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Updated: Jan 16, 2026

Author Spotlight: Accelerating Diagnostic Accuracy with Direct Identification of Gram-Negatives from Blood Culture Bottles
Published on: May 24, 2024
Direct identification and antimicrobial susceptibility testing of microorganisms from positive blood culture bottles
Tsui-Ping Liu1,2, Hui-Fang Wu1, Pai-Ling Chang3
1Department of Laboratory Medicine, Tao-Yuan General Hospital, Ministry of Health and Welfare, Taoyuan, Taiwan.
Background:
Bloodstream infections (BSIs) are a major cause of morbidity and mortality globally. Rapid and accurate pathogen identification and antimicrobial susceptibility testing (AST) are crucial for timely and effective treatment. Conventional blood culture (BC) workflows are time-consuming, typically requiring 18-48 h. Although integrating matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with direct AST protocols is promising, certain limitations remain. Therefore, we aimed to establish a faster and more reliable method for the direct identification and AST of microorganisms from positive BC bottles using a membrane filtration-based protocol.
Results:
The membrane filtration-based method achieved an overall identification success rate of 76.5%. Rates were highest for Gram-negative bacteria (88.1%), followed by anaerobes (80.0%), Gram-positive cocci (70.2%), and Gram-positive bacilli (43.8%). Yeast identification was unsuccessful. AST results showed strong concordance with those from the conventional method, with essential agreement (EA) exceeding 95% across all groups. For Gram-negative bacteria, EA was 98% and categorical agreement (CA) was 95.4%, with 3.6%, 0.5%, and 0.5% minor, major, and very major errors, respectively. EA and CA were 96.1% and 94.2% for Gram-positive cocci, and 95.5% and 93.4% for Streptococcus spp.
Conclusions:
The membrane filtration-based method, effective for Gram-negative bacteria, reduced turnaround time by 10-12 h compared to conventional workflows. Further optimization can improve accuracy for Gram-positive bacteria and yeast, offering a promising, streamlined workflow to enhance BSI diagnostics and guide targeted antimicrobial therapy.
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