Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is necessary especially in elderly patients. Artificial intelligence shows benefits in early warning. The aim of the study was to construct an early machine warning model for elderly sepsis patients and evaluate its performance. We collected elderly patients from General Hospital of Ningxia Medical University emergency department and intensive care unit from 01 January 2021 to 01 August 2023. The clinical data was divided into a training set and a test set. A total of 2976 patients and 12 features were screened. We used 8 machine learning models to build the warning model. In conclusion, we developed a model based on XGBoost with an AUROC of 0.971, AUPRC of 0.862, accuracy of 0.95, specificity of 0.964 and F1 score of 0.776. Of all the features, baseline APTT played the most important role, followed by baseline lymphocyte count. Higher level of baseline APTT and lower level of baseline lymphocyte count may indicate higher risk of sepsis occurrence. We developed a high-performance early warning model for sepsis in old age based on machine learning in order to facilitate early treatment but also need further external validation.

Data of low-density neutrophils (LDN), the neutrophils in the peripheral blood mononuclear cells (PBMC) fraction, in sepsis is still less. As such, LDN (CD66b-positive cells in PBMC) was highest in intensive care unit (ICU) patients with sepsis (n=24) compared with non-sepsis (n=10) and healthy control (n=20), with a negative correlation with lymphocyte count and could predict secondary infection and mortality with the area under the curve (AUC) at 0.79 and 0.84, respectively. Compared with sepsis normal-density neutrophils (NDN), sepsis-LDN demonstrated higher expression of CD66b, CD63, CD11b, and CD184, but lower expression of CD62L and CD182 and defects of effector functions, including phagocytosis and apoptosis. The t-distributed stochastic neighbor embedding (t-SNEs) demonstrated high program cell death ligand-1 (PD-L1) in sepsis-LDN. In sepsis samples, the T cell proliferation in PBMC (T cells with LDNs) was lower than that in the isolated T cells (T cells alone) and incubation of anti-PD-L1 neutralizing antibody, but not a reactive oxygen species (ROS) scavenger (N-acetyl cysteine), improved the T cell suppression. Additionally, 30 min lipopolysaccharide (LPS) activation altered healthy control NDN into LPS-LDN (reduced density) and LPS-NDN (maintain density) with similarly elevated CD66b, CD11B, and CD62L. However, LPS-LDN (in vitro LDN) showed lower expression of CD63, CD184, and PD-L1 compared with LDN from patients (sepsis-LDN), suggesting a partial LPS impact on LDN generation. From the microscopic-based method (Wright's staining in PBMC), sepsis-LDN demonstrated a mixed population of mature and immature cells with a good correlation with the flow-based analysis (Bland-Altman analysis and AUC). In conclusion, LDN in sepsis, partly generated by LPS activation, was associated with secondary infection and T cell suppression, mainly through the expression of PD-L1, which might be an immune suppression biomarker, especially with a less expensive microscopic-based method.

The most frequently ordered laboratory test worldwide is the complete blood count (CBC). As clinical chemists are increasingly assigned to assist or direct laboratories outside of the traditional clinical chemistry sections, such as the automated hematology section, expertise must be established. This review article is a dedication to that ongoing effort.

In this primer, the white blood cell (WBC) test components of the CBC are introduced, followed by a discussion of the laboratory evaluation of leukopenia and leukocytosis.

The laboratorian's approach to consult cases should be guided by the patient's clinical history and presentation while being able to provide key laboratory-based insights to assist in resolving result discrepancies that may otherwise go unnoticed.

Stress due to surgical trauma decreases postoperative lymphocyte counts (LCs), potentially favouring the occurrence of postoperative infections (PIs).

We aimed to determine whether postoperative lymphopaenia following thoracic or gastrointestinal cancer surgery is an independent risk factor for PIs and to identify modifiable factors related to anaesthesia and surgical procedures that might affect its occurrence.

The EVALYMPH study was a prospective, multicentre cohort study with a 30-day patient follow-up. Multivariate analyses were performed to determine the risk factors for PIs and for postoperative lymphopaenia.

Patients were included from January 2016 to September 2017 in 25 French centres.

Adult patients admitted for thoracic or gastrointestinal cancer surgery were eligible for inclusion.

PIs within 30 days after surgery were defined as urinary tract infections, pneumonia, surgical site infections and other infections (bloodstream infections or pleurisy).

Of 1207 patients included, 273 (22.6%) developed at least one infection within 30 days after surgery, with a median [IQR] time to onset of 8 [5 to 11] days. An increased risk of PI was significantly associated with an ASA score of IV: hazard ratio (HR) 4.27 (95% confidence interval (CI), 1.87 to 9.72), surgery > 200 min (HR 1.58 (1.15 to 2.17) and lymphopaenia on postoperative day 1 (POD1) (HR 1.56 (1.08 to 2.25). This risk was associated with changes in postoperative LC over time ( P  = 0.001) but not with preoperative LC ( P  = 0.536).POD1 lymphopenia was related to patient characteristics and duration of surgery but not to potentially modifiable other surgical or anaesthetics factors.

POD1 lymphopaenia was associated with PIs in patients undergoing thoracic or gastrointestinal cancer surgery. To individualise care, patient characteristics and surgery duration should be taken into account.

ClinicalTrials.gov Identifier: NCT02799251.

Immunosuppressive agents, although indispensable in the treatment of chronic kidney diseases (CKD), could compromise the patient's immune function. The risk factor for in-hospital mortality in immunocompromised CKD patients with severe infections remain elusive.

We conducted a retrospective analysis of the clinical data of CKD patients who received immunosuppressive agents and presented severe infections. The cohort comprised 272 patients, among whom 73 experienced mortalities during their hospitalization. Logistic regression was employed on the training set to identify key feature variables and construct a predictive model for in-hospital mortality among immunocompromised CKD patients following severe infections. To facilitate clinical application, we constructed a nomogram to visually represent the predictive model.

Our findings indicate that ventilator use, vasoactive drug administration, elevated lactate dehydrogenase (LDH), total bilirubin (TBIL) levels, and persistent lymphopenia(PL) are effective predictors of in-hospital mortality in immunocompromised patients with severe infections. These variables were subsequently incorporated to construct a robust prognostic model. Our model demonstrated excellent discriminative ability (AUC = 0.959, 95% CI, 0.924-0.994), significantly outperforming the Sequential Organ Failure Assessment (SOFA) score (AUC = 0.878, 95% CI, 0.825-0.930) and quick Pitt Bacteremia Score (qPBS) (AUC = 0.897, 95% CI, 0.846-0.947). Calibration curve analysis and the Hosmer-Lemeshow (HL) test corroborate the concordance of our model with empirical observations. Furthermore, decision curve analysis (DCA) underscores the superior clinical utility of our predictive model when compared to the SOFA score and qPBS score. Most importantly, our results showed that PL is the most important predictor of in-hospital mortality in immunocompromised patients following severe infection.

