Daily Sepsis Research Analysis
Analyzed 58 papers and selected 3 impactful papers.
Summary
Analyzed 58 papers and selected 3 impactful articles.
Selected Articles
1. Meta-analysis of the prognostic value of skin perfusion parameters in sepsis patients: Evidence integration based on the Mottling Score, capillary refill time, and peripheral perfusion index.
Across 22 studies (n=2,727), higher mottling scores, prolonged capillary refill time, and lower peripheral perfusion index were each strongly associated with increased mortality in sepsis. Sensitivity analyses indicated robust findings with no significant publication bias, supporting these noninvasive bedside measures for early risk stratification.
Impact: Validates simple, widely available bedside perfusion markers as prognostic tools in sepsis, potentially informing triage and resuscitation targets. Integrates heterogeneous evidence with robust effect sizes.
Clinical Implications: Incorporating mottling score, CRT, and PPI into early sepsis assessments may improve identification of high-risk patients and guide titration of resuscitation. Standardized measurement protocols and thresholds could enhance consistency across settings.
Key Findings
- Mottling Score associated with higher 28-day mortality (OR 2.27; 95% CI 1.79–2.87) and 14-day mortality (OR 1.96; 95% CI 1.32–2.91).
- Prolonged capillary refill time predicted 28-day (OR 3.29; 95% CI 2.08–5.21) and in-hospital mortality (OR 2.46; 95% CI 1.18–5.12).
- Low peripheral perfusion index predicted 28-day (OR 5.05; 95% CI 3.65–6.98) and in-hospital mortality (OR 4.56; 95% CI 3.32–6.26).
Methodological Strengths
- Comprehensive multi-database search with independent screening and NOS bias assessment.
- Robust sensitivity analyses with no significant publication bias reported.
Limitations
- Heterogeneity in measurement protocols and thresholds across included studies.
- Observational designs limit causal inference; potential residual confounding.
Future Directions: Prospective multicenter studies to standardize measurement protocols, define intervention thresholds, and test perfusion-guided resuscitation strategies.
BACKGROUND: Despite advances in intensive care, sepsis and septic shock still have high morbidity and mortality. Microcirculatory disturbance is a key issue in sepsis, leading to hypoperfusion, hypoxia, and organ failure. The skin is a sensitive indicator of microcirculatory changes and often shows early systemic changes. Recently, bedside skin perfusion indicators such as the Mottling score (MS), Capillary Refill Time (CRT), and Peripheral Perfusion Index (PPI) have become common in practice. However, their value in predicting outcomes lacks strong evidence. METHODS: A systematic search was conducted across databases, including PubMed, Web of Science, Cochrane Library, EBSCO, China National Knowledge Infrastructure (CNKI), Wanfang, and VIP, with a search period spanning from the inception of the databases to January 2026. Cohort studies or case-control studies investigating the correlation between skin perfusion parameters and the prognosis of sepsis patients (primary outcomes: 28-day mortality, 14-day mortality, and in-hospital mortality) were included. Two researchers independently performed literature screening, data extraction, and assessment of the Newcastle-Ottawa Scale (NOS) bias risk. A meta-analysis was performed using RevMan 5.4.1 software. RESULTS: This study included a total of 22 articles, encompassing 2,727 study subjects. The meta-analysis results demonstrated that: (1) Mottling Score (MS), was significantly associated with 28-day mortality (Odds Ratio OR=2.27, 95% Confidence Interval CI: 1.79, 2.87, P<0.001) and 14-day mortality (OR=1.96, 95% CI: 1.32, 2.91, P<0.001); (2) Prolonged Capillary Refill Time (CRT) duration was significantly associated with 28-day mortality (OR=3.29, 95% CI: 2.08, 5.21, P<0.001) and in-hospital mortality (OR=2.46, 95% CI: 1.18, 5.12, P<0.001); (3) Reduced Peripheral Perfusion Index (PPI) was significantly associated with 28-day mortality (OR=5.05, 95% CI: 3.65, 6.98, P<0.001) and in-hospital mortality (OR=4.56, 95% CI: 3.32, 6.26, P<0.001). Sensitivity analysis confirmed robust results with no significant publication bias. CONCLUSION: The MS, CRT, and PPI, as bedside and non-invasive skin perfusion parameters, demonstrate significant predictive value for mortality risk in sepsis patients. Integrating these indicators facilitates early clinical identification of high-risk patients, guiding risk stratification and resuscitation therapy. Future large-sample prospective studies are required to further standardize their assessment protocols and intervention thresholds.
