Incorporation of dynamic segmented neutrophil-to-monocyte ratio with leukocyte count for sepsis risk stratification

Prognostic Value of Dynamic Segmented Neutrophil to Monocyte (SeMo) Ratio Changes in Patients with Moderate to Severe Traumatic Brain Injury

BACKGROUND

Traumatic brain injury (TBI) is a leading cause of morbidity and mortality in trauma patients, necessitating reliable prognostic tools. The segmented neutrophil-to-monocyte (SeMo) ratio, indicative of the inflammatory response, has emerged as a valuable biomarker. This study evaluates the prognostic value of dynamic changes in the SeMo ratio in predicting outcomes for patients with moderate to severe TBI.

METHODS

A retrospective analysis was conducted on data from 1118 TBI patients admitted to the surgical intensive care unit at a level I trauma center between January 2009 and December 2020. Patients were selected based on an Abbreviated Injury Scale (AIS) score ≥ 3 in the head region. Initial and follow-up SeMo ratios were calculated upon admission and 48-72 h later, respectively. The dynamic SeMo ratio was defined as the difference between the second and initial SeMo ratios. Statistical analyses included receiver operating characteristic (ROC) curve analysis to determine the optimal threshold for mortality prediction, and comparative analysis of clinical outcomes.

RESULTS

The study cohort included 121 deceased and 997 surviving patients. Deceased patients had significantly higher second SeMo ratios (20.9 ± 16.1 vs. 15.8 ± 17.2, p = 0.001) and dynamic SeMo ratios (2.4 ± 19.8 vs. -2.1 ± 19.5, p = 0.019) than those survival patients. In the multivariate analysis, the dynamic SeMo is a significant independent risk factor for in-hospital mortality (OR 1.01, 95%CI: 1.01-1.03, p = 0.031). The optimal cut-off for the dynamic SeMo ratio was 5.96, above which patients exhibited higher mortality (21.4% vs. 8.5%, p < 0.001), higher adjusted mortality (adjusted odds ratio: 2.98; 95% confidence interval: 1.95-4.56; p = 0.005), and longer hospital stays (23.6 days vs. 19.7 days, p = 0.005).

DISCUSSION

Dynamic SeMo ratio changes serve as a prognostic marker for in-hospital mortality and hospital stay duration in moderate to severe TBI patients. A higher dynamic SeMo ratio indicates increased risk, highlighting the importance of early monitoring and intervention. Future prospective studies should validate these findings and explore integration with other biomarkers for enhanced prognostication.

Blood and CSF findings of cellular immunity in anti-NMDAR encephalitis

OBJECTIVES

To investigate the immunopathogenic mechanisms of anti-N-methyl-D-aspartate receptor encephalitis (NMDAR-E) by characterizing the changes of immune cells in both peripheral blood (PB) and cerebrospinal fluid (CSF) of patients with NMDAR-E.

METHODS

Cytology and flow cytometry were used to explore and compare different immunological parameters in PB and CSF of patients with NMDAR-E, viral encephalitis (VE) and healthy volunteers. Moreover, different models were established to assess the possibility of identifying NMDAR-E patients based on PB and CSF parameters.

RESULTS

The neutrophil counts and monocyte-to-lymphocyte ratios (MLR) in PB are higher in NMDAR-E patients than in both VEs and controls (P < 0.001, respectively), while the percentages of CD3 + T, CD4 + T lymphocytes, and the leukocytes count in CSF were lower in NMDAR-Es than in VEs (P < 0.01, respectively). The higher percentages of CD8 + T cells in blood and CSF were both correlated with more severe NMDAR-E (P < 0.05, respectively). The poor neurological status group had significantly higher PB leukocytes but lower CSF leukocyte count (P < 0.05). Longitudinal observations in patients with NMDAR-E showed a decreasing trend of leukocyte count, neutrophils count, neutrophil-to-monocyte ratios (NMR), and neutrophil-to-lymphocyte ratios (NLR) with the gradual recovery of neurological function.

CONCLUSIONS

The expression patterns of T lymphocyte subsets were different in patients with NMDAR-E and viral encephalitis. The changing trends of leukocyte and lymphocyte populations in peripheral blood and cerebrospinal fluid may provide clues for the diagnosis of different types of encephalitides, including NMDARE, and can be used as immunological markers to assess and predict the prognosis.

