Daily ReportSep 29, 2026
Sepsis, September 29 edition
We read 29 papers and selected 3.
Summary
The most impactful studies advanced mechanistic, precision-treatment, and prognostic research in sepsis. Neutrophil extracellular traps were linked to CD4+ T-cell dysfunction, routinely available immune-cell indices showed potential to identify corticosteroid-responsive septic shock, and a meta-analysis demonstrated moderate-to-good performance of sepsis-associated acute kidney injury prediction models but substantial heterogeneity.
Research Themes
- Mechanisms of sepsis-induced immunosuppression
- Precision corticosteroid therapy in septic shock
- Prediction of sepsis-associated acute kidney injury
Selected Articles
1. NETs drive CD4⁺ T cell dysfunction in sepsis via mitochondrial ROS and impaired calcium signalling.
This translational study combined plasma analyses in 50 patients with sepsis and 31 healthy controls, a murine cecal ligation and puncture model, and cellular experiments. Circulating neutrophil extracellular traps (NETs) increased with disease severity and were inversely associated with peripheral CD4+ T cells, supporting a NETs-mitochondrial reactive oxygen species pathway as a driver of sepsis-associated T-cell dysfunction.
Impact: The study connects excessive neutrophil extracellular trap formation with adaptive immune dysfunction through a specific mitochondrial and calcium-signalling mechanism. This provides a biologically testable explanation for sepsis-induced immunosuppression and identifies potential therapeutic targets beyond broad immunostimulation.
Clinical Implications: NETs, mitochondrial oxidative stress, and CD4+ T-cell dysfunction may become candidate biomarkers or therapeutic targets for sepsis-associated immunosuppression. The findings are not yet sufficient to support clinical NET inhibition or immune-restorative therapy.
Key Findings
- Circulating NETs were elevated in patients with sepsis and correlated positively with SOFA score.
- NET levels were negatively associated with peripheral CD4+ T-cell abundance, indicating a relationship with immunosuppression.
- The study identified a NETs-mitochondrial reactive oxygen species pathway with impaired calcium signalling as a potential mechanism of CD4+ T-cell dysfunction.
Methodological Strengths
- Integration of human patient data, an in vivo sepsis model, and in vitro cellular experiments.
- Assessment of both clinical severity associations and mechanistic cellular pathways.
Limitations
- The available abstract does not provide detailed information on patient selection, temporal sampling, or adjustment for clinical confounders.
- Mechanistic findings from murine and in vitro systems require validation in larger, clinically phenotyped cohorts and interventional studies.
Future Directions: Future studies should determine whether NET or mitochondrial oxidative-stress markers define clinically meaningful immunosuppressed phenotypes and whether targeted inhibition improves infection control, organ failure, or survival without increasing secondary infections.
BACKGROUND: Sepsis is a life-threatening condition with high mortality, in which sepsis-induced immunosuppression-characterized by CD4 METHODS: We integrated plasma analysis from 50 sepsis patients and 31 healthy controls, a murine cecal ligation and puncture (CLP) sepsis model, and in vitro assays with Jurkat cells and primary CD4 RESULTS: Circulating NETs were significantly elevated in sepsis patients, positively correlated with disease severity (SOFA score) and negatively correlated with peripheral CD4 CONCLUSION: The NETs-mtROS axis represents an important pathway driving CD4
2. Lymphopenia and elevated NLR identify patients with septic shock who may benefit from corticosteroids: a target trial emulation study.
Using 5,533 septic shock stays from the MIMIC-IV database, this target trial emulation applied augmented inverse probability weighting to estimate corticosteroid benefit. Lower lymphocyte counts and higher neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios modestly identified patients with reduced model-estimated ICU mortality after corticosteroid treatment.
Impact: The study addresses a central unresolved question in septic shock: whether corticosteroid effects vary by host immune phenotype. It proposes inexpensive, widely available markers for treatment-effect stratification, while appropriately showing that their predictive performance remains modest.
Clinical Implications: Lymphocyte count, NLR, and PLR could support hypothesis-generating bedside stratification of septic shock patients when considering corticosteroids, especially in resource-limited settings. They should not yet replace clinical assessment or be used as sole criteria for treatment.
Key Findings
- The cohort included 5,533 septic shock stays, of which 1,009 received corticosteroids.
- Lower lymphocyte count, higher NLR, and higher PLR were associated with greater model-estimated benefit from corticosteroids.
- Discrimination was modest: AUROC was 0.65 for lymphocyte count, 0.62 for NLR, and 0.63 for PLR.
Methodological Strengths
- Large critical-care cohort with clinically relevant mortality and organ-support outcomes.