2. Association of Presepsis Statin Prescription With Kidney and Mortality Outcomes: Cause-Specific, Overlap-Weighted Analyses.
In 30,765 ICU patients with Sepsis-3, presepsis statin prescription within 24 hours was associated with lower risks of kidney outcome (HR 0.83), cause-specific mortality without kidney outcome (HR 0.56), and overall mortality (HR 0.78) using overlap weighting and cause-specific Cox models. Protective associations were consistent across subgroups.
Impact: Large, methodologically rigorous real-world analysis suggests a readily implementable, low-cost therapy may improve survival and kidney outcomes in sepsis, informing hypotheses for randomized trials.
Clinical Implications: For patients already on statins or at risk of sepsis, continuation of therapy may be beneficial; findings motivate careful consideration of peri-sepsis statin management while awaiting RCT confirmation.
Key Findings
- Presepsis statin prescription associated with reduced kidney outcome risk (HR 0.83; 95% CI 0.80–0.87).
- Lower cause-specific mortality without kidney outcome (HR 0.56; 95% CI 0.51–0.63) and overall mortality (HR 0.78; 95% CI 0.71–0.84).
- Subgroup analyses broadly consistent; larger benefit signals in younger patients and those without CKD for kidney outcomes.
Methodological Strengths
- Overlap weighting for covariate balance and cause-specific Cox competing-risk framework.
- Large sample size with consistent subgroup analyses.
Limitations
- Single-database retrospective design with potential residual confounding.
- Incomplete capture of sepsis severity and statin dosing/type details.
Future Directions: Prospective randomized trials to test statin initiation/continuation strategies in sepsis, with stratification by age, CKD status, and prior cardiovascular disease.
RATIONALE & OBJECTIVE: Sepsis, complicated by kidney injury, poses a mortality risk in intensive care unit patients. Although statins are thought to offer protective effects against kidney injury through anti-inflammatory mechanisms, evidence remains inconclusive. This study aimed to evaluate whether statin prescription before sepsis onset affects the risks of kidney injury and mortality. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: Adult intensive care unit patients who met Sepsis-3 criteria in Medical Information Mart for Intensive Care-IV. EXPOSURE: Statin prescription within the 24 hours preceding sepsis onset. OUTCOMES: The primary outcome was the prespecified kidney outcome (need for kidney replacement therapy or a reduction in estimated glomerular filtration rate of ≥50%). Secondary outcomes were mortality without the kidney outcome (cause-specific) and overall mortality. ANALYTICAL APPROACH: We used overlap weighting to balance baseline characteristics. Cause-specific Cox models estimated associations for the kidney outcome and mortality without the kidney outcome; a weighted Cox model estimated associations for overall mortality. RESULTS: The final cohort included 30,765 patients with sepsis, with 19.3% exposed to statins. Statin prescription was associated with a reduced risk of kidney outcome (HR, 0.83; 95% CI, 0.80-0.87), mortality without kidney outcome (HR, 0.56; 95% CI, 0.51-0.63), and overall mortality (HR, 0.78; 95% CI, 0.71-0.84). Subgroup analyses were broadly consistent across prespecified strata. For the kidney outcome, interaction testing suggested greater risk reduction among patients aged <65 years, those without chronic kidney disease, and those with hypertension. For death without prior kidney outcome and for overall mortality, protective associations were consistent across subgroups, with a larger effect among patients with prior myocardial infarction. Overall, statin prescription was consistently associated with lower risks of kidney outcome and mortality. LIMITATIONS: Single-database retrospective design and incomplete capture of sepsis severity measures. CONCLUSIONS: Presepsis statin prescription was associated with lower risks of kidney outcome and mortality, indicating potential clinical benefits in patients with sepsis. Sepsis is a severe infection that can threaten life and damage organs. Statins are medicines best known for lowering cholesterol, but they may also reduce inflammation and stabilize blood vessels. We studied adults in intensive care who met modern (Sepsis-3) criteria for sepsis and compared patients who were prescribed a statin within 24 hours before sepsis onset with those who were not. People who were taking statins before sepsis started had lower risks of kidney function decline and death. The association seemed stronger for survival than for kidney outcomes. These findings suggest that statins may offer clinical benefits for patients with sepsis and motivate future work to determine which statin types and doses are most helpful.