Segmented neutrophil-to-monocyte ratio and systemic immune-inflammation index associated with the severity and functional prognosis of acute ischemic stroke

PURPOSE/AIM OF THE STUDY

To identify the inflammation indexes associated with the severity and functional prognosis in ischemic stroke.

MATERIAL AND METHODS

A prospective study was conducted with ischemic stroke cases included in the i-ReNe clinical registry. Patients were divided into groups according to the severity on admission measured by the National Institutes of Health Stroke Scale (NIHSS) and the functional prognosis at 30 and 90 days of discharge measured by the modified Rankin Scale (mRS).

RESULTS

We included 145 patients with a mean age of 61.5 ± 12.75, 97 (66.9%) were men. The leukocyte and neutrophil counts, Neutrophil-to-Lymphocyte ratio (NLR), Derived Neutrophil-to-Lymphocyte ratio (dNLR), Platelet-to-Lymphocyte ratio (PLR), Segmented Neutrophil-to-Monocyte ratio (SeMo ratio), and Systemic Immune-inflammation index (SII) were higher in moderate-to-severe stroke (NIHSS ≥6). NLR, PLR, SeMo ratio, and SII were higher in the group with severe disability and death at 30 days (mRS ≥4). In the multiple logistic regression analyses, SeMo ratio >14.966 and SII >623.723 were associated with moderate-to-severe stroke (NIHSS ≥6). In addition, SeMo ratio >7.845 was associated with severe disability and death at 30 days (mRS ≥4).

CONCLUSIONS

Systemic inflammation indexes could be rapid and low-cost markers used in the initial evaluation of ischemic stroke, whose values could help to stratify patients according to their severity and functional prognosis. This is the first study to establish a relationship between ischemic stroke and the SeMo ratio.

The best of both worlds: no apparent trade-off between immunity and reproduction in two group-living African mole-rat species

Co-operatively breeding mammals often exhibit a female reproductive skew and suppression of the subordinate non-breeding group members. According to evolutionary theory and the immunity-fertility axis, an inverse relationship between reproductive investment and survival (through immunocompetence) is expected. As such, this study investigated if a trade-off between immunocompetence and reproduction arises in two co-operatively breeding African mole-rat species, namely the Damaraland mole-rat (Fukomys damarensis) and common mole-rat (Cryptomys hottentotus hottentotus), which possess female reproductive division of labour. This study also attempted to investigate the relationship between the immune and endocrine systems in Damaraland mole-rats. There was no trade-off between reproduction and immunocompetence in co-operatively breeding African mole-rat species, and in the case of the Damaraland mole-rats, breeding females (BFs) possessed increased immunocompetence compared with non-breeding females (NBFs). Furthermore, the increased levels of progesterone possessed by Damaraland mole-rat BFs compared with NBFs appear to be correlated to increased immunocompetence. In comparison, BF and NBF common mole-rats possess similar immunocompetence. The species-specific differences in the immunity-fertility axis may be due to variations in the strengths of reproductive suppression in each species. This article is part of the theme issue 'Evolutionary ecology of inequality'.

Elevated neutrophil - to - monocyte ratio as a prognostic marker for poor outcomes in neonatal sepsis

Objectives

Neonatal sepsis is one of the leading causes of neonatal death. The aim of this study was to evaluate the value of neutrophil - to - monocyte ratio (NMR) in predicting mortality in neonatal sepsis.

Methods

In this present retrospective study, a total of 134 neonates with sepsis were included. Baseline laboratory parameters were collected. The best cutoff value of NMR was determined by receiver operating characteristic (ROC) curve. Univariate and multivariate analysis were carried out to survey the predict value of NMR.

Results

The results showed that NMR in non-survival group was significantly higher than that in survival group. Results from multivariate analysis showed that high NMR was an independent risk factor for neonatal sepsis (Hazard ratio (HR): 7.519, p = 0.001). ROC displayed that the area under curve (AUC) of NMR was 0.740, sensitivity and specificity of NMR were 80% and 65.8% when 7.65 was selected.

Conclusions

NMR could be a promising prognostic factor for neonatal sepsis.

