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Prognostic Relevance of Altered Lymphocyte Subpopulations in Critical Illness and Sepsis


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Lymphopenia and functional defects in lymphocytes may impact the prognosis in patients with critical illness or sepsis. Therefore, we prospectively analyzed peripheral blood leukocytes from 63 healthy volunteers, 50 non-critically ill standard care (SC) patients with infections, and 105 intensive care unit (ICU) patients (52 with sepsis, 53 without sepsis) using flow cytometry. Compared to healthy volunteers, SC and ICU patients showed significant leukocytosis, especially in sepsis, while lymphocyte numbers were significantly decreased. All major lymphocyte populations (B, T, and natural killer (NK) cells) decreased in ICU patients. However, we observed a relative reduction of T cells, alongside decreased CD8+ T cells, in critically ill patients, independent of sepsis. High absolute T cell counts (>0.36/nL) at ICU admission were associated with a significantly reduced mortality, independent of patient’s age. Moreover, patients that survived ICU treatment showed dynamic changes within 48 h towards restoration of lymphopenia and T cell depletion, while non-surviving patients failed to restore lymphocyte counts. In conclusion, the flow-cytometric analysis of peripheral blood revealed striking changes in circulating lymphocyte subsets in critically ill patients, independent of sepsis. Lymphopenia and T cell depletion at ICU admission were associated with increased mortality, supporting their relevance as predictive biomarkers and potential therapeutic targets in intensive care medicine.
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J. Clin. Med. 2019, 8, 353; doi:10.3390/jcm8030353
Prognostic Relevance of Altered Lymphocyte
Subpopulations in Critical Illness and Sepsis
Philipp Hohlstein 1, Hendrik Gussen 1, Matthias Bartneck 1, Klaudia Theresa Warzecha 1,
Christoph Roderburg 1, Lukas Buendgens 1, Christian Trautwein 1, Alexander Koch 1 and
Frank Tacke 1,2,*
1 Department of Medicine III, RWTH-University Hospital Aachen, 52074 Aachen, Germany; (P.H.); (H.G.); (M.B.); (K.T.W.); (C.R.); (L.B.); (C.T.); (A.K.)
2 Department of Gastroenterology/Hepatology, Charité University Medical Center Berlin,
13353 Berlin, Germany
* Correspondence: &
Received: 8 February 2019; Accepted: 9 March 2019; Published: 12 March 2019
Abstract: Lymphopenia and functional defects in lymphocytes may impact the prognosis in patients
with critical illness or sepsis. Therefore, we prospectively analyzed peripheral blood leukocytes
from 63 healthy volunteers, 50 non-critically ill standard care (SC) patients with infections, and 105
intensive care unit (ICU) patients (52 with sepsis, 53 without sepsis) using flow cytometry.
Compared to healthy volunteers, SC and ICU patients showed significant leukocytosis, especially
in sepsis, while lymphocyte numbers were significantly decreased. All major lymphocyte
populations (B, T, and natural killer (NK) cells) decreased in ICU patients. However, we observed
a relative reduction of T cells, alongside decreased CD8+ T cells, in critically ill patients, independent
of sepsis. High absolute T cell counts (>0.36/nL) at ICU admission were associated with a
significantly reduced mortality, independent of patient’s age. Moreover, patients that survived ICU
treatment showed dynamic changes within 48 h towards restoration of lymphopenia and T cell
depletion, while non-surviving patients failed to restore lymphocyte counts. In conclusion, the flow-
cytometric analysis of peripheral blood revealed striking changes in circulating lymphocyte subsets
in critically ill patients, independent of sepsis. Lymphopenia and T cell depletion at ICU admission
were associated with increased mortality, supporting their relevance as predictive biomarkers and
potential therapeutic targets in intensive care medicine.
Keywords: ICU; adaptive immunity; mortality; prognosis; flow cytometry
1. Introduction
Inappropriate systemic inflammation is a key characteristic in critically ill medical patients
admitted to the intensive care unit (ICU) [1], especially in patients with sepsis [2]. In fact, sepsis is
nowadays defined as a dysregulated host response to an infection causing a life-threatening organ
dysfunction [3]. Interestingly, patients with sepsis typically display defects in innate as well as
adaptive immunity [4]. While leukocytes and systemic cytokines are highly prevalent during the
onset of sepsis [5], granulocytes have an immature phenotype that suppresses adaptive immunity
(oftentimes termed “myeloid-derived suppressor cells”) [5]. Because of this immune-suppressive
myeloid phenotype, lymphocytes likely upregulate markers of cell exhaustion [6] and are unable to
mount proper cytokine responses [7]. Altogether, these features of immunosuppression have been
convincingly linked to the risk of sepsis and organ failure in patients with infections [8] as well as to
increased mortality due to sepsis [7]. The assessment of the granular characteristics of immune cells
J. Clin. Med. 2019, 8, 353 2 of 11
from peripheral blood leukocytes by flow cytometry has been proposed and validated in multicentric
analyses to identify patients at risk for deterioration [8,9]. Moreover, the in-depth understanding of
immune pathogenesis may offer novel, tailored therapeutic interventions in intensive care medicine [10].
Lymphocytes have long been recognized as a key component of dysregulated immune
responses in critical illness and particularly in sepsis [6,11]. An effective functioning pool of
lymphocytes is essential to control and then eradicate infections [4]. For instance, CD4+ T cells are
activated in response to antigen presentation by dendritic cells or monocytes, release immune-regulatory
cytokines, and orchestrate cytotoxic CD8+ T cell functions [4]. Natural killer (NK) cell subsets
contribute to cytotoxic and cytokine-releasing activities [12], and B cells support humoral immune
responses [4]. At the onset of sepsis, lymphocyte numbers are typically low [6]. During the acute phase of
sepsis (i.e., the first seven days in patients), lymphocytes—T cells in particular—upregulate the inhibitory
receptors cytotoxic T lymphocyte antigen-4 (CTLA4), T cell immunoglobulin mucin-3 (TIM-3),
lymphocyte activation gene 3 (LAG-3), or interleukin-7 (IL-7) receptor [6]. Recovery from these
immune cell alterations is generally associated with a favorable outcome [4].
Many of the mentioned studies have used sophisticated staining panels for leukocyte subset
activation markers and/or ex vivo stimulation of lymphocytes to assess, for instance, cytokine release
by T cells. While these studies have generated insightful data on the pathogenic involvement of
leukocyte subsets in the course of sepsis, they are technically demanding, which limits their
practicability in clinical routine. In addition, most experimental data were generated in patients with
either infections or sepsis, while the role of leukocytes and, particularly, of lymphocyte subsets in non-
septic critical illness is less clear. In our prospective, mono-centered cohort study, we therefore
addressed the following aims: (a) assess the composition and clinical relevance of leukocytes and
lymphocyte subsets using a straightforward flow-cytometric subset characterization in critically ill
patients with and without sepsis, and (b) test whether lymphocyte subsets obtained at ICU admission
and 48 h later hold prognostic value in critically ill medical patients in general.
2. Experimental Section
2.1. Patients and Controls
This study was approved by the local ethics committee (EK 150/06) of the University Hospital
Aachen, RWTH Aachen, and written informed consent was obtained from every participant or
authorized relatives in case of loss of consciousness. Critically ill patients were prospectively
included between October 2013 and March 2015 from the intensive care unit and standard care wards
of the Department of Medicine III of the RWTH University Hospital in Aachen, following an
established protocol [13,14]. Septic ICU patients had a clinically suspected or verified infection
diagnosed by the intensive care physicians and were subsequently treated with antibiotics. Sepsis
was established following a diagnosed infection and an increase in the Sepsis-related Organ Failure
Assessment (SOFA) score greater than or equal to two points [3]. Non-critically ill patients, admitted
because of infectious diseases to the standard care ward, served as a diseased control population.
