microbial culture associations were estimated, including additional gram-positive microorganisms, especially Staphylococcus aureus. Three primary infections of Staphylococcus aureus presented approximately 14 % of all identified infections (55 %, the table 1).
Table 1
Patient and Infection Characteristics
|
Patients (n) |
All (40) |
Controls (18) |
Infected (22) |
p |
||
|
Age, years, Ìå (IQR) |
38 (25-55) |
30 (23-16) |
48(29-56) |
0.10** |
||
|
Sex, n (%): |
|
|
|
|
||
|
Male |
28 (70 %) |
13 (72 %) |
15(68 %) |
1.00* |
||
|
Female |
12 (30 %) |
5 (28 %) |
7 (32 %) |
|
||
|
Trauma type, n (%): |
|
|
|
|
||
|
Associated |
35 (88 %) |
14 (78 %) |
21 (96 %) |
0.16* |
||
|
Multiple |
5 (12 %) |
4 (22 %) |
1 (4 %) |
|
||
|
Antibiotic use, n (%) |
|
|
|
|
||
|
First 24 h |
26 (65 %) |
11 (61 %) |
15 (68 %) |
0.74* |
||
|
First week
|
35 (88 %) |
14 (78 %) |
21(95 %) |
0.11* |
||
|
Infection location |
Days after trauma |
|||||
|
|
n |
M (SD) |
Me (IQR) |
|||
|
All |
29 |
7 (5) |
6 (3-9) |
|||
|
Pneumonia |
11 |
8 (6) |
7 (4-9) |
|||
|
Urinary tract infection |
10 |
12 (7) |
11 (6-16) |
|||
|
Bloodstream infection |
5 |
6 (2) |
6 (4-8) |
|||
|
Other infections |
3 |
6 (1) |
6 (5-7) |
|||
|
Isolated organisms |
|
|
|
|||
|
Gram negative |
n |
|
|
|||
|
Escherichia coli |
8 |
|
|
|||
|
Acinetobacter baumannii |
4 |
|
|
|||
|
Enterobacter cloacae |
2 |
|
|
|||
|
Enterobacter faecalis |
2 |
|
|
|||
|
Pseudomonas aeruginosa |
2 |
|
|
|||
|
Klebsiella pneumoniae |
2 |
|
|
|||
|
Bacteroides fragilis |
1 |
|
|
|||
|
Citrobacter koseri |
1 |
|
|
|||
|
Enterobacter aerogenes |
1 |
|
|
|||
|
Proteus mirabilis |
1 |
|
|
|||
|
Serratia marcescens |
1 |
|
|
|||
|
Gram positive |
|
|
|
|||
|
Staphylococcus aureus |
3 |
|
|
|||
|
Staphylococcus epidermidis |
2 |
|
|
|||
|
Fungi |
|
|
|
|||
|
Candida parapsilosis |
1 |
|
|
|||
|
Candida albicans |
1 |
|
|
|||
Note: M (SD) – mean (standard deviation); Me – median, IQR – interquartile range; *Fisher’s exact test and χ2-test; **Mann-Whitney’s U-test.
Patients with post-injury infections with serious physiological disorders within the first 24 hours
The table 2 shows the characteristics of clinical, physiological and laboratory parameters in polytrauma at the moment of admission for hospital treatment in the studied groups.
The clinical characteristics of the first day of admission were analyzed in the main group (infection +, infections by the moment of the day 21) and in the controls (no infection). The patients of the studied groups had the high level of leukocytes and blood glucose, a low level of pH in the blood, and a low ratio ÐàÎ2/FiO2 (the table 2). pH (p = 0.02) and ÐàÎ2/FiO2 (p = 0.03) showed some statistical differences when comparing the groups. The patients of the main group showed the much lower mean arterial pressure in relation to the control values of M (SD): 78 (27) and 100 (p = 0.01), and higher ISS (p = 0.01), APACHE-III (p = 0.01) and SOFA (p = 0.01) (the table 2).
