Daily Sepsis Research Analysis

IMPORTANCE: Sepsis-associated acute kidney injury (SA-AKI) is a common and clinically important condition in patients who are critically ill. Dysregulated inflammation may contribute to it. Intravenous hydrocortisone may decrease the risk of SA-AKI progression. OBJECTIVE: To describe the associations of hydrocortisone use with the incidence and outcomes of requirement for kidney replacement therapy (KRT), as well as source of sepsis, mean arterial pressure (MAP), and MAP indexed to required vasopressor (norepinephrine equivalent [NEE]). DESIGN, SETTING, AND PARTICIPANTS: This cohort study was conducted as a post hoc analysis of the Adjunctive Corticosteroid Treatment in Critically Ill Patients with Septic Shock (ADRENAL) randomized clinical trial (RCT), a multicenter placebo-controlled RCT of hydrocortisone in patients with septic shock in 69 intensive care units in Australia, the United Kingdom, New Zealand, Saudi Arabia, and Denmark that recruited between 2013 and 2017. Participants were patients enrolled in the ADRENAL study with septic shock who did not require KRT in the 24 hours prior to randomization and who did not have a prior longstanding dialysis requirement. Data were analyzed between July and September 2024. EXPOSURES: Receipt of hydrocortisone (vs placebo), MAP at enrollment, vasopressor dose (NEE) and MAP:NEE ratio, source of sepsis, causative organism, bacteremia, and the use of nephrotoxic antimicrobials, vasopressin, or specific inotropes. MAIN OUTCOMES AND MEASURES: Outcomes of interest were KRT requirement and liberation from KRT, measured as days alive and free of KRT. RESULTS: A cohort of 3161 patients (median [IQR] age, 65 [53-74] years, 1921 [61%] male) was identified, including 1589 patients randomized to receive hydrocortisone and 1572 patients who received the placebo. Allocation to treatment with hydrocortisone was associated with a significantly reduced incidence of KRT requirement compared with placebo (329 patients [21%] vs 372 patients [24%]; odds ratio [OR], 0.84 [95% CI, 0.70 to 0.99]; P = .04). When controlled for factors associated with KRT requirement, randomization to hydrocortisone remained significantly associated with a reduced odds of new KRT requirement (OR, 0.79 [95% CI, 0.66 to 0.95]; P = .01). Among patients who started KRT following randomization, hydrocortisone was not associated with reduced days alive and free of KRT (mean difference, 1.28 [95% CI, -4.31 to 6.87] days; P = .65). CONCLUSIONS AND RELEVANCE: In this post hoc cohort study of patients with septic shock enrolled in a large RCT, intravenous hydrocortisone was associated with a reduced risk of new KRT requirement following randomization.

BACKGROUND: Major Adverse Kidney Events within 30 days (MAKE30) is an important patient-centered outcome for assessing the impact of acute kidney injury (AKI). Existing prediction models for MAKE30 are static and overlook dynamic changes in clinical status. We introduce ORAKLE, a novel deep-learning model that utilizes evolving time-series data to predict MAKE30, enabling personalized, patient-centered approaches to AKI management and outcome improvement. METHODS: We conducted a retrospective study using three publicly available critical care databases: MIMIC-IV as the development cohort, and SiCdb and eICU-CRD as external validation cohorts. Patients with sepsis-3 criteria who developed AKI within 48 h of intensive care unit admission were identified. Our primary outcome was MAKE30, defined as a composite of death, new dialysis or persistent kidney dysfunction within 30 days of ICU admission. We developed ORAKLE using Dynamic DeepHit framework for time-series survival analysis and its performance against Cox and XGBoost models. We further assessed model calibration using Brier score. RESULTS: We analyzed 16,671 patients from MIMIC-IV, 2665 from SICdb, and 11,447 from eICU-CRD. ORAKLE outperformed the XGBoost and Cox models in predicting MAKE30, achieving AUROCs of 0.84 (95% CI: 0.83-0.86) vs. 0.81 (95% CI: 0.79-0.83) vs. 0.80 (95% CI: 0.78-0.82) in MIMIC-IV internal test set, 0.83 (95% CI: 0.81-0.85) vs. 0.80 (95% CI: 0.78-0.83) vs. 0.79 (95% CI: 0.77-0.81) in SICdb, and 0.85 (95% CI: 0.84-0.85) vs. 0.83 (95% CI: 0.83-0.84) vs. 0.81 (95% CI: 0.80-0.82) in eICU-CRD. The AUPRC values for ORAKLE were also significantly better than that of XGBoost and Cox models. The Brier score for ORAKLE was 0.21 across the internal test set, SICdb, and eICU-CRD, suggesting good calibration. CONCLUSIONS: ORAKLE is a robust deep-learning model for predicting MAKE30 in critically ill patients with AKI that utilizes evolving time series data. By incorporating dynamically changing time series features, the model captures the evolving nature of kidney injury, treatment effects, and patient trajectories more accurately. This innovation facilitates tailored risk assessments and identifies varying treatment responses, laying the groundwork for more personalized and effective management approaches.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Current treatments are limited to source control and supportive care, underscoring the urgent need for novel therapeutic interventions. Endogenous molecules released from stressed or damaged cells, known as damage-associated molecular patterns (DAMPs), exacerbate inflammation, organ injury, and mortality in sepsis. In this study, we discovered a novel therapeutic compound, opsonic peptide 18 (OP18), designed to scavenge multiple DAMPs, including extracellular cold-inducible RNA-binding protein (eCIRP), high mobility group box 1 (HMGB1) and histone H3, by facilitating their clearance via macrophages. OP18 was developed by identifying a 15-amino acid (aa) binding site within the extracellular domain of Toll-like receptor 4 (TLR4) shared by eCIRP, HMGB1, and histone H3, then extending it with an α