Those patients were admitted to the hospital following a diagnosis of infection by the treating
physician (based on clinical judgment, laboratory results, and/or microbial cultures) and received
antibiotic therapy. Healthy volunteers from the local blood transfusion institute served as a healthy
control population. Blood samples of the recruited patients were obtained by peripheral
venipuncture or from inlying central venous or arterial catheters at admission and 48 h after
admission. Adding 250 units of heparin (Rotexmedica, Frittach, Germany) per milliliter blood
prevented coagulation of the blood samples.
2.2. Isolation of Peripheral Blood Mononuclear Cells
Peripheral blood mononuclear cells (PBMC) were isolated by using a Ficoll-based density
gradient. Blood and cells were kept at 4 °C during the whole procedure to ensure minimal cell
activation. Whole blood was mixed with an equal amount of phosphate-buffered saline (PBS, PAN
Biotech Aidenbach, Germany), then carefully manually layered over 1077 Lymphocyte Separation
J. Clin. Med. 2019, 8, 353 3 of 11
Medium (PAA, Pasching, Austria), followed by a centrifugation at 1600 rpm for 40 min without the
use of a brake at room temperature. The intermediate layer containing the PBMC was then carefully
harvested, washed with PBS, and centrifuged at 1300 rpm for 10 min three times. Subsequently, the
cells were resuspended in PBS and counted using a Neubauer chamber for antibody staining.
2.3. Flow Cytometry
Two million cells were resuspended in PBS and blocking buffer (2% bovine serum albumin, 2%
rabbit serum, 2% human serum, 2% mouse serum, 2% rat serum) to block unspecific binding of
antibodies. PBMC were stained with fluorescence-conjugated antibodies (CD14, CD56, CD45, CD3,
CD4, CD19 by eBioscience; CD16, CD8 by BD Pharmingen). After 30 min of light-protected
incubation, the cells were washed, centrifuged, and subjected to flow-cytometric analysis using a
FACS Canto-II (BD, Heidelberg, Germany). In a subsequent analysis using FlowJo software (TreeStar
Inc., Ashland, OR, USA), cell populations were defined after exclusion of doublets by antibody
positivity in the following manner: T cells as CD3+CD56- (subsequent analysis for CD4 and CD8),
natural killer cells as CD3-CD19-CD56+ (subsequent analysis of CD16 and CD56), and B cells as CD19+.
Absolute cell numbers were calculated on the basis of automated differential white blood cell counts.
2.4. Statistical Analysis
Data were analyzed using SPSS (version 22, IBM Corp., Armonk, NY, USA) and GraphPad Prism 5
(GraphPad Software, Inc., La Jolla, CA, USA). As a normal distribution of samples could not be
assumed, the Kruskal–Wallis test followed by a post hoc testing by Dunn’s multiple comparison test
was used for more than two groups, the two-tailed Mann–Whitney U test was used for two groups
of unpaired samples, and the two-tailed Wilcoxon signed rank test was used for paired samples. A
significance level of α = 0.05 was used in all corresponding calculations. Associations with survival
were assessed by multivariate Cox regression, and patient survival was depicted by Kaplan–Meier
curves using SPSS. The Youden index was calculated to identify the optimal cut-off values for
parameters to discriminate prognosis [15]. Correlations of lymphocyte subpopulations to clinical or
laboratory parameters and to age as a potential confounding factor were analyzed by Spearman’s
rank correlation test. To control for age as a confounding variable, all analyses comparing different
subgroups were also performed with age-matched study populations.
3. Results
3.1. Peripheral Blood Leukocytosis and Lymphopenia are Characteristics of Critical Illness
The numbers and composition of circulating leukocyte subsets might be related to the severity and
the clinical course of critical illness [9]. We therefore prospectively enrolled 63 healthy controls (HC), 50
standard care (SC) patients with ongoing infection diagnosed less than 24 h before, and 105 intensive
care unit (ICU) patients submitted to the ICU less than 24 h before (Table 1), in order to conduct a
detailed flow-cytometric analysis of circulating leukocytes. Among the ICU patients, n = 52 (49.5%)
had been admitted because of sepsis. Compared to healthy volunteers, patients in SC or ICU wards
showed a significant increase in leukocytes (Figure 1A), which was expectedly pronounced in
critically ill patients with sepsis (Table 1). On the contrary, the absolute numbers of lymphocytes were
significantly decreased in infected SC and in ICU patients (Figure 1A).
Table 1. Characteristics of healthy volunteers, standard care patients with bacterial infections, and
intensive care patients.
Parameter HC SC ICU ICU: No Sepsis
ICU: Sepsis
63 50 105 53 52
Sex (male/female)
37/26 33/17 66/39 35/18 31/21
Age (years) 48 (22–77) 66.5 (21–90) 66 (18–97) 60 (23–92) 68 (18–97)
RBC (per nL) 4.8 (4.2–6.7) 4.15 (2.2–6.2) 3.5 (2–9.4) 3.7 (2–6.3) 3.4 (2.1–9.4)
Hemoglobin (g/dL) 14.1 (12–16) 12.5 (7.1–17.5) 10.2 (5.6–16.1) 10.8 (5.6–15.5) 9.55 (6.2–16.1)
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Hematocrit (%) 41.4 (36.1–46.1)
36.9 (23.7–51.3)
30.9 (16.6–50.5)
32 (16.6–50.5) 29.8 (19.1–50.3)
WBC (per nL) 5.8 (3.7–10) 9.2 (1.7–23) 13.5 (0.5–42.9) 10.6 (2.7–31.4) 15.4 (0.5–42.9)
Lymphocytes (per nL) 1.86 (0.72–3.13)
0.75 (0–3.46) 0.64 (0–6.86) 0.75 (0–3.46) 0.53 (0.02–6.86)
B cells (per nL) 0.13 (0.04–0.60)
0.066 (0–0.55) 0.088 (0–1.40) 0.10 (0–0.66) 0.064 (0–1.40)
T cells (per nL) 1.34 (0.27–2.54)
0.66 (0.09–2.67)
0.43 (0–3.28) 0.51 (0–2.09) 0.34 (0.01–3.28)
NK cells (per nL) 0.26 (0.08–0.78)
0.11 (0.01–0.79)
0.084 (0–2.59) 0.10 (0–1.65) 0.053 (0–2.59)
The median and range are given, unless indicated otherwise. The two right columns differentiate the
characteristics of ICU patients with or without sepsis. Abbreviations: WBC: white blood cell count,
RBC: red blood cell count, HC: healthy control, SC: standard care patients, ICU: intensive care unit
NK cells: natural killer cells.
