Hao-Min Lan , Chin-Chieh Wu , Su-Hsun Liu , Chih-Huang Li , Yu-Kang Tu , Kuan-Fu Chen
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Eligible studies assessed the diagnostic accuracies of biomarkers, the quick Sequential Organ Failure Assessment (qSOFA) score, or Systemic Inflammatory Response Syndrome (SIRS) criteria in detecting sepsis. Bivariate hierarchical random effects arm-based beta-binomial models were used for quantitative synthesis (PROSPERO Registration Number: CRD42018086545).</div></div><div><h3>Results</h3><div>We included 78 studies representing 34,234 patients and compared qSOFA score, SIRS criteria alongside seven of the most studied biomarkers: procalcitonin, C-reactive protein (CRP), interleukin-6 (IL-6), presepsin (cluster of differentiation 14 subtypes), CD64, soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), and lipopolysaccharide-binding protein (LBP). CD64 demonstrated the highest superiority index, followed by sTREM-1 and presepsin (diagnostic odds ratio: 20.17 vs 18.73 and 10.04, 95 % credible interval [CrI]: 8.39–38.61 vs 1.31–83.98 and 6.71–14.24; quality of evidence: moderate vs low and low). Multivariable meta-regression analysis identified significant sources of heterogeneity, including study design, proportion of sepsis, sample size, and the risk of bias (patient selection).</div></div><div><h3>Conclusions</h3><div>The best diagnostic accuracy for sepsis was shown by CD64, with a moderate quality of evidence. Compared to CD64, sTREM-1 and presepsin provided suboptimal and low evidence. These biomarkers were more effective at identifying updated sepsis than clinical scores. We recommend re-considering the addition of biomarkers in screening for sepsis or sepsis-related conditions, as this could lead to more accurate and timely decisions for future clinical interventions.</div></div>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"88 ","pages":"Article 155087"},"PeriodicalIF":3.2000,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of the diagnostic accuracies of various biomarkers and scoring systems for sepsis: A systematic review and Bayesian diagnostic test accuracy network meta-analysis\",\"authors\":\"Hao-Min Lan , Chin-Chieh Wu , Su-Hsun Liu , Chih-Huang Li , Yu-Kang Tu , Kuan-Fu Chen\",\"doi\":\"10.1016/j.jcrc.2025.155087\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><div>Sepsis affects approximately 50 million people worldwide, resulting in 11 million deaths annually. Conflicting results and insufficient evidence comparing performance biomarkers exist. The study aimed to comprehensively compare available biomarkers and clinical scores for detecting sepsis since its redefinition in 2016 with this systematic review and Bayesian diagnostic test accuracy network meta-analysis.</div></div><div><h3>Materials and methods</h3><div>We conducted searches in the PubMed, EMBASE, and Scopus databases between January 2016 and December 2023. Eligible studies assessed the diagnostic accuracies of biomarkers, the quick Sequential Organ Failure Assessment (qSOFA) score, or Systemic Inflammatory Response Syndrome (SIRS) criteria in detecting sepsis. Bivariate hierarchical random effects arm-based beta-binomial models were used for quantitative synthesis (PROSPERO Registration Number: CRD42018086545).</div></div><div><h3>Results</h3><div>We included 78 studies representing 34,234 patients and compared qSOFA score, SIRS criteria alongside seven of the most studied biomarkers: procalcitonin, C-reactive protein (CRP), interleukin-6 (IL-6), presepsin (cluster of differentiation 14 subtypes), CD64, soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), and lipopolysaccharide-binding protein (LBP). CD64 demonstrated the highest superiority index, followed by sTREM-1 and presepsin (diagnostic odds ratio: 20.17 vs 18.73 and 10.04, 95 % credible interval [CrI]: 8.39–38.61 vs 1.31–83.98 and 6.71–14.24; quality of evidence: moderate vs low and low). Multivariable meta-regression analysis identified significant sources of heterogeneity, including study design, proportion of sepsis, sample size, and the risk of bias (patient selection).</div></div><div><h3>Conclusions</h3><div>The best diagnostic accuracy for sepsis was shown by CD64, with a moderate quality of evidence. Compared to CD64, sTREM-1 and presepsin provided suboptimal and low evidence. These biomarkers were more effective at identifying updated sepsis than clinical scores. 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引用次数: 0
