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Blood biomarker algorithms for the diagnosis of mycoplasma pneumoniae respiratory infections
Journal of Immunological Methods ( IF 1.6 ) Pub Date : 2020-11-07 , DOI: 10.1016/j.jim.2020.112908
Per Venge 1 , Staffan Eriksson 2 , Karlis Pauksen 3
Affiliation  

The correct diagnosis of acute infections as to bacteria, mycoplasma or virus is a clinical challenge and has a great impact on the therapeutic decisions. Current diagnostic tests of mycoplasma pneumoniae infections of the respiratory tract such as PCR and serology are either somewhat unreliable or slow and do not entirely meet the clinical needs of accurate and fast diagnosis. The aim of this report was to examine a panel of candidate biomarkers and their capacity to distinguish mycoplasma pneumoniae respiratory infections from respiratory infections caused by either bacterial or virus.

Method

Patients with confirmed etiology of their acute respiratory infections (n = 156) were included of which 28 patients were diagnosed with mycoplasma pneumoniae. Blood was taken before any antibiotics treatment and analysed for Azurocidin (HBP), Calprotectin, CRP, Human Neutrophil Lipocalin (HNL), Interferon γ-induced Protein 10 kDa (IP-10), Procalcitonin (PCT), Thymidine Kinase 1 (TK1), TNF-Related Apoptosis-Inducing Ligand (TRAIL).

Results

Individually the concentrations of IP-10, TK1 and P-HNL distinguished mycoplasma pneumoniae from bacterial infections with AUCs of 0.79–0.85. However, in combination, TK1 with either IP-10 or P-HNL showed an AUC of 0.97–0.95. In the distinction between mycoplasma pneumoniae and viral respiratory infections CRP, Calprotectin and TRAIL showed individual AUCs of 0.94–0.84. Together with either P-HNL dimer or PCT, CRP showed AUCs of 0.97.

Conclusion

Our results indicate that it may be possible to design useful diagnostic algorithms of biomarkers that could help distinguish mycoplasma pneumoniae from respiratory infections caused by bacteria or virus. The development of rapid point-of-care assays based on such algorithms could be clinically useful tools in the therapeutic decision-making.



中文翻译:

用于诊断肺炎支原体呼吸道感染的血液生物标志物算法

正确诊断细菌、支原体或病毒的急性感染是一项临床挑战,对治疗决策有很大影响。目前对呼吸道肺炎支原体感染的诊断测试,如 PCR 和血清学检测,要么有些不可靠,要么速度缓慢,不能完全满足准确快速诊断的临床需求。本报告的目的是检查一组候选生物标志物及其区分肺炎支原体呼吸道感染与细菌或病毒引起的呼吸道感染的能力。

方法

包括确诊为急性呼吸道感染病因的患者 ( n  = 156),其中 28 名患者被诊断为肺炎支原体。在任何抗生素治疗前采血并分析天青素 (HBP)、钙卫蛋白、CRP、人中性粒细胞脂质运载蛋白 (HNL)、干扰素 γ 诱导蛋白 10 kDa (IP-10)、降钙素原 (PCT)、胸苷激酶 1 (TK1) , TNF 相关凋亡诱导配体 (TRAIL)。

结果

IP-10、TK1 和 P-HNL 的浓度分别将肺炎支原体与细菌感染区分开来,AUC 为 0.79-0.85。然而,TK1 与 IP-10 或 P-HNL 的组合显示出 0.97-0.95 的 AUC。在区分肺炎支原体和病毒性呼吸道感染 CRP、钙卫蛋白和 TRAIL 时,个体 AUC 为 0.94-0.84。CRP 与 P-HNL 二聚体或 PCT 一起显示 AUC 为 0.97。

结论

我们的结果表明,有可能设计有用的生物标志物诊断算法,帮助区分肺炎支原体与细菌或病毒引起的呼吸道感染。基于这种算法的快速床旁检测的开发可能是临床上有用的治疗决策工具。

更新日期:2020-11-09
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