We next focused on the different lymphocyte populations in peripheral blood and determined
the composition of lymphocyte subsets both as absolute numbers (per nL blood) and by their relative
contribution to the circulating lymphocytes (Figure 1B). NK as well as B cells declined by absolute
numbers in SC and ICU patients compared with HC, and T cells were even reduced in the lymphocyte
pool. On the contrary, B cell numbers decreased in SC and ICU patients as well but constituted a
larger proportion of lymphocytes in critically ill patients (Figure 1B). For further analysis,
subpopulations of T and NK cells were studied in order to assess CD4- and CD8-positive T cells as %
of T cells (Figure 1C), and CD56brightCD16- versus CD56dimCD16+ NK cell subpopulations, respectively
(Figure 1D). In ICU patients, CD8+ T cells were particularly reduced, while CD4+ T cells accounted
for the vast majority of circulating T cells in all cohorts (Figure 1E). Regarding NK cell subsets,
CD56dimCD16+ NK cells were moderately reduced in ICU patients, while CD56brightCD16- cells
remained unchanged (Figure 1F).
To analyze the possibility of age as a confounder in the determination of the different leukocyte
populations, we performed a correlation analysis (Spearman’s rho correlation test), which revealed
an inverse correlation between age and leukocytes and positive correlations between age and
lymphocytes, B, T, and NK cells over the whole study population (i.e., control populations and ICU
patients combined, data not shown). To control for age as a potentially confounding variable, we
generated age-matched populations (HC n = 33, SC n = 33, ICU n = 81; median age 58.5 years), maintaining
the original case–control distribution. The same analyses as seen in Figure 1 were performed on an age-
adjusted study cohort with mean age of 58 to 59 (data not shown). Age did not differ across the patient
cohorts (p = 0.518) in these age-adjusted cohorts. The significant differences depicted in Figure 1 were
overall retained in age-adjusted subgroups, except for the difference in B cells per nL between HC
and ICU patients (which were not significant anymore).
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Figure 1. Leukocytes and lymphocyte subsets in healthy volunteers, standard care patients with
infection, and intensive care patients. Leukocytes were harvested from peripheral blood using
density-gradient centrifugation and subjected to flow cytometry. (a) A representative forward vs
sideward scatter plot of the different cell types from whole blood is shown. The distributions of
leukocytes and lymphocytes in the different patient cohorts are shown as box plots. Dots indicate
outliers. (b) Circulating B, T, and NK cells are depicted by box plots as absolute cells counts and as
percentage of all lymphocytes. (c,d) Representative FACS plots to identify CD4- and CD8-positive T
cells (c) pregated on CD3+CD56- lymphocytes as well as CD56- and CD16-expressing NK cells (d)
pregated on CD3-CD56+ lymphocytes. (e) Percentages of CD4- and CD8-positive T cells. (f)
Percentages of CD56brightCD16- and CD56dimCD16+ NK cells. Statistics: * indicates p < 0.05, ** p < 0.01,
*** p < 0.001. For comparison of two groups, the Mann–Whitney U test was used, for more than two
groups the Kruskal–Wallis test was performed followed by a post hoc test by Dunn´s multiple
comparison test. Sample sizes: Healthy controls (HC) n = 63, standard care (SC) n = 50, intensive care
unit (ICU) n = 105.
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3.2. Lymphopenia in Critical Illness is Independent of Sepsis
Immunosuppressive features of circulating leukocytes, such as lymphopenia, have been
particularly related to sepsis [7,8]. We therefore compared the subgroups of ICU patients admitted
because of non-sepsis or sepsis, on the basis of current definitions [3]. While leukocytes (especially
neutrophils) were significantly higher in ICU patients with sepsis, absolute lymphocyte numbers did
not differ between critically ill patients with or without sepsis (Figure 2A). Regarding lymphocyte
subpopulations, only NK cells were significantly less frequent in septic as compared to non-septic
patients (Figure 2B). Age did not differ when comparing septic to non-septic patients (p = 0.118),
thereby excluding it as a confounder in this analysis. The statistical analysis of CD4- and CD8-positive
T lymphocytes as well as CD56brightCD16- and CD56dimCD16+ NK cells did not reveal significant
differences between septic and non-septic ICU patients (data not shown). However, flow-cytometric
assessment of leukocyte subsets revealed some weak correlations between cell populations and
inflammatory biomarkers. Total lymphocytes, but also T cells, inversely correlated with interleukin-10
(IL-10, Table 2). Furthermore, NK cells inversely correlated with procalcitonin (PCT, Table 2). All
other significant correlations were found to be negligible (Spearman’s rho below ±0.3).
Figure 2. Leukocyte subsets in ICU patients with and without sepsis. (a) Absolute numbers of
circulating leukocytes and lymphocytes in septic and non-septic ICU patients. (b) Lymphocyte subset
distribution in the respective cohorts. Statistics: * indicates p < 0.05. For comparison of two groups,
the Mann–Whitney U test was used. Sample sizes: No sepsis n = 53, sepsis n = 52.
Table 2. Correlation between leukocytes, lymphocytes, and their subsets with laboratory parameters
of ICU patients.
Leukocytes Lymphocytes B Cells T Cells NK Cells
CRP 0.215 0.030 −0.133 n.s. −0.176 n.s. −0.090 n.s. −0.153 n.s.
PCT 0.064 n.s. −0.236 0.025 −0.136 n.s. −0.146 n.s. −0.444 0.000
IL10 0.162 n.s. −0.316 0.003 −0.123 n.s. −0.305 0.004 −0.223 0.037
CX3CL1 −0.091 n.s. −0.062 n.s. −0.034 n.s. −0.024 n.s. −0.271 0.016
GFR −0.204 0.038 −0.016 n.s. −0.154 n.s. 0.002 n.s. 0.092 n.s.
SCr 0.197 0.045 0.023 n.s. 0.137 n.s. 0.020 n.s. −0.108 n.s.
Abbreviations: CRP: C-reactive protein, PCT: procalcitonin, IL10: interleukin-10, CX3CL1: fractalkine,
GFR: glomerular filtration rate, SCr: serum creatinine, r: Spearman’s rho correlation coefficient, p value:
significance level; n.s.: not significant.
3.3. Lymphopenia and T Cell Depletion are Associated with Mortality in ICU Patients
Lymphopenia has been related to adverse outcome in sepsis, and this has been functionally
linked to the exhaustion of T cells [6,7]. We therefore analyzed the possible link between circulating
leukocyte subsets and mortality in critically ill patients (Figure 3). Critically ill patients that survived
the ICU treatment showed significantly higher numbers of leukocytes and lymphocytes at ICU
J. Clin. Med. 2019, 8, 353 7 of 11
admission (Figure 3A). In particular, T and NK cells were significantly higher in surviving ICU
patients compared to patients succumbed to death (Figure 3B). In a subgroup analysis comparing
septic to non-septic patients, those changes were retained (detailed data not shown). In addition,
surviving sepsis patients had significantly higher levels of B cells per nL (p = 0.009), while surviving
non-septic patients showed significantly higher percentages of CD8+ T cells (p = 0.037). To control for
age as a confounding variable (which did differ between surviving and non-surviving patients, p = 0.048),
we performed the same analyses on the age-adjusted study population (in which age did not differ
between surviving and non-surviving patients, p = 0.293). Here, the changes, as seen in Figure 3A and 3B,
were retained, except for NK cells.
For a more granular analysis, we calculated Cox regressions for all cell types (omnibus test of
model coefficients, leukocytes p = 0.246, lymphocytes p = 0.086, B cells p = 0.455, T cells p = 0.008, and
NK cells p = 0.641 for variables in the equation). Only T cells showed a statistical significance with
respect to survival. In a multivariate cox regression, age alone yielded for a hazard ratio (HR) of 1.038
(95% confidence interval 1.015–1.061, p = 0.001), thus age was not a significant predictor of mortality
in our ICU cohort. Adding T cells per nL to the model accounted for a significant difference to the
previous model (p = 0.002), with a HR of 0.319 for T cells (95% confidence interval 0.137–0.744, p = 0.008),
describing T cells as a beneficial factor for patient survival (data not shown). Using the Youden index,
we calculated an optimal cutoff value of 0.36 T cells per nL. By Kaplan–Meier curve analysis (Figure 3C),
the chances for survival of ICU patients with more than 0.36 T cells per nL were almost doubled
compared to ICU patients with low T cell numbers.