Our findings highlight PL as the most significant predictor of in-hospital mortality in immunocompromised CKD patients. A clinical prediction model incorporating PL as a key variable exhibited robust performance in terms of diagnostic accuracy and clinical utility.

Lymphopenia and failure of lymphocytes to mount an early IFN-γ response correlate with increased mortality in COVID-19. Given the essential role of CD4 helper and CD8 cytotoxic cells in eliminating viral pathogens, this profound loss in lymphocytes may impair patients' ability to eliminate the virus. IL-7 is a pleiotropic cytokine that is obligatory for lymphocyte survival and optimal function.

We conducted a prospective, double-blind, randomized, placebo-controlled trial of CYT107, recombinant human IL-7, in 109 critically ill, patients with lymphopenia who have COVID-19. The primary endpoint was to assess CYT107's effect on lymphocyte recovery with secondary clinical endpoints including safety, ICU and hospital length-of-stay, incidence of secondary infections, and mortality.

CYT107 was well tolerated without precipitating a cytokine storm or worsening pulmonary function. Absolute lymphocyte counts increased in both groups without a significant difference between CYT107 and placebo. Patients with COVID-19 receiving CYT107 but not concomitant antiviral medications, known inducers of lymphopenia, had a final lymphocyte count that was 43% greater than placebo (P = 0.067). There were significantly fewer treatment-emergent adverse events in CYT107 versus placebo-treated patients (P < 0.001), consistent with a beneficial drug effect. Importantly, CYT107-treated patients had 44% fewer hospital-acquired infections versus placebo-treated patients (P = 0.014).

Given that hospital-acquired infections are responsible for a large percentage of COVID-19 deaths, this effect of CYT107 to decrease nosocomial infections could substantially reduce late morbidity and mortality in this highly lethal disease. The strong safety profile of CYT107 and its excellent tolerability provide support for trials of CYT107 in other potential pandemic respiratory viral infections.

NCT04379076, NCT04426201, NCT04442178, NCT04407689, NCT04927169.

Funding for the trial was provided by RevImmune and the Cancer Research Institute.

Sepsis induces profound derangements in the immune system, including lymphopenia, which correlates with immunosuppression and poor prognosis. However, most evaluations of immunosuppression in sepsis patients rely on static, sporadic lymphocyte counts, lacking dynamic modeling over the disease course. This study aimed to apply latent class mixed modeling on longitudinal lymphocyte counts to uncover heterogeneous trajectory phenotypes in sepsis patients and assess their predictive value for clinical outcomes.

Four lymphocyte trajectory phenotypes were identified in the retrospective cohort (n=2,149) and externally validated (n=2,388): high-declining (α, 3.8%), stable-medium (β, 69.3%), high-increasing (γ, 3.2%), and stable-low (δ, 23.8%). The α phenotype exhibited the highest disease severity and mortality (25.9%) compared with other phenotypes in both cohorts. In the prospective cohort (n=1,056), all lymphocyte subset counts differed among phenotypes on admission (P <.001) and were lower in non-survivors (P<.05). Multivariable regression demonstrated that age, Acute Physiology and Chronic Health Evaluation-II score, heart rate, natural killer cell count, infection source, and lymphocyte trajectory phenotype were independent predictors of 28-day mortality. A nomogram combining these variables provided individualized risk estimations.

The lymphocyte trajectories delineated novel dynamic phenotypes associated with divergent sepsis outcomes. Incorporating longitudinal trajectory modeling and lymphocyte subsets may improve prognostic risk assessment and guide the selection of immunotherapies tailored to specific immune phenotypes in sepsis patients.

https://www.chictr.org.cn/showproj.aspx?proj=18277, identifier ChiCTR-40 ROC-17010750.

Sepsis remains a significant cause of morbidity and mortality worldwide. Although many more patients are surviving the acute event, a substantial number enters a state of persistent inflammation and immunosuppression, rendering them more vulnerable to infections. Modulating the host immune response has been a focus of sepsis research for the past 50 years, yet novel therapies have been few and far between. Although many septic patients have similar clinical phenotypes, pathways affected by the septic event differ not only between individuals but also within an individual over the course of illness. These differences ultimately impact overall immune function and response to treatment. Defining the immune state, or endotype, of an individual is critical to understanding which patients will respond to a particular therapy. In this review, we highlight current approaches to define the immune endotype and propose that these technologies may be used to "prescreen" individuals to determine which therapies are most likely to be beneficial.

Multiple organ dysfunction syndrome (MODS), defined as two or more organ dysfunction during infection or following shock or trauma, correlates with poor outcomes. Clinical data, including MODS in the renal intensive care unit (ICU), are scarce. Therefore, we investigate the clinical characteristics and prognosis of patients with MODS in the renal ICU.

A single-center, retrospective cohort study of 99 adult patients with MODS admitted to the renal ICU of the National Clinical Research Center of Kidney Disease, Jinling Hospital, Nanjing, China, from October 1, 2011 to October 1, 2021.

99 patients had a mean age of 49.7 ± 16.5 years old, and 51 (51.5%) patients died within 28 days after being admitted to the renal ICU. Infection (80 patients, 80.8%) was the most common reason for admission, with 47 cases being pulmonary infections. Of all of the 99 patients, 73 (73.7%) presented with persistent lymphocytopenia (lymphocyte count < 1.1 × 109/L from the day of ICU admission through to day 7), with 33 and 40 presenting moderate (lymphocyte count 0.6-1.1 × 109/L) and severe persistent lymphopenia (lymphocyte count ≤ 0.6 × 109/L), respectively. These patients had higher illness severity and chronic kidney disease (CKD) prevalence. Patients with severe persistent lymphopenia were associated with higher 28-day ICU mortality (87.5% vs. 42.4% vs. 7.7%, p < 0.001) versus those with moderate and without persistent lymphopenia. Multivariable logistic regression analysis revealed that the number of organs involved, APACHE-II score, and persistent lymphopenia were independent risk factors for 28-day mortality in patients with MODS. The value of lymphocyte count on day 7 of admission in predicting poor prognosis of patients was higher than on other days (Area Under Curve, AUC = 0.831).

Patients with MODS are critically ill with high mortality. Persistent lymphopenia is frequent in patients with MODS and is independently associated with 28-day mortality. Lymphocyte counts on day 7 of admission were shown to be highly predictive of prognosis.

Sepsis causes significant worldwide morbidity and mortality. Inability to clear an infection and secondary infections are known complications in severe sepsis and likely result in worsened outcomes. We sought to characterize risk factors of these complications.

We performed a secondary analysis of clinical data from 401 subjects enrolled in the PHENOtyping sepsis-induced Multiple organ failure Study. We examined factors associated with prolonged infection, defined as infection that continued to be identified 7 days or more from initial identification, and secondary infection, defined as new infections identified ≥ 3 days from presentation. Multivariable adjustment was performed to examine laboratory markers of immune depression, with immunocompromised and immunocompetent subjects analyzed separately.

