Development and validation of immune dysfunction score to predict 28-day mortality of sepsis patients

Development and validation of an interpretable model for predicting sepsis mortality across care settings

There are numerous prognostic predictive models for evaluating mortality risk, but current scoring models might not fully cater to sepsis patients' needs. This study developed and validated a new model for sepsis patients that is suitable for any care setting and accurately forecasts 28-day mortality. The derivation dataset, gathered from 20 hospitals between September 2019 and December 2021, contrasted with the validation dataset, collected from 15 hospitals from January 2022 to December 2022. In this study, 7436 patients were classified as members of the derivation dataset, and 2284 patients were classified as members of the validation dataset. The point system model emerged as the optimal model among the tested predictive models for foreseeing sepsis mortality. For community-acquired sepsis, the model's performance was satisfactory (derivation dataset AUC: 0.779, 95% CI 0.765-0.792; validation dataset AUC: 0.787, 95% CI 0.765-0.810). Similarly, for hospital-acquired sepsis, it performed well (derivation dataset AUC: 0.768, 95% CI 0.748-0.788; validation dataset AUC: 0.729, 95% CI 0.687-0.770). The calculator, accessible at https://avonlea76.shinyapps.io/shiny_app_up/ , is user-friendly and compatible. The new predictive model of sepsis mortality is user-friendly and satisfactorily forecasts 28-day mortality. Its versatility lies in its applicability to all patients, encompassing both community-acquired and hospital-acquired sepsis.

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.

Ex Vivo Endotoxin Stimulation of Blood for Predicting Survival in Patients With Sepsis: A Systematic Review

BACKGROUND

Sepsis is a syndrome characterized by host immune dysfunction, with the extent of immunoparalysis differing among patients. Lipopolysaccharide (LPS) is used commonly to assess the immune function of critically ill patients with sepsis. However, the reliability of this ex vivo diagnostic test in predicting clinical outcomes remains uncertain.

RESEARCH QUESTION

Does LPS-induced tumor necrosis factor (TNF) production from the blood of patients with sepsis predict mortality? Secondary outcomes included ICU and hospital stay durations, nosocomial infection rate, and organ recovery rate.

STUDY DESIGN AND METHODS

Human sepsis studies from various databases through April 2023 were evaluated. Inclusion criteria encompassed LPS-stimulated blood assays, English language, and reported clinical outcomes. Bias risk was evaluated using the Newcastle-Ottawa scale (NOS). Relationships between TNF production and mortality were analyzed at sepsis onset and during established sepsis, alongside secondary outcomes.

RESULTS

Of 11,580 studies, 17 studies (14 adult and three pediatric) were selected for analysis. Although 15 studies were evaluated as moderate to high quality using the NOS, it is important to note that some of these studies also had identifiable biases, such as unclear methods of participant recruitment. Nine studies detailed survival outcomes associated with LPS-induced TNF production at sepsis onset, whereas five studies explored TNF production's relationship with mortality during established sepsis. Trends suggested that lower LPS-induced TNF production correlated with higher mortality. However, heterogeneity in methodologies, especially the LPS assay protocol, hindered definitive conclusions. Publication bias was highlighted using funnel plot analysis. Concerning secondary outcomes, diminished TNF production might signify worsening organ dysfunction, although the link between cytokine production and nosocomial infection varied among studies.

INTERPRETATION

For functional immune profiling in sepsis, streamlined research methodologies are essential. This entails organizing cohorts based on microbial sources of sepsis, establishing standardized definitions of immunoparalysis, using consistent types and dosages of immune stimulants, adhering to uniform blood incubation conditions, and adopting consistent clinical outcomes.