Figure 3. Prognostic value of lymphocyte subsets in ICU patients. (a) Leukocytes and lymphocytes,
as obtained at ICU admission, in patients who subsequently died or survived in the ICU. (b)
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Lymphocytes subset distribution at ICU admission in patients surviving or dying in the ICU. (c)
Kaplan–Meier curve for T cells lower than or equal to 0.36 per nanoliter (grey) and higher than 0.36
per nanoliter (black) in ICU patients. Censored events are indicated by a crossing vertical line.
Statistics: * indicates p < 0.05, ** p < 0.01, *** p < 0.001. For comparison of two groups, the Mann–Whitney U
test was used. Cox regression was performed to determine the prognostic value. Cutoff values of the
Kaplan–Meier curve were determined by the Youden index. Sample sizes: death n = 35, survival n = 70.
3.4. Lymphopenia and T Cell Depletion are Rapidly Restored in Surviving Compared to Non-Surviving ICU
It had been hypothesized that the rapid restoration of innate and adaptive immune defects may
promote a beneficial prognosis in patients with sepsis [4]. We were able to obtain follow-up samples
in a subset of critically ill patients 48 h after admission to the ICU (n = 28). Strikingly, in patients that
survived in the ICU (n = 17), we observed a reduction in leukocytes followed by a trend towards
higher lymphocyte numbers at 48 h after ICU admission, that reached levels observed in healthy
volunteers (Figure 4A). Moreover, T cell numbers increased in surviving ICU patients within 48 h,
although the small number of patients with available follow-up samples did not allow to obtain
significant results (Figure 4A). On the contrary, patients who died during the ICU treatment (n = 11)
did not display such dynamics in their leukocytes or lymphocyte subpopulations (Figure 4B),
supporting that the early restoration of immune cell alterations within 48 h in the ICU is a beneficial
prognostic factor.
Figure 4. Longitudinal assessment of leukocyte subsets in ICU patients and prognosis. Peripheral
blood leukocytes were assessed at ICU admission (0 h) as well as after 48 h (48 h) of ICU treatment in
critically ill patients. (a) Leukocytes, lymphocytes, and their subsets per nanoliter in surviving ICU patients
at admission and after 48 h of ICU treatment. (b) Leukocytes, lymphocytes, and their subsets per nanoliter
in non-survivors at admission and after 48 h of ICU treatment. Statistics: * indicates p < 0.05. For
J. Clin. Med. 2019, 8, 353 9 of 11
comparison of two paired groups, the Wilcoxon signed rank test was used. Sample sizes with matched
samples 0 h and 48 h: Deaths n = 11, survivors n = 17.
4. Discussion
It has been shown that the distribution of peripheral blood leukocyte subsets yields information
about the severity and development of critical illness, especially sepsis [9]. In this study, we
investigated the distributional changes of lymphocytes and their subsets in infected and septic
patients using flow cytometry, which is a straightforward and reproducible method, on the basis of
activation markers or ex vivo cytokine secretion. We found that numbers of T and NK cells were
diminished in infected and in ICU patients compared to healthy controls, which was most likely due
to the migration of those cells either to sites of infections and organ injury or to peripheral lymphatic
tissue during the immune response [4,16]. Relative to each other, T cells were diminished, and B cells
were increased in infection and sepsis, whereas NK cells did not change in frequency. Subsets of T
and NK cells only showed minor shifts, i.e., a depletion of CD8+ T cells as well as a decline in CD16+
NK cells. These immunosuppressive features, in particular lymphopenia, have been previously
linked to sepsis [7,8]. Interestingly, changes in B, T, and NK cell numbers were independent of sepsis
in our study but represented a characteristic feature of critical illness. Our findings thereby indicate
that the critical illness itself, rather than sepsis, may promote immunosuppression and consequently
poor prognosis.
The rapid restoration of immune defects may be beneficial for the prognosis of patients with sepsis
[4]. Our data fully support this concept, as patients that subsequently survived critical illness
demonstrated significantly higher lymphocyte numbers at ICU admission, especially T and NK cells.
As an essential part of the acquired immune response in infection, lymphocytes and their subsets
play an important role in sepsis and survival. In a smaller study of 87 ICU patients with severe sepsis,
the surviving patients showed higher counts of Th1 lymphocytes [17]. In protracted disease, several
lymphocyte populations in patients with acute sepsis can upregulate the expression of receptors
associated with cell exhaustion, such as CTLA4, TIM-3, LAG-3, or IL-7 receptor [6]. In our analysis,
only T cells could predict the survival of the ICU patients, as low T cell counts were associated with
a significantly increased risk of mortality. Our results are consistent with those of a large multicentric
study [9]. The association between low number of circulating T cells and mortality may be due to
different mechanisms. Firstly, the low number of circulating T cells may reflect a stronger migration
of T cells into peripheral lymphatic tissue due to severe infection. Secondly, patients with an already
low T cell count may have a reduce ability to counteract systemic inflammation and infections.
Thirdly, reduced T cell numbers could be the result of an increased rate of cell death in critical illness,
leading to compromised immune responses and thus increased risk of mortality. Undoubtedly, the
overall reduced T cell counts are the net result of complex interactions, which may also include the
induction of T cell lymphopenia by immature granulocytes [5].
It is important to openly mention the limitations of our study. We conducted a single-center
study with a limited number of patients. While this approach allowed a high technical accuracy and
reproducibility of the elaborate flow cytometric analysis, it restricts the options to conduct extensive
subgroup analyses (e.g., based on age groups, etiology of disease, or site of infection). Possibly related
to this, we identified several statistically significant correlations between laboratory parameters and
lymphocytes and their subsets, but because of the weakness of those linear correlations, the clinical
value must be considered low (or negligible) in all cases (Table 2). Furthermore, the follow-up of
patients was limited. Larger prospective multicenter studies would very likely lead to more
informative subgroup analyses and would allow for a better definition of the predictive value of T
cells for the survival of critically ill patients.
Although only a subgroup of our ICU patient cohort was available for longitudinal follow-up
analysis, our study revealed a clear trend of a rapid restoration of lymphopenia and low T cell counts
within 48 h in patients that subsequently survived the critical illness, while patients that subsequently
died failed to restore these alterations within 48 h. Our data thereby support the concept of
therapeutically augmenting immune responses in critical illness by novel, tailored therapeutic
J. Clin. Med. 2019, 8, 353 10 of 11
interventions in intensive care medicine [10], for example the restoration of T cell exhaustion and of
T cell function in sepsis [6]. As supported by our study, altered immune cell numbers, composition,
and function not only determine responses to infectious threats but also appear to be decisive for the
course of critical illness and organ failure per se. Future studies should aim at validating our findings
in larger longitudinal sampling and may determine the optimal strategy and timing for such novel
therapeutic interventions in critical care medicine.
