98%
921
2 minutes
20
Objectives: Early identification of sepsis is critical to improving patient outcomes. Impact of the new sepsis definition (Sepsis-3) on timing of recognition in the emergency department has not been evaluated. Our study objective was to compare time to meeting systemic inflammatory response syndrome (Sepsis-2) criteria, Sequential Organ Failure Assessment (Sepsis-3) criteria, and quick Sequential Organ Failure Assessment criteria using electronic health record data.
Design: Retrospective, observational study.
Setting: The emergency department at the University of California, San Francisco.
Patients: Emergency department encounters between June 2012 and December 2016 for patients greater than or equal to 18 years old with blood cultures ordered, IV antibiotic receipt, and identification with sepsis via systemic inflammatory response syndrome or Sequential Organ Failure Assessment within 72 hours of emergency department presentation.
Interventions: None.
Measurements And Main Results: We analyzed timestamped electronic health record data from 16,612 encounters identified as sepsis by greater than or equal to 2 systemic inflammatory response syndrome criteria or a Sequential Organ Failure Assessment score greater than or equal to 2. The primary outcome was time from emergency department presentation to meeting greater than or equal to 2 systemic inflammatory response syndrome criteria, Sequential Organ Failure Assessment greater than or equal to 2, and/or greater than or equal to 2 quick Sequential Organ Failure Assessment criteria. There were 9,087 patients (54.7%) that met systemic inflammatory response syndrome-first a median of 26 minutes post-emergency department presentation (interquartile range, 0-109 min), with 83.1% meeting Sequential Organ Failure Assessment criteria a median of 118 minutes later (interquartile range, 44-401 min). There were 7,037 patients (42.3%) that met Sequential Organ Failure Assessment-first, a median of 113 minutes post-emergency department presentation (interquartile range, 60-251 min). Quick Sequential Organ Failure Assessment was met in 46.4% of patients a median of 351 minutes post-emergency department presentation (interquartile range, 67-1,165 min). Adjusted odds of in-hospital mortality were 39% greater in patients who met systemic inflammatory response syndrome-first compared with those who met Sequential Organ Failure Assessment-first (odds ratio, 1.39; 95% CI, 1.20-1.61).
Conclusions: Systemic inflammatory response syndrome and Sequential Organ Failure Assessment initially identified distinct populations. Using systemic inflammatory response syndrome resulted in earlier electronic health record sepsis identification in greater than 50% of patients. Using Sequential Organ Failure Assessment alone may delay identification. Using systemic inflammatory response syndrome alone may lead to missed sepsis presenting as acute organ dysfunction. Thus, a combination of inflammatory (systemic inflammatory response syndrome) and organ dysfunction (Sequential Organ Failure Assessment) criteria may enhance timely electronic health record-based sepsis identification.
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http://dx.doi.org/10.1097/CCM.0000000000004132 | DOI Listing |
Acta Anaesthesiol Scand
October 2025
Centre for Anaesthesiological Research, Department of Anaesthesiology, Zealand University Hospital, Køge, Denmark.
Background: Multiple organ dysfunction syndrome (MODS) in critical illness involves dysregulated immune and inflammatory responses, endotheliopathy, and coagulation activation. We investigated how three types of endotheliopathy biomarkers relate to pro- and anti-inflammatory responses and clinical outcomes in intensive care unit (ICU) patients.
Methods: In this secondary, explorative analysis of a prospective single-centre cohort (n = 459), we assessed associations between endotheliopathy biomarkers (syndecan-1, soluble thrombomodulin (sTM), platelet endothelial cell adhesion molecule-1 (PECAM-1)) and inflammatory biomarkers (pro-inflammatory: IFN-ϒ, IL-1β, IL-2, IL-6, IL-8, IL-12p70, TNF-α; anti-inflammatory: IL-4, IL-10, IL-13) at ICU admission using linear regression.
J Int Med Res
September 2025
Intensive Care Department, King Abdulaziz Medical City, Ministry of National Guard-Health Affairs, Saudi Arabia.
ObjectivesTo assess the association of obesity with outcomes among patients with severe acute respiratory infection.MethodsThis is a retrospective cohort study of patients with severe acute respiratory infection admitted to the intensive care units in four referral hospitals in Saudi Arabia between September 2012 and June 2018. Patients were classified into two groups: overweight-obese patients (body mass index ≥25 kg/m) and normal-weight patients (body mass index between 18.
View Article and Find Full Text PDFOpen Access Emerg Med
September 2025
Department of Emergency Medicine and Critical Care, Center Hospital of the National Center for Global Health and Medicine, Tokyo, 162-8655, Japan.
Background: A simple screening tool is needed for resource-limited settings because rapid treatment is crucial in sepsis. We investigated whether a simplified score, the reverse shock index multiplied by the Glasgow Coma Scale score (rSIG), could replace the Modified Early Warning Score (MEWS) or the quick Sequential Organ Failure Assessment (qSOFA) for sepsis screening.
Methods: We used data from a Japanese multicenter prospective observational study.
Anesthesiol Res Pract
August 2025
Anesthesiology and Pain Medicine Department, Democritus University of Thrace, Alexandroupoli, Greece.
Nutritional screening is gaining recognition in perioperative medicine, as anesthesiologists need to assess patients' nutritional status to identify malnutrition risks. Poor nutritional status is associated with increased perioperative complications, including postoperative pain. Effective pain management is crucial to prevent acute pain from developing into chronic pain.
View Article and Find Full Text PDFCrit Care Res Pract
August 2025
Clinical Tuberculosis and Epidemiology Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Sepsis remains one of the leading causes of morbidity and mortality worldwide, particularly among critically ill patients in intensive care units (ICUs). Traditional diagnostic approaches, such as the Sequential Organ Failure Assessment (SOFA) and systemic inflammatory response syndrome (SIRS) criteria, often detect sepsis after significant organ dysfunction has occurred, limiting the potential for early intervention. In this study, we reviewed how artificial intelligence (AI)-driven methodologies, including machine learning (ML), deep learning (DL), and natural language processing (NLP), can aid physicians.
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