Daily Sepsis Research Analysis

IMPORTANCE: Presenting signs and symptoms affect the care of patients with possible sepsis. However, signs and symptoms are not incorporated into most large observational studies because they are difficult to extract from clinical notes at scale. OBJECTIVE: To assess the use of large language models (LLMs) to extract presenting signs and symptoms from admission notes and characterize their associations with infectious diagnoses, multidrug-resistant infections, and mortality. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study obtained data from 5 Massachusetts hospitals within 1 health care system between June 1, 2015, and August 1, 2022. Participants were hospitalized adult patients with possible infection (determined by blood culture drawn and intravenous antibiotics administered within 24 hours of arrival). An LLM (LLaMA 3 8B; Meta) was used to extract up to 10 presenting signs and symptoms from each patient's history-and-physical admission notes. LLM-generated labels were validated by blinded review of 303 random admission notes. Data analyses were performed from July 2023 to August 2025. EXPOSURES: Thirty most common signs and symptoms were retained as exposures, and unsupervised clustering was used to create syndromes, which were compared with infection sources derived from the International Statistical Classification of Diseases, Tenth Revision, Clinical Modification discharge codes. MAIN OUTCOMES AND MEASURES: Outcomes included positive cultures for methicillin-resistant Staphylococcus aureus (MRSA), positive cultures for multidrug-resistant gram-negative (MDRGN) organisms, and in-hospital mortality. Multivariable logistic regression was used to adjust for demographics, comorbidities, physiologic markers of severity of illness, and time to antibiotics. RESULTS: Among the 104 248 patients (median [IQR] age, 66 [52-78] years; 54 137 males [51.9%]) included, 23 619 (22.7%) had sepsis without shock, 25 990 (24.9%) had septic shock, and 94 913 (91.0%) had 1 or more admission note within 24 hours. The LLM labeled the notes of 93 674 of 94 913 patients (98.7%). On manual validation, LLM labels had an accuracy of 99.3% (95% CI, 99.2%-99.3%), balanced accuracy of 84.6% (95% CI, 83.5%-85.8%), positive predictive value of 68.4% (95% CI, 66.0%-70.7%), sensitivity of 69.7% (95% CI, 67.3%-72.0%), and specificity of 99.6% (95% CI, 99.6%-99.6%) compared with the physician medical record reviewer. The 30 most common signs and symptoms were clustered into syndromes that correlated with infection sources. Presence of skin and soft tissue symptoms (adjusted odds ratio [AOR], 1.73; 95% CI, 1.49-2.00) and absence of gastrointestinal (AOR, 0.63; 95% CI, 0.54-0.73) or urinary tract symptoms (AOR, 0.34; 95% CI, 0.22-0.50) were associated with MRSA culture positivity; inverse associations were seen for MDRGN organisms. Cardiopulmonary symptoms were associated with increased mortality (AOR, 1.30; 95% CI, 1.17-1.45). CONCLUSIONS AND RELEVANCE: This cohort study found that an LLM accurately extracted presenting signs and symptoms from admission notes that clustered into syndromes differentially correlated with infection sources, multidrug-resistant infections, and mortality. Further research is warranted to evaluate the value of large-scale sign-and-symptom data in models of antibiotic choice, effectiveness, and outcomes in patients with possible sepsis.

