ArticleMicrobial biotechnology2025
Rapid Identification and Typing of Carbapenem-Resistant Klebsiella pneumoniae Using MALDI-TOF MS and Machine Learning.
Article in Microbial biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of machine learning on clinical MALDI-TOF MS.Briefings in bioinformatics · 2026Pooled it
- Rapid identification of carbapenem-resistant Acinetobacter baumannii based on MALDI-TOF mass spectrometry and machine learning.BMC microbiology · 2026Article
- Artificial Intelligence for Antimicrobial Resistance Detection and Prediction inInfection and drug resistance · 2026Review
- Rapid Identification and Typing of Carbapenem-Resistant Klebsiella pneumoniae Using MALDI-TOF MS and Machine Learning.Microbial biotechnology · 2025Article
- MALDI-TOF MS in conjunction with machine learning: toward a new era for antimicrobial susceptibility testing.Frontiers in cellular and infection microbiology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Use matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS) to screen the specific mass peaks of carbapenem-resistant Klebsiella pneumoniae (CRKP), compare the differences in spectrum peaks between intestinal and bloodstream screening of CRKP, and assess the utility of MALDI-TOF MS in quickly identifying various CRKP sources. From 2014 to 2023, a total of 267 Klebsiella pneumoniae strains were collected at Quzhou People's Hospital, including 60 intestinal screening isolates from ICU patients and 207 bloodstream infection isolates. MALDI-TOF MS was used to profile peptides in CRKP and carbapenem-sensitive Klebsiella pneumoniae (CSKP), followed by analysis with flexAnalysis and ClinProTools 3.0. Statistically significant protein peaks were selected to build classification models, which were verified using non-duplicate strains. MALDI-TOF MS achieved > 99.9% accuracy in identifying Klebsiella pneumoniae. Characteristic peaks (2523.43, 3041.62, 4520.11, 10,079.18 Da) were used to develop resistance analysis models, with the optimal model (SNN) showing 90.08% sensitivity, 95.80% specificity and identification accuracies of 90% for CSKP and 89.66% for CRKP. Another model using peaks (8876, 8993, 9139 Da) differentiated CRKP origins, with the ideal model (QC) achieving 86.85% sensitivity, 88.46% specificity, and accuracies of 81.82% for bloodstream and 95.00% for intestinal CRKP.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.