Association of Hypernatremia with Immune Profiles and Clinical Outcomes in Adult Intensive Care Unit Patients with Sepsis

Both hypernatremia and an abnormal immune response may increase hospital mortality in patients with sepsis. This study examined the association of hypernatremia with abnormal immune response and mortality in 520 adult patients with sepsis in an intensive care unit (ICU). We compared the mortality and ex vivo lipopolysaccharide (LPS)-induced inflammatory response differences among patients with hyponatremia, eunatremia, and hypernatremia, as well as between patients with acquired hypernatremia on ICU day 3 and those with sustained eunatremia over first three ICU days. Compared with eunatremia or hyponatremia, hypernatremia led to higher 7 day, 14 day, 28 day, and hospital mortality rates (p = 0.030, 0.009, 0.010, and 0.033, respectively). Compared with sustained eunatremia, acquired hypernatremia led to higher 7, 14, and 28 day mortality rates (p = 0.019, 0.042, and 0.028, respectively). The acquired hypernatremia group nonsignificantly trended toward increased hospital mortality (p = 0.056). Day 1 granulocyte colony-stimulating factor (G-CSF) and tumor necrosis factor (TNF) α levels were relatively low in patients with hypernatremia (p = 0.020 and 0.010, respectively) but relatively high in patients with acquired hypernatremia (p = 0.049 and 0.009, respectively). Thus, in ICU-admitted septic patients, hypernatremia on admission and in ICU-acquired hypernatremia were both associated with higher mortality. The higher mortality in patients with hypernatremia on admission was possibly related to the downregulation of G-CSF and TNF-α secretion after endotoxin stimulation. Compared to sustained eunatremia, acquired hypernatremia showed immunoparalysis at first and then hyperinflammation on day 3.

The Survival of Septic Patients with Compensated Liver Cirrhosis Is Not Inferior to That of Septic Patients without Liver Cirrhosis: A Propensity Score Matching Analysis

Background: We aimed to determine whether septic patients with liver cirrhosis (LC) had worse survival than septic patients without liver cirrhosis (WLC). We also investigated the survival of septic patients with compensated liver cirrhosis (CLC) and decompensated liver cirrhosis (DLC). Methods: This study enrolled 776 consecutive adult patients with sepsis admitted to the medical intensive care units of a tertiary referral hospital. Clinical factors and laboratory data were collected for analysis. Propensity scoring was also used for the control of selection bias. The variables included in the propensity model were age, sex, presence of diabetes mellitus, hypertension, cardiovascular accident, chronic kidney disease, malignancy, APCHE II (Acute Physiology and Chronic Health Evaluation) score, hemoglobin, and platelet data on the day when sepsis was confirmed. Seven-day, ICU, and hospital mortality were analyzed after correcting for these confounding factors. Results: Of the 776 septic patients, 64 (8.2%) septic patients presented with LC. Patients were divided into two groups—LC (n = 64) and WLC (n = 712)—which presented different rates of hospital mortality (LC: 62.5% vs. WLC: 41.0%, p = 0.001). We further separated septic patients with LC into two groups: patients with CLC (n = 24) and those with DLC (n = 40). After propensity score matching, the survival of septic patients with CLC (63.6%) was not inferior to patients WLC (54.5%) (p = 0.411). Patients with DLC had more hospital mortality, even after matching (p < 0.05). The Quick SOFA (qSOFA) score, SOFA score, and sub-SOFA score were also comparable between groups. SOFA scores were not significantly different between the CLC and WLC groups after matching. Poor SOFA scores were observed in the DLC group on days 3 and 7 after matching (p < 0.05). Conclusions: Septic patients with LC had higher mortality compared to patients WLC before matching. However, after propensity score matching, the survival of septic patients with CLC was non-inferior to patients WLC.

Application of Peak Glucose Range and Diabetes Status in Mortality Risk Stratification in Critically Ill Patients with Sepsis