摘要
目的脓毒症影响全世界约5000万人,每年造成1100万人死亡。存在相互矛盾的结果和比较性能生物标志物的证据不足。本研究旨在通过系统评价和贝叶斯诊断测试准确性网络荟萃分析,全面比较自2016年脓毒症重新定义以来可用的生物标志物和临床评分。材料与方法我们于2016年1月至2023年12月在PubMed、EMBASE和Scopus数据库中进行了检索。符合条件的研究评估了生物标志物、快速顺序器官衰竭评估(qSOFA)评分或系统性炎症反应综合征(SIRS)标准在检测败血症中的诊断准确性。定量合成采用基于二元分层随机效应臂的β -二项模型(PROSPERO注册号:CRD42018086545)。结果:我们纳入了78项研究,代表34,234例患者,并比较了qSOFA评分、SIRS标准以及研究最多的7种生物标志物:降钙素原、c反应蛋白(CRP)、白细胞介素-6 (IL-6)、presepsin(14亚型的分化聚类)、CD64、髓细胞表达的可溶性触发受体-1 (sTREM-1)和脂多糖结合蛋白(LBP)。CD64表现出最高的优势指数,其次是sTREM-1和presepsin(诊断优势比:20.17 vs 18.73和10.04,95%可信区间[CrI]: 8.39 ~ 38.61 vs 1.31 ~ 83.98和6.71 ~ 14.24;证据质量:中等vs低和低)。多变量荟萃回归分析确定了重要的异质性来源,包括研究设计、败血症比例、样本量和偏倚风险(患者选择)。结论CD64对脓毒症的诊断准确率最高,证据质量中等。与CD64相比,sTREM-1和presepsin提供了次优和低证据。这些生物标志物在识别更新的败血症方面比临床评分更有效。我们建议重新考虑在败血症或败血症相关疾病的筛查中添加生物标志物,因为这可以为未来的临床干预提供更准确和及时的决策。
Comparison of the diagnostic accuracies of various biomarkers and scoring systems for sepsis: A systematic review and Bayesian diagnostic test accuracy network meta-analysis
Purpose
Sepsis affects approximately 50 million people worldwide, resulting in 11 million deaths annually. Conflicting results and insufficient evidence comparing performance biomarkers exist. The study aimed to comprehensively compare available biomarkers and clinical scores for detecting sepsis since its redefinition in 2016 with this systematic review and Bayesian diagnostic test accuracy network meta-analysis.
Materials and methods
We conducted searches in the PubMed, EMBASE, and Scopus databases between January 2016 and December 2023. Eligible studies assessed the diagnostic accuracies of biomarkers, the quick Sequential Organ Failure Assessment (qSOFA) score, or Systemic Inflammatory Response Syndrome (SIRS) criteria in detecting sepsis. Bivariate hierarchical random effects arm-based beta-binomial models were used for quantitative synthesis (PROSPERO Registration Number: CRD42018086545).
Results
We included 78 studies representing 34,234 patients and compared qSOFA score, SIRS criteria alongside seven of the most studied biomarkers: procalcitonin, C-reactive protein (CRP), interleukin-6 (IL-6), presepsin (cluster of differentiation 14 subtypes), CD64, soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), and lipopolysaccharide-binding protein (LBP). CD64 demonstrated the highest superiority index, followed by sTREM-1 and presepsin (diagnostic odds ratio: 20.17 vs 18.73 and 10.04, 95 % credible interval [CrI]: 8.39–38.61 vs 1.31–83.98 and 6.71–14.24; quality of evidence: moderate vs low and low). Multivariable meta-regression analysis identified significant sources of heterogeneity, including study design, proportion of sepsis, sample size, and the risk of bias (patient selection).
Conclusions
The best diagnostic accuracy for sepsis was shown by CD64, with a moderate quality of evidence. Compared to CD64, sTREM-1 and presepsin provided suboptimal and low evidence. These biomarkers were more effective at identifying updated sepsis than clinical scores. We recommend re-considering the addition of biomarkers in screening for sepsis or sepsis-related conditions, as this could lead to more accurate and timely decisions for future clinical interventions.
期刊介绍:
The Journal of Critical Care, the official publication of the World Federation of Societies of Intensive and Critical Care Medicine (WFSICCM), is a leading international, peer-reviewed journal providing original research, review articles, tutorials, and invited articles for physicians and allied health professionals involved in treating the critically ill. The Journal aims to improve patient care by furthering understanding of health systems research and its integration into clinical practice.
The Journal will include articles which discuss:
All aspects of health services research in critical care
System based practice in anesthesiology, perioperative and critical care medicine
The interface between anesthesiology, critical care medicine and pain
Integrating intraoperative management in preparation for postoperative critical care management and recovery
Optimizing patient management, i.e., exploring the interface between evidence-based principles or clinical insight into management and care of complex patients
The team approach in the OR and ICU
System-based research
Medical ethics
Technology in medicine
Seminars discussing current, state of the art, and sometimes controversial topics in anesthesiology, critical care medicine, and professional education
Residency Education.