Using Body Composition Analysis for Improved Nutritional Intervention in Septic Patients: A Prospective Interventional Study

The study aimed to determine whether using body composition data acquired through bio-electrical impedance analysis (BIA) to adjust diet formulas could improve outcomes in septic patients. There were 132 septic patients in medical intensive care units enrolled in the prospective, randomized, double-blind, interventional study. For the intervention group, dietitians had access to BIA data for adjusting diet formulas according to body composition variables on days 1, 3, and 8. The patients were also stratified based on nutritional risk using the modified Nutrition Risk in Critically ill (mNUTRIC) score. Patients with intervention were more likely to achieve caloric and protein intake goals compared to the control group, especially in the low-risk group. The intervention did not significantly affect mortality, but the survival curves suggested potential benefits. The high-risk group had longer ICU stays and mechanical ventilation duration, which were mitigated by the intervention. Certain body composition variables (e.g., extracellular water to total body water ratio and phase angle) showed differences between high-risk and low-risk groups and may be related to patient outcomes. Non-invasive body composition assessment using BIA can help dietitians adjust diet formulas for critically ill septic patients. Body composition variables may be associated with sepsis outcomes, but further research with larger patient numbers is needed to confirm these findings.

Persistently Elevated Soluble Triggering Receptor Expressed on Myeloid Cells 1 and Decreased Monocyte Human Leucocyte Antigen DR Expression Are Associated With Nosocomial Infections in Septic Shock Patients

Sepsis-acquired immunosuppression may play a major role in patients' prognosis through increased risk of secondary infections. Triggering receptor expressed on myeloid cells 1 (TREM-1) is an innate immune receptor involved in cellular activation. Its soluble form (sTREM-1) has been described as a robust marker of mortality in sepsis. The objective of this study was to evaluate its association with the occurrence of nosocomial infections alone or in combination with human leucocyte antigen-DR on monocytes (mHLA-DR).

DESIGN

Observational study.

SETTING

University Hospital in France.

PATIENTS

One hundred sixteen adult septic shock patients as a post hoc study from the IMMUNOSEPSIS cohort (NCT04067674).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Plasma sTREM-1 and monocyte HLA-DR were measured at day 1 or 2 (D1/D2), D3/D4, and D6/D8 after admission. Associations with nosocomial infection were evaluated through multivariable analyses. At D6/D8, both markers were combined, and association with increased risk of nosocomial infection was evaluated in the subgroup of patients with most deregulated markers in a multivariable analysis with death as a competing risk. Significantly decreased mHLA-DR at D6/D8 and increased sTREM-1 concentrations were measured at all time points in nonsurvivors compared with survivors. Decreased mHLA-DR at D6/D8 was significantly associated with increased risk of secondary infections after adjustment for clinical parameters with a subdistribution hazard ratio of 3.61 (95% CI, 1.39-9.34; p = 0.008). At D6/D8, patients with persistently high sTREM-1 and decreased mHLA-DR presented with a significantly increased risk of infection (60%) compared with other patients (15.7%). This association remained significant in the multivariable model (subdistribution hazard ratio [95% CI], 4.65 [1.98-10.9]; p < 0.001).

CONCLUSIONS

In addition to its prognostic interest on mortality, sTREM-1, when combined with mHLA-DR, may help to better identify immunosuppressed patients at risk of nosocomial infections.

Clinical Impact of Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor Associated Clostridioides difficile Infection Among Patients with Lung Cancer

Aim

Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKIs)-associated Clostridioides difficile infection (CDI) among lung cancer patients have been reported in case reports and adverse events reporting system databases in the United States and Japan, but clinical data remained insufficient. This study aims to evaluate CDI in lung cancer patients receiving EGFR-TKIs.

Methods

We conducted a retrospective cohort study using multi-institutional electronic medical records database. We included patients aged older than 20 years diagnosed with lung cancer and treated with EGFR-TKIs (gefitinib, erlotinib, afatinib). We defined EGFR-TKI initiation date as the index date and occurrence of diarrhea with CDI or without CDI as the event date. We followed patients from the index date until the event date, ICU admission, death, or 12/31/2019.