5. Conclusions
We conclude, that our flow-cytometric analysis of peripheral blood revealed striking changes in
circulating lymphocyte subsets in critically ill patients, namely depletion of lymphocytes, T cells and
NK cells in infected and in ICU patients, which was independent of sepsis. Furthermore,
lymphopenia and depletion of T cells at ICU admission were linked to increased mortality,
supporting their relevance as predictive biomarkers and potential therapeutic targets in critically ill
Author Contributions: P.H. and H.G. collected blood samples, performed FACS analyses, and conducted data
analyses. M.B. and K.T.W. supported the flow-cytometric experiments. C.R., L.B., and C.T. contributed to data
collection and analysis. A.K. and F.T. designed and supervised the study. P.H. and F.T. wrote the manuscript.
All authors corrected and approved the manuscript.
Funding: This research was funded by the German Research Foundation (DFG; Ta434/5-1 and SFB/TRR57).
Conflicts of Interest: The authors disclose no conflict of interest related to this study. The funders had no role
in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript,
or in the decision to publish the results.
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... Lymphocytopenia and immune dysfunction are fundamental characteristics of immunosuppression [3]. A decrease in the number of immune cells, especially lympho-cytes, is the first sign of immune paralysis [4]. A previous study has found that lymphocytopenia and immunosuppression in patients with advanced sepsis were associated with CD4+ and CD8+ T cell apoptosis [3]. ...
... Therefore, investigation on the mechanism of immune imbalance is crucial for developing molecule-based therapies to prevent organ dysfunction and improve sepsis outcomes [2,3]. Overwhelming studies have shown that T cell loss caused by apoptosis was not only one of the important pathological features in sepsis but also played a vital role in immunosuppression in sepsis [4,5]. DDX3X serves as an important checkpoint of cell death, and it was initially found to be overexpressed in a variety of invasive cancers and associated with poor clinical prognosis [8,9]. ...
... As far as we are concern, reduction in the number of T cells is one of the critical causes of immunosuppression in sepsis [17]. Previous studies have implicated that the number of CD4+ T cells was one of the effective predictors of poor prognosis in sepsis [4]. Moreover, the depletion of T cells has always been considered as a contributor to apoptosis in sepsis [16]. ...
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Purpose: DDX3X acts as the critical checkpoint of death in stressed cells. The purpose of this study was to evaluate the mRNA expression level of DDX3X in T cells in peripheral blood of patients with sepsis and to explore its correlation with the prognosis of sepsis. Methods: Seventy-nine patients with traumatic sepsis were enrolled in this prospective cohort study. Blood samples were collected within 24 hours after the diagnosis of sepsis or septic shock, and the mRNA expression level of DDX3X in T cells was detected by PCR. Results: The level of DDX3X mRNA in T cells was significantly increased in septic patients as well as in septic shock patients. The level of DDX3X mRNA was negatively correlated with T cell count and positively correlated with acute physiological and chronic health assessment (APACHE) score and sequential organ failure assessment (SOFA) score (P < 0.01). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was 0.79 (95% confidence interval (CI), 0.68-0.90). A Cox proportional hazard model identified an association between an increased DDX3X mRNA level (≥1.575) and the risk of 28-day mortality (hazard ratio = 9.540, 95% CI, 2.452-37.108). Conclusions: High level of DDX3X mRNA in T cells in sepsis is associated with the severity of sepsis and the mortality of patients with sepsis.
... The lymphopenia in our patients was more severe than in general ICU populations, where lymphocyte counts of 0.5-1 × 10 9 /L were reported [3,4]. Whether this is related to HM and chemotherapy or reflects a more pronounced critical illness immunoparalysis remains unclear. ...
... Whether this is related to HM and chemotherapy or reflects a more pronounced critical illness immunoparalysis remains unclear. In a similar analysis in 407 ICU patients with HM but without neutropenia, we observed a similar flat curve for the lymphocyte count throughout admission but at a level close to 0.8 × 10 9 /L (not shown), similar to reports in unselected ICU patients [3,4]. Second, while lymphopenia has been well documented in critically ill patients [3,4], most studies focused on ICU admission values with little information on kinetics. ...
... In a similar analysis in 407 ICU patients with HM but without neutropenia, we observed a similar flat curve for the lymphocyte count throughout admission but at a level close to 0.8 × 10 9 /L (not shown), similar to reports in unselected ICU patients [3,4]. Second, while lymphopenia has been well documented in critically ill patients [3,4], most studies focused on ICU admission values with little information on kinetics. Lymphopenia in our population was very prolonged. ...
... Profound and persistent lymphopenia, partly reflecting migration of T-cells into infection sites, is closely related to infection and sepsis, being associated with expansion of immunosuppressive cell populations such as regulatory T-lymphocytes, IL-10-producing B-lymphocytes and myeloid-derived suppressor cells, whose rise may last for months [18][19][20]. Immune homeostasis is perturbed by a strong inflammatory response, as in a septic episode, followed by a rapid negative feedback due to the compensatory anti-inflammatory response, leading a decrease in functional T-lymphocytes [19,35,36]. Previous studies indicated that lymphopenia may occur early in the course of sepsis and that decreases of specific lymphocyte subsets, including CD4 T cells, may help identify fragile patients at higher risk of disease progression among those hospitalized due to infection [18][19][20]. ...
... Wu et al. (2013) enrolled 87 ICU patients with severe sepsis, showing higher numbers of CD4 T-Th1 lymphocytes in survivors [38]. Similarly, Hohlstein et al. (2019) demonstrated that numbers of T and NK lymphocyte at ICU admission were significantly higher in septic shock survivors than in non-survivors [35]. CD4 T lymphocytes play a pivotal role in response to microbial spread [18] and decreased circulating CD4 T lymphocytes may increase the risk of acquiring bloodstream infections [20]. ...
... Wu et al. (2013) enrolled 87 ICU patients with severe sepsis, showing higher numbers of CD4 T-Th1 lymphocytes in survivors [38]. Similarly, Hohlstein et al. (2019) demonstrated that numbers of T and NK lymphocyte at ICU admission were significantly higher in septic shock survivors than in non-survivors [35]. CD4 T lymphocytes play a pivotal role in response to microbial spread [18] and decreased circulating CD4 T lymphocytes may increase the risk of acquiring bloodstream infections [20]. ...
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Background Early recognition of patients hospitalized for sepsis at higher risk of poor clinical outcome is a mandatory task and many studies suggested that indicators of the immune status may be useful for this purpose. We performed a retrospective, monocentric cohort study to evaluate whether lymphocyte subsets may be useful in predicting in-hospital mortality of septic patients. Methods Data of all consecutive patients with a diagnosis of sepsis at discharge and an available peripherical blood lymphocyte subset (CD4, CD8, CD16/CD56 and CD19) analysis at hospital entry were retrospectively collected between January 2015 and August 2018. Clinical characteristics of patients, past medical history and other laboratory parameters were also considered. Results Two-hundred-seventy-eight septic patients, 171 (61.5%) males, mean age 63.2 ± 19.6 years, were enrolled. Total counts of lymphocytes, CD4 T cells, CD8 T cells and B cells were found significantly lower in deceased than in surviving patients. At univariate analyses, CD4 T cells/µL (OR 0.99 for each incremental unit, 95%CI 0.99–1.10, p < 0.0001), age (OR 1.06, 95%CI 1.04–1.09, p < 0.0001), procalcitonin (OR 1.01, 95%CI 1.01–1.02, p < 0.0001) and female gender (OR 2.81, 95%CI 1.49–5.28, p = 0.001) were associated with in-hospital mortality. When a dichotomic threshold of < 400/µL for CD4 T cells as a dependent variable was considered in multivariate models, age (OR 1.04; 95%CI 1.01–1.09, p = 0.018); female gender (OR 3.18; 95%CI 1.40–7.20, p = 0.006), qSOFA (OR 4.00, 95%CI 1.84–8.67, p < 0.001) and CD4 T cells < 400/µL (OR 5.3; 95%CI 1.65–17.00, p = 0.005) were the independent predictors. Conclusions In adjunct to biomarkers routinely determined for the prediction of prognosis in sepsis, CD4 T lymphocytes, measured at hospital entry, may be useful in identifying patients at higher risk of in-hospital death.
