Ding Haiqi, Huang Jiexin, Lin Lan, Chen Yang, Wang Qijin, Li Wenbo, Huang Ying, Fang Xinyu, Zhang Wenming
Fuzhou University Affiliated Provincial Hospital, School of Medicine, Fuzhou University, Fuzhou, China.
Department of Orthopaedic Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Front Cell Infect Microbiol. 2024 Nov 25;14:1457639. doi: 10.3389/fcimb.2024.1457639. eCollection 2024.
The objective of this study is to utilize metagenomic next-generation sequencing (mNGS) to analyze the risk factors causing negative microbial cultures, comprehensively delineate the microbial profiles neglected by traditional cultures, and optimize the pathogenetic diagnostic procedure accordingly.
We enrolled 341 patients diagnosed with OI at our center between 2016 and 2022, and gathered data including age, gender, clinical diagnosis, duration of antibiotic use prior to sampling, microbial culture results, and mNGS results for these patients. According to microbial detection results, risk factors for negative microbial culture and mNGS results were investigated through univariate and multivariate analyses, and the microbial profile in cases with negative microbial cultures was summarized in conjunction with mNGS results. Building upon this, we suggest strategies to enhance the positivity rate of microbial cultures based on clinical experience.
Invasive osteoarticular infection (IOI), multi-infections, rare pathogen infections, and prior antibiotic use are risk factors for negative microbial cultures. When the duration of prior antibiotic use is ≥3 days, mNGS demonstrates significantly higher pathogen detection efficiency than microbial culture. Moreover, the risk of negative microbial culture increases by 4.8 times with the exposure to each additional risk factor (OR=4.043, 95%CI [2.835, 5.765], <0.001). Additionally, over one-third of culture-negative OI involve polymicrobial infections or rare pathogens.
Clinicians should tailor microbial culture strategies based on patient conditions. When needed, they can collaborate with mNGS or optimize microbial culture conditions based on mNGS results to enhance the efficiency of pathogen diagnosis.
本研究的目的是利用宏基因组下一代测序(mNGS)分析导致微生物培养结果为阴性的风险因素,全面描绘传统培养所忽视的微生物谱,并据此优化致病诊断程序。
我们纳入了2016年至2022年间在本中心诊断为骨与关节感染(OI)的341例患者,收集了这些患者的年龄、性别、临床诊断、采样前抗生素使用时长、微生物培养结果和mNGS结果等数据。根据微生物检测结果,通过单因素和多因素分析研究微生物培养阴性和mNGS结果的风险因素,并结合mNGS结果总结微生物培养阴性病例的微生物谱。在此基础上,我们根据临床经验提出提高微生物培养阳性率的策略。
侵袭性骨与关节感染(IOI)、多重感染、罕见病原体感染和既往使用抗生素是微生物培养阴性的风险因素。当前抗生素使用时长≥3天时,mNGS显示出比微生物培养显著更高的病原体检测效率。此外,每增加一个风险因素,微生物培养阴性的风险增加4.8倍(OR=4.043,95%CI[2.835,5.765],<0.001)。此外,超过三分之一的培养阴性的OI涉及多种微生物感染或罕见病原体。
临床医生应根据患者情况调整微生物培养策略。必要时,他们可以与mNGS合作或根据mNGS结果优化微生物培养条件,以提高病原体诊断效率。