Results

We included 2242 diarrhea patients, 51 were EGFR-TKI with CDI cohort, and 2191 were diarrhea without CDI cohort. Patients who were concurrently taking antibiotics (hazard ratio [HR], 3.30; 95% CI, 1.67-6.5) and systemic steroids (HR, 4.9; 95% CI, 2.65-9.06) had an increased risk of CDI. First-generation EGFR-TKIs tended to be associated with an increased risk of CDI compared with afatinib (HR, 1.81, 95% CI, 0.94-3.47). EGFR-TKI with CDI had a higher ICU admission rate (HR, 3.42, 95% CI, 1.98-5.91) and mortality rate (HR, 2.34, 95% CI, 1.67-3.28) than diarrhea without CDI.

Conclusion

Patients with CDI had higher ICU admission rates and mortality rates than those without CDI. Concurrent use of antibiotics and systemic steroids were risk factors for CDI among patients with lung cancer receiving EGFR-TKIs. Afatinib was not associated with a higher risk of CDI than first-generation EGFR-TKIs.

The Childhood Acute Illness and Nutrition (CHAIN) network nested case-cohort study protocol: a multi-omics approach to understanding mortality among children in sub-Saharan Africa and South Asia

Introduction: Many acutely ill children in low- and middle-income settings have a high risk of mortality both during and after hospitalisation despite guideline-based care. Understanding the biological mechanisms underpinning mortality may suggest optimal pathways to target for interventions to further reduce mortality. The Childhood Acute Illness and Nutrition (CHAIN) Network ( www.chainnnetwork.org) Nested Case-Cohort Study (CNCC) aims to investigate biological mechanisms leading to inpatient and post-discharge mortality through an integrated multi-omic approach. Methods and analysis; The CNCC comprises a subset of participants from the CHAIN cohort (1278/3101 hospitalised participants, including 350 children who died and 658 survivors, and 270/1140 well community children of similar age and household location) from nine sites in six countries across sub-Saharan Africa and South Asia. Systemic proteome, metabolome, lipidome, lipopolysaccharides, haemoglobin variants, toxins, pathogens, intestinal microbiome and biomarkers of enteropathy will be determined. Computational systems biology analysis will include machine learning and multivariate predictive modelling with stacked generalization approaches accounting for the different characteristics of each biological modality. This systems approach is anticipated to yield mechanistic insights, show interactions and behaviours of the components of biological entities, and help develop interventions to reduce mortality among acutely ill children. Ethics and dissemination. The CHAIN Network cohort and CNCC was approved by institutional review boards of all partner sites. Results will be published in open access, peer reviewed scientific journals and presented to academic and policy stakeholders. Data will be made publicly available, including uploading to recognised omics databases. Trial registration NCT03208725.

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.

Proinflammatory cytokines levels in sepsis and healthy volunteers, and tumor necrosis factor-alpha associated sepsis mortality: A systematic review and meta-analysis

BACKGROUND

Sepsis is a global health challenge associated with significant morbidity and mortality. Detrimental sepsis effects are attributed to excessive inflammation or a "cytokine storm." However, anti-inflammation therapies have failed to lower sepsis mortality. We aim to characterize levels of key inflammatory cytokines in patients with sepsis and compare levels with those in healthy individuals and relate tumor necrosis factor (TNF) α levels to patient characteristics and outcomes.

METHODS

We performed a systematic review and meta-analysis. Medline, Embase, Cochrane Library, and Web of Science Core Collection databases were searched between 1985 and May 2020. Analysis was restricted to studies in English. We included randomized controlled trials (RCTs), controlled trials, cohort studies, case series, and cross-sectional studies that reported mean levels of cytokines in the circulation thought to be relevant for sepsis pathogenesis. We also evaluated concentrations of these cytokines in healthy individuals. The Quality in Prognosis Studies tool was used to assess the methodological quality of included studies. We extracted summary data from published reports. Data analyses were performed using a random-effects model to estimate pooled odds ratios (OR) with 95% confidence intervals for cytokine levels and mortality. This systematic review is registered in PROSPERO (CRD42020179800).