Illness severity, immunocompromised status, invasive procedures, and site of infection were associated with secondary infection and/or prolonged infection. Persistent lymphopenia, defined as an absolute lymphocyte count (ALC) < 1000 cells/µL twice in the first five days, and persistent neutropenia, defined as absolute neutrophil count (ANC) < 1000 cells/µL twice in the first five days, were associated with secondary and prolonged infections. When adjusted in multivariable analysis, persistent lymphopenia remained associated with secondary infection in both immunocompromised (aOR = 14.19, 95% CI [2.69, 262.22] and immunocompetent subjects (aOR = 2.09, 95% CI [1.03, 4.17]). Persistent neutropenia was independently associated with secondary infection in immunocompromised subjects (aOR = 5.34, 95% CI [1.92, 15.84]). Secondary and prolonged infections were associated with worse outcomes, including death.

Laboratory markers of immune suppression can be used to predict secondary infection. Lymphopenia is an independent risk factor in immunocompromised and immunocompetent patients for secondary infection.

Low blood absolute lymphocyte count (ALC) may predict severe COVID-19 outcomes. Knowledge gaps remain regarding the relationship of ALC trajectory with clinical outcomes and factors associated with lymphopenia.

Our post hoc analysis of the Therapeutics for Inpatients with COVID-19 platform trial utilized proportional hazards models to assess relationships between Day (D) 0 lymphopenia (ALC < 0.9 cells/uL), D0 severe lymphopenia (ALC < 0.5 cells/uL) or lymphopenia trajectory between D0 and D5 with mortality and secondary infections, and with sustained recovery using Fine-Gray models. Logistic regression was used to assess relationships between clinical variables and D0 lymphopenia or lymphopenia trajectory.

D0 lymphopenia (1426/2579) and severe lymphopenia (636/2579) were associated with increased mortality (aHR 1.48; 1.08, 2.05, p = 0.016 and aHR 1.60; 1.20, 2.14, p = 0.001) and decreased recovery (aRRR 0.90; 0.82, 0.99, p = 0.033 and aRRR 0.78; 0.70, 0.87, p < 0.001 respectively). Trial participants with persistent D5 lymphopenia had increased mortality, and increased secondary infections, and participants with persistent or new lymphopenia had impaired recovery, as compared to participants with no lymphopenia. Persistent and new lymphopenia were associated with older age, male sex; prior immunosuppression, heart failure, aspirin use, and normal body mass index; biomarkers of organ damage (renal and lung), and ineffective immune response (elevated IL-6 and viral nucleocapsid antigen levels). Similar results were observed with severe lymphopenia.

Lymphopenia was predictive of severe COVID-19 outcomes, particularly when persistent or new during hospitalization. A better understanding of the underlying risk factors for lymphopenia will help illuminate disease pathogenesis and guide management strategies.

The D-dimer to lymphocyte ratio (DLR), a novel inflammatory biomarker, had been shown to be related to adverse outcomes in patients with various diseases. However, there was limited research on the relationship between the DLR and adverse outcomes in patients with infectious diseases, particularly those with sepsis. Therefore, this study aimed to explore the association between the DLR and in hospital all-cause mortality in elderly patients with sepsis.

A total of 1123 patients admitted in intensive care unit (ICU) were included in this study. The patients were categorized into quartiles (Q1-Q4) based on their DLR values. The primary outcomes included hospital mortality and ICU mortality. Kaplan-Meier analysis was conducted to compare all-cause mortality among the four DLR groups. The association between DLR and all-cause mortality in patients with sepsis was further elucidated using the receiver operating characteristic (ROC) curve and Cox proportional hazards regression analysis.

The study included participants with a median age of 75 (65-84) years, with 707 (63.0%) being male. The rates of hospital mortality and ICU mortality were 33.7% and 31.9%, respectively. Kaplan-Meier analysis highlighted a significantly increased risk of all-cause mortality among patients with elevated DLR values (log-rank p < 0.001). ROC curve analyses revealed that DLR had a stronger ability to predict hospital mortality and ICU mortality in patients with sepsis than D-dimer or Lym. Multivariable Cox proportional hazards analyses revealed DLR as an independent predictor of hospital death [per 1 SD increase in DLR: HR (95% CI): 1.098 (1.020-1.181); p = 0.013] and ICU death [per 1 SD increase in DLR: HR (95% CI): 1.095 (1.017-1.180); p = 0.017] during the hospital stay.

A higher DLR value was associated with hospital and ICU all-cause death in elderly patients with sepsis. This finding demonstrated that the DLR could be a convenient and useful prognostic marker for sepsis prognosis.

This article aimed to investigate the correlation between blood immune cells and the prognosis in the early phase of pediatric sepsis and construct a prediction model for pediatric intensive care unit (PICU) mortality.

A total of 348 children admitted with sepsis to our PICU were retrospectively collected between January 2020 and June 2024. Of these, 242 children admitted from January 2020 to October 2022 were designated as the modeling group, while 106 children admitted between November 2022 and June 2024 were designated as the prospective validation group. Peripheral blood immune-related parameters, measured from the day of PICU admission to day 7, were analyzed in the modeling group. Risk factors were identified through multivariate logistic regression and integrated into a predictive nomogram. The nomogram was then applied to the prospective validation group to assess its discrimination and calibration. The nomogram's performance was evaluated using the area under the receiver operating characteristic curves (AUC), calibration plots, and decision curve analysis for both groups.

Complicated with underlying diseases, invasive mechanical ventilation, increased pediatric risk of mortality score or pediatric sequential organ failure assessment score, and lymphopenia (d1) were independent risk factors for PICU mortality. The 90-day survival of patients with lymphopenia on the first day after admission was low. In addition, patients with persistent lymphopenia had higher mortality. The nomogram showed an AUC of 0.861 (95% CI: 0.813 to 0.909) in the modeling group and 0.875 (95% CI: 0.797 to 0.953) in the prospective validation group. The nomogram also performed well based on the calibration curve and decision curve analysis.

Assessing lymphocytes within seven days of PICU admission may be conducive to identifying children with sepsis at increased mortality risk. The nomogram performed well in predicting PICU mortality among patients of interest.

Immunoparalysis is a state of immune dysfunction characterized by a marked reduction in the immune system's responsiveness, often observed following severe infections, trauma, or critical illness. This study aimed to perform a longitudinal assessment of immune function over the initial two weeks following the onset of sepsis and critical illness.

We compared ex vivo-stimulated cytokine release from whole blood of critically ill patients to traditional markers of immunoparalysis, including monocyte Human Leukocyte Antigen (mHLA)-DR expression and absolute lymphocyte count (ALC). A total of 64 critically ill patients were recruited in a tertiary care academic medical setting, including 31 septic and 33 non-septic patients.

While mHLA-DR expression significantly increased over time, this was primarily driven by the non-septic subset of critically ill patients. ALC recovery was more pronounced in septic patients. Ex vivo stimulation of blood from septic patients revealed significant increases in TNF and IL-6 production over time. However, interferon-gamma production varied depending on the ex vivo stimulant used, and after normalization of cytokine concentrations to lymphocyte counts, it did not show significant recovery over time from illness onset. No significant correlation was found between mHLA-DR expression and other immunoparalysis biomarkers.

