Daily Sepsis Research Analysis

BACKGROUND: Sepsis is common and deadly, and subtypes are proposed to guide precision treatment. However, little is known about the uncertainty in subtype classification, and its implications for trajectory and treatment response. METHODS: In multiple electronic health record and trial data of adults with sepsis, we assigned patients clinical sepsis subtypes (α, β, γ, or δ-type), and measured uncertainty by defining core (≥90%) and margin (<90%) strata for each subtype according to model-derived membership probabilities. In multivariable logistic regression models, we determined the association between subtype, core/margin strata, and two outcomes, i.) change in subtype over 48 h and ii.) 365-day mortality in the ProCESS randomised trial. FINDINGS: We included 35,691 adult patients (mean age 68 [SD 16] years; 51% male, 85% White, 5.7% in-hospital mortality) with community-acquired sepsis according to Sepsis-3. Most patients changed clinical sepsis subtype during the 48 h after presentation (82%) regardless of initial subtype. The majority of patients were in the margin stratum of the subtype (α-type: 70%, β-type: 66%, γ-type: 64%), except for those in δ-type (18% margin strata). The odds of subtype change over 48 h was increased in the margin strata (interaction p = 0.023), where, for example, patients with the margin delta subtype had significantly higher odds than patients with alpha core (ref) subtype (odds ratio, 7.13; 95% confidence interval [CI], 5.16-9.85). For risk-adjusted 365-day mortality in the ProCESS trial, the effect of randomised treatment was modified by the subtype margin strata (interaction p = 0.026). INTERPRETATION: In patients with community sepsis, clinical subtypes are dynamic. Patients on the subtype margin are more likely to change groups, and uncertainty of subtype classification modified treatment effects. FUNDING: National Institutes of Health, National Institute of General Medical Sciences (R35GM119519).

Sepsis is a major global health crisis where early recognition and effective management remain significant challenges for healthcare systems. As part of the Lausanne University Hospital sepsis quality of care program, we developed and validated an Artificial Intelligence (AI)-powered Sepsis Learning Health System (SLHS) to enhance sepsis care. The SLHS combines a standardized clinical pathway with HERACLES, an AI algorithm that retrospectively classifies patient data into confirmed, possible, or invalidated sepsis cases every 6 h. Predictions inform dynamic dashboards displaying quality-of-care indicators to guide clinical interventions. Analysis of 97,559 stays in wards using the SLHS and 25,851 stays in control wards showed that in-hospital and 90-day mortality decreased for HERACLES-flagged sepsis in SLHS wards, while control wards did not. Further, sepsis coding increased in SLHS wards but did not change in control wards. This real-world example demonstrates how clinician-integrated AI systems can improve sepsis detection and outcomes.

INTRODUCTION: Sepsis is a leading cause of morbidity and mortality in intensive care units, characterized by a dysregulated host response to infection. Recent evidence suggests fluoxetine, a selective serotonin reuptake inhibitor, may exert immunometabolic effects beneficial in sepsis. The aim of this study is to evaluate the effect of fluoxetine on vasopressor duration, organ dysfunction, inflammatory markers, and mortality in adult patients with severe sepsis. MATERIALS AND METHODS: In this single-center, randomized, double-blind, placebo-controlled trial conducted at Ain Shams University Hospitals (December 2024-June 2025), 46 patients with severe sepsis were randomized 1:1 to receive either fluoxetine (40 mg/day) or placebo in addition to standard sepsis care. The primary outcome was vasopressor duration. Secondary outcomes included Sequential Organ Failure Assessment (SOFA) scores, inflammatory biomarkers (CRP, TNF-α, IL-1, procalcitonin), lactate levels, ICU length of stay, and 28-day mortality. RESULTS: Fluoxetine significantly reduced vasopressor duration (6.2 ± 0.4 vs. 7.9 ± 0.8 days; p < 0.001), ICU stay (15.9 ± 1.6 vs. 17.1 ± 1.1 days; p = 0.005), and inflammatory markers by day 7, including TNF-α, IL-1, CRP, and procalcitonin (all p < 0.05). SOFA and APACHE II scores were also lower in the fluoxetine group on days 7 and 10. No significant difference in 28-day mortality was observed (8.7% vs. 17.4%; p = 0.381). CONCLUSIONS: Fluoxetine as adjunctive therapy in severe sepsis may reduce vasopressor dependence, attenuate inflammation, and shorten ICU stay without increasing adverse effects. Its mortality benefit remains uncertain and warrants further investigation.