Chemical-Clinical Analysis Laboratory, Department of Laboratory Medicine and Transfusion, San Donato Hospital, Arezzo, Italy.
Emergency Department, Azienda USL Toscana Sudest, Ospedale san Donato, Arezzo, Italy.
Clin Chim Acta. 2022 Sep 1;534:65-70. doi: 10.1016/j.cca.2022.07.007. Epub 2022 Jul 16.
The aim of this study was to evaluate the diagnostic accuracy of sepsis markers and to develop a multiparametric score, using demographic and clinical variables as well as laboratory parameters to predict sepsis in patients admitted in the ED with suspected symptoms.
Patients with clinical presentation of suspected sepsis were enrolled in the ED of San Donato Hospital in Arezzo between September 2019 and May 2020. Anagraphic, anamnestic, clinical and laboratory data were collected for all subjects. PCT, MDW, WBC, MPV and BT were utilised to formulate FANS score.
The AUC of the FANS score, PCT, MDW and CRP was 0.87, 0.80, 0.77 and 0.71, respectively, when used to predict sepsis in all 308 subjects. Instead, the AUC of the FANS (Fighting Action To Neutralize Sepsis) score, PCT, MDW and CRP was 0.93, 0.84, 0.83 and 0.77, respectively, when used to predict sepsis excluding subjects with infection (clinically classified as the Infections group).
The results obtained with PCT, PCR and MDW confirm the results of these markers for the identification of sepsis obtained from other studies. The multiparametric approach, obtained from the statistical study of the parameters using binary logistic regression, identified those PCT, WBC, MPV, BT and MDW as the most significant and effective clinical classifiers for diagnosing sepsis.
本研究旨在评估脓毒症标志物的诊断准确性,并开发一种多参数评分,使用人口统计学和临床变量以及实验室参数来预测急诊科疑似症状患者的脓毒症。
2019 年 9 月至 2020 年 5 月,在阿雷佐的圣多纳托医院急诊科招募了有疑似脓毒症临床表现的患者。所有患者均采集了人口统计学、病史、临床和实验室数据。使用降钙素原(PCT)、血小板分布宽度(MDW)、白细胞计数(WBC)、血小板平均体积(MPV)和凝血酶时间(BT)来制定 FANS 评分。
在 308 例所有患者中,FANS 评分、PCT、MDW 和 CRP 预测脓毒症的 AUC 分别为 0.87、0.80、0.77 和 0.71。而 FANS(打击行动中和脓毒症)评分、PCT、MDW 和 CRP 预测无感染患者(临床分类为感染组)的 AUC 分别为 0.93、0.84、0.83 和 0.77。
PCT、PCR 和 MDW 的结果证实了这些标志物在其他研究中用于识别脓毒症的结果。多参数方法是通过使用二元逻辑回归对参数进行统计学研究得出的,确定了 PCT、WBC、MPV、BT 和 MDW 是诊断脓毒症最显著和有效的临床分类器。