3. Development and External Validation of a Propensity Score-Matched Predictive Model for 48-Hour Intensive Care Unit Readmission in Patients With Sepsis.
Using MIMIC-IV data, a six-variable logistic model predicted 48-hour ICU readmission after sepsis with strong discrimination (C-index 0.82 development; 0.76 external validation). Predictors are routinely available, enabling pragmatic early risk stratification and targeted post-ICU interventions.
Impact: Provides a simple, externally validated tool to anticipate early clinical deterioration after ICU discharge in sepsis, addressing a key transition-of-care gap.
Clinical Implications: Can inform targeted monitoring, step-down unit selection, and early outreach for high-risk patients to reduce unplanned ICU readmissions.
Key Findings
- Six predictors (albumin at 24h of ICU admission, 24h aPTT, antibiotic use, mechanical ventilation, pre-discharge heart rate, APS III) yielded a C-index of 0.82 (development) and 0.76 (external).
- Propensity score matching reduced baseline imbalances prior to model development.
- Performance was consistent in internal validation (C-index 0.81), supporting robustness.
Methodological Strengths
- Use of LASSO for feature selection and separate internal and external validation.
- Propensity score matching to mitigate confounding in development data.
Limitations
- External validation cohort was relatively small (n=100), limiting generalizability.
- Single-database retrospective derivation; prospective impact evaluation is lacking.
Future Directions: Prospective, multicenter validation with implementation trials to test whether model-guided workflows reduce early ICU readmissions and improve outcomes.
OBJECTIVE: This study aimed to develop and validate a clinically applicable predictive model for estimating the probability of intensive care unit (ICU) readmission within 48 hours following ICU discharge in patients with sepsis. The model's predictive performance was evaluated across development and validation cohorts. METHODS: Clinical data from patients with sepsis-classified according to 48-hour ICU readmission status-were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database using structured query language. Propensity score matching was applied to balance baseline covariates and reduce confounding between comparison groups. Candidate variables were identified through univariate analysis and refined using least absolute shrinkage and selection operator regression. A logistic regression-based predictive model was subsequently constructed and validated using an independent dataset. RESULTS: The predictive model was developed using clinical data from 1,002 patients and validated in an independent external cohort of 100 patients. The final model incorporated 6 predictors, including the 24-hour serum albumin level at ICU admission, 24-hour activated partial thromboplastin time, antibiotic use, mechanical ventilation, heart rate within 24 hours prior to ICU discharge, and the Acute Physiology Score III. The model demonstrated robust predictive performance, with C-index values of 0.82 in the development cohort, 0.81 in the internal validation cohort, and 0.76 in the external validation cohort. CONCLUSION: The predictive model demonstrated reliable performance in estimating the probability of ICU readmission within 48 hours among patients with sepsis following ICU discharge. The variables incorporated into the model are routinely collected in clinical practice, supporting its feasibility for early risk stratification and targeted interventions aimed at reducing early ICU readmission rates.