Daily Sepsis Research Analysis
Three studies advance sepsis care across stewardship, diagnostics, and precision glycemic risk stratification. A prospective NICU stewardship program reduced 14- and 28-day mortality, an interpretable MIMIC-IV cohort showed metabolic state–specific mortality risk from combined stress hyperglycemia ratio and glucose variability, and implementation of BCID2 multiplex PCR in bacteremia was associated with lower in-hospital mortality.
Summary
Three studies advance sepsis care across stewardship, diagnostics, and precision glycemic risk stratification. A prospective NICU stewardship program reduced 14- and 28-day mortality, an interpretable MIMIC-IV cohort showed metabolic state–specific mortality risk from combined stress hyperglycemia ratio and glucose variability, and implementation of BCID2 multiplex PCR in bacteremia was associated with lower in-hospital mortality.
Research Themes
- Antibiotic stewardship and outcomes in neonatal sepsis
- Precision glycemic phenotyping for sepsis prognosis
- Rapid molecular diagnostics for bacteremia and sepsis care
Selected Articles
1. Clinical impact of an antibiotic stewardship program in a neonatal intensive care unit at a tertiary care hospital: a prospective quasi-experimental clinical study.
In a prospective quasi-experimental study of 1200 NICU patients, implementing a locally tailored antibiotic stewardship program—including NICU-specific antibiograms and a revised neonatal sepsis protocol—improved prescribing and significantly reduced 14- and 28-day mortality. The program increased appropriate diagnostics (e.g., CRP testing) alongside protocolized therapy.
Impact: Prospective, real-world stewardship implementation with mortality benefit in neonatal sepsis is rare and highly actionable. It demonstrates that local antibiograms and protocolized care can translate to survival gains.
Clinical Implications: Hospitals should implement NICU-specific antibiotic stewardship with local antibiograms and protocolized neonatal sepsis regimens, including diagnostic stewardship (e.g., CRP), to reduce short-term mortality while combating resistance.
Key Findings
- Prospective quasi-experimental NICU stewardship (n=1200) reduced 14- and 28-day mortality.
- Program included NICU-specific antibiograms and protocolized neonatal sepsis therapy aligned with local susceptibility patterns.
- Diagnostic stewardship increased (e.g., CRP testing frequency rose), supporting targeted antibiotic use.
Methodological Strengths
- Prospective quasi-experimental design with predefined stewardship measures and trial registration (NCT04039152).
- Large NICU cohort with phase-wise evaluation and protocolized implementation.
Limitations
- Single-center, nonrandomized design may be subject to secular trends and confounding.
- Abstract does not report effect sizes for all outcomes; full data needed for external benchmarking.
Future Directions: Cluster-randomized or stepped-wedge trials across NICUs to confirm mortality benefits, assess antimicrobial resistance trajectories, and evaluate unintended consequences (e.g., fungal infections).
BACKGROUND: Antimicrobial resistance represents a great global concern and initiating an antimicrobial stewardship program is one of the main efforts to control antimicrobial resistance through optimizing antimicrobial utilization. Antibiotics are used extensively and inappropriately in neonatal intensive care units (NICUs). The present study aimed to assess the clinical impact of the antibiotics stewardship program (ASP) in the NICU. METHODS: The study was conducted in two phases at the NICU, Assiut University Children’s Hospital, where 1200 patients were enrolled from January 2019 to June 2020. The pre-ASP phase included making NICU-specific antibiograms, choosing the antibiotic use evaluation measures, conducting antibiotic use evaluations, and designing the ASP. The ASP intervention phase included the implementation of ASP, which involved modifying the neonatal sepsis treatment protocol according to the local antibiotic susceptibility patterns and measuring its clinical outcomes. Categorical data were tested with Pearson’s chi-squared test and Fisher’s exact test. Numerical data were tested with the Wilcoxon rank sum test. RESULTS: A total of 603 and 597 patients were enrolled in the pre-ASP and intervention-ASP phases, respectively. The ASP intervention phase showed a significant increase in the number of C-reactive protein tests [1(1–2)vs 2(1–3), CONCLUSION: ASP implementation was successful in improving antibiotic prescribing and modifying the neonatal sepsis treatment protocol according to the local antibiotic susceptibility patterns, which resulted in reduced 14- and 28-day mortality. TRIAL REGISTRATION: Clinical Impact of an Antibiotic Stewardship Program in a Neonatal Intensive Care Unit, Registration number NCT04039152. Registered 31 July 2019 - Retrospectively registered. https://classic.clinicaltrials.gov/ct2/show/NCT04039152.
2. Simultaneous Assessment of Stress Hyperglycemia Ratio and Glucose Variability to Predict All-cause Mortality in Sepsis Patients Across Different Glucose Metabolic States: an Observational Cohort Study With Interpretable Machine Learning Approach.
In 4,838 sepsis patients from MIMIC-IV, combined SHR and GV stratified 28-day mortality differentially by glucose metabolic state: high SHR/high GV in NGR, low SHR/high GV in Pre-DM, and high SHR/low GV in DM carried the greatest risks. Interpretable ML models achieved AUCs up to 0.776, highlighting a precision glycemic risk framework.
Impact: This study operationalizes precision glycemic phenotyping in sepsis, showing that the prognostic impact of SHR and GV depends on baseline glucose metabolism. It provides actionable risk markers and interpretable models to guide tailored glycemic management.
Clinical Implications: Monitor both SHR and GV and interpret them in the context of baseline glucose status (NGR, Pre-DM, DM) to risk-stratify sepsis patients. These markers could inform targets and aggressiveness of glycemic control pending prospective validation.