... The number of peripheral blood leukocytes fluctuates significantly during the course of sepsis [12]. While a noticeable increase in neutrophil and monocyte populations is observed in the first 2-4 days from septic onset, the lymphopenic state quickly follows the resolution of the cytokine storm [13]. The marked decrease in the number of B cells, CD4 + and CD8 + T cells, and NK cells following sepsis onset is the result of apoptotic loss [12][13][14]. ...
... While a noticeable increase in neutrophil and monocyte populations is observed in the first 2-4 days from septic onset, the lymphopenic state quickly follows the resolution of the cytokine storm [13]. The marked decrease in the number of B cells, CD4 + and CD8 + T cells, and NK cells following sepsis onset is the result of apoptotic loss [12][13][14]. Lymphocyte numbers normalize within a month in sepsis survivors, but the functionality of the immune cells is reduced for an extended period [15] (Fig 1C). Failure to regulate either leukocytosis or lymphopenia in the early stages of sepsis correlates with increased mortality in patients [16]. ...
Sepsis is a life-threatening condition characterized by an acute cytokine storm followed by prolonged dysfunction of the immune system in the survivors. Post-septic lymphopenia and functional deficits of the remaining immune cells lead to increased susceptibility to secondary infections and other morbid conditions causing late death in the patients. This state of post-septic immunoparalysis may also influence disorders stemming from inappropriate or overactive immune responses, such as autoimmune and immunoinflammatory diseases, including multiple sclerosis. In addition, ongoing autoimmunity likely influences the susceptibility to and outcome of sepsis. This review article addresses the bidirectional relationship between sepsis and multiple sclerosis, with a focus on the immunologic mechanisms of the interaction and potential directions for future studies.
... e lymphocyte count of patients in the death group was significantly lower than that of the survival group, similar to findings from studies on SARS [14]. Studies have shown that persistent lymphocytopenia in sepsis predicts early and late mortality [15,16]. e degree of lymphocytopenia might reveal either the severity of viral invasion or the state of antiviral immunity, both of which are key factors related to the severity and mortality of various diseases [8]. ...
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Objective: To systematically evaluate the value of lymphocytes, platelets, and interleukin-6 in predicting the mortality of patients with coronavirus disease 2019 (COVID-19) and to provide medical evidence for the long-term prognosis of patients with COVID-19. Methods: The latest studies published until July 1, 2021, were retrieved from databases including PubMed, Embase, and Cochrane Library to analyze the ability of lymphocyte and platelet counts as well as interleukin-6 levels to predict mortality in patients with COVID-19. Two reviewers independently screened the literature and extracted data, then evaluated the risk of bias of included studies using the Newcastle-Ottawa Scale (NOS), and used Stata 15.0 software for meta-analysis. Results: A total of nine studies were included, involving 4340 patients. There were 1330 patients in the death group and 3010 patients in the survival group. Meta-analysis showed that, compared with the survival group, lymphocyte counts in the death group were significantly lower (SMD = -0.64, 95% CI: -0.86--0.43, p < 0.01), platelet counts were significantly lower (SMD = -0.47, 95% CI: -0.67--0.27, p < 0.01), and interleukin-6 levels were significantly higher (SMD = 1.07, 95% CI: 0.62-1.53, p < 0.01). Conclusion: Lymphocyte and platelet counts, as well as interleukin-6 levels, can help predict the mortality of patients with COVID-19. Due to the limitation of the number and quality of the included studies, these conclusions need to be validated by additional high-quality studies.
... Pre-existing lymphopenia, critical illness-induced immune paralysis, and steroids may have synergistically led to the development of HSVE. However, despite a high prevalence of lymphopenia and immune paralysis in critically ill patients, regardless of the presence of sepsis [30], the occurrence of ICU-acquired HSVE is very rare [31] and its reality has even been challenged [32]. It is therefore likely that steroids played a key role in our patient even though a causal link with HSVE cannot be proven. ...
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BACKGROUND Several cases of herpes simplex virus type 1 meningoencephalitis (HSVE) have been reported in patients receiving steroids, but the exact contribution of steroids to the disorder remains unclear because other risk factors, such as chemotherapy, brain radiation, or surgery, were present in almost all cases. CASE REPORT We report the case of a 76-year-old man who developed HSVE following the administration of pulse-dose steroids. The patient had occupational asbestos exposure and a chronic interstitial lung disease of unclear etiology (sarcoidosis versus hypersensitivity pneumonitis) and was admitted for acute-on-chronic respiratory failure requiring mechanical ventilation. After a negative infectious workup and several days of antibiotics without improvement, pulse-dose steroids were administered. In the following days, the patient developed a fever and worsening encephalopathy. A lumbar puncture showed elevated nucleated cells and positive polymerase chain reaction for herpes simplex virus 1 in the cerebrospinal fluid, confirming the diagnosis of HSVE. Acyclovir treatment was initiated, but the patient later died as a result of persistent severe encephalopathy and respiratory failure with an inability to wean mechanical ventilation. CONCLUSIONS Clinicians should keep in mind that HSVE is a potential complication of steroids and carefully consider the benefit/risk ratio of pulse-dose steroids, taking into account associated factors of immunosuppression. A high level of awareness should be especially maintained in critically ill patients because of associated risk factors (critical illness immune paralysis) and because neurological signs of HSVE may be missed in mechanically ventilated, sedated patients.
... Also, Sheikh Motahar Vahedi et al. found that lymphocytopenia is a predictor of 28-day mortality in patients with sepsis admitted to the ED [29]. Finally, Hohlstein et al. showed that lymphocytopenia at ICU admission is associated with increased mortality [30]. ...
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Sepsis represents an important global health burden due to its high mortality and morbidity. The rapid detection of sepsis is crucial in order to prevent adverse outcomes and reduce mortality. However, the diagnosis of sepsis is still challenging and many efforts have been made to identify reliable biomarkers. Unfortunately, many investigated biomarkers have several limitations that do not support their introduction in clinical practice, such as moderate diagnostic and prognostic accuracy, long turn-around time, and high-costs. Complete blood count represents instead a precious test that provides a wealth of information on individual health status. It can guide clinicians to early-identify patients at high risk of developing sepsis and to predict adverse outcomes. It has several advantages, being cheap, easy-to-perform, and available in all wards, from the emergency department to the intensive care unit. Noteworthy, it represents a first-level test and an alteration of its parameters must always be considered within the clinical context, and the eventual suspect of sepsis must be confirmed by more specific investigations. In this review, we describe the usefulness of basic and new complete blood count parameters as diagnostic and prognostic biomarkers of sepsis.