Table 2
Clinical characteristics
|
|
|
Controls (18) |
Infected (22) |
|
|||||
|
Physiology measures |
Mean (SD) |
Median |
IQR |
Mean (SD) |
Median |
IQR |
ð |
||
|
Systolic blood pressure, mm Hg |
129 (18) |
|
|
100 (35) |
|
|
< 0.01 |
||
|
Diastolic blood pressure, mm Hg |
85 (18) |
|
|
67 (24) |
|
|
0.01 |
||
|
Mean arterial pressure, mm Hg |
100 (16) |
|
|
78 (27) |
|
|
0.01 |
||
|
Heart rate, bpm |
103 (18) |
|
|
107 (33) |
|
|
0.63 |
||
|
Temperature, °C |
36.3 (0.6) |
|
|
35.7 (1.2) |
|
|
0.06 |
||
|
Respiratory rate, breaths per min |
|
20 |
18-25 |
|
22 |
15-26 |
0.70* |
||
|
Oxygen saturation, % |
|
99 |
96-100 |
|
96 |
93-98 |
0.04 |
||
|
Clinical scores |
Mean (SD) |
Median |
IQR |
Mean (SD) |
Median |
IQR |
ð |
||
|
Glasgow Coma Scale |
|
15 |
14-15 |
|
12 |
3-15 |
0.06* |
||
|
ISS |
26 (12) |
|
|
35 (11) |
|
|
0.01 |
||
|
APACHE III |
58 (64) |
|
|
80 (78) |
|
|
0.01 |
||
|
SOFA |
5.1 (0,38) |
|
|
6,6 (0,44) |
|
|
0.05 |
||
|
Laboratory measures |
Reference range |
Mean (SD) |
Median |
IQR |
Mean (SD) |
Median |
IQR |
ð |
|
|
Glucose, mmol/l |
6-10 |
|
13.5 |
12.2-16.5 |
14.4 |
|
13.1-18.8 |
0.41* |
|
|
White blood cell count (x109/l) |
4.0-10.6 |
|
15 |
9.8-21 |
|
14 |
12-25 |
0.60* |
|
|
P Platelet count (x109/l) |
150-400 |
|
233 |
201-281 |
|
237 |
159-298 |
0.95* |
|
|
Creatinine, µmol/l |
80-130 |
|
110 |
80-130 |
|
100 |
80-120 |
0.91* |
|
|
Hematocrit, % |
F, 36-48; M, 42-53 |
39 (5.6) |
|
|
39 (5.2) |
|
|
0.95 |
|
|
Arterial blood gas, pH |
7.39-7.42 |
7.33 (0.07) |
|
|
7.26 (0.08) |
|
|
0.02 |
|
|
PaO2/FiO2 |
|
313(137) |
|
|
218 (100) |
|
|
0.03 |
|
|
Fluid resuscitation |
Mean (SD) |
Median |
IQR |
Mean (SD) |
Median |
IQR |
ð |
||
|
Preadmission crystalloid administration, l |
2.3 (1.6) |
1.9 |
1.0-3.3 |
4.0 (1.7) |
3.8 |
2.9-5.2 |
< 0.01 |
||
|
Blood products transfused, l |
|
0.0 |
0.0-12 |
|
2.4 |
1.4-7.8 |
< 0.01 |
||
|
Packed Red Blood Cells transfused, l |
|
0.0 |
0.0-1.2 |
|
2.1 |
1.2-4.5 |
< 0.01* |
||
|
Plasma transfused, l |
|
0.0 |
0.0-0.0 |
|
0.0 |
0.0-2.0 |
< 0.01* |
||
|
Outcomes |
|
Median |
IQR |
|
Median |
IQR |
ð |
||
|
Length of stay, d |
|
11 |
5-15 |
|
30 |
22-54 |
< 0.01* |
||
|
ICU length of stay, d |
|
3 |
1-4 |
|
17 |
12-25 |
< 0.01* |
||
|
Ventilator-dependent days |
|
0 |
0-1 |
|
16 |
9-21 |
< 0.01* |
||
Note: M (SD) – mean (standard deviation); Me – median, IQR – interquartile range; *Fisher’s exact test and χ2-test; **Mann-Whitney’s U-test.
Infected patients with polytrauma require for more hospital recourses
The patients with post-injury infections required for much higher use of hospital resources than the patients without infections. The table 2 shows that the volume of crystalloid solutions was two times higher in the main group than in the control one, M (SD): 4.0 (1.7) l as compared to 2.2 (1.6) l (p < 0.01). Also they required for higher amount of blood components for transfusion (p < 0.01). 27 patients received the blood components, 11 patients – only blood plasma. The patients of the main group showed an increase in hospital period (p < 0.01) as compared to the controls, including ICU stay, and increasing number of ALV days (the table 2).
Preventive use of antibiotics does not depend on cases of identification of infections
According to severity of condition, 65 % of patients with polytrauma (n = 40) received the preventive antibiotics in the first day of admission to the clinic (the table 1). 88 % of the patients received the antibiotics within 7 days after trauma (usually, cephalosporins of the first generation). Even in absence of evident infection, some patients received the complete course of antibiotics. There were not any significant differences in prescription of antibiotics in the main and control groups (the table 1).
Generalized manifestation of systemic inflammatory response
High antigenic stimulation (more intense in presence of infection) of cells producing the monocytic and macrophagic cytokines and neutrophils was testified by a significant increase in IL-6 – 1.8 times on average over the whole period of follow-up (Fig. 1).
Figure 1
IL-6 and IL-2R in blood of patients with polytrauma
Note: # – reliability of differences between the groups at p < 0.05.
