ArticleMicroorganisms2024
Rapid Classification and Differentiation of Sepsis-Related Pathogens Using FT-IR Spectroscopy.
Article in Microorganisms, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Vibrational spectroscopic characterisation of fluorescent-protein-tagged and wild-type bacteria in surface-associated microdroplets.Faraday discussions · 2026Article
- Classifying smoking status using linear and non-linear models based on clinical health records.Analytical and bioanalytical chemistry · 2026Article
- Application of Rapid Evaporative Ionization Mass Spectrometry (REIMS) to Identify Antimicrobial Resistance in UropathogenicAnalytical chemistry · 2025Article
- Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants.Scientific reports · 2025Article
- Advanced One-Pot RPA-CRISPR/Cas12a Reaction with Glycerol and Betaine for High-Sensitivity Diagnosis ofACS omega · 2025Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sepsis is a life-threatening condition arising from a dysregulated host immune response to infection, leading to a substantial global health burden. The accurate identification of bacterial pathogens in sepsis is essential for guiding effective antimicrobial therapy and optimising patient outcomes. Traditional culture-based bacterial typing methods present inherent limitations, necessitating the exploration of alternative diagnostic approaches. This study reports the successful application of Fourier-transform infrared (FT-IR) spectroscopy in combination with chemometrics as a potent tool for the classification and discrimination of microbial species and strains, primarily sourced from individuals with invasive infections. These samples were obtained from various children with suspected sepsis infections with bacteria and fungi originating at different sites. We conducted a comprehensive analysis utilising 212 isolates from 14 distinct genera, comprising 202 bacterial and 10 fungal isolates. With the spectral analysis taking several weeks, we present the incorporation of quality control samples to mitigate potential variations that may arise between different sample plates, especially when dealing with a large sample size. The results demonstrated a remarkable consistency in clustering patterns among 14 genera when subjected to principal component analysis (PCA). Particularly,
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