The effects of diabetes and glucose on the outcomes of patients with sepsis are somewhat conflicting. This retrospective study enrolled 1214 consecutive patients with sepsis, including a subpopulation of 148 patients with immune profiles. The septic patients were stratified according to their Diabetes mellitus (DM) status or peak glucose level (three-group tool; P1: ≤140 mg/dL, P2: 141–220 mg/dL, P3: >220 mg/dL) on day 1. Although the DM group had a lower hazard ratio (HR) for 90-day mortality compared to non-DM patients, the adjusted HRs were insignificant. The modified sequential organ failure assessment-glucose (mSOFA-g) score can predict 90-day survival in patients with and without diabetes (β = 1.098, p < 0.001; β = 1.202, p < 0.001). The goodness of fit of the mSOFA-g score was 5% higher than the SOFA score of the subgroup without diabetes. The SOFA score and human leukocyte antigen-D-related (HLA-DR) expression were comparable between the groups. The P3 group had lower HLA-DR expression on days 1 and 3 and a higher 90-day mortality. The three-group tool was useful for predicting 90-day mortality in patients with separate Kaplan-Meier survival curves and mortality HRs in the construction and validation cohorts. The peak glucose level, instead of diabetes status, can be used as an easy adjunctive tool for mortality risk stratification in critically ill septic patients.

Application of a 72 h National Early Warning Score and Incorporation with Sequential Organ Failure Assessment for Predicting Sepsis Outcomes and Risk Stratification in an Intensive Care Unit: A Derivation and Validation Cohort Study

We investigated the best timing for using the National Early Warning Score 2 (NEWS2) for predicting sepsis outcomes and whether combining the NEWS2 and the Sequential Organ Failure Assessment (SOFA) was applicable for mortality risk stratification in intensive care unit (ICU) patients with severe sepsis. All adult patients who met the Third International Consensus Definitions for Sepsis and Septic Shock criteria between August 2013 and January 2017 with complete clinical parameters and laboratory data were enrolled as a derivation cohort. The primary outcomes were the 7-, 14-, 21-, and 28-day mortalities. Furthermore, another group of patients under the same setting between January 2020 and March 2020 were also enrolled as a validation cohort. In the derivation cohort, we included 699 consecutive adult patients. The 72 h NEWS2 had good discrimination for predicting 7-, 14-, 21-, and 28-day mortalities (AUC: 0.780, 0.724, 0.700, and 0.667, respectively) and was not inferior to the SOFA (AUC: 0.740, 0.680, 0.684, and 0.677, respectively). With the new combined NESO tool, the hazard ratio was 1.854 (1.203-2.950) for the intermediate-risk group and 6.810 (3.927-11.811) for the high-risk group relative to the low-risk group. This finding was confirmed in the validation cohort using a separated survival curve for 28-day mortality. The 72 h NEWS2 alone was non-inferior to the admission SOFA or day 3 SOFA for predicting sepsis outcomes. The NESO tool was found to be useful for 7-, 14-, 21-, and 28-day mortality risk stratification in patients with severe sepsis.

Dynamic monitoring of kidney injury status over 3 days in the intensive care unit as a sepsis phenotype associated with hospital mortality and hyperinflammation

Background

Sepsis-associated acute kidney injury (AKI) often worsens with the deterioration of a patient's condition. Therefore, we hypothesized that monitoring AKI dynamically from day 1 to day 3 was potential to predict hospital mortality. Specifically, we explored whether monitoring AKI dynamically in the intensive care unit (ICU) could be a sepsis phenotype predictive of mortality. A new classification was established based on the change in the AKI stage from admission day 1 and day 3. We compared the hospital mortality, cytokines, and immune response pattern between each group.

Methods

We retrospectively enrolled 523 patients with sepsis, and we calculated the AKI stages on day 1 and day 3 admission to ICUs.

Among these 523 people, 388 of them were assigned to normal, improved, and deteriorated groups according to the changes in the AKI stages. 263 of which did not develop AKI on day 1 and day 3 (normal group). The AKI stage improved in 68 patients (improved group) and worsened in 57 (deteriorated group). We compared the mortality rates between the groups, and identified the relationship between the dynamic AKI status, immune response patterns, and cytokine levels.

Results

The hospital mortality rate in the deteriorated group was higher than that in the non-deteriorated group (combination of normal and improved group) (p = 0.004). Additionally, according to the Kaplan–Meier analysis, the non-deteriorated group had a distinct hospital survival curve (p = 0.004). Furthermore, both the overexpression of tumor necrosis factor-α and decreased monocyte expression of human leukocyte antigen-DR were present in the deteriorated group.

Conclusions

The deteriorated group was associated with a higher hospital mortality rate, potentially resulting from an abnormal inflammatory response. Worsening AKI in the first 3 days of ICU admission may be a sepsis phenotype predictive of hospital mortality.