These findings suggest the need for more nuanced immune monitoring approaches beyond the traditional 'sepsis' versus 'non-sepsis' classifications in critically ill patients. Additionally, they provide further evidence of a potential window for targeted immunotherapy in the first weeks of critical illness.

Persistent lymphopenia can be regarded as an important index of acquired immune dysfunction in sepsis. Whether the specific immune factor changes in septic patients with lymphopenia and the correlation to gut microbiota and metabolites remain unclear.

This single-center prospective observation conducted lymphocyte subgroup analysis of blood samples and 16S rRNA gene amplicons sequencing and untargeted metabolomics analysis of fecal samples from 36 subjects with the persistent (≥3d) (n = 21) and non-persistent lymphopenia (<3d) (n = 15).

The persistent lymphopenia showed higher the 28d mortality and 90d mortality, while significantly lower CD3+T/LY, CD3+T cells, CD3+CD4+T cells, CD3+CD8+T cells, Th1 cells, Th2 cells, CD45RA + Treg cells. The 16S rRNA results showed that Staphylococcus, Peptostreptococcus, Bulleidia, Leuconostoc were significant enriched in the persistent lymphopenia. The metabolomics analysis showed that α-Ketoisovaleric acid was increased and 7-DHCA, α-MCA, β-MCA, HCA, LCA-3S, CA, UCA and Citramalic acid were decreased in the persistent lymphopenia.

In the process of interaction between host receptors and gut microbiota in patients with persistent lymphopenia sepsis, with a significant reduction in gut microbiota diversity and bile acid metabolites. That can affect various inflammatory pathways of gut immune cells, causing immune dysfunction in the body, which may be one of the main causes of death.

The objective of this study was to evaluate the association between the minimal count of lymphocyte (Ly_Min) after cardiac surgery with cardiopulmonary bypass and the occurrence of infections within the first 30 postoperative days (POD).

From a local European Congenital Heart Surgeons Association (ECHSA) database, all cardiac surgeries with cardiopulmonary bypass in children under 18 years old between January 2014 and December 2021 were eligible. Infections occurring within 30 POD were prospectively recorded according to ECHSA definitions, and classified into sepsis, pneumonia, wound infection, mediastinitis or endocarditis. For each surgery, Ly_Min was collected during the first 2 POD and the optimal threshold for predicting infection was chosen using receiver operating characteristic curve analysis. Univariate and multivariate logistic regression analyses were performed to identify variables associated with the risk of infection.

Of 1428 surgeries conducted over the 8-year period, 111 (8%) were complicated by at least 1 infection, including pneumonia (n = 45), wound infection (n = 41), sepsis (n = 24), mediastinitis (n = 20) and endocarditis (n = 3). Mean Ly_Min in the first 2 POD was lower in the infected group compared with the noninfected group (1.32 ± 0.81 vs. 1.81 ± 1.05 × 109/L, P < 0.001). After adjusting for confounders, Ly_Min <1.105 × 109/L within the first 1 POD was independently associated with an increased risk of postoperative infections (adjusted odds ratio = 1.75, 95% confidence interval: 1.10-2.79, P = 0.019).

In this large single-center cohort of pediatric cardiac surgeries, Ly_Min during the first 2 POD was associated with the development of infections within 30 days after cardiopulmonary bypass.

Sepsis pathophysiology involves a dysregulated immune response to infection, excessive inflammation, and immune paralysis. This study explores the relationships between cell death biomarkers (serum-soluble levels of programmed cell death protein 1 (PD-1), programmed death ligand 1 (PD-L1), and interleukin-7 (IL-7)) and the percentages of various lymphocyte subsets in relation to the severity and progression of sepsis. This prospective, observational study included 87 critically ill patients. We monitored parameters on days 1 (sepsis was diagnosed according to the Sepsis-3 Consensus) and 5. We established an IL-7 cutoff value of 1.94 pg/mL by comparing levels between a healthy control group and patients with sepsis (p < 0.0001). Lymphopenia was observed in all patients, with negative correlations between helper T lymphocytes and cytotoxic and B lymphocytes, and positive correlations involving cytotoxic lymphocytes across all groups. We found correlations between PD-1/PD-L1 and lymphocyte subsets. IL-7 showed a statistical correlation with PD-1 in non-survivors. Assessing lymphocyte levels shows potential as a biomarker for evaluating the progression of sepsis. Monitoring IL-7 levels could help assess survival, as low levels are associated with higher mortality risk. Monitoring IL-7 levels could help assess survival, as low levels are associated with higher mortality risk. Elevated PD-1/PD-L1 expression impairs costimulatory signalling, reducing T cell responses and lymphopenia, which increases the risk of nosocomial infections.

This study aimed to assess the influence of ulinastatin (UTI) on lymphocyte apoptosis and autophagy in sepsis patients, as well as its effect on inflammatory factors and vital organ function, with the goal of providing insights for improved clinical management of sepsis. A total of 40 sepsis patients were randomly assigned to the UTI group or the control group. The UTI group received standard treatment plus intravenous UTI, while the control group received standard treatment alone. Peripheral blood samples were collected at multiple time points for analysis of lymphocyte apoptosis, autophagy, inflammatory markers, and organ function. Various experimental techniques including Hoechst staining, transmission electron microscopy, and Western blot analysis were utilized to assess lymphocyte apoptosis, autophagy, and related protein expression levels. The study revealed that UTI treatment significantly inhibited lymphocyte apoptosis and promoted autophagy in sepsis patients. The levels of autophagy-related proteins LC3-II and Beclin-1 were substantially elevated, while the ratio of anti-apoptotic Bcl-2 to pro-apoptotic Bax was increased following UTI treatment. Furthermore, the levels of inflammatory markers IL-6, procalcitonin, and C-reactive protein were markedly reduced in the UTI group compared to the control group. Additionally, UTI treatment led to improved liver, kidney and cardiac function as evidenced by reduced levels of liver enzymes and creatinine, and cardiac enzymes. The findings of this study demonstrate that UTI exerts a protective effect on septic patients by inhibiting lymphocyte apoptosis, promoting autophagy, and attenuating systemic inflammation. Moreover, UTI treatment was associated with improved liver, kidney, and cardiac function in septic patients. These results contribute to a better understanding of the clinical management of sepsis and underscore the potential of UTI as a therapeutic intervention in septic patients.

Weaning outcomes of patients receiving mechanical ventilation (MV) are affected by multiple factors. A clinical feature of critically ill patients is the presence of lymphopenia, however the clinical significance of lymphopenia in patients receiving prolonged MV remains unclear.

We enrolled patients who received at least 21 consecutive days of MV in a medical center in Taiwan between 2007 and 2016. Patients with and without lymphopenia (mean count <1000/μL) were compared after propensity score matching.

