Daily Sepsis Research Analysis
Proteome-based phenotyping identified three biologically and clinically distinct ARDS subtypes with differential outcomes and treatment responses, advancing precision care in sepsis-related critical illness. A prospective study validated robust, cross-etiology performance of urinary [TIMP-2]•[IGFBP7] for AKI prediction, and a meta-analysis found that early vasopressin may shorten hospital stay in septic shock without improving mortality.
Summary
Proteome-based phenotyping identified three biologically and clinically distinct ARDS subtypes with differential outcomes and treatment responses, advancing precision care in sepsis-related critical illness. A prospective study validated robust, cross-etiology performance of urinary [TIMP-2]•[IGFBP7] for AKI prediction, and a meta-analysis found that early vasopressin may shorten hospital stay in septic shock without improving mortality.
Research Themes
- Precision phenotyping in ARDS and sepsis
- Early AKI prediction using urinary stress biomarkers
- Timing of adjunct vasopressin therapy in septic shock
Selected Articles
1. Large-scale proteomic profiling identifies distinct inflammatory phenotypes in Acute Respiratory Distress Syndrome (ARDS): A multi-center, prospective cohort study.
Using early serum proteomics and latent class analysis across 1,048 ARDS patients, the study identified three validated inflammatory phenotypes with distinct mortality, shock incidence, and ventilator-free days. Radiomics and pathway enrichment supported biological divergence, and heterogeneous treatment effects suggested differential responses to glucocorticoids and ventilation strategies.
Impact: This large, multicenter, prospectively collected dataset links proteomic phenotypes to outcomes and treatment heterogeneity, laying a foundation for biomarker-guided ARDS (including sepsis-related ARDS) trials.
Clinical Implications: Proteome-defined phenotypes could enable risk stratification and selection of patients more likely to benefit from specific therapies (e.g., glucocorticoids, tailored ventilation). Implementation should await prospective biomarker-stratified interventional trials.
Key Findings
- Three inflammatory ARDS phenotypes (C1–C3) were identified in 1,048 patients and validated in two external cohorts.
- Phenotype C1 had the highest 90-day mortality, highest shock incidence, and the fewest ventilator-free days; C2 had the best outcomes.
- Radiomics showed a larger proportion of poorly/non-inflated lung in C1, and pathway enrichment indicated distinct molecular programs.
- Heterogeneous treatment effects suggested differential responses to glucocorticoids and ventilation strategies.
Methodological Strengths
- Multicenter, prospective cohort with early sampling and large sample size (n=1,048)
- External validation of phenotypes and use of radiomics, pathway enrichment, and IPTW-adjusted HTE analyses
Limitations
- Observational design limits causal inference for treatment effects; HTEs are hypothesis-generating.
- Generalizability may depend on proteomic platform and cohort characteristics.
Future Directions: Prospective biomarker-stratified randomized trials to test phenotype-specific therapies; development of parsimonious classifiers for bedside application.
BACKGROUND: Host responses during ARDS are highly heterogeneous, contributing to inconsistent therapeutic outcomes. Proteome-based phenotyping may identify biologically and clinically distinct phenotypes to guide precision therapy. METHODS: In this multicenter cohort study, we used latent class analysis (LCA) of targeted serum proteomics to identify ARDS phenotypes. Serum samples were collected within 72 h of diagnosis to capture early-phase profiles. Validation was conducted in external cohorts. Pathway enrichment assessed molecular heterogeneity. Lung CT scans were analyzed using machine learning-based radiomics to explore phenotypic distinctions. Heterogeneous treatment effects (HTEs) for glucocorticoids and ventilation strategies were evaluated using inverse probability of treatment weighting (IPTW) adjusted Cox regression. A multinomial XGBoost model was developed to classify phenotypes. RESULTS: Among 1048 patients, three inflammatory phenotypes (C1, C2, C3) were identified and validated in two independent cohorts. The phenotype C1 with a larger proportion of poorly/non-inflated lung compartments had the highest 90-day mortality, shock incidence, and fewest ventilator-free days, followed by C3, while C2 patients had the best outcomes (
2. Predictive value of urinary [TIMP-2]•[IGFBP7] for AKI among sepsis, stroke, and cardiac surgery cohorts: A prospective study.
In 337 patients across sepsis, stroke, and cardiac surgery, urinary [TIMP-2]•[IGFBP7] predicted AKI with high accuracy (AUC 0.82–0.90) without significant differences across etiologies. A combined model incorporating biomarker levels and clinical risk factors further improved prediction.
Impact: Demonstrates robust, cross-etiology performance of a widely available urinary stress biomarker for early AKI prediction, supporting broader clinical adoption and risk-stratified nephroprotective strategies.
Clinical Implications: Incorporating urinary [TIMP-2]•[IGFBP7] into admission risk assessment for sepsis and other high-risk cohorts can trigger early nephroprotective measures (e.g., fluid stewardship, avoidance of nephrotoxins, KDIGO bundles).
Key Findings
- Across three cohorts (stroke, sepsis, cardiac surgery), urinary [TIMP-2]•[IGFBP7] predicted AKI with AUCs of 0.86, 0.82, and 0.90, respectively.
- No significant differences in AUC between etiologies by DeLong’s test (P=0.20 vs stroke; P=0.21 vs sepsis).
- A combined prediction model integrating biomarker levels and clinical risk factors improved AKI prediction.
