Evidence map›Paper›PMID 41900392›Full record

ArticleMicroorganisms2026

Rapid Bacterial Identification and Quantitative Antimicrobial Susceptibility Assessment from Positive Blood Cultures to Optimize Bloodstream Infection Management.

Lucia Sliviaková Matúšková, Michala Vladárová, Elena Nováková

Abstract read
In one paragraph

Article in Microorganisms, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Lucia Sliviaková MatúškováDepartment of Clinical Microbiology, Clinical Biochemistry Ltd., 01007 Žilina, Slovakia.
Michala VladárováDepartment of Clinical Microbiology, Clinical Biochemistry Ltd., 01007 Žilina, Slovakia.
Elena NovákováInstitute of Microbiology and Immunology, Jessenius Faculty of Medicine in Martin, 03601 Martin, Slovakia.ORCID 0000-0001-5939-3820

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bloodstream infection (BSI) is a serious clinical condition associated with high morbidity and mortality, requiring rapid identification of causative agents and timely antimicrobial susceptibility testing (AST). This study evaluated accelerated bacterial identification from positive blood culture samples using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with two rapid processing approaches: a serum separation tube-based centrifugation method (SST method) and shortened cultivation on solid media. Rapid identification was followed by accelerated AST, performed either from a bacterial cell pellet (SST method) and from early-grown bacterial biomass (shortened cultivation protocol). The results were compared with those obtained using routine laboratory procedures. A total of 270 positive blood culture samples were analyzed, with 135 samples processed by each protocol. Both approaches achieved an identification success rate of 93.33%. Rapid AST using the SST method showed error rates of 0.51% minor errors, 0.57% major errors, and 0.23% very major errors, with an overall agreement of 98.69%. The shortened cultivation protocol demonstrated lower error rates (0.46% minor errors and 0.23% major errors) and an overall agreement of 99.31%. These findings confirm that MALDI-TOF MS enables reliable early identification of BSI pathogens and rapid AST, supporting timely optimization of antimicrobial therapy and early detection of multidrug-resistant strains.

Indexed as

antibiotic susceptibility testingblood culturesbloodstream infectionMALDI-TOF MSrapid microbiological diagnosticstreatment of BSI

Identifiers

PMID41900392
PMCPMC13028864

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Registered trials

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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.