FINDINGS

We identified 3654 records, and 104 studies were included with a total of 3250 participants. The pooled estimated mean TNFα concentration in sepsis patients was 58.4 pg/ml (95% Confidence Interval or CI 39.8-85.8 pg/ml), and in healthy individuals was 5.5 pg/ml (95% CI 3.8-8.0 pg/ml). Pooled estimate means for IL-1β and IFN-γ in sepsis patients were 21.8 pg/ml and 63.3 pg/ml, respectively. Elevated TNFα concentrations associated with increased 28-day sepsis mortality (p = 0.001). In subgroup analyses, we did not detect an association between TNFα levels and sepsis source, sepsis severity, or sequential organ failure assessment (SOFA) score. A TNF-α cutoff level ≥14.7 pg/ml separated sepsis patients from healthy individuals with a sensitivity of 82.6%, a specificity of 91.7%, and a likelihood ratio of 9.9.

INTERPRETATION

Sepsis mean TNFα concentration is increased approximately 10-fold compared to mean concentration in healthy individuals, and TNFα associated with sepsis mortality but not sepsis severity. The concept that elevated cytokines cause sepsis should be revisited in the context of these data.

FUNDING

None.

A stratification strategy to predict secondary infection in critical illness-induced immune dysfunction: the REALIST score

BACKGROUND

Although multiple individual immune parameters have been demonstrated to predict the occurrence of secondary infection after critical illness, significant questions remain with regards to the selection, timing and clinical utility of such immune monitoring tests.

RESEARCH QUESTION

As a sub-study of the REALISM study, the REALIST score was developed as a pragmatic approach to help clinicians better identify and stratify patients at high risk for secondary infection, using a simple set of relatively available and technically robust biomarkers.

STUDY DESIGN AND METHODS

This is a sub-study of a single-centre prospective cohort study of immune profiling in critically ill adults admitted after severe trauma, major surgery or sepsis/septic shock. For the REALIST score, five immune parameters were pre-emptively selected based on their clinical applicability and technical robustness. Predictive power of different parameters and combinations of parameters was assessed. The main outcome of interest was the occurrence of secondary infection within 30 days.

RESULTS

After excluding statistically redundant and poorly predictive parameters, three parameters remained in the REALIST score: mHLA-DR, percentage of immature (CD10^- CD16^-) neutrophils and serum IL-10 level. In the cohort of interest (n = 189), incidence of secondary infection at day 30 increased from 8% for patients with REALIST score of 0 to 46% in patients with a score of 3 abnormal parameters, measured ad D5-7. When adjusted for a priori identified clinical risk factors for secondary infection (SOFA score and invasive mechanical ventilation at D5-7), a higher REALIST score was independently associated with increased risk of secondary infection (42 events (22.2%), adjusted HR 3.22 (1.09-9.50), p = 0.034) and mortality (10 events (5.3%), p = 0.001).

INTERPRETATION

We derived and presented the REALIST score, a simple and pragmatic stratification strategy which provides clinicians with a clear assessment of the immune status of their patients. This new tool could help optimize care of these individuals and could contribute in designing future trials of immune stimulation strategies.

The Childhood Acute Illness and Nutrition (CHAIN) network nested case-cohort study protocol: a multi-omics approach to understanding mortality among children in sub-Saharan Africa and South Asia

Introduction: Many acutely ill children in low- and middle-income settings have a high risk of mortality both during and after hospitalisation despite guideline-based care. Understanding the biological mechanisms underpinning mortality may suggest optimal pathways to target for interventions to further reduce mortality. The Childhood Acute Illness and Nutrition (CHAIN) Network ( www.chainnnetwork.org) Nested Case-Cohort Study (CNCC) aims to investigate biological mechanisms leading to inpatient and post-discharge mortality through an integrated multi-omic approach. Methods and analysis; The CNCC comprises a subset of participants from the CHAIN cohort (1278/3101 hospitalised participants, including 350 children who died and 658 survivors, and 270/1140 well community children of similar age and household location) from nine sites in six countries across sub-Saharan Africa and South Asia. Systemic proteome, metabolome, lipidome, lipopolysaccharides, haemoglobin variants, toxins, pathogens, intestinal microbiome and biomarkers of enteropathy will be determined. Computational systems biology analysis will include machine learning and multivariate predictive modelling with stacked generalization approaches accounting for the different characteristics of each biological modality. This systems approach is anticipated to yield mechanistic insights, show interactions and behaviours of the components of biological entities, and help develop interventions to reduce mortality among acutely ill children. Ethics and dissemination. The CHAIN Network cohort and CNCC was approved by institutional review boards of all partner sites. Results will be published in open access, peer reviewed scientific journals and presented to academic and policy stakeholders. Data will be made publicly available, including uploading to recognised omics databases. Trial registration NCT03208725.