Background Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the gastrointestinal tract. Treatment for patients who have a monogenic cause of their IBD, often the youngest children, known as very early onset IBD (VEO-IBD), can be different from standard treatment for polygenic cases. Yet, ascertainment of these patients is difficult. Methods We analyzed cases of VEO-IBD to understand the breadth of monogenic etiology and to identify clinical, laboratory, and flow cytometric correlates of this subpopulation. Results Genetic causes of very early onset inflammatory bowel disease are highly diverse ranging from pure epithelial defects to classic T cell defects. Flow cytometry, other than testing for chronic granulomatous disease, has a low sensitivity for monogenic etiologies. Poor growth was a clinical feature associated with monogenic causality. Conclusions Genetic testing is, at this moment, the most robust method for the identification of monogenic cases of very early onset IBD.
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In a prospective observational pilot study on patients undergoing elective cardiac surgery with cardiopulmonary bypass, we evaluated label-free quantitative phase imaging (QPI) with digital holographic microscopy (DHM) to describe perioperative inflammation by changes in biophysical cell properties of lymphocytes and monocytes. Blood samples from 25 patients were investigated prior to cardiac surgery and postoperatively at day 1, 3 and 6. Biophysical and morphological cell parameters accessible with DHM, such as cell volume, refractive index, dry mass, and cell shape related form factor, were acquired and compared to common flow cytometric blood cell markers of inflammation and selected routine laboratory parameters. In all examined patients, cardiac surgery induced an acute inflammatory response as indicated by changes in routine laboratory parameters and flow cytometric cell markers. DHM results were associated with routine laboratory and flow cytometric data and correlated with complications in the postoperative course. In a subgroup analysis, patients were classified according to the inflammation related C-reactive protein (CRP) level, treatment with epinephrine and the occurrence of postoperative complications. Patients with regular courses, without epinephrine treatment and with low CRP values showed a postoperative lymphocyte volume increase. In contrast, the group of patients with increased CRP levels indicated an even further enlarged lymphocyte volume, while for the groups of epinephrine treated patients and patients with complicative courses, no postoperative lymphocyte volume changes were detected. In summary, the study demonstrates the capability of DHM to describe biophysical cell parameters of perioperative lymphocytes and monocytes changes in cardiac surgery patients. The pattern of correlations between biophysical DHM data and laboratory parameters, flow cytometric cell markers, and the postoperative course exemplify DHM as a promising diagnostic tool for a characterization of inflammatory processes and course of disease.
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This study investigates the prognostic value of immune cell subsets in assessing the risk of death in patients with sepsis. This retrospective study collected 169 patients from March 2020 to February 2021 at our hospital. Baseline data were collected from patients. The absolute values (Abs) and percentages (%) of immune cell subsets for lymphocytes, T cells, CD4+ cells, CD8+, B cells, NK cells, and NKT cells were measured using flow Cytometry. Among the included patients, 43 patients were in the nonsurvivor group and 126 patients were in the survivor group. The age of patients in the nonsurvivor survivor was higher than that of survivor group patients ( P = .020). SOFA, APACHE II, C-reactive protein, and procalcitonin were higher in the nonsurvivor group than in the survivor group (all P values < .05). Multivariate regression analysis showed that lymphocytes (%) and SOFA were independent risk factors affecting patients’ prognosis. Lymphocytes (%) have the highest area under the receiver operating characteristic (ROC) curve (0.812). The model area under the ROC curve for immune cell subsets was 0.800, with a sensitivity of 72.09%, and specificity of 79.27% ( z = 7.796, P < .001). Analysis of patient prognosis by immune cell subsets diagnostic showed statistically significant differences in the grouping of cut-off values for all 5 indicators (all P < .05). The lymphocytes (%) and SOFA score are independent risk factors affecting the prognosis of patients. A moderate predictive power for mortality in sepsis patients by immune cell subsets model.
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Purpose Reliable biomarkers for predicting subsequent sepsis among patients with suspected acute infection are lacking. In patients presenting to emergency departments (EDs) with suspected acute infection, we aimed to evaluate the reliability and discriminant ability of 47 leukocyte biomarkers as predictors of sepsis (Sequential Organ Failure Assessment score ≥ 2 at 24 h and/or 72 h following ED presentation). Methods In a multi-centre cohort study in four EDs and intensive care units (ICUs), we standardised flow-cytometric leukocyte biomarker measurement and compared patients with suspected acute infection (cohort-1) with two comparator cohorts: ICU patients with established sepsis (cohort-2), and ED patients without infection or systemic inflammation but requiring hospitalization (cohort-3). Results Between January 2014 and February 2016, we recruited 272, 59 and 75 patients to cohorts 1, 2, and 3, respectively. Of 47 leukocyte biomarkers, 14 were non-reliable, and 17 did not discriminate between the three cohorts. Discriminant analyses for predicting sepsis within cohort-1 were undertaken for eight neutrophil (cluster of differentiation antigens (CD) CD15; CD24; CD35; CD64; CD312; CD11b; CD274; CD279), seven monocyte (CD35; CD64; CD312; CD11b; HLA-DR; CD274; CD279) and a CD8 T-lymphocyte biomarker (CD279). Individually, only higher neutrophil CD279 [OR 1.78 (95% CI 1.23–2.57); P = 0.002], higher monocyte CD279 [1.32 (1.03–1.70); P = 0.03], and lower monocyte HLA-DR [0.73 (0.55–0.97); P = 0.03] expression were associated with subsequent sepsis. With logistic regression the optimum biomarker combination was increased neutrophil CD24 and neutrophil CD279, and reduced monocyte HLA-DR expression, but no combination had clinically relevant predictive validity. Conclusions From a large panel of leukocyte biomarkers, immunosuppression biomarkers were associated with subsequent sepsis in ED patients with suspected acute infection. Clinical trial registration NCT02188992.
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Caspase-cleaved fragments of the intermediate filament protein keratin 18 (cytokeratin-18 (CK18)) can be detected in serum as M30 levels and may serve as a circulating biomarker indicating apoptosis of epithelial and parenchymal cells. In order to evaluate M30 as a biomarker in critical illness, we analyzed circulating M30 levels in 243 critically ill patients (156 with sepsis, 87 without sepsis) at admission to the medical intensive care unit (ICU), in comparison to healthy controls ( n=32 ). M30 levels were significantly elevated in ICU patients compared with healthy controls. Circulating M30 was closely associated with disease severity but did not differ between patients with sepsis and ICU patients without sepsis. M30 serum levels were correlated with biomarkers of inflammation, cell injury, renal failure, and liver failure in critically ill patients. Patients that died at the ICU showed increased M30 levels at admission, compared with surviving patients. A similar trend was observed for the overall survival. Regression analyses confirmed that M30 levels are associated with mortality, and patients with M30 levels above 250.8 U/L displayed an excessive short-term mortality. Thus, our data support the utility of circulating levels of the apoptosis-related keratin fragment M30 as a prognostic biomarker at ICU admission.
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Recent advances in technology and better understanding of mechanisms underlying disease are beginning to enable us to better characterize critically ill patients. Instead of using nonspecific syndromic groupings, such as sepsis or acute respiratory distress syndrome, we can now classify individual patients according to various specific characteristics, such as immune status. This “personalized” medicine approach will enable us to distinguish patients who have similar clinical presentations but different cellular and molecular responses that will influence their need for and responses (both negative and positive) to specific treatments. Treatments will be able to be chosen more accurately for each patient, resulting in more rapid institution of appropriate, effective therapy. We will also increasingly be able to conduct trials in groups of patients specifically selected as being most likely to respond to the intervention in question. This has already begun with, for example, some new interventions being tested only in patients with coagulopathy or immunosuppressive patterns. Ultimately, as we embrace this era of precision medicine, we may be able to offer precision therapies specifically designed to target the molecular set-up of an individual patient, as has begun to be done in cancer therapeutics.
