Assessment of S100A8/A9 and resistin as predictive biomarkers for mortality in critically ill patients with sepsis.

IF 4.6 2区 医学 Q2 IMMUNOLOGY
Frontiers in Cellular and Infection Microbiology Pub Date : 2025-06-03 eCollection Date: 2025-01-01 DOI:10.3389/fcimb.2025.1555307
Jing Chen, Zhengquan Liu, Fan Zhou, Ye Sun, Zhenyou Jiang, Pingsen Zhao
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引用次数: 0

Abstract

Introduction: Sepsis is associated with high mortality. Early intervention is crucial to reducing sepsis-related mortality. This study aims to assess the clinical potential of S100A8/A9 and resistin as novel biomarkers for predicting mortality risk in sepsis patients.

Method: Serum samples were collected and analyzed from 141 adult sepsis patients (discovery cohort), 43 non-sepsis intensive care units (ICU) patients, 15 healthy volunteers, and 55 sepsis patients along with 17 non-sepsis ICU patients (validation cohort). The 28-day mortality and sequential organ failure assessment (SOFA) scores of the participants were compared. Additionally, the predictive ability of S100A8/A9 and resistin for sepsis mortality was evaluated using the area under the receiver operating characteristic curve at ICU admission.

Results: The concentrations of S100A8/A9 and resistin in sepsis patients were noticeably increased relative to non-sepsis patients and healthy controls. Serum S100A8/A9 concentrations in surviving sepsis patients were significantly higher than in non-surviving patients. On the day of admission, serum resistin concentrations in Gram-negative (G-) sepsis patients were considerably elevated relative to Gram-positive (G+) infected sepsis patients. Among sepsis patients admitted to the ICU, the AUC for S100A8/A9 in predicting 28-day mortality was 0.617 (P = 0.032; 95% confidence bounds 0.513-0.721), and for SOFA was 0.750 (P < 0.0001; 95% confidence bounds 0.660-0.840). Sepsis patients with high serum S100A8/A9 concentrations (≥ 377.53 ng/mL) had a higher survival rate relative to those with low concentrations (<377.53 ng/mL). In the validation cohort, the AUC for S100A8/A9 and 28-day mortality was 0.708 (P = 0.032; 95% confidence bounds 0.563-0.854), and for SOFA was 0.698 (P = 0.025; 95% confidence bounds 0.550-0.845). Additionally, sepsis patients with high serum S100A8/A9 concentrations (≥ 377.53 ng/mL) also had a higher survival rate relative to those with lower concentrations (< 377.53 ng/mL). Furthermore, serum resistin levels in patients with a normal phenotype and mixed phenotype with hyperinflammation were predictive of mortality, with an AUC of 0.810 (P = 0.034; 95% confidence bounds 0.605-1.00) and 0.708 (P = 0.015; 95% confidence bounds 0.571-0.846). In patients with a normal sepsis phenotype, those with high serum resistin levels (≥ 63.695 ng/mL) had a lower survival rate compared to those with low resistin levels (< 63.695 ng/mL). In contrast, in patients with a mixed phenotype with hyperinflammation, those with high serum resistin levels (≥ 107.64 ng/mL) had a higher survival rate compared to those with lower resistin levels (< 107.64 ng/mL).

Discussion: Sepsis, the leading cause of death in intensive care unit patients. Identifying reliable biomarkers is essential for improving both the diagnosis and treatment of sepsis. We found that serum S100A8/A9 concentration at ICU admission is a significant predictor of 28-day mortality risk in sepsis patients. Additionally, resistin levels at ICU admission play an important role in predicting 28-day mortality risk in patients with both normal and mixed phenotypes with hyperinflammation. These findings suggest that S100A8/A9 and resistin could serve as effective biomarkers. Moreover, these findings could guide early clinical decisions in the treatment of sepsis patients.