A new haematocytometric index: Predicting severity and mortality risk value in COVID-19 patients

INTRODUCTION

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 virus, is a major public health concern spanning from healthy carriers to patients with life-threatening conditions. Although most of COVID-19 patients have mild-to-moderate clinical symptoms, some patients have severe pneumonia leading to death. Therefore, the early prediction of disease prognosis and severity is crucial in COVID-19 patients. The main objective of this study is to evaluate the haemocytometric parameters and identify severity score associated with SARS-CoV-2 infection.

METHODS

Clinical and laboratory records were retrospectively reviewed from 97 cases of COVID-19 admitted to hospitals in Istanbul, Turkey. The patient groups were subdivided into three major groups: Group 1 (Non-critical): 59 patients, Group 2 (Critical-Survivors): 23 patients and Group 3 (Critical-Non-survivors):15 patients. These data was tested for correlation, including with derived haemocytometric parameters. The blood analyses were performed the Sysmex XN-series automated hematology analyser using standard laboratory protocols. All statistical testing was undertaken using Analyse-it software.

RESULTS

97 patients with COVID-19 disease and 935 sequential complete blood count (CBC-Diff) measurements (days 0-30) were included in the final analyses. Multivariate analysis demonstrated that red cell distribution width (RDW) (>13.7), neutrophil to lymphocyte ratio (NLR) (4.4), Hemoglobin (Hgb) (<11.4 gr/dL) and monocyte to neutrophil ratio (MNR) (0.084) had the highest area under curve (AUC) values, respectively in discrimination critical patients than non-critical patients. In determining Group 3, MNR (<0.095), NLR (>5.2), Plateletcount (PLT) (>142 x103/L) and RDW (>14) were important haemocytometric parameters, and the mortality risk value created by their combination had the highest AUC value (AUC = 0.911, 95% CI, 0886-0.931). Trend analysis of CBC-Diff parameters over 30 days of hospitalization, NLR on day 2, MNR on day 4, RDW on day 6 and PLT on day 7 of admission were found to be the best time related parameters in discrimination non-critical (mild-moderate) patient group from critical (severe and non-survivor) patient group.

CONCLUSION

NLR is a strong predictor for the prognosis for severe COVID-19 patients when the cut-off chosen was 4.4, the combined mortality risk factor COVID-19 disease generated from RDW-CV, NLR, MNR and PLT is best as a mortality haematocytometric index.

Impact of Body Mass Index on the Survival of Patients with Sepsis with Different Modified NUTRIC Scores

Nutritional status affects the survival of patients with sepsis. This retrospective study analyzed the impact of body mass index (BMI) and modified nutrition risk in critically ill (mNUTRIC) scores on survival of these patients. Data of 1291 patients with sepsis admitted to the intensive care unit (ICU) were extracted. The outcomes were mortality, duration of stay, ICU stay, and survival curve for 90-day mortality. Logistic regression analysis was performed to examine the risk factors for mortality. Cytokine and biomarker levels were analyzed in 165 patients. The 90-day survival of underweight patients with low mNUTRIC scores was significantly better than that of normal-weight patients with low mNUTRIC scores (70.8% vs. 58.3%, respectively; p = 0.048). Regression model analysis revealed that underweight patients with low mNUTRIC scores had a lower risk of mortality (odds ratio = 0.557; p = 0.082). Moreover, normal-weight patients with low mNUTRIC scores had the lowest human leukocyte antigen DR (HLA-DR) level on days 1 (underweight vs. normal weight vs. overweight: 94.3 vs. 82.1 vs. 94.3, respectively; p = 0.007) and 3 (91.8 vs. 91.0 vs. 93.2, respectively; p = 0.047). Thus, being underweight may not always be harmful if patients have optimal clinical nutritional status. Additionally, HLA-DR levels were the lowest in patients with low survival.