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.

Hematological Ratios Are Associated with Acute Kidney Injury and Mortality in Patients That Present with Suspected Infection at the Emergency Department

The early recognition of acute kidney injury (AKI) is essential to improve outcomes and prevent complications such as chronic kidney disease, the need for renal-replacement therapy, and an increased length of hospital stay. Increasing evidence shows that inflammation plays an important role in the pathophysiology of AKI and mortality. Several inflammatory hematological ratios can be used to measure systemic inflammation. Therefore, the association between these ratios and outcomes (AKI and mortality) in patients suspected of having an infection at the emergency department was investigated. Data from the SPACE cohort were used. Cox regression was performed to investigate the association between seven hematological ratios and outcomes. A total of 1889 patients were included, of which 160 (8.5%) patients developed AKI and 102 (5.4%) died in <30 days. The Cox proportional-hazards model revealed that the neutrophil-to-lymphocyte ratio (NLR), segmented-neutrophil-to-monocyte ratio (SMR), and neutrophil-lymphocyte-platelet ratio (NLPR) are independently associated with AKI <30 days after emergency-department presentation. Additionally, the NLR, SMR and NLPR were associated with 30-day all-cause mortality. These findings are an important step forward for the early recognition of AKI. The use of these markers might enable emergency-department physicians to recognize and treat AKI in an early phase to potentially prevent complications.

Immunomonitoring of Monocyte and Neutrophil Function in Critically Ill Patients: From Sepsis and/or Trauma to COVID-19

Immune cells and mediators play a crucial role in the critical care setting but are understudied. This review explores the concept of sepsis and/or injury-induced immunosuppression and immuno-inflammatory response in COVID-19 and reiterates the need for more accurate functional immunomonitoring of monocyte and neutrophil function in these critically ill patients. in addition, the feasibility of circulating and cell-surface immune biomarkers as predictors of infection and/or outcome in critically ill patients is explored. It is clear that, for critically ill, one size does not fit all and that immune phenotyping of critically ill patients may allow the development of a more personalized approach with tailored immunotherapy for the specific patient. In addition, at this point in time, caution is advised regarding the quality of evidence of some COVID-19 studies in the literature.

Establishment and validation of the predictive model for the in-hospital death in patients with sepsis

BACKGROUND

Identifying sepsis patients with risk of in-hospital death early can improve the prognosis of patients. This study aimed to develop a model to predict in-hospital death of sepsis patients based on the Medical Information Mart for Intensive Care-Ⅲ (MIMIC-Ⅲ) database, and use clinical data to externally validate the model.

METHODS

A total of 1,839 sepsis patients were used for model development, and 125 clinical cases were used for external validation. The discriminatory ability of the model was determined by calculating the area under the curve (AUC) with 95% confidence intervals (CI).

RESULTS

The AUC of the random forest model and logistic regression model was 0.754 (95%CI, 0.732-0.776) and 0.703 (95%CI, 0.680-0.727), respectively, and the random forest model had higher AUC (Z = 3.070, P = .002). External validation showed that the AUC of the random forest model was 0.539 (95%CI, 0.440-0.628). Further validation was carried out according to gender and SOFA score. The AUC of the model in males and females was 0.648 and 0.412, respectively. In addition, the AUC of the model in the population with SOFA scores of 3-8, 9-12, and 13-15 were 0.705, 0.495, and 0.769, respectively.

