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Background: The quick sequential organ failure assessment (qSOFA) score is suggested to use for screening patients with a high risk of clinical deterioration in the general wards, which could simply be regarded as a general early warning score. However, comparison of unselected admissions to highlight the benefits of introducing qSOFA in hospitals already using Modified Early Warning Score (MEWS) remains unclear. We sought to compare qSOFA with MEWS for predicting clinical deterioration in general ward patients regardless of suspected infection.
Methods: The predictive performance of qSOFA and MEWS for in-hospital cardiac arrest (IHCA) or unexpected intensive care unit (ICU) transfer was compared with the areas under the receiver operating characteristic curve (AUC) analysis using the databases of vital signs collected from consecutive hospitalized adult patients over 12 months in five participating hospitals in Korea.
Results: Of 173,057 hospitalized patients included for analysis, 668 (0.39%) experienced the composite outcome. The discrimination for the composite outcome for MEWS (AUC, 0.777; 95% confidence interval [CI], 0.770-0.781) was higher than that for qSOFA (AUC, 0.684; 95% CI, 0.676-0.686; < 0.001). In addition, MEWS was better for prediction of IHCA (AUC, 0.792; 95% CI, 0.781-0.795 vs. AUC, 0.640; 95% CI, 0.625-0.645; < 0.001) and unexpected ICU transfer (AUC, 0.767; 95% CI, 0.760-0.773 vs. AUC, 0.716; 95% CI, 0.707-0.718; < 0.001) than qSOFA. Using the MEWS at a cutoff of ≥ 5 would correctly reclassify 3.7% of patients from qSOFA score ≥ 2. Most patients met MEWS ≥ 5 criteria 13 hours before the composite outcome compared with 11 hours for qSOFA score ≥ 2.
Conclusion: MEWS is more accurate that qSOFA score for predicting IHCA or unexpected ICU transfer in patients outside the ICU. Our study suggests that qSOFA should not replace MEWS for identifying patients in the general wards at risk of poor outcome.
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http://dx.doi.org/10.3346/jkms.2022.37.e122 | DOI Listing |
Ulus Travma Acil Cerrahi Derg
September 2025
Department of Emergency Medicine, Ankara Etlik City Hospital, Ankara-Türkiye.
Background: The quick Sequential Organ Failure Assessment (qSOFA) score is widely used for bedside risk stratification in sepsis patients. However, its limited sensitivity may hinder early identification. The lactate-enhanced qSOFA (LqSOFA), which incorporates serum lactate levels into the qSOFA score, may improve prognostic accuracy.
View Article and Find Full Text PDFAm J Emerg Med
August 2025
Department of Emergency Medicine, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, United States of America. Electronic address:
Background: Chemotherapy-associated febrile neutropenia (FN) is a common, life-threatening oncologic emergency. Scores to identify low-risk patients eligible for outpatient treatment, like the Multinational Association for Supportive Care in Cancer (MASCC), Clinical Index of Stable Febrile Neutropenia (CISNE), and quick Sepsis Related Organ Failure Assessment (qSOFA) scores, are infrequently used. New tools are needed to inform risk and enable appropriate management.
View Article and Find Full Text PDFBiomol Biomed
August 2025
Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Key Laboratory of Children's Vital Organ Development and Disease of Chon
Sepsis remains a leading global health challenge, with delayed recognition and limited diagnostic accuracy of current tools contributing to high morbidity and mortality. Conventional clinical scores (SOFA/qSOFA), standard biomarkers (CRP, PCT), and blood cultures suffer from delayed responsiveness, insufficient specificity, or slow turnaround, underscoring the urgent need for more reliable early diagnostic strategies. Presepsin, a soluble CD14 subtype generated during pathogen recognition by innate immune cells, has emerged as a promising biomarker with potential to reflect infection status earlier and more specifically than traditional markers.
View Article and Find Full Text PDFEClinicalMedicine
September 2025
Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.
Background: How to identify suspected infection for sepsis surveillance purposes remains a well-recognised challenge. This study aimed to operationalise suspected infection for sepsis surveillance by developing an interpretable machine learning (ML) model for retrospective identification of patients with sepsis.
Methods: This multicentre cohort and machine learning study was conducted in two Dutch tertiary care hospitals.
Rev Bras Enferm
August 2025
Universidade Estadual de Londrina. Londrina, Paraná, Brazil.
Objectives: to evaluate the SOFA score, qSOFA, SIRS criteria, and risk factors for hospital mortality in burn victims with suspected infection admitted to an intensive care unit.
Methods: a retrospective longitudinal study conducted at a public hospital between January 2017 and January 2020. We analyzed sepsis diagnostic scores at two time points: hospital admission and date of infection.