- AKI incidence was 50% in sepsis, 31.6% post-cardiac surgery, and 22.2% in stroke, underscoring high risk in sepsis.
Methodological Strengths
- Prospective design with predefined cohorts and ROC/AUC analyses including DeLong’s comparisons
- Development of a combined clinical-biomarker prediction model with logistic regression
Limitations
- Single prospective dataset without multicenter external validation may limit generalizability.
- Timing and frequency of biomarker sampling relative to AKI onset were not extensively detailed.
Future Directions: Multicenter validation, clinical impact studies testing biomarker-triggered care bundles, and cost-effectiveness analyses across etiologies including sepsis.
BACKGROUND: TIMP-2 and IGFBP7 have shown effectiveness as biomarkers for predicting Acute Kidney Injury (AKI). However, the variations in the predictive capacity of urinary [TIMP-2]• [IGFBP7] for AKI across different etiologies remain unexplored. This study aimed to assess the predictive capability of urinary [TIMP-2]• [IGFBP7] for AKI in three distinct disease cohorts (stroke, sepsis, and cardiac surgery) characterized by differing AKI etiologies. METHODS: This prospective observational study evaluated the predictive value of urinary [TIMP-2]• [IGFBP7] among three cohorts with varying AKI causes. Binary logistic regression was employed to identify AKI's independent risk factors and develop a combined prediction model. The predictive value was assessed using Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) analyses. RESULTS: 337 patients were included in the final analysis, with 109 (32.3%) developing AKI. AKI occurred in 39 (22.2%) stroke patients, 52 (50%) sepsis patients, and 18 (31.6%) post-cardiac surgery patients. [TIMP-2]• [IGFBP7] exhibited predictive value for AKI with an AUC of 0.86 (95% CI 0.75-0.90) in stroke, 0.82 (95% CI 0.74-0.91) in sepsis, and 0.90 (95% CI 0.82-0.98) in post-cardiac surgery. DeLong's test indicated no significant differences in the predictive value of [TIMP-2]• [IGFBP7] between the cardiac surgery group and the stroke (P=0.20) and sepsis (P=0.21) groups. CONCLUSION: The combined prediction model, which integrates urinary [TIMP-2]• [IGFBP7] concentrations and AKI risk factors, significantly enhances AKI prediction. No significant differences were found in the predictive value of urinary [TIMP-2]• [IGFBP7] for AKI among the stroke, sepsis, and cardiac surgery cohorts.
3. Early vasopressin plus norepinephrine versus delayed or no vasopressin in septic shock: A systematic review and meta-analysis.
Across six studies (n=1,167; including two RCTs), early vasopressin addition shortened hospital length of stay but did not reduce in-hospital or 28-day mortality, nor improve other key outcomes. Risk of bias was assessed with RoB2/ROBINS-I; heterogeneity and variable definitions of ‘early’ limit conclusions.
Impact: Synthesizes the best available evidence on vasopressin timing in septic shock, clarifying that routine early initiation is not supported despite a modest LOS benefit.
Clinical Implications: Clinicians should continue to prioritize norepinephrine and consider vasopressin as an adjunct when indicated, without presuming mortality benefit from early initiation. Focus should remain on source control, fluids, and individualized hemodynamic targets.
Key Findings
- Across 6 studies (n=1,167), early vasopressin plus norepinephrine significantly shortened hospital LOS (MD −4.48 days; 95% CI −8.37 to −0.60).
- No reduction in in-hospital or 28-day mortality with early vasopressin compared to delayed or no vasopressin.
- No consistent improvements in ICU LOS, vasopressor duration, SOFA scores, arrhythmias, or need for RRT.
- Risk-of-bias assessments (RoB2/ROBINS-I) and heterogeneity in ‘early’ definitions temper certainty of effect.
Methodological Strengths
- Systematic review with random-effects meta-analysis and formal risk-of-bias assessment (RoB2/ROBINS-I)
- Predefined clinical outcomes including mortality, LOS, organ support, and safety
Limitations
- Only two RCTs; remaining studies observational, with heterogeneity in timing definitions and co-interventions.
- Potential publication bias and limited power to detect mortality differences.
Future Directions: Large, protocolized RCTs using standardized ‘early’ timing and biomarker- or phenotype-guided selection to test vasopressin’s role in septic shock.
INTRODUCTION: Norepinephrine is the first-line vasopressor in septic shock, with vasopressin commonly added if shock persists. Evidence suggests that early initiation of vasopressin may improve hemodynamic and clinical outcomes; however, data remain conflicting. This meta-analysis evaluates early vasopressin administration. METHODS: We searched PubMed, Embase, and Cochrane for studies comparing early vasopressin plus norepinephrine versus norepinephrine alone or later vasopressin initiation in septic shock. Outcomes included hospital and ICU length of stay (LOS), SOFA score, vasopressor duration, mortality (in-hospital and 28-day), arrhythmias, and renal replacement therapy (RRT). A random-effects model was used. Risk of bias was assessed using RoB2 and ROBINS-I tools. RESULTS: Six studies (n = 1167 patients) met inclusion criteria, including two RCTs. Early vasopressin was associated with a significantly shorter hospital LOS (mean difference [MD] -4.48 days; 95 % CI -8.37 to -0.60; p = 0.02; I CONCLUSION: Early vasopressin may reduce hospital LOS in septic shock but does not improve mortality or other outcomes. Even though there is a possible benefit, current evidence does not support routine early use.