The level of soluble receptor of IL-2R was studied as the marker of cellular activation in peripheral blood of critically ill patients. Higher levels of IL-2R in the groups of infected patients over the whole period of follow-up probably cause the lymphocyte hyperproliferation, and cytokine-mediated injury to target organs (Fig. 1). The maximal levels of IL-6 and IL-2R were noted in the first day after trauma.
The relationships of biological inflammatory response in critically states were characterized by a significant decrease in Apo-B in the main group as compared to the control one (p = 0.02, Fig. 2). Moreover, the mean values of Apo-B were lower in the main group.
Figure 2
Apolipoprotein (ApoB) in blood of patients with polytrauma. The data is presented as median, interquartile range and confidence interval (Me, 25-75 %, 95 % CI); p < 0.01 between the groups
Extended inflammatory parameters of hematological analysis
It is known that leukocytes play the key role in inflammatory response and immune response of the body. Therefore, an increase in blood level of leukocytes by means of stab neutrophils within three days testified the early stages of these processes, and stimulation of protective cells of the body to produce and strength the blood levels of acute phase proteins (a table in the figure 4). Subsequently, we noted an increase in blood level of cells of monocytic-macrophage link in patients with infection.
Estimation of functional activity of neutrophils with use of hematological analysis of the extended inflammatory parameters showed the higher intensity of neutrophil reactivity (NEUT-RI) (average increase by 37.1 %, p < 0.001) (Fig. 3) in critically ill patients of the main group, and higher NEUT-GI (by 7 % on average, p < 0.05) (the table in the figure 4).
Figure 3
NEUT–RI diagram in blood of patients in the first 3 days after trauma
Figure 4
ROC of inflammation parameters as predictive markers of infection
Note: AUC – are under curve, CI – confidence interval, OR – odds ratio.
There were not any statistically significant differences in AS-LYMP and RE-LYMP in the patients.
Relationship between inflammatory parameters and risk of infection
For further analysis of a relationship between the inflammation parameters (NEUT-RI) and the risk of infection, we studied the ROC-curves, and post-injury nosocomial infections (Fig. 4). A significant relationship was found between NEUT-RI (p = 0.03), NEUT-GI (p = 0.02) and infection (confirmed by microbiological examination) in later period (Fig. 4).
We matched these findings to other well-known risk factors of infection, including IL-6 (as inflammation marker), ISS, and volume of transfused crystalloids. The figure 4 shows the tested calculations of the area under curve, and p values of each marker.
A relationship between RE-LYMP and infection was not statistically significant for α = 0.05 (p = 0.051) with AUC = 0.69. AS-LYMP was not associated with risk of infection.
The difference in the mean values of NEUT-RI and NEUT-GI was 10 FI and 10 SI. As for NEUT-RI, the increase by 10 FI was associated with increasing probability of infection (relative risk – 1.9; 95 % CI, 1.1-3.6). The absolute increase in NEUT-GI by 10 SI was associated with less significant increase in probability of infection (relative risk – 2.7; 95 % CI, 1.1-6.6). Interleukin-6, ISS, crystalloids and blood transfusion were also associated with increasing probability of infection (Fig. 4). The results show that early changes in NEUT-RI and NEUT-GI were associated with the risk of nosocomial infection in later period. Moreover, the intensity of increasing blood level of inflammation mediators, and functional activity of neutrophils (NEUT-RI and NEUT-GI) can define a degree of severity in critically ill patients.
The main objective of our case-control study was estimation of intensity of differences in extended inflammation parameters of hematological analysis in patients with infection as compared to the patients without infection. We found some differences in such values as NEUT-RI and NEUT-GI in the patients with infections within 21 days after severe trauma as compared to the patients without infection. The data shows that an increase in functional activity of neutrophils was associated with the risk of post-injury infection. Probably, from one side, these changes can show a decrease in immune protection of the body, but, from other side, they are the consequence of changes in metabolism and physiology which promote the worsening of immune protection of the body.
It is known that neutrophils take the leading position in antimicrobial protection. Moreover, in sepsis, the higher role is taken not by general level of neutrophils, but by presence of cellular subpopulation, which phenotype and level of activation stimulate the tissue injury. Conversely, persistent inflammation can lead to a decrease in sensitivity of neutrophils to complement components, resulting in contagion [14]. As result, timely estimation of functional activity of neutrophils is the same important as quantitative values [15-17].
CONCLUSION
Therefore, the identified significant relationship between the extended inflammatory parameters of hematologic analysis (NEUT-RI and NEUT-GI) and risk of infection in critically ill patients shows the diagnostic and predictive significance of these values, and possibility for their use as early markers of infectious complications. Monitoring of NEUT-RI and NEUT-GI allows estimating the intensity of systemic response and generalization of the infection process.
Information on financing and conflict of interest
The study was conducted without sponsorship. The authors declare the absence of any clear or potential conflicts of interest relating to this article.