Serum N-Glycomics Stratifies Bacteremic Patients Infected with Different Pathogens

Bacteremia—i.e., the presence of pathogens in the blood stream—is associated with long-term morbidity and is a potential precursor condition to life-threatening sepsis. Timely detection of bacteremia is therefore critical to reduce patient mortality, but existing methods lack precision, speed, and sensitivity to effectively stratify bacteremic patients. Herein, we tested the potential of quantitative serum N-glycomics performed using porous graphitized carbon liquid chromatography tandem mass spectrometry to stratify bacteremic patients infected with Escherichia coli (n = 11), Staphylococcus aureus (n = 11), Pseudomonas aeruginosa (n = 5), and Streptococcus viridans (n = 5) from healthy donors (n = 39). In total, 62 N-glycan isomers spanning 41 glycan compositions primarily comprising complex-type core fucosylated, bisecting N-acetylglucosamine (GlcNAc), and α2,3-/α2,6-sialylated structures were profiled across all samples using label-free quantitation. Excitingly, unsupervised hierarchical clustering and principal component analysis of the serum N-glycome data accurately separated the patient groups. P. aeruginosa-infected patients displayed prominent N-glycome aberrations involving elevated levels of fucosylation and bisecting GlcNAcylation and reduced sialylation relative to other bacteremic patients. Notably, receiver operating characteristic analyses demonstrated that a single N-glycan isomer could effectively stratify each of the four bacteremic patient groups from the healthy donors (area under the curve 0.93–1.00). Thus, the serum N-glycome represents a new hitherto unexplored class of potential diagnostic markers for bloodstream infections.

Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population

Since December 2019 the novel coronavirus SARS-CoV-2 has been identified as the cause of the pandemic COVID-19. Early symptoms overlap with other common conditions such as common cold and Influenza, making early screening and diagnosis are crucial goals for health practitioners. The aim of the study was to use machine learning (ML), an artificial neural network (ANN) and a simple statistical test to identify SARS-CoV-2 positive patients from full blood counts without knowledge of symptoms or history of the individuals. The dataset included in the analysis and training contains anonymized full blood counts results from patients seen at the Hospital Israelita Albert Einstein, at São Paulo, Brazil, and who had samples collected to perform the SARS-CoV-2 rt-PCR test during a visit to the hospital. Patient data was anonymised by the hospital, clinical data was standardized to have a mean of zero and a unit standard deviation. This data was made public with the aim to allow researchers to develop ways to enable the hospital to rapidly predict and potentially identify SARS-CoV-2 positive patients. We find that with full blood counts random forest, shallow learning and a flexible ANN model predict SARS-CoV-2 patients with high accuracy between populations on regular wards (AUC = 94-95%) and those not admitted to hospital or in the community (AUC = 80-86%). Here, AUC is the Area Under the receiver operating characteristics Curve and a measure for model performance. Moreover, a simple linear combination of 4 blood counts can be used to have an AUC of 85% for patients within the community. The normalised data of different blood parameters from SARS-CoV-2 positive patients exhibit a decrease in platelets, leukocytes, eosinophils, basophils and lymphocytes, and an increase in monocytes. SARS-CoV-2 positive patients exhibit a characteristic immune response profile pattern and changes in different parameters measured in the full blood count that are detected from simple and rapid blood tests. While symptoms at an early stage of infection are known to overlap with other common conditions, parameters of the full blood counts can be analysed to distinguish the viral type at an earlier stage than current rt-PCR tests for SARS-CoV-2 allow at present. This new methodology has potential to greatly improve initial screening for patients where PCR based diagnostic tools are limited.

Risk factors and associated outcomes of ventilator-associated events developed in 28 days among sepsis patients admitted to intensive care unit

We hypothesized that Ventilator-Associated Event (VAE) within 28 days upon admission to medical intensive care units (ICUs) can be a predictor for poor outcomes in sepsis patients. We aimed to determine the risk factors and associated outcomes of VAE. A total of 453 consecutive mechanically ventilated (MV) sepsis patients were enrolled. Of them, 136 patients had immune profile study. Early VAE (< 7-day MV, n = 33) was associated with a higher mortality (90 days: 81.8% vs. 23.0% [non-VAE], P < 0.01), while late VAE (developed between 7 and 28 days, n = 85) was associated with longer MV day (43.8 days vs. 23.3 days [non-VAE], P < 0.05). The 90-day Kaplan–Meier survival curves showed three lines that separate the groups (non-VAE, early VAE, and late VAE). Cox regression models with time-varying coefficient covariates (adjusted for the number of days from intubation to VAE development) confirmed that VAE which occurred within 28 days upon admission to the medical ICUs can be associated with higher 90-day mortality. The risk factors for VAE development include impaired immune response (lower human leukocyte antigen D-related expression, higher interleukin-10 expression) and sepsis progression with elevated SOFA score (especially in coagulation sub-score).