Of the 3460 patients included in the analysis, 1625 (47.0%) were liberated from MV within 100 days. Lymphopenia and severe lymphopenia (mean count <500/μL) during the first 21 days of MV were common (52.9% and 14.5%, respectively), and restricted cubic spline analysis showed a significant reduction in weaning success when the lymphocyte count dropped below 1000/μL. After propensity score matching, the patients with lymphopenia during the third week had a lower rate of weaning success within 100 days (p = 0.005) and a higher in-hospital mortality rate (p = 0.001) than those without lymphopenia. The lymphopenia group also had significantly reduced platelet (p < 0.001) and albumin (p < 0.001) levels.

Our findings suggest that lymphopenia during the first 3 weeks may be a marker of poor weaning outcomes in patients with prolonged MV.

Identifying high-risk children with poor prognoses during the early stages of sepsis and providing timely and appropriate interventions are imperative. The objective of this study was to develop a prognostic prediction model for pediatric sepsis utilizing the neutrophil to lymphocyte and platelet ratio (NLPR).

A multivariable logistic regression analysis was conducted to investigate the association between the NLPR and in-hospital mortality among septic children upon admission. To minimize the potential confounding factors that could introduce bias, a propensity score matching analysis was employed. Subsequently, a nomogram prediction model was developed to assess the risk of in-hospital mortality in septic children, incorporating the NLPR as a key factor. The performance of this prediction model was then evaluated.

A total of 230 septic children were enrolled in the study. Multivariate logistic regression analysis revealed that the NLPR was an independent risk factor for in-hospital mortality, with an odds ratio of 8.31 (95% CI 3.69-18.68). The finding remained consistent after propensity score matching analysis. A nomogram prediction model was developed that incorporates the NLPR, arterial blood lactate level, and Pediatric Critical Illness Score (PCIS). Among the various models, this nomogram exhibited the highest area under the curve (AUC) value of 0.831. The calibration curve demonstrated good agreement between the predicted and observed outcomes. Decision curve analysis indicated that the prediction model outperformed the PCIS. Internal validation of the model yielded an AUC value of 0.824 and a kappa value of 0.420, indicating its reliability and accuracy.

The NLPR serves as an independent risk factor for in-hospital mortality among septic children. The nomogram prognostic prediction model could effectively guide clinicians in accurately predicting the prognosis of septic children, thus enabling timely and effective treatment interventions.

Septic melioidosis is associated with high mortality in resource-limited settings. The current study aims to find 28-d all-cause mortality predictors within 24 h of admission in melioidosis patients presenting to an emergency department.

This retrospective cohort study (2018-2022) included melioidosis patients divided into two groups based on their primary outcomes (28-d mortality). All the clinically relevant factors significant in univariate analysis were selected for binary logistic regression analysis. Those factors significant in logistic regression analysis were considered independent predictors of mortality.

Of the 53 patients with melioidosis, the 28-d mortality of melioidosis patients admitted to the emergency department was 51% (n=27). Respiratory involvement, renal dysfunction, haemodynamic instability, elevated aspartate transaminase, elevated activated partial thromboplastin time, elevated CRP, elevated procalcitonin, decreased albumin, decreased absolute neutrophil count, decreased absolute lymphocyte count and use of piperacillin-tazobactam or azithromycin were significant predictors of mortality on univariate analysis. Vasopressor requirement (p=0.03) and low serum albumin level (0.041) at presentation were independent predictors of mortality.

Vasopressor requirement and low albumin levels at presentation in the emergency department are independent predictors of mortality. There is a need to create awareness among primary care physicians to enable early diagnosis and prompt initiation of treatment.

Polytrauma is a complex condition associated with poor outcomes and high mortality rates resulting from severe damage and complicated complications. This study sought to ascertain the incidence of chronic complications in polytrauma patients, as well as the early immune changes and risk factors.

A multicenter, prospective and observational cohort study was conducted at the emergency surgery or traumatic intensive care unit (TICU) of the Advanced Trauma Center from August 2020 to July 2023. A total of 2033 consecutive trauma patients were included in the study. In the first 1, 7, and 14 days after admission, flow cytometry and immunoassay kits were used to examine cytokine release and lymphocyte count.

Trauma patients were reported 33.8% (687/2033) chronic complication rates, with monotrauma patients reported 8.1% (55/683) and polytrauma patients reported 59.4% (802/1350). And the four most frequent chronic complications in polytrauma patients were chronic musculoskeletal pain (30.4%), post-traumatic osteoarthritis (27.2%), chronic wound (21.6%), and chronic lung injury (14.1.%) .There were significant differences in lymphocyte ratios and cytokine levels, at 1, 7, and 14 day of admission between chronic complication groups (CCP) and not chronic complication groups (N-CCP) in polytrauma. Polytrauma patients with characteristics of higher ratio of Ts7d ratio (95% CI: 2.01-6.21), Treg14d (95% CI: 1.12-5.43) and level of IL-67d (95% CI: 1.22-4.43), TNF-α7d (95% CI: 1.05-3.83), IL-1014d (95% CI: 2.01-6.84) were found to have a higher likelihood of experiencing a chronic complication. Conversely, a higher ratio of Tc1d (95% CI: 0.53-0.86), Th1d (95% CI: 0.64-0.95) and Th/Ts14d (95% CI: 0.21-0.64) were identified as independent protective factors against a chronic complication event.

Polytrauma patients exhibit a notable prevalence of chronic complications. Some immune and inflammatory indicators can be observed early in combination after injury to predict the risk of chronic complications after polytrauma.

Given the critical role of immune cells and their responses in sepsis pathogenesis, this study aimed to evaluate the prognostic significance of various immune cell ratios in septic children through the collection and analysis of clinical data.

Clinical data were collected from septic children admitted to the pediatric intensive care unit (PICU) of Shenzhen Children's Hospital between January 2019 and September 2021. The peripheral blood immune cell ratios included the neutrophil to lymphocyte ratio (NLR), the derived neutrophil to lymphocyte ratio (dNLR), the neutrophil to lymphocyte and platelet ratio (NLPR), the monocyte to lymphocyte ratio (MLR), and the platelet to lymphocyte ratio (PLR). To investigate the associations between these immune cell ratios and mortality, we utilized the locally weighted scatterplot smoothing (LOWESS) method, receiver operating characteristic (ROC) analysis, and Kaplan‒Meier (K‒M) analysis.

A total of 230 septic children were enrolled in the study. When comparing the immune cell ratios between the deceased and surviving groups, all ratios except for the PLR were elevated in the deceased group. Using the LOWESS method, we observed that the MLR, NLR, dNLR, and NLPR exhibited an approximately linear association with in-hospital mortality. Among the various immune cell ratios, the NLPR exhibited the highest AUC of 0.748, which was statistically comparable to that of the Pediatric Critical Illness Score (PCIS) (0.748 vs. 0.738, P = 0.852). The NLR (0.652), MLR (0.638), and dNLR (0.615) followed in terms of AUC values. K‒M analysis revealed that children with elevated MLR, NLR, dNLR, and NLPR exhibited increased 30-day mortality.