CONCLUSIONS

The random forest model had a better predictive ability and a good applicability to external populations with SOFA score of 13-15.

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 critical appraisal of the prognostic predictive models for patients with sepsis: Which model can be applied in clinical practice?

BACKGROUND

Sepsis is associated with high mortality and predictive models can help in clinical decision-making. The objective of this study was to carry out a systematic review of these models.

METHODS

In 2019, we conducted a systematic review in MEDLINE and EMBASE (CDR42018111121:PROSPERO) of articles that developed predictive models for mortality in septic patients (inclusion criteria). We followed the CHARMS recommendations (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies), extracting the information from its 11 domains (Source of data, Participants, etc). We determined the risk of bias and applicability (participants, outcome, predictors and analysis) through PROBAST (Prediction model Risk Of Bias ASsessment Tool).

RESULTS

A total of 14 studies were included. In the CHARMS extraction, the models found showed great variability in its 11 domains. Regarding the PROBAST checklist, only one article had an unclear risk of bias as it did not indicate how missing data were handled while the others all had a high risk of bias. This was mainly due to the statistical analysis (inadequate sample size, handling of continuous predictors, missing data and selection of predictors), since 13 studies had a high risk of bias. Applicability was satisfactory in six articles. Most of the models integrate predictors from routine clinical practice. Discrimination and calibration were assessed for almost all the models, with the area under the ROC curve ranging from 0.59 to 0.955 and no lack of calibration. Only three models were externally validated and their maximum discrimination values in the derivation were from 0.712 and 0.84. One of them (Osborn) had undergone multiple validation studies.

DISCUSSION

Despite most of the studies showing a high risk of bias, we very cautiously recommend applying the Osborn model, as this has been externally validated various times.

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.

Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU

Background

Early and accurate identification of sepsis patients with high risk of in-hospital death can help physicians in intensive care units (ICUs) make optimal clinical decisions. This study aimed to develop machine learning-based tools to predict the risk of hospital death of patients with sepsis in ICUs.

Methods

The source database used for model development and validation is the medical information mart for intensive care (MIMIC) III. We identified adult sepsis patients using the new sepsis definition Sepsis-3. A total of 86 predictor variables consisting of demographics, laboratory tests and comorbidities were used. We employed the least absolute shrinkage and selection operator (LASSO), random forest (RF), gradient boosting machine (GBM) and the traditional logistic regression (LR) method to develop prediction models. In addition, the prediction performance of the four developed models was evaluated and compared with that of an existent scoring tool – simplified acute physiology score (SAPS) II – using five different performance measures: the area under the receiver operating characteristic curve (AUROC), Brier score, sensitivity, specificity and calibration plot.

Results

The records of 16,688 sepsis patients in MIMIC III were used for model training and test. Amongst them, 2949 (17.7%) patients had in-hospital death. The average AUROCs of the LASSO, RF, GBM, LR and SAPS II models were 0.829, 0.829, 0.845, 0.833 and 0.77, respectively. The Brier scores of the LASSO, RF, GBM, LR and SAPS II models were 0.108, 0.109, 0.104, 0.107 and 0.146, respectively. The calibration plots showed that the GBM, LASSO and LR models had good calibration; the RF model underestimated high-risk patients; and SAPS II had the poorest calibration.

Conclusion

The machine learning-based models developed in this study had good prediction performance. Amongst them, the GBM model showed the best performance in predicting the risk of in-hospital death. It has the potential to assist physicians in the ICU to perform appropriate clinical interventions for critically ill sepsis patients and thus may help improve the prognoses of sepsis patients in the ICU.

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).