S100A8/A9和抵抗素作为脓毒症危重患者死亡率的预测性生物标志物的评估
败血症与高死亡率相关。早期干预对于降低败血症相关死亡率至关重要。本研究旨在评估S100A8/A9和抵抗素作为预测脓毒症患者死亡风险的新型生物标志物的临床潜力。方法:收集141例成年脓毒症患者(发现队列)、43例非脓毒症重症监护病房(ICU)患者、15名健康志愿者、55例脓毒症患者及17例非脓毒症重症监护病房患者(验证队列)的血清样本进行分析。比较参与者的28天死亡率和顺序器官衰竭评估(SOFA)评分。此外,采用ICU入院时患者工作特征曲线下面积评价S100A8/A9和抵抗素对脓毒症死亡率的预测能力。结果:脓毒症患者血清S100A8/A9和抵抗素浓度明显高于非脓毒症患者和健康对照组。存活脓毒症患者血清S100A8/A9浓度显著高于未存活脓毒症患者。入院当天,革兰氏阴性(G-)脓毒症患者血清抵抗素浓度明显高于革兰氏阳性(G+)感染脓毒症患者。在ICU住院的脓毒症患者中,S100A8/A9预测28天死亡率的AUC为0.617 (P = 0.032;95%置信区间为0.513-0.721),SOFA为0.750 (P < 0.0001;95%置信区间0.66 -0.840)。血清S100A8/A9浓度高(≥377.53 ng/mL)的脓毒症患者生存率高于浓度低的脓毒症患者(P = 0.032;95%置信区间0.563-0.854),SOFA为0.698 (P = 0.025;95%置信区间0.550-0.845)。此外,血清S100A8/A9浓度较高(≥377.53 ng/mL)的脓毒症患者生存率也高于血清浓度较低(< 377.53 ng/mL)的脓毒症患者。此外,正常表型和混合表型伴高炎症患者的血清抵抗素水平可预测死亡率,AUC为0.810 (P = 0.034;95%置信区间为0.605-1.00)和0.708 (P = 0.015;95%置信区间0.571-0.846)。在正常脓毒症表型的患者中,血清抵抗素水平高(≥63.695 ng/mL)的患者生存率低于血清抵抗素水平低(< 63.695 ng/mL)的患者。相比之下,在伴有高炎症的混合表型患者中,血清抵抗素水平高(≥107.64 ng/mL)的患者比血清抵抗素水平低(< 107.64 ng/mL)的患者生存率更高。讨论:脓毒症是重症监护病房患者死亡的主要原因。确定可靠的生物标志物对于改善败血症的诊断和治疗至关重要。我们发现ICU入院时血清S100A8/A9浓度是脓毒症患者28天死亡风险的重要预测因子。此外,ICU入院时的抵抗素水平在预测正常表型和混合型高炎症患者28天死亡风险方面发挥重要作用。这些发现提示S100A8/A9和抵抗素可以作为有效的生物标志物。此外,这些发现可以指导脓毒症患者治疗的早期临床决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.90
自引率
7.00%
发文量
1817
审稿时长
14 weeks
期刊介绍: Frontiers in Cellular and Infection Microbiology is a leading specialty journal, publishing rigorously peer-reviewed research across all pathogenic microorganisms and their interaction with their hosts. Chief Editor Yousef Abu Kwaik, University of Louisville is supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide. Frontiers in Cellular and Infection Microbiology includes research on bacteria, fungi, parasites, viruses, endosymbionts, prions and all microbial pathogens as well as the microbiota and its effect on health and disease in various hosts. The research approaches include molecular microbiology, cellular microbiology, gene regulation, proteomics, signal transduction, pathogenic evolution, genomics, structural biology, and virulence factors as well as model hosts. Areas of research to counteract infectious agents by the host include the host innate and adaptive immune responses as well as metabolic restrictions to various pathogenic microorganisms, vaccine design and development against various pathogenic microorganisms, and the mechanisms of antibiotic resistance and its countermeasures.
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