BACKGROUND: Multiple organ dysfunction syndrome (MODS) remains a major cause of morbidity and mortality in pediatric intensive care units (PICUs), particularly when triggered by SARS-CoV-2 or bacterial sepsis. This study aimed to investigate the association between inflammatory and oxidative stress biomarkers and the development and outcome of MODS in critically ill children with confirmed SARS-CoV-2 or bacterial infections. METHODS: In this prospective, single-center cohort study (May 2020-December 2024), 62 pediatric patients (29 days to <18 years) were stratified into three groups: SARS-CoV-2 without MODS (n = 22), SARS-CoV-2 with MODS (n = 20), and bacterial MODS (n = 20). Circulating cytokines (IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γ, IL-17A) and oxidative stress markers (GSH, TBARS, TEAC) were quantified at PICU admission and on day 5. Associations with organ dysfunction and 28-day mortality were assessed using non-parametric statistical analyses and Kaplan-Meier survival estimates. RESULTS: MODS groups exhibited on day 1 sustained elevations in TNF-α, IFN-γ, and IL-17A-most pronounced in bacterial MODS (Group 3; p < 0.0001). IFN-γ was notably increased in viral MODS (Group 2). Group 3 also showed marked elevations in IL-6, IL-2, and IL-10 (p < 0.0001). By day 5, both MODS groups demonstrated significant reduced GSH and TEAC and elevated TBARS, the most severe in Group 3. In contrast, Group 1 exhibited stable cytokine profiles and preserved antioxidant status throughout. Non-survivors showed persistently elevated IL-6, TNF-α, IFN-γ, and IL-17A, coupled with sustained depletion of GSH and TEAC, and increased TBARS levels (all p < 0.0001). IL-6 and IFN-γ were particularly elevated in non-survivors with bacterial and viral MODS, respectively. Biomarker trajectories diverged between survivors and non-survivors by day 5, with failure to normalize immune-redox profiles associated with mortality. Accessible indices such as NLR, CAR, and VIS correlated with biomarker levels and disease severity. Kaplan-Meier analysis confirmed reduced survival in MODS groups (p = 0.0005). CONCLUSIONS: A distinct cytokine and oxidative stress signature-marked by early and sustained elevations in IL-6, TNF-α, IFN-γ, IL-17A, and TBARS, and depletion of GSH and TEAC-is associated with mortality in pediatric MODS. Bacterial MODS was distinguished by the most severe immune-redox imbalance. Integrated immune-redox profiling offers prognostic value and may inform precision-targeted interventions, particularly in resource-limited settings.

OBJECTIVE: Rapid identification of high-risk and low-risk patients presenting to the emergency department (ED) influences clinical management and can help optimise patient outcomes as well as resource allocation. This study aims to externally validate the Risk Stratification in the Emergency Department in Acutely Ill Older Patients (RISE UP) score in adult patients in the ED with suspected infection. Furthermore, generalisability was assessed by comparing the discriminatory ability of the RISE UP with the quick Sequential Organ Failure Assessment (qSOFA) as well as the Modified Early Warning Score (MEWS) and National Early Warning Score (NEWS). DESIGN: Retrospective cohort study. SETTING: Single-centre study in the ED of a tertiary, university-affiliated hospital. PARTICIPANTS: Adult patients with suspected infection presenting at the ED for internal medicine from 2016 to 2022. OUTCOMES: The primary outcome was all-cause 30-day mortality. Secondary outcomes were all-cause 14-day mortality, 7-day mortality and intensive care unit (ICU) admission. METHODS: Prognostic performance was evaluated using discrimination (area under the receiver operating characteristic curve (AUC)) and a calibration plot. RESULTS: Of the included 5038 ED visits, there was a 30-day mortality of 7.1%. Discrimination of RISE UP for 30-day mortality was good (AUC 0.809; 95% CI 0.786 to 0.832) and significantly higher than that for the other risk scores: qSOFA (AUC 0.675; 95% CI 0.644 to 0.707), MEWS (AUC 0.688; 95% CI 0.658 to 0.718) and NEWS (AUC 0.725; 95% CI 0.696 to 0.754) (p<0.001). For 14-day and 7-day mortality, RISE UP had the highest AUC, but NEWS performed best for ICU admission. The RISE UP score was well calibrated and had significantly better discriminatory ability in older patients aged ≥65 years (AUC 0.772; 95% CI 0.738 to 0.806; p<0.001) and patients with sepsis (AUC 0.746; 95% CI 0.695 to 0.798; p<0.05) compared with the other scores. Low-risk patients with a RISE UP score of <5% yielded a negative predictive value of 97.7% (95% CI 97.2 to 98.1) and a sensitivity of 79.3% (95% CI 74.7 to 83.4). CONCLUSIONS: The RISE UP score outperformed the qSOFA, MEWS and NEWS in predicting 30-day mortality. It is generalisable to an adult infection-specific cohort and may facilitate distinction between high-risk and low-risk patients in the ED, particularly to rule out poor outcomes.