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

The association between sepsis and segmented neutrophil-to-monocyte (SeMo) ratio is unclear. We postulated that an increase in dynamic SeMo ratio measurement can be applied in risk stratification. This retrospective study included 727 consecutive sepsis patients in medical intensive care units (ICUs), including a subpopulation of 153 patients. According to the leukocyte (white blood cell, WBC) count on day 3 (normal range, between 4,000/µL and 12,000/µL) and delta SeMo (value of SeMo ratio on day 3 minus value of SeMo ratio on day 1; normal delta SeMo, <7), patients were grouped into 3 (delta SeMo & WBC tool). The survival lines separated significantly with hazard ratios of 1.854 (1.342–2.560) for the delta SeMo or WBC abnormal group and 2.860 (1.849–4.439) for the delta SeMo and WBC abnormal group compared to the delta SeMo and WBC normal group. Delta SeMo & WBC tool and delta sequential organ failure assessment (SOFA) tool performed better than the other tools (delta SeMo, delta WBC, day 3 WBC, and day 1 WBC). Severity in delta SeMo & WBC tool and delta SeMo tool reflected the immune dysfunction score, cytokine expression, and human leukocyte antigen D-related monocyte expression on day 1 and day 3. There was correspondence between delta SOFA and delta WBC and between delta SeMo and delta cytokine expression. Incorporation of dynamic SeMo ratio with WBC count provides risk stratification for sepsis patients admitted in the ICU.

Effect of do-not-resuscitate orders on patients with sepsis in the medical intensive care unit: a retrospective, observational and propensity score-matched study in a tertiary referral hospital in Taiwan

OBJECTIVE

The aim of this study was to determine whether do-not-resuscitate (DNR) orders affect outcomes in patients with sepsis admitted to intensive care unit (ICU).

DESIGN

This is a retrospective observational study.

PARTICIPANTS

We enrolled 796 consecutive adult intensive care patients at Kaohsiung Chang Gung Memorial Hospital, a 2700-bed tertiary teaching hospital in southern Taiwan. A total of 717 patients were included.

MAIN MEASURES

Clinical factors such as age, gender and other clinical factors possibly related to DNR orders and hospital mortality were recorded.

KEY RESULTS

There were 455 patients in the group without DNR orders and 262 patients in the group with DNR orders. Within the DNR group, patients were further grouped into early (orders signed on intensive care day 1, n=126) and late (signed after day 1, n=136). Patients in the DNR group were older and more likely to have malignancy than the group without DNR orders. Mortality at days 7, 14 and 28, as well as intensive care and hospital mortality, were all worse in these patients even after propensity-score matching. There were higher Charlson Comorbidity Index in the emergency room, but better outcomes in those with early-DNR orders compared with late-DNR orders.

CONCLUSIONS

DNR orders may predict worse outcomes for patients with sepsis admitted to medical ICUs. The survival rate in the early-DNR order group was not inferior to the late-DNR order group.

Application of dynamic pulse pressure and vasopressor tools for predicting outcomes in patients with sepsis in intensive care units

PURPOSE

We aimed to determine whether the combination of dynamic pulse pressure and vasopressor (DPV) use is applicable for mortality risk stratification in patients with severe sepsis. We proposed the use of the DPV tool and compared it with traditional sepsis severity indices.

MATERIALS AND METHODS

All adult patients who met the sepsis criteria of the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) between August 2013 and January 2017 were eligible for the study. Patients who expired within 3 days of admission to the intensive care unit (ICU) were excluded. The primary outcomes were 7-day and 28-day mortality.

RESULTS

The study participants included 757 consecutive adult patients. A subpopulation of 155 patients underwent immune profiling assays on days 1, 3, and 7 of ICU admission. The DPV tool had a better performance for predicting 7-day mortality (area under curve, AUC: 0.70), followed by the Sequential Organ Failure Assessment (SOFA) (AUC: 0.64), the plus pulse pressure (AUC: 0.64). For predicting 28-day mortality, the DPV tool was not inferior to the SOFA (AUC: 0.61), DPV tool (AUC: 0.59).

CONCLUSIONS

The DPV tool can be applied for 7-day and 28-day mortality risk prediction in patients with sepsis.