The predictive capacity of the NLPR is comparable to that of the PCIS, suggesting that the NLPR has potential as a robust prognostic indicator for septic children.

Background/Objectives: Periprosthetic joint infection (PJI) is a disastrous complication after joint replacement procedures as the diagnosis remains a significant challenge. The objective of this study is to assess the accuracy and test the interdependency of the proposed compound serum biomarkers for the diagnosis of PJI after total hip arthroplasties (THA). Methods: From January 2019 to December 2023, 77 consecutive cases that underwent revision total hip arthroplasties (rTHA) were included in a single-retrospective, observational cohort study. A total of 32 arthroplasties were classified as having septic complications using the European Bone and Joint Infection Society (EBJIS) definition from 2021, while the other 45 cases were assigned as aseptic failures (AF). Results: In the univariate analysis between the two groups created, statistically significant differences (p < 0.005) were found for the following variables: time from primary arthroplasty to symptom onset (Time PA-SO), neutrophil count, Lymphocyte count, haematocrit level (HCT) and haemoglobin level (HGB), C-reactive protein (CRP), the neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), monocyte lymphocyte ratio (MLR), systemic inflammation index (SII), systemic inflammation response index (SIRI), and aggregate inflammation systemic index (AISI). The ROC curve analysis showed that the SII (sensitivity 90.6% and specificity 62.2%) and the NLR (sensitivity 84.4% and specificity 64.4%) are the most accurate biomarkers. The multivariate analysis confirmed that NLR > 2.63 (p = 0.006), PLR > 147 (p = 0.021), MLR > 0.31 (p = 0.028), SII > 605.31 (p = 0.002), SIRI > 83.34 (p = 0.024), and AISI > 834.86 (p = 0.011) are all closely related to PJI diagnosis independently. Conclusions: The proposed serum biomarkers can be correlated with PJI diagnosis with the reserve of relatively low specificities.

This narrative review provides an overview of the evolving significance of lymphopenia in sepsis, emphasizing its critical function in this complex and heterogeneous disease. We describe the causal relationship of lymphopenia with clinical outcomes, sustained immunosuppression, and its correlation with sepsis prediction markers and therapeutic targets. The primary mechanisms of septic lymphopenia are highlighted. In addition, the paper summarizes various attempts to treat lymphopenia and highlights the practical significance of promoting lymphocyte proliferation as the next research direction.

The lymphocyte-to-C-reactive protein ratio (LCR) was a novel biomarker of inflammation that had been implicated in various diseases. Nevertheless, the role of LCR in the context of sepsis patients admitted to the Intensive Care Unit (ICU) had not been thoroughly elucidated. This study aimed to determine the significance of the LCR in predicting the prognosis of sepsis patients within ICU.

A sample of sepsis patients requiring ICU care was selected from the Affiliated Hospital of Jiangsu University. These patients were then segmented into four quartiles based on their LCR levels. The primary endpoint of the study was 30-day mortality and the secondary endpoint was the occurrence of Acute Kidney Injury (AKI). Survival analysis, via the Kaplan-Meier method and log-rank test, was conducted to assess survival rates. Cox proportional hazards regression and logistic regression models were employed to investigate the association between LCR and clinical outcomes. Additional subgroup analyses were conducted to evaluate the influence of other confounding factors on the relationship between LCR and patient outcomes.

A total of 1,123 patients were enrolled in this study, with a median age of 75 (65-84) years, and 707 (63.0%) of them were male. The 30-day mortality rate was 28.1%, while the incidence of AKI was 45.6%. A progressive decrease in LCR levels was found to be associated with an increased cumulative incidence of 30-day mortality (log-rank P < 0.001). Multivariable Cox proportional hazards analyses demonstrated that LCR was an independent predictor of 30-day mortality [per 1-unit increase in LCR: HR (95%CI): 0.370 (0.142-0.963); P = 0.042]. Additionally, multivariable logistic regression analysis revealed a significant association between LCR and AKI occurrence [per 1-unit increase in LCR: OR (95%CI): 0.541 (0.307-0.953); P = 0.034]. Furthermore, subgroup analysis indicated a stronger correlation for patients aged over 65 years compared to those aged 65 or younger (p for interaction <0.05) in predicting 30-day mortality or AKI occurrence based on LCR.

A reduction in LCR was notably linked to 30-day mortality and the occurrence of AKI in sepsis patients. These findings suggested that LCR could potentially serve as a valuable tool in identifying sepsis patients at a heightened risk of adverse outcomes.

In sepsis, the relationship between lymphocyte counts and patient outcomes is complex. Lymphocytopenia and lymphocytosis significantly influence survival, illustrating the dual functionality of lymphocytes in responding to infections. This study investigates this complex interaction, focusing on how variations in lymphocyte counts correlate with all-cause hospital mortality among sepsis patients.

This retrospective cohort study analyzed data from two extensive critical care databases: the Medical Information Mart for Intensive Care IV 2.0 (MIMIC-IV 2.0) from Beth Israel Deaconess Medical Center, Boston, Massachusetts, and the eICU Collaborative Research Database (eICU-CRD), which was Multi-center database from over 200 hospitals across the United States conducted by Philips eICU Research Institute. We included adult patients aged 18 years and older who met the Sepsis-3 criteria, characterized by documented or suspected infection and a Sequential Organ Failure Assessment (SOFA) score of 2 or higher. Sepsis patients were categorized into quartiles based on lymphocyte counts. The primary outcome was all-cause mortality in the hospital, with 90 and 60-day all-cause mortality as the secondary outcomes. Univariable and multivariable Cox proportional hazard regressions were utilized to assess lymphocyte counts' impact on hospital mortality. An adjusted restricted cubic spline (RCS) analysis was performed to elucidate this relationship further. Subgroup analyses were also conducted to explore the association across various comorbidity groups among sepsis and septic shock patients.

Our study included 37,054 patients, with an observed in-hospital mortality rate of 16.6%. Univariable and multivariable Cox proportional hazard regression models showed that lymphocyte counts were independently associated with in-hospital mortality (HR = 1.04, P < 0.01; HR = 1.06, P < 0.01). RCS regression analysis revealed a U-shaped relationship between lymphocyte levels and hospital mortality risk in sepsis and septic shock patients (P for overall < 0.001, P for nonliner < 0.01; P for overall = 0.002, P for nonliner = 0.014). Subgroup analyses revealed that elevated lymphocyte counts correlated with increased hospital mortality among sepsis patients with liver disease and requiring renal replacement therapy (P for overall = 0.021, P for nonliner = 0.158; P for overall = 0.025, P for nonliner = 0.759). These findings suggest that lymphocytes may have enhanced prognostic value in specific subsets of critically ill sepsis patients.

