Literature DB >> 33883455

Gene Expression-Based Diagnosis of Infections in Critically Ill Patients-Prospective Validation of the SepsisMetaScore in a Longitudinal Severe Trauma Cohort.

Simone Thair1, Caspar Mewes2,3, José Hinz3, Ingo Bergmann2, Benedikt Büttner2, Stephan Sehmisch4, Konrad Meissner2, Michael Quintel2, Timothy E Sweeney1,5, Purvesh Khatri1,5, Ashham Mansur2,6.   

Abstract

OBJECTIVES: Early diagnosis of infections is pivotal in critically ill patients. Innovative gene expression-based approaches promise to deliver precise, fast, and clinically practicable diagnostic tools to bedside. This study aimed to validate the SepsisMetaScore, an 11-gene signature previously reported by our study group, in a representative longitudinal cohort of trauma patients.
DESIGN: Prospective observational cohort study.
SETTING: Surgical ICUs of the University Medical Center Goettingen, Germany. PATIENTS: Critically ill patients with severe traumatic injuries.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Paired box gene (PAXgene) RNA blood tubes were drawn at predefined time points over the course of disease. The performance of the SepsisMetaScore was tested using targeted polymerase chain reaction and compared with Procalcitonin using area under the receiver operating characteristics analyses. The SepsisMetaScore showed significant differences between infected and noninfected patients (n = 52). It was able to accurately discriminate infectious from noninfectious acute inflammation with an area under the receiver operating characteristics of 0.92 (95% CI, 0.85-0.99) and significantly outperformed Procalcitonin (area under the receiver operating characteristics curve = 0.53; 95% CI, 0.42-0.64) early in the course of infection (p = 0.014).
CONCLUSIONS: We demonstrated the clinical utility for diagnosis of infections with higher accuracy using the SepsisMetaScore compared with Procalcitonin in a prospective cohort of severe trauma patients. Future studies should assess whether the SepsisMetaScore may substantially improve clinical practice by accurate differentiation of infections from sterile inflammation and identification of patients at risk for sepsis. Our results support further investigation of the SepsisMetaScore for the development of tailored precision treatment of critically ill patients.
Copyright © 2021 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.

Entities:  

Year:  2021        PMID: 33883455     DOI: 10.1097/CCM.0000000000005027

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  3 in total

1.  A robust gene expression signature for NASH in liver expression data.

Authors:  Yehudit Hasin-Brumshtein; Suraj Sakaram; Purvesh Khatri; Yudong D He; Timothy E Sweeney
Journal:  Sci Rep       Date:  2022-02-16       Impact factor: 4.379

Review 2.  Evolving Applications of Artificial Intelligence and Machine Learning in Infectious Diseases Testing.

Authors:  Nam K Tran; Samer Albahra; Larissa May; Sarah Waldman; Scott Crabtree; Scott Bainbridge; Hooman Rashidi
Journal:  Clin Chem       Date:  2021-12-30       Impact factor: 12.167

Review 3.  Pediatric sepsis biomarkers for prognostic and predictive enrichment.

Authors:  Hector R Wong
Journal:  Pediatr Res       Date:  2021-06-14       Impact factor: 3.953

  3 in total

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