Daily Sepsis Research Analysis
Analyzed 41 papers and selected 3 impactful papers.
Summary
Three impactful sepsis studies span treatment, diagnosis, and prognosis. A pragmatic randomized trial protocol will test oral midodrine to reduce intravenous vasopressor time in sepsis-associated hypotension; a dual-cohort study validates the red cell distribution width-to-albumin ratio (RAR) as a short-term mortality predictor in severe pulmonary sepsis; and a multi-dataset machine-learning analysis nominates RORA and GPR183 as robust pediatric sepsis biomarkers.
Research Themes
- Pragmatic randomized evaluation of an oral vasopressor-sparing strategy (midodrine) in sepsis
- Validated prognostic biomarker (RAR) for short-term mortality in severe pulmonary sepsis
- Machine-learning discovery of pediatric sepsis biomarkers across multi-cohort transcriptomics
Selected Articles
1. Midodrine for Sepsis Treatment and Early Vasopressor Weaning (MID-STEP): protocol for a pragmatic randomised clinical trial.
This pragmatic, open-label RCT will randomize 308 adults with sepsis-associated hypotension to standard care with or without enteral midodrine 10 mg TID. The primary endpoint is time alive and off IV vasopressors through day 28, with secondary outcomes capturing vasopressor exposure, line use, fluid balance, and lengths of stay. EHR-based ascertainment, ITT analysis, and a prespecified Bayesian analysis strengthen the design.
Impact: If positive, this trial could provide high-quality evidence for an inexpensive, scalable, oral strategy to reduce IV vasopressor exposure and ICU resource use in sepsis. It addresses a widespread off-label practice with rigorous methodology.
Clinical Implications: Clinicians may gain an evidence-based option to shorten vasopressor duration, potentially reducing central line days and ICU length of stay, pending trial results. Safety monitoring for bradycardia, hypertension, and renal events will be key.
Key Findings
- Randomized, pragmatic, open-label design enrolling 308 adults with sepsis-associated hypotension
- Primary endpoint: time alive and off IV vasopressors through day 28
- Secondary outcomes include vasopressor exposure, central line use, fluid balance, ICU/hospital LOS, and support-free days
- Intention-to-treat primary analysis with prespecified Bayesian secondary analysis
Methodological Strengths
- Pragmatic RCT with EHR-based outcome ascertainment and blinded adjudication
- Intention-to-treat analysis with stratified van Elteren testing and prespecified Bayesian analysis
Limitations
- Open-label design may introduce performance bias
- Protocol paper without results; external generalizability and effect size remain to be established
Future Directions: If efficacy is demonstrated, follow-up implementation trials and cost-effectiveness analyses across diverse health systems will be warranted, as well as subgroup analyses for shock phenotypes.
INTRODUCTION: Sepsis is a global health priority with nearly 50 million cases annually. Cardiovascular dysfunction is common, frequently manifesting as hypotension that persists despite fluid resuscitation. Most affected patients require the use of intravenous (IV) vasoactive agents, typically necessitating intensive care unit (ICU)-level monitoring, invasive interventions and contributing substantially to healthcare costs. Midodrine, an oral alpha-1 agonist approved for orthostatic hypotension, has increasingly been used off-label as a vasopressor-sparing (reducing IV vasopressor use) strategy in sepsis, despite limited and inconsistent evidence. This pragmatic, randomised, open-label trial evaluates the efficacy and safety of midodrine in patients with sepsis-associated hypotension. We hypothesise that, compared with standard care, midodrine administration will reduce the duration of IV vasopressor use. METHODS AND ANALYSIS: A total of 308 adult patients with sepsis-associated hypotension will be enrolled (154 per arm). The intervention group will, in addition to standard of care, receive enteral midodrine 10 mg three times daily. Outcomes will be ascertained pragmatically via electronic health record-based data retrieval and adjudicated by research coordinators blinded to treatment assignment. The primary outcome is time alive and off IV vasopressors in the first 28 days (in hours) after randomisation. Secondary outcomes include cumulative vasopressor exposure; use and duration of central venous access; cumulative fluid balance over the first 48 hours and up to 7 days of ICU stay; ICU and hospital length of stay; and ICU-, hospital-, and organ support-free days through day 28. Safety outcomes include adverse events potentially attributable to midodrine during hospitalisation including acute kidney injury. Primary analyses will follow an intention-to-treat framework, including all randomised participants according to their assigned treatment groups. Primary and secondary outcomes will be compared using a van Elteren test stratified by randomisation factors. A predefined secondary Bayesian analysis of the primary outcome will provide complementary estimates of treatment effect. Safety outcomes will be summarised descriptively without formal between-arm hypothesis testing. ETHICS AND DISSEMINATION: The Mayo Clinic Institutional Review Board approved this protocol and required written informed consent from all participants (IRB# 24-0 00 121). Findings will be disseminated through peer-reviewed publications and international conference presentations. TRIAL REGISTRATION NUMBER: NCT06319248.
2. Identification of biomarkers for pediatric sepsis based on machine learning and bioinformatics analysis.
Integrating six pediatric sepsis RNA-seq datasets (497 cases, 116 controls), the authors applied WGCNA and 14 machine-learning models to prioritize 237 candidate biomarkers, converging on RORA and GPR183. Functional enrichment implicated immune regulation, transcription/translation, and senescence, while immune deconvolution suggested reduced adaptive immune compartments.
Impact: This work advances biomarker discovery by combining multi-cohort transcriptomics with diverse machine-learning approaches to nominate reproducible targets (RORA, GPR183) for pediatric sepsis. It provides a prioritized roadmap for translational validation.
Clinical Implications: Pending prospective validation, RORA and GPR183 could underpin early diagnostic assays or immune-monitoring panels in pediatric sepsis and guide immunomodulatory strategies.