Insufficient Nutrition and Mortality Risk in Septic Patients Admitted to ICU with a Focus on Immune Dysfunction

Immune dysfunction is seen both in sepsis patients and in those with malnutrition. This study aimed to determine whether insufficient nutrition and immune dysfunction have a synergistic effect on mortality in critically ill septic patients. We conducted a prospective observational study from adult sepsis patients admitted to intensive care units (ICUs) between August 2013 and June 2016. Baseline characteristics including age, gender, body mass index, NUTRIC, Acute Physiology and Chronic Health Evaluation (APACHE) II and Sequential Organ Failure Assessment (SOFA) scores were recorded. Immune dysfunction, defined by human leukocyte antigen DR (HLA-DR) expression, was tested at days 1, 3, and 7 of ICU admission. The study included 151 patients with sepsis who were admitted to the ICU. The 28-day survivors had higher day 7 caloric intakes (89% vs. 73%, p = 0.042) and higher day 1-HLA-DR expression (88.4 vs. 79.1, p = 0.045). The cut-off points of day 7 caloric intake and day 1-HLA-DR determined by operating characteristic curves were 65.1% and 87.2%, respectively. Immune dysfunction was defined as patients with day 1-HLA-DR < 87.2%. Insufficient nutrition had no influence on survival outcomes in patients with immune dysfunction. However, patients with insufficient nutrition had poor prognosis when they were immune competent. Insufficient nutrition and immune dysfunction did not have a synergistic effect on mortality in critically ill septic patients.

Ventilator Dependence Risk Score for the Prediction of Prolonged Mechanical Ventilation in Patients Who Survive Sepsis/Septic Shock with Respiratory Failure

We intended to develop a scoring system to predict mechanical ventilator dependence in patients who survive sepsis/septic shock with respiratory failure. This study evaluated 251 adult patients in medical intensive care units (ICUs) between August 2013 to October 2015, who had survived for over 21 days and received aggressive treatment. The risk factors for ventilator dependence were determined. We then constructed a ventilator dependence (VD) risk score using the identified risk factors. The ventilator dependence risk score was calculated as the sum of the following four variables after being adjusted by proportion to the beta coefficient. We assigned a history of previous stroke, a score of one point, platelet count less than 150,000/μL a score of one point, pH value less than 7.35 a score of two points, and the fraction of inspired oxygen on admission day 7 over 39% as two points. The area under the curve in the derivation group was 0.725 (p < 0.001). We then applied the VD risk score for validation on 175 patients. The area under the curve in the validation group was 0.658 (p = 0.001). VD risk score could be applied to predict prolonged mechanical ventilation in patients who survive sepsis/septic shock.

Histone deacetylase 2 (HDAC2) attenuates lipopolysaccharide (LPS)-induced inflammation by regulating PAI-1 expression

Background

Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection, and is primarily characterized by an uncontrolled systemic inflammatory response. In the present study, we developed an effective adjunct therapy mediated by a novel mechanism, to attenuate overt inflammation. LPS-treated macrophages were adopted as an in vitro model of endotoxin-induced inflammation during sepsis. Experiments were carried out using primary mouse peritoneal macrophages and the murine macrophage cell line RAW264.7, to elucidate the mechanisms by which HDAC2 modulates endotoxin-induced inflammation.

Results

Results revealed that PAI-1, TNF, and MIP-2 expression were inhibited by theophylline, an HDAC2 enhancer, in a RAW macrophage cell line, following LPS-induced inflammation. Thus, HDAC2 plays an important role in immune defense by regulating the expression of inflammatory genes via the c-Jun/PAI-1 pathway. During LPS-induced inflammation, overexpression of HDAC2 was found to inhibit PAI-1, TNF, and MIP-2 expression. Following LPS stimulation, HDAC2 knockdown increased nuclear translocation and DNA binding of c-Jun to the PAI-1 gene promoter, thereby activating PAI-1 gene transcription. Furthermore, inhibition of PAI-1 by TM5275 alone or in combination with theophylline notably suppressed TNF and MIP-2 expression.

Conclusion

HDAC2 can attenuate lipopolysaccharide-induced inflammation by regulating c-Jun and PAI-1 expression in macrophages.