Our findings demonstrate that lymphocyte counts are a significant independent predictor of hospital mortality in sepsis and septic shock patients. We observed a U-shaped association between lymphocyte levels and mortality risk, indicating that high and low counts are linked to increased mortality. This result highlights the complex role of lymphocytes in sepsis outcomes and suggests the need for further investigation into the underlying mechanisms and potential therapeutic approaches. Integrating lymphocyte count assessment into risk stratification algorithms and clinical decision support tools could enhance the early identification of high-risk sepsis patients.

Background: Septic patients with persistent lymphopenia may be in an immunosuppressed state. Therefore, we evaluated and compared the clinical characteristics and outcomes of septic patients with persistent lymphopenia (≥2d) and those with nonpersistent lymphopenia. Methods: A retrospective cohort study was designed. A total of 1306 patients with sepsis who were attended to the First Affiliated Hospital of Dalian Medical University from March 2016 to August 2022 were included. The primary clinical outcome was 90d mortality. The secondary clinical outcomes were the length of stay, hospital mortality, 28d mortality, the incidence of secondary infection, and differences in clinical characteristics. Results: Among 1306 patients with sepsis, 913 (69.9%) patients developed persistent lymphopenia. Compared with patients with nonpersistent lymphopenia, patients with persistent lymphocytopenia were admitted to intensive care unit (75.7% vs 52.7%, P < .05), treated with mechanical ventilation (67.6% vs 39.2%, P < .05), positive rate of microbial culture pathogens (86.7% vs 71.2%, P < .05), SOFA [8.0 (6.0-10.0) vs 6.0 (4.0-8.0), P < .05], length of stay [17.0d (12.0-27.0) vs 13.0d (10.0-21.0), P < .05], hospital mortality (37.7% vs 24.2%, P < .05), 28d mortality (38.0% vs 22.9%, P < .05), and 90d mortality (51.2% vs 31.3%, P < .05) were higher. As the duration of lymphocytopenia increased, so did the mortality rate in hospital. In addition, the onset time of persistent lymphopenia was not associated with SOFA. But we found that the frequency of persistent lymphopenia during hospitalization was positively associated with SOFA. Conclusion: Septic patients with persistent lymphopenia have higher mortality, worse conditions, increased risk of secondary infection, and poor prognosis regardless of shock.

To compare the 18-month survival between patients with newly diagnosed cancer discharged home after early unplanned ICU admission and those without early unplanned ICU admission; we also evaluated the frequency and risk factors for early unplanned ICU admission.

Observational study with prospectively collected data from September 2019 to June 2021 and 18 months follow-up.

Single dedicated cancer center in São Paulo, Brazil.

We screened consecutive adults with suspected cancer and included those with histologically proven cancer from among 20 highly prevalent cancers.

None.

The exposure was early unplanned ICU admission, defined as admission for medical reasons or urgent surgery during the first 6 months after cancer diagnosis. The main outcome was 18-month survival after cancer diagnosis, and the main analysis was Cox's proportional hazards model adjusted for confounders and immortal time bias. Propensity score matching was used in the sensitivity analysis. We screened 4738 consecutive adults with suspected cancer and included 3348 patients. Three hundred twelve (9.3%) had early unplanned ICU admission, which was associated with decreased 18-month survival both in the unadjusted (hazard ratio, 4.03; 95% CI, 2.89-5.62) and adjusted (hazard ratio, 1.84; 95% CI, 1.29-2.64) models. The sensitivity analysis confirmed the results because the groups were balanced after matching, and the 18-month survival of patients with early ICU admission was lower compared with patients without early ICU admission (87.0% vs. 93.9%; p = 0.01 log-rank test). Risk factors for early unplanned ICU admission were advanced age, comorbidities, worse performance status, socioeconomic deprivation, metastatic tumors, and hematologic malignancies.

Patients with newly diagnosed cancer discharged home after early unplanned ICU admission have decreased 18-month survival compared with patients without early unplanned ICU admission.

Background Patients with chronic critical illness (CCI) experience poor prognoses and incur high medical costs. However, there is currently limited clinical awareness of sepsis-associated CCI, resulting in insufficient vigilance. Therefore, it is necessary to build a machine learning model that can predict whether sepsis patients will develop CCI. Methods Clinical data on 19,077 sepsis patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were analyzed. Predictive factors were identified using the Student's t-test, Mann-Whitney U test, or χ 2 test. Six machine learning classification models, namely, the logistic regression, support vector machine, decision tree, random forest, extreme gradient enhancement, and artificial neural network, were established. The optimal model was selected on the basis of its performance. Calibration curves were used to evaluate the accuracy of model classification, while the external validation dataset was used to evaluate the performance of the model. Results Thirty-seven characteristics, such as elevated alanine aminotransferase, rapid heart rate, and high Logistic Organ Dysfunction System scores, were identified as risk factors for developing CCI. The area under the receiver operating characteristic curve (AUROC) values for all models were above 0.73 on the internal test set. Among them, the extreme gradient enhancement model exhibited superior performance (F1 score = 0.91, AUROC = 0.91, Brier score = 0.052). It also exhibited stable prediction performance on the external validation set (AUROC = 0.72). Conclusion A machine learning model was established to predict whether sepsis patients will develop CCI. It can provide useful predictive information for clinical decision-making.

Innate myeloid cells especially neutrophils and their extracellular traps are known to promote intravascular coagulation and thrombosis formation in infections and various other conditions. Innate myeloid cell-dependent fibrin formation can support systemic immunity while its dysregulation enhances the severity of infectious diseases. Less is known about the immune mechanisms preventing dysregulation of fibrin homeostasis in infection. During experimental systemic infections local fibrin deposits in the liver microcirculation cause rapid arrest of CD4+ T cells. Arrested T-helper cells mostly represent Th17 cells that partially originate from the small intestine. Intravascular fibrin deposits activate mouse and human CD4+ T cells which can be mediated by direct fibrin-CD4+ T-cell interactions. Activated CD4+ T cells suppress fibrin deposition and microvascular thrombosis by directly counteracting coagulation activation by neutrophils and classical monocytes. T-cell activation, which is initially triggered by IL-12p40- and MHC-II-dependent mechanisms, enhances intravascular fibrinolysis via LFA-1. Moreover, CD4+ T cells disfavor the association of the thrombin-activatable fibrinolysis inhibitor (TAFI) with fibrin whereby fibrin deposition is increased by TAFI in the absence but not in the presence of T cells. In human infections thrombosis development is inversely related to microvascular levels of CD4+ T cells. Thus, fibrin promotes LFA-1-dependent T-helper cell activation in infections which drives a negative feedback cycle that rapidly restricts intravascular fibrin and thrombosis development.

The aim of this study was to clarify the relationship between expression level of CTLA-4 on CD4+ T cells and sepsis-associated immunosuppression (SAI), and to elucidate the possible mechanism of mTOR pathway mediated autophagic-lysosomal disorder in regulating CTLA-4 expression.