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Recent advances in sepsis therapy exclusively involve improvements in supportive care, while sepsis mortality rates remain disturbingly high at 30%. These persistently high sepsis mortality rates arise from the absence of sepsis specific therapies. However with improvements in supportive care, patients with septic shock commonly partially recover from the infection that precipitated their initial illness, yet they frequently succumb to subsequent health care associated infections. Remarkably today the pathophysiology of sepsis in humans, a common disease in western society, remains largely a conundrum. Conventionally sepsis was regarded as primarily a disorder of inflammation. More recently the importance of immune compromise in the pathophysiology of sepsis and health care associated infection has now become more widely accepted. Accordingly a review of the human evidence for this novel sepsis paradigm is timely. Septic patients appear to exhibit a complex and long-lasting immune deficiency state, involving lymphocytes of both the innate and adaptive immune responses that have been linked with mortality and the occurrence of health care associated infection. Such is the pervasive nature of immune compromise in sepsis that ultimately immune modulation will play a crucial role in sepsis therapies of the future.
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Background Endothelin 1 (ET-1) is a strong vasoconstrictor, which is involved in inflammation and reduced tissue perfusion. C-terminal proendothelin-1 (CT-proET-1) is the stable circulating precursor protein of ET-1. We hypothesized that CT-proET-1, reflecting ET-1 activation, is involved in the pathogenesis of critical illness and associated with its prognosis. Methods Two hundred seventeen critically ill patients (144 with sepsis, 73 without sepsis) were included prospectively upon admission to the medical intensive care unit (ICU), in comparison to 65 healthy controls. CT-proET-1 serum concentrations were correlated with clinical data and extensive laboratory parameters. Overall survival was followed for up to 3 years. ResultsCT-proET-1 serum levels at admission were significantly increased in critically ill patients compared to controls. CT-proET-1 serum levels showed significant correlations to systemic inflammation as well as multiple markers of organ dysfunction (kidney, liver, heart). Patients with sepsis displayed higher circulating CT-proET-1 than ICU patients with non-septic diseases. CT-proET-1 levels >74 pmol/L at ICU admission independently predicted ICU death (adjusted hazard ratio (HR) 2.66, 95% confidence interval (CI) 1.30–5.47) and overall mortality during follow-up (adjusted HR 2.19, 95%-CI 1.21–3.98). ConclusionsCT-proET-1 serum concentrations at admission are increased in critically ill patients and associated with sepsis, disease severity, organ failure, and mortality.
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Objective: To provide an update to "Surviving Sepsis Campaign Guidelines for Management of Sepsis and Septic Shock: 2012." Design: A consensus committee of 55 international experts representing 25 international organizations was convened. Nominal groups were assembled at key international meetings (for those committee members attending the conference). A formal conflict-of-interest (COI) policy was developed at the onset of the process and enforced throughout. A stand-alone meeting was held for all panel members in December 2015. Teleconferences and electronic-based discussion among subgroups and among the entire committee served as an integral part of the development. Methods: The panel consisted of five sections: hemodynamics, infection, adjunctive therapies, metabolic, and ventilation. Population, intervention, comparison, and outcomes (PICO) questions were reviewed and updated as needed, and evidence profiles were generated. Each subgroup generated a list of questions, searched for best available evidence, and then followed the principles of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system to assess the quality of evidence from high to very low, and to formulate recommendations as strong or weak, or best practice statement when applicable. Results: The Surviving Sepsis Guideline panel provided 93 statements on early management and resuscitation of patients with sepsis or septic shock. Overall, 32 were strong recommendations, 39 were weak recommendations, and 18 were best-practice statements. No recommendation was provided for four questions. Conclusions: Substantial agreement exists among a large cohort of international experts regarding many strong recommendations for the best care of patients with sepsis. Although a significant number of aspects of care have relatively weak support, evidence-based recommendations regarding the acute management of sepsis and septic shock are the foundation of improved outcomes for these critically ill patients with high mortality.
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For more than two decades, sepsis was defined as a microbial infection that produces fever (or hypothermia), tachycardia, tachypnoea and blood leukocyte changes. Sepsis is now increasingly being considered a dysregulated systemic inflammatory and immune response to microbial invasion that produces organ injury for which mortality rates are declining to 15–25%. Septic shock remains defined as sepsis with hyperlactataemia and concurrent hypotension requiring vasopressor therapy, with in-hospital mortality rates approaching 30–50%. With earlier recognition and more compliance to best practices, sepsis has become less of an immediate life-threatening disorder and more of a long-term chronic critical illness, often associated with prolonged inflammation, immune suppression, organ injury and lean tissue wasting. Furthermore, patients who survive sepsis have continuing risk of mortality after discharge, as well as long-term cognitive and functional deficits. Earlier recognition and improved implementation of best practices have reduced in-hospital mortality, but results from the use of immunomodulatory agents to date have been disappointing. Similarly, no biomarker can definitely diagnose sepsis or predict its clinical outcome. Because of its complexity, improvements in sepsis outcomes are likely to continue to be slow and incremental.
Background: In this study, we primarily sought to assess the ability of flow cytometry to predict early clinical deterioration and overall survival in septic patients admitted in the emergency department and intensive care unit. Methods: Patients admitted for community-acquired acute sepsis from 11 hospital centers were eligible. Early (Day 7) and late (Day 28) deaths were notified. Levels of CD64pos granulocytes, CD16pos monocytes, CD16dim immature granulocytes (IG), T and B lymphocytes were assessed by flow cytometry, using an identical, cross-validated, robust and simple consensus standardized protocol in each center. Results: Among 1062 patients screened, 781 patients with confirmed sepsis were studied (age: 67±48 years, SAPS II: 36±17, SOFA: 5±4). Patients were divided into three groups (sepsis, severe sepsis and septic shock) on Day 0 and on Day 2. On Day 0, septic patients exhibited increased level of CD64pos granulocytes, CD16pos monocytes and IG with T-cell lymphopenia. Clinical severity was associated with higher percentages of IG and deeper T-cell lymphopenia. IG percentages tended to be higher in patients whose clinical status worsened on Day 2 (35.1 ± 35.6 vs 43.5 ± 35.2, p=0.07). Increased IG percentages were also related to occurrence of new organ failures on Day 2. Increased IG percentages, especially when associated with T-cell lymphopenia, were independently associated with early (p<0.01) and late (p<0.01) death. Conclusions: Increased circulating IG at the acute phase of sepsis are linked to clinical worsening, especially when associated with T-cell lymphopenia. Early flow cytometry could help clinicians to target patients at high risk of clinical deterioration.
CD4⁺ T cells are critical regulators of the adaptive immune system and have diverse roles in regulating responses to the broad array of microbes encountered. Appropriate execution of their effector function requires precise and coordinated migration of these cells to specific lymphoid niches and peripheral sites. This migration is largely controlled by dynamic expression of chemokine receptors and the discrete functions of distinct subsets of CD4⁺ T cells can often be determined from their expression of specific chemokine receptors. In this chapter, we discuss recent advances in the subset-specific homing of distinct T helper populations, focusing on new insights stemming from the increased diversity and plasticity now observed among CD4⁺ T cells as well as how chemokine receptors can govern T cell-fate decisions. We also discuss current understanding of CD4⁺ memory T cells with reference to their diversification based on chemokine receptor expression.