Key Findings
- Integrated six bulk RNA-seq datasets (497 pediatric sepsis, 116 healthy controls)
- Screened 237 high-confidence biomarkers across 14 machine-learning models; RORA and GPR183 consistently prioritized
- Functional enrichment implicated immune regulation, transcription/translation, and senescence pathways
- Immune infiltration analysis suggested reduced adaptive immune cells (e.g., B cells, CD8+ T cells)
Methodological Strengths
- Multi-cohort integration with WGCNA to identify disease-associated modules
- Ensemble evaluation across 14 machine-learning models to ensure robustness
Limitations
- Retrospective secondary analysis with potential batch effects
- Lack of prospective clinical validation and protein-level confirmation
Future Directions: Prospective, multi-center validation with standardized assays, longitudinal sampling, and integration with clinical phenotypes to build diagnostic/prognostic panels.
Pediatric sepsis is a systemic inflammatory syndrome caused by dysregulated host immune responses, with a high mortality rate and a lack of effective biomarkers, posing significant challenges for early diagnosis and treatment. This study integrated six bulk RNA-seq datasets related to pediatric sepsis, including 497 patients and 116 healthy control samples. Weighted gene co-expression network analysis was used to identify gene modules significantly associated with pediatric sepsis, and 237 high-confidence biomarkers were screened based on 14 machine learning models, among which RORA and GPR183 stood out in multiple models. Functional analysis indicated that these biomarkers were mainly involved in biological processes such as transcription and translation, the immune system, and cellular senescence. Immune infiltration analysis revealed a significant reduction in adaptive immune cells such as B cells and CD8
3. The red cell distribution width to albumin ratio as a novel biomarker for predicting short-term mortality in severe pulmonary sepsis: a retrospective study with dual-cohort validation.
Across 6,065 patients with pulmonary sepsis, higher RAR independently predicted increased 28-day ICU and in-hospital mortality with a dose-response relationship. An RAR-augmented Cox model outperformed traditional critical illness scores, and results were replicated in an external cohort.
Impact: Provides a simple, readily available biomarker that integrates inflammation and nutrition to improve short-term risk stratification in severe pulmonary sepsis, with external validation.
Clinical Implications: RAR can be incorporated into early risk assessment to identify high-risk patients for intensified monitoring, hemodynamic optimization, and timely escalation of therapies.
Key Findings
- Dual-cohort retrospective analysis including 6,065 pulmonary sepsis patients (single-center + MIMIC-IV)
- Higher RAR independently associated with increased 28-day ICU and in-hospital mortality (HR 1.52 and 1.30 per unit increase)
- Dose-response relationship confirmed by restricted cubic spline analysis
- RAR-enhanced multivariable model outperformed traditional scores and was validated externally
Methodological Strengths
- Large sample size with external validation and multiple analytic approaches (Cox, RCS, ML feature selection)
- Comparative performance testing against established scoring systems
Limitations
- Retrospective design with potential residual confounding
- RAR may be affected by laboratory variability and comorbid conditions influencing albumin
Future Directions: Prospective, multicenter validation with predefined thresholds and assessment of RAR-guided management impact on outcomes.
BACKGROUND: The Red Cell Distribution Width to Albumin Ratio (RAR) is a biomarker that reflects a patient's nutritional status, inflammatory response, and oxidative stress, showing significant potential in critical care medicine. To investigate its prognostic value, we conducted a retrospective study using a dual-cohort design to assess the association between RAR and short-term (28-day) mortality in patients with pulmonary sepsis. MATERIALS AND METHODS: We retrospectively identified patients with sepsis secondary to pulmonary infections from the Binzhou Medical University Hospital medical records and the Medical Information Mart for Intensive Care (MIMIC-IV) database. To examine the association between RAR and short-term adverse outcomes in these patients, we employed several statistical methods, including Kaplan-Meier survival curves, multivariable Cox regression, and restricted cubic spline (RCS) analysis. Subsequently, we applied machine learning algorithms-namely the Boruta algorithm, LASSO-COX regression, and Random Forests-to identify the most predictive features. These features were then used to develop a final multivariable Cox regression model for risk prediction. The performance of this predictive model was evaluated using receiver operating characteristic (ROC) curve analysis. RESULT: The final analysis included 6,065 patients with pulmonary sepsis. The 28-day ICU and in-hospital mortality rates were 20.50 and 19.30%, respectively. In the fully adjusted multivariable model, a higher RAR was significantly associated with increased 28-day ICU and in-hospital mortality, whether treated as a continuous or categorical variable. For each unit increase in the continuous RAR score, the hazard ratios (HR) for 28-day ICU and in-hospital mortality were 1.52 (95% CI: 1.28-1.80) and 1.30 (95% CI: 1.09-1.55), respectively. Similarly, when compared to the low RAR group, the high RAR group had hazard ratios of 1.45 (95% CI: 1.23-1.70) and 1.29 (95% CI: 1.09-1.52) for the two outcomes. The restricted cubic spline (RCS) analysis revealed a positive dose-response relationship between RAR levels and short-term adverse outcomes. Furthermore, the risk prediction model incorporating RAR and eight other independent predictors demonstrated superior performance in identifying high-risk patients compared to traditional critical illness scoring systems, as shown by receiver operating characteristic (ROC) analysis. All findings were consistently validated in the external cohort. CONCLUSION: In conclusion, our study demonstrates a significant inverse association between the RAR and short-term survival in patients with severe pulmonary sepsis. The RAR-based scoring system we developed shows promise as a practical adjunct tool for clinical risk assessment. Prospective validation is warranted to confirm its utility in improving risk stratification for this patient population.