Using time-course as an essential factor to accurately predict sepsis-associated mortality among patients with suspected sepsis

Shih-Chieh Yen; Chin-Chieh Wu; Yi-Ju Tseng; Chih-Huang Li; Kuan-Fu Chen

doi:10.1016/j.bj.2023.100632

Using time-course as an essential factor to accurately predict sepsis-associated mortality among patients with suspected sepsis

Biomed J. 2023 Jul 17:100632. doi: 10.1016/j.bj.2023.100632. Online ahead of print.

Authors

Shih-Chieh Yen¹, Chin-Chieh Wu², Yi-Ju Tseng³, Chih-Huang Li⁴, Kuan-Fu Chen⁵

Affiliations

¹ Clinical Informatics and Medical Statistics Research Center, Chang Gung University, Taoyuan, Taiwan. Electronic address: yenj851230@gmail.com.
² Clinical Informatics and Medical Statistics Research Center, Chang Gung University, Taoyuan, Taiwan. Electronic address: wujinja@gmail.com.
³ Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan. Electronic address: yjtseng@nycu.edu.tw.
⁴ Department of Emergency Medicine, Chang Gung Memorial Hospital, Taipei, Taiwan. Electronic address: y17322@cgmh.org.tw.
⁵ Clinical Informatics and Medical Statistics Research Center, Chang Gung University, Taoyuan, Taiwan; Department of Emergency Medicine, Chang Gung Memorial Hospital, Keelung, Taiwan. Electronic address: drkfchen@gmail.com.

PMID: 37467969
DOI: 10.1016/j.bj.2023.100632

Abstract

Background: Biomarker dynamics in different time-courses might be the primary reason why a static measurement of a single biomarker cannot accurately predict sepsis outcomes. Therefore, we conducted this prospective hospital-based cohort study to simultaneously evaluate the performance of several conventional and novel biomarkers of sepsis in predicting sepsis-associated mortality on different days of illness among patients with suspected sepsis.

Methods: We evaluated the performance of 15 novel biomarkers including angiopoietin-2, pentraxin 3, sTREM-1, ICAM-1, VCAM-1, sCD14 and 163, E-selectin, P-selectin, TNF-alpha, interferon-gamma, CD64, IL-6, 8, and 10, along with few conventional markers for predicting sepsis-associated mortality. Patients were grouped into quartiles according to the number of days since symptom onset. Receiver operating characteristic curve (ROC) analysis was used to evaluate the biomarker performance.

Results: From 2014 to 2017, 1,483 patients were enrolled, of which 78% fulfilled the systemic inflammatory response syndrome criteria, 62% fulfilled the sepsis-3 criteria, 32% had septic shock, and 3.3% developed sepsis-associated mortality. IL-6, pentraxin 3, sCD163, and the blood gas profile demonstrated better performance in the early days of illness, both before and after adjusting for potential confounders (adjusted area under ROC curve [AUROC]:0.81-0.88). Notably, the Sequential Organ Failure Assessment (SOFA) score was relatively consistent throughout the course of illness (adjusted AUROC:0.70-0.91).

Conclusion: IL-6, pentraxin 3, sCD163, and the blood gas profile showed excellent predictive accuracy in the early days of illness. The SOFA score was consistently predictive of sepsis-associated mortality throughout the course of illness, with an acceptable performance.

Keywords: biomarkers; dynamic; mortality; prognosis; sepsis.