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简单评分系统在鉴别不明原因发热病例中细菌感染的效用。

Utility of a Simple Scoring System in Differentiating Bacterial Infections in Cases of Fever of Unknown Origin.

机构信息

Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China.

Key Laboratory of Clinical Pharmacology of Antibiotics, National Health and Family Planning Commission, Shanghai, China.

出版信息

Clin Infect Dis. 2020 Dec 23;71(Suppl 4):S409-S415. doi: 10.1093/cid/ciaa1520.

Abstract

BACKGROUND

Infectious disease is the leading cause of fever of unknown origin (FUO). Serum inflammatory markers historically used to diagnose bacterial infection have sufficient diagnostic sensitivity but low specificity. This study aimed to develop a simple scoring system for differentiating bacterial infections from other causes of early-stage FUO.

METHODS

This study included a retrospective cohort of patients presenting with FUO at the Huashan Hospital (January 2014 to June 2017). The diagnostic utility of serum inflammatory markers for bacterial infection was evaluated using the receiver operating characteristic (ROC) curve analysis. Relevant markers were subsequently measured prospectively in a separate cohort of FUO patients (December 2017 to May 2019). A scoring system was based on inflammatory markers and other test results.

RESULTS

Bacterial infection was identified in 34% of patients in the retrospective cohort. The area under the ROC curve (AUC) was 0.644 (95% confidence interval [CI], .595-.693) for C-reactive protein, 0.624 (95% CI, .573-.675) for procalcitonin, and 0.646 (95% CI, .595-.697) for serum ferritin (SF) in diagnosing bacterial infection. Bacterial infection was found in 29% of cases in the prospective cohort. A model based on serum amyloid A (SAA) and SF levels and neutrophil percentage yielded an AUC of 0.775 (95% CI, .695-.854). Validation analysis indicated lower probability (<15%) of bacterial infection for patients with a score <16.5 points.

CONCLUSIONS

A scoring system based on SAA and SF levels and neutrophil percentage can help distinguish bacterial infection from other causes of FUO, potentially reducing antibiotic use.

摘要

背景

传染病是不明原因发热(FUO)的主要原因。历史上用于诊断细菌感染的血清炎症标志物具有足够的诊断敏感性,但特异性低。本研究旨在开发一种简单的评分系统,用于区分细菌感染与 FUO 的其他早期病因。

方法

本研究纳入了华山医院 2014 年 1 月至 2017 年 6 月期间就诊的 FUO 患者的回顾性队列。使用受试者工作特征(ROC)曲线分析评估血清炎症标志物对细菌感染的诊断效能。随后,在 FUO 患者的另一个独立队列中前瞻性测量了相关标志物(2017 年 12 月至 2019 年 5 月)。评分系统基于炎症标志物和其他测试结果。

结果

回顾性队列中 34%的患者被确定为细菌感染。C 反应蛋白、降钙素原和血清铁蛋白的 ROC 曲线下面积(AUC)分别为 0.644(95%置信区间[CI],0.595-0.693)、0.624(95%CI,0.573-0.675)和 0.646(95%CI,0.595-0.697)。前瞻性队列中,29%的病例为细菌感染。基于血清淀粉样蛋白 A(SAA)和 SF 水平及中性粒细胞百分比的模型 AUC 为 0.775(95%CI,0.695-0.854)。验证分析表明,评分<16.5 分的患者细菌感染的可能性较低(<15%)。

结论

基于 SAA 和 SF 水平及中性粒细胞百分比的评分系统有助于区分细菌感染与 FUO 的其他病因,可能减少抗生素的使用。

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