- Use of target trial emulation and an augmented inverse probability weighting doubly robust estimator to address treatment-selection confounding.
Limitations
- This was a retrospective database analysis, so residual confounding, exposure misclassification, and immortal-time or timing-related biases may remain.
- The inflammatory indices had only modest predictive discrimination and require prospective validation before treatment decisions can be guided by them.
Future Directions: Prospective biomarker-stratified randomized trials should test whether lymphopenia, NLR, or PLR can enrich for corticosteroid benefit and whether combining them with dynamic clinical variables improves treatment-effect prediction.
BACKGROUND: Septic shock is the most severe form of sepsis and has high mortality. Despite the widespread use of corticosteroids, evidence of their benefit remains unclear; precision critical care medicine has sought to identify which patients will benefit. The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are widely available markers of inflammation and immune function. This study aimed to determine whether these parameters can identify septic shock patients likely to benefit from corticosteroid treatment. METHODS: A target trial was emulated using data from the Medical Information Mart for Intensive Care IV database. Adult patients in the ICU for at least 24 h who met the Sepsis-3 definition for septic shock were included. The cohort was divided into those who received corticosteroids and those who did not. Covariates extracted included NLR and PLR. An Augmented Inverse Probability Weighting (AIPW) double-robust estimator was applied to evaluate the effect of corticosteroids on ICU mortality (primary outcome), in-hospital mortality, the need for renal replacement therapy, the duration of vasopressor therapy, and the length of ICU and hospital stay (secondary outcomes). Univariate AUROC was used to compare the predictive performance of the evaluated parameters.
3. Prediction models for sepsis-associated acute kidney injury: a systematic review and meta-analysis.
This PRISMA-oriented systematic review and meta-analysis included 15 studies involving 46,490 patients. The pooled C-statistic for sepsis-associated acute kidney injury prediction was 0.817, but substantial heterogeneity across models and studies limits immediate clinical generalizability and emphasizes the need for external validation.
Impact: The study provides the broadest quantitative synthesis among the selected papers and clarifies that apparently good discrimination does not guarantee transportability or clinical utility. Its emphasis on PROBAST-based bias assessment and external validation addresses major barriers to implementation of sepsis risk models.
Clinical Implications: Existing prediction models may help identify patients at risk for sepsis-associated acute kidney injury, but clinicians should not assume uniform performance across hospitals or populations. Local or population-specific external validation should precede clinical deployment and decisions about renal-protective interventions.
Key Findings
- Fifteen studies involving 46,490 patients were included.
- The pooled C-statistic was 0.817, with a 95% confidence interval of 0.781 to 0.847.
- Substantial heterogeneity across studies indicates that external validation and population-specific model development are essential.
Methodological Strengths
- Systematic searches across PubMed, The Cochrane Library, Web of Science, and Embase.
- Use of PROBAST for risk-of-bias assessment and random-effects pooling with subgroup exploration of heterogeneity.
Limitations
- The included prediction models were heterogeneous in populations, predictors, outcomes, and validation methods.
- The abstract reports substantial heterogeneity, and the available data do not establish clinical utility, calibration, or impact on patient outcomes.
Future Directions: Future research should use transparent reporting, prospective multicenter external validation, calibration assessment, decision-curve analysis, and impact studies to determine whether prediction models improve early recognition or outcomes of sepsis-associated acute kidney injury.
OBJECTIVES: This study aims to systematically evaluate the predictive performance of risk models for sepsis-associated acute kidney injury (SA-AKI). Furthermore, we explore the specific factors that influence how effectively these models perform in clinical settings. METHODS: We systematically searched PubMed, The Cochrane Library, Web of Science, and Embase to identify cohort studies published up to 30 March 2026. These studies focused on the development and validation of SA-AKI prediction models. To ensure the quality of the evidence, the risk of bias was assessed using the Prediction model study Risk Of Bias ASsessment Tool (PROBAST). Data synthesis involved a random-effects model, which we used to pool C-statistics and their 95% confidence intervals (CIs). Finally, sources of heterogeneity were explored through subgroup analysis. RESULTS: A total of 15 studies involving 46,490 patients were included in this meta-analysis. The pooled C-statistic was 0.817 (95% CI: 0.781-0.847), indicating a moderate-to-good discriminative ability for SA-AKI. However, substantial heterogeneity was observed ( CONCLUSION: Current prediction models for SA-AKI demonstrate moderate-to-good predictive performance; however, high heterogeneity was observed across the included studies. Future research should prioritize external validation and emphasize the reduction of bias risk. Furthermore, we recommend that investigators explore robust, population-specific models to enhance clinical utility and generalizability. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/prospero/, identifier CRD420261347810.