Author:
Li Ying,Shan Mingzhu,Zhu Zuobin,Mao Xuhua,Yan Mingju,Chen Ying,Zhu Qiuju,Li Hongchun,Gu Bing
Abstract
Abstract
Background
Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been rapidly developed and widely used as an analytical technique in clinical laboratories with high accuracy in microorganism identification.
Objective
To validate the efficacy of MALDI-TOF MS in identification of clinical pathogenic anaerobes.
Methods
Twenty-eight studies covering 6685 strains of anaerobic bacteria were included in this meta-analysis. Fixed-effects models based on the P-value and the I-squared were used for meta-analysis to consider the possibility of heterogeneity between studies. Statistical analyses were performed by using STATA 12.0.
Results
The identification accuracy of MALDI-TOF MS was 84% for species (I2 = 98.0%, P < 0.1), and 92% for genus (I2 = 96.6%, P < 0.1). Thereinto, the identification accuracy of Bacteroides was the highest at 96% with a 95% CI of 95–97%, followed by Lactobacillus spp., Parabacteroides spp., Clostridium spp., Propionibacterium spp., Prevotella spp., Veillonella spp. and Peptostreptococcus spp., and their correct identification rates were all above 90%, while the accuracy of rare anaerobic bacteria was relatively low. Meanwhile, the overall capabilities of two MALDI-TOF MS systems were different. The identification accuracy rate was 90% for VITEK MS vs. 86% for MALDI biotyper system.
Conclusions
Our research showed that MALDI-TOF-MS was satisfactory in genus identification of clinical pathogenic anaerobic bacteria. However, this method still suffers from different drawbacks in precise identification of rare anaerobe and species levels of common anaerobic bacteria.
Funder
Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province
the National Natural Science Foundation of China
Jiangsu Privincial Natural Science Foundation
Jiangsu Privincial Medical Talent
Six talent peaks project of Jiangsu Province
Advanced health talent of six-one project of Jiangsu Province
the Natural Science Foundation of Jiangsu Province
Publisher
Springer Science and Business Media LLC
Cited by
72 articles.
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