S01E02 Timing Matters in Sepsis: Community-Onset vs Hospital-Onset (Machine Learning Insights)

Episode titleTiming Matters in Sepsis: Community-Onset vs Hospital-Onset (Machine Learning Insights)Hospital-onset sepsis (HOS) is often treated as “the same disease” as community-onset sepsis (COS)—but timing changes the phenotype, the treatment timeline, and outcomes. In this episode of PRISM Rounds (S1 E2), we break down a retrospective cohort study (2019–2023) from a large academic medical center comparing COS vs HOS and using random forest modeling to identify which variables matter most for mortality, ICU use, and length of stay.Key findings: HOS was associated with higher in-hospital mortality (38.2% vs 28.5%), longer hospital and ICU stays, higher comorbidity burden, and delayed antibiotic initiation. Timing of onset (HOS vs COS) emerged as an important predictor of mortality and hospital length of stay in machine learning models—supporting “timing-aware” sepsis surveillance and escalation pathways.Article links:PubMed: https://pubmed.ncbi.nlm.nih.gov/41618258/DOI: https://doi.org/10.1186/s12911-026-03353-zVerma R, Elhance A, Marsh TJ, et al. Timing Matters: A Machine Learning–Driven Comparison of Community and Hospital-Onset Sepsis. BMC Medical Informatics and Decision Making (2026).DOI: https://doi.org/10.1186/s12911-026-03353-zHOS is common and clinically distinct, yet many sepsis pathways and predictive models implicitly assume one “sepsis phenotype.”This paper combines clinical comparisons plus ML-based variable-importance to argue for timing-aware detection and management.Retrospective cohort (adults ≥18) hospitalized with sepsis, Jan 2019–Aug 2023.Sepsis identified by linking two sources: institutional Adult Sepsis Events (ASE) surveillance definition + Vizient ICD-10 sepsis dataset.COS vs HOS based on onset timing: COS on/before hospital day 2; HOS on/after hospital day 3 (timing defined by dataset rules).In-hospital mortality, hospital length of stay, ICU days, vasopressor use, mechanical ventilation.Mortality: HOS 38.2% vs COS 28.5%Hospital LOS (median): HOS 24 vs COS 11 daysICU days (median): HOS 7 vs COS 2 daysAntibiotics: COS more likely to receive antibiotics within 24h of sepsis onset (81.7% vs 42.9%); HOS more likely to have been on antibiotics >24h before meeting sepsis criteria (49.3% vs 16.6%).ML insight: COS/HOS status was an important predictor for mortality and especially hospital LOS (ranked 3rd for LOS).HOS may show less dramatic “classic” physiology (e.g., less pronounced abnormalities / lower lactate) yet worse outcomes—so inpatient detection thresholds may need recalibration after hospital day 2.Consider timing-aware decision support: models and screening protocols should treat COS and HOS differently to reduce missed cases and delays.Single-center; dataset linkage may bias retained cases; some clinical confounders unavailable (e.g., infection source, antibiotic appropriateness, full SOFA).Tags: Sepsis, Hospital-Onset Sepsis, Community-Onset Sepsis, Critical Care, ICU, Inpatient Medicine, Clinical Informatics, Machine Learning in Medicine, Random Forest, Early Warning Systems, Antibiotic Timing, Quality Improvement, Patient Safety, Outcomes Research, Evidence-Based Medicine