Key Findings
- In 4,838 sepsis patients, the combination of high SHR (>1.23) and high GV (>28.56) conferred the highest 28-day mortality risk in NGR (HR 2.06; 95% CI 1.40–3.04).
- Pre-DM patients with low SHR/high GV had the greatest 28-day mortality risk (HR 2.45; 95% CI 1.73–3.48); DM patients with high SHR/low GV had the highest risk (HR 1.46; 95% CI 1.06–2.01).
- Interpretable ML models (RF, LR AUC 0.776; XGBoost AUC 0.746) identified SHR and GV as key predictors across metabolic strata.
Methodological Strengths
- Large, well-characterized ICU cohort (MIMIC-IV) with robust survival analyses (KM, Cox, RCS, landmark).
- Model transparency via SHAP enhances interpretability and clinical translation.
Limitations
- Retrospective single-database analysis with potential residual confounding and measurement biases.
- No external prospective validation; interventional implications for glycemic control remain to be tested.
Future Directions: Prospective, multi-center validation and randomized trials to test SHR/GV-guided glycemic strategies by metabolic phenotype.
BACKGROUND: Stress hyperglycemia ratio (SHR) and glycemic variability (GV) reflect acute glucose elevation and fluctuation, which are associated with adverse outcomes in patients with some diseases. However, the relationship between combined assessment of SHR and GV and mortality risk in sepsis remains unclear. This study aims to investigate the associations of SHR, GV, and their combination with sepsis mortality among individuals with different glucose metabolic states, and to develop a mortality prediction model using machine learning (ML) models. METHODS: Patients with sepsis were screened in the MIMIC-IV database, stratified into normal glucose regulation (NGR), pre-diabetes mellitus(Pre-DM), and diabetes mellitus(DM) groups based on glucose metabolic status. Associations with mortality were analyzed using Kaplan-Meier(KM) curves, Cox proportional hazards model, restricted cubic splines(RCS), and landmark analyses. Five ML algorithms were employed for prediction, with SHapley Additive explanations (SHAP) interpreting key predictors. RESULTS: A total of 4,838 patients were enrolled, with a median age of 68 years. Overall, 641 patients (13.2%) died in the ICU, and 936 patients (19.3%) died within 28 days after admission to the ICU. In NGR patients, combined high SHR (>1.23; highest tertile) and high GV (>28.56; highest tertile)-determined based on tertile distribution-conferred the highest 28-day mortality risk (HR = 2.06, 95% CI: 1.40-3.04). Pre-DM patients with low SHR/high GV (SHR<1.23, GV>28.56) showed the greatest 28-day mortality risk (HR = 2.45, 95% CI: 1.73-3.48). DM patients with high SHR/low GV (SHR>1.23, GV<28.56) had the highest 28-day mortality risk (HR = 1.46, 95% CI: 1.06-2.01). Machine learning models-particularly XGBoost (AUC: 0.746), Random Forest (AUC: 0.776), and Logistic Regression (AUC: 0.776)-demonstrated the strongest predictive performance for these endpoints. CONCLUSIONS: The combined assessment of SHR and GV may provide useful information for predicting mortality in sepsis patients-particularly among individuals with NGR and Pre-DM. This integrated approach highlights the potential need for personalized glycemic management strategies, which warrants further investigation in prospective studies.
3. Impact of multiplex polymerase chain reaction testing in patients with bacteremia.
In a retrospective pre-post study of 2,872 bacteremic inpatients, implementing the FilmArray BCID2 panel was associated with significantly lower in-hospital mortality (aOR 0.58, 95% CI 0.37–0.92). Outcomes included LOS, DOT, and DASC, supporting the clinical utility of rapid multiplex PCR to optimize therapy.
Impact: Real-world evidence links rapid multiplex molecular diagnostics to survival gains in bacteremia, a cornerstone of sepsis care, supporting broader BCID2 adoption integrated with stewardship.
Clinical Implications: Integrate BCID2 with antimicrobial stewardship to shorten time-to-targeted therapy, reduce broad-spectrum exposure (DASC), and potentially improve survival in bacteremia and sepsis pathways.
Key Findings
- Among 2,872 positive blood culture patients, BCID2 implementation was associated with reduced in-hospital mortality (aOR 0.58; 95% CI 0.37–0.92).
- Pre- vs post-implementation comparison assessed LOS, DOT, and DASC alongside mortality.
- Findings support rapid pathogen and resistance gene detection to optimize antimicrobial therapy.
Methodological Strengths
- Large pre-post cohort with adjusted analyses linking implementation to outcomes.
- Evaluated multiple clinically relevant endpoints (mortality, LOS, DOT, DASC).
Limitations
- Single-center retrospective design; potential secular trends and unmeasured confounders.
- Abstract truncation limits visibility into effect sizes for LOS, DOT, and DASC.
Future Directions: Prospective multicenter implementation studies with time-to-therapy metrics, cost-effectiveness, and integration with stewardship protocols.
Rapid identification of pathogens in bacteremia is critical for optimizing antimicrobial therapy. The FilmArray blood culture identification 2 (BCID2) panel enables multiplex PCR-based detection of pathogens and resistance genes. This study aimed to evaluate the clinical impact of BCID2 implementation in hospitalized patients with bacteremia. To this end, we conducted a retrospective study at a single Japanese center (May 2018-December 2024). The outcomes included length of stay, in-hospital mortality, antimicrobial days of therapy (DOT), and days of antimicrobial spectrum coverage (DASC) score. The pre-BCID2 and BCID2 implementation periods were compared. Among the 2,872 patients with positive blood cultures, BCID2 implementation was associated with a significant reduction in mortality (adjusted odds ratio [aOR] 0.58, 95% CI: 0.37-0.92,