We enrolled 63 sepsis patients admitted to our ICU between January 1 and June 30, 2023. Peripheral blood mononuclear cells were isolated from the patients within 24 hours of recruitment. Expression levels of mTOR, P62, LC3II, and CTLA-4 on circulating CD4+ T lymphocytes were quantitated using flow cytometry. The association of these markers and relationship between CTLA-4 expression and the incidence of SAI and 28-day mortality were comprehensively analyzed.

Compared with non-immunosuppressed patients with sepsis, patients with SAI had a higher 28-day mortality rate (37.5% vs 13.0%, P=0.039) and higher CTLA-4 mean fluorescence intensity (MFI) on CD4+ T cells (328.7 versus 78.7, P<0.0001). CTLA-4 MFI on CD4+ cells was independently associated with the occurrence of SAI (95% confidence interval: 1.00-1.14, P=0.044). In patients with sepsis and SAI, non-survivors had higher CTLA-4 expression than survivors (sepsis: 427.5 versus 130.6, P=0.002; and SAI: 506.7 versus 225.2, P<0.0001). The sensitivity and specificity of CTLA-4 MFI at predicting 28-day mortality in patients with SAI was 100% and 80% respectively with the cutoff value of 328.7 and the area under the curve of 0.949. The MFI of mTOR, P62, and LC3II on CD4+ T cells were statistically higher in patients with SAI than in non-immunosuppressed patients (267.2 versus 115.9, P<0.0001; 314.8 versus 173.7, P<0.0001; and 184.7 versus 1123.5, P=0.012, respectively); P62 and LC3II were markedly higher in non-survivors than in survivors of sepsis (302.9 versus 208.9, P=0.039; and 244.3 versus 122.8, P<0.0001 respectively). The expression of CTLA-4 statistically correlated with that of LC3II in patients with sepsis, patients with SAI, and patients with SAI who did not survive (correlation coefficient: 0.69, 0.68, and 0.73, respectively, P<0.0001).

CTLA-4 overexpression on CD4+ T cells was markedly associated with the incidence of SAI and had great relevance to 28-day mortality. mTOR pathway mediated autophagic-lysosomal disorder showed significant association with CTLA-4 expression.

Sepsis is a life-threatening condition caused by dysregulated host responses to infection. Myeloid cell accumulation and lymphocyte decline are widely recognized phenomena in septic patients. However, the fate of specific immune cells remains unclear. Here, we report the results of a human explorative study of patients with septic peritonitis and patients undergoing abdominal surgery without sepsis. We analyzed pairwise peritoneal fluid and peripheral blood taken 24 h after surgery to characterize immediate immune cell changes. Our results show that myeloid cell expansion and lymphocyte loss occur in all patients undergoing open abdominal surgery, indicating that these changes are not specific to sepsis. However, B1-like lymphocytes were specifically increased in the peritoneal fluid of septic patients, correlating positively with sequential organ failure assessment (SOFA) and acute physiology and chronic health evaluation II (APACHE-II) clinical severity scores. In support of this notion, we identified an accumulation of peritoneal B1b lymphocytes in septic mice.

Immunoparalysis is a significant concern in patients with sepsis and critical illness, potentially leading to increased risk of secondary infections. This study aimed to perform a longitudinal assessment of immune function over the initial two weeks following the onset of sepsis and critical illness. We compared ex vivo stimulated cytokine release to traditional markers of immunoparalysis, including monocyte Human Leukocyte Antigen (mHLA)-DR expression and absolute lymphocyte count (ALC). A total of 64 critically ill patients were recruited in a tertiary care academic medical setting, including 31 septic and 33 non-septic patients. Results showed that while mHLA-DR expression significantly increased over time, this was primarily driven by the non-septic subset of critically ill patients. ALC recovery was more prominent in septic patients. Ex vivo stimulation revealed significant increases in TNF and IL-6 production over time in septic patients. However, IFNγ production varied with the stimulant used and did not show significant recovery when normalized to cell count. No significant correlation was found between mHLA-DR expression and other immunoparalysis biomarkers. These findings suggest the need for more nuanced immune monitoring approaches beyond the traditional 'sepsis' versus 'non-sepsis' classifications in critically ill patients. It also provided further evidence of a potential window for targeted immunotherapeutic interventions in the first week of critical illness.

Sepsis is described as a life-threatening organ dysfunction and a heterogeneous syndrome that is a leading cause of morbidity and mortality in intensive care settings. Severe sepsis could incite an uncontrollable surge of inflammatory cytokines, and the host immune system's immunosuppression could respond to counter excessive inflammatory responses, characterized by the accumulated anti-inflammatory cytokines, impaired function of immune cells, over-proliferation of myeloid-derived suppressor cells and regulatory T cells, depletion of immune effector cells by different means of death, etc. In this review, we delve into the underlying pathological mechanisms of sepsis, emphasizing both the hyperinflammatory phase and the associated immunosuppression. We offer an in-depth exploration of the critical mechanisms underlying sepsis, spanning from individual immune cells to a holistic organ perspective, and further down to the epigenetic and metabolic reprogramming. Furthermore, we outline the strengths of artificial intelligence in analyzing extensive datasets pertaining to septic patients, showcasing how classifiers trained on various clinical data sources can identify distinct sepsis phenotypes and thus to guide personalized therapy strategies for the management of sepsis. Additionally, we provide a comprehensive summary of recent, reliable biomarkers for hyperinflammatory and immunosuppressive states, facilitating more precise and expedited diagnosis of sepsis.

The objective of the study was to assess the clinical predictive value of the dynamics of absolute lymphocyte count (ALC) for 90-day all-cause mortality in sepsis patients in intensive care unit (ICU).

Retrospective cohort study using big data.

This study was conducted using the Medical Information Mart for Intensive Care IV database V.2.0 database.

The primary outcome was 90-day all-cause mortality.

Patients were included if they were diagnosed with sepsis on the first day of ICU admission. Exclusion criteria were ICU stay under 24 hours; the absence of lymphocyte count on the first day; extremely high lymphocyte count (>10×109/L); history of haematolymphatic tumours, bone marrow or solid organ transplants; survival time under 72 hours and previous ICU admissions. The analysis ultimately included 17 329 sepsis patients.

The ALC in the non-survivors group was lower on days 1, 3, 5 and 7 after admission (p<0.001). The ALC on day 7 had the highest area under the curve (AUC) value for predicting 90-day mortality. The cut-off value of ALC on day 7 was 1.0×109/L. In the restricted cubic spline plot, after multivariate adjustments, patients with higher lymphocyte counts had a better prognosis. After correction, in the subgroups with Sequential Organ Failure Assessment score ≥6 or age ≥60 years, ALC on day 7 had the lowest HR value (0.79 and 0.81, respectively). On the training and testing set, adding the ALC on day 7 improved all prediction models' AUC and average precision values.

Dynamic changes of ALC are closely associated with 90-day all-cause mortality in sepsis patients. Furthermore, the ALC on day 7 after admission is a better independent predictor of 90-day mortality in sepsis patients, especially in severely ill or young sepsis patients.