Prediction of methicillin-resistant Staphylococcus aureus and carbapenem-resistant Klebsiella pneumoniae from flagged blood cultures by combining rapid Sepsityper MALDI-TOF mass spectrometry with machine learning

被引:11
|
作者
Yu, Jiaxin [1 ]
Lin, Hsiu-Hsien [2 ]
Tseng, Kun-Hao [2 ]
Lin, Yu-Tzu [2 ,3 ]
Chen, Wei-Cheng [4 ,5 ,6 ]
Tien, Ni [2 ,3 ]
Cho, Chia-Fong [1 ]
Liang, Shinn-Jye [4 ]
Ho, Lu-Ching [7 ,8 ]
Hsieh, Yow-Wen [7 ,8 ]
Hsu, Kai Cheng [1 ,9 ,10 ]
Ho, Mao-Wang [9 ,11 ]
Hsueh, Po-Ren [3 ,9 ,11 ,13 ,14 ]
Cho, Der-Yang [12 ,15 ]
机构
[1] China Med Univ Hosp, AI Ctr, Taichung, Taiwan
[2] China Med Univ Hosp, Dept Lab Med, Taichung, Taiwan
[3] China Med Univ, Dept Med Lab Sci & Biotechnol, Taichung, Taiwan
[4] China Med Univ Hosp, Dept Internal Med, Div Pulm & Crit Care Med, Taichung, Taiwan
[5] China Med Univ, Coll Med, Grad Inst Biomed Sci, Taichung, Taiwan
[6] China Med Univ, Coll Med, Sch Med, Taichung, Taiwan
[7] China Med Univ Hosp, Dept Pharm, Taichung, Taiwan
[8] China Med Univ, Sch Pharm, Taichung, Taiwan
[9] China Med Univ, Dept Med, Taichung, Taiwan
[10] China Med Univ Hosp, Dept Neurol, Taichung, Taiwan
[11] China Med Univ Hosp, Dept Internal Med, Div Infect Dis, Taichung, Taiwan
[12] China Med Univ Hosp, Dept Neurosurg, Taichung, Taiwan
[13] China Med Univ Hosp, Dept Lab Med, 2 Yude Rd, Taichung 404332, Taiwan
[14] China Med Univ Hosp, Dept Internal Med, 2 Yude Rd, Taichung 404332, Taiwan
[15] China Med Univ Hosp, Dept Neurosurg, 2 Yude Rd, Taichung 404332, Taiwan
关键词
Carbapenem-resistant Klebsiella pneumoniae; Methicillin-resistant Staphylococcus aureus; MALDI-TOF MS; Machine learning; Specific MBT-Sepsityper module; Prediction platform; IDENTIFICATION; IMPACT;
D O I
10.1016/j.ijantimicag.2023.106994
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
This study investigated combination of the Rapid Sepsityper Kit and a machine learning (ML)-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) approach for rapid prediction of methicillin-resistant Staphylococcus aureus (MRSA) and carbapenem-resistant Klebsiella pneumoniae (CRKP) from positive blood culture bottles. The study involved 461 patients with monomicrobial bloodstream infections. Species identification was performed using the conventional MALDI-TOF MS Biotyper system and the Rapid Sepsityper protocol. The data underwent preprocessing steps, and ML models were trained using preprocessed MALDI-TOF data and corresponding labels. The interpretability of the model was enhanced using SHapely Additive exPlanations values to identify significant features. In total, 44 S. aureus isolates comprising 406 MALDI-TOF MS files and 126 K. pneumoniae isolates comprising 1249 MALDI-TOF MS files were evaluated. This study demonstrated the feasibility of predicting MRSA among S. aureus and CRKP among K. pneumoniae isolates using MALDI-TOF MS and Sepsityper. Accuracy, area under the receiver operating characteristic curve, and F1 score for MRSA/methicillin-susceptible S. aureus were 0.875, 0.898 and 0.904, respectively; for CRKP/carbapenem-susceptible K. pneumoniae, these values were 0.766, 0.828 and 0.795, respectively. In conclusion, the novel ML-based MALDI-TOF MS approach enables rapid identification of MRSA and CRKP from flagged blood cultures within 1 h. This enables earlier initiation of targeted antimicrobial therapy, reducing deaths due to sepsis. The favourable performance and reduced turnaround time of this method suggest its potential as a rapid detection strategy in clinical microbiology laboratories, ultimately improving patient outcomes.(c) 2023 Elsevier Ltd and International Society of Antimicrobial Chemotherapy. All rights reserved.
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页数:7
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