Evidence map›Paper›PMID 10755996›Full record

ReviewClinical microbiology reviews2000

Applications of flow cytometry to clinical microbiology.

A Alvarez-Barrientos, J Arroyo, R Cantón, C Nombela, M Sánchez-Pérez

Abstract readReview
In one paragraph

Review in Clinical microbiology reviews, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.

0numbers the graph read from it
0cells of the map it votes in
71citing 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

71 citing papers in PubMed.

  1. Article
  2. Advances in pathogen detection ofInfectious medicine · 2025
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11 more citing papers are in PubMed but not listed here.

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

5 authors.

A Alvarez-BarrientosDepartamento de Microbiología II, Facultad de Farmacia, Universidad Complutense de Madrid, Spain.
J Arroyo
R Cantón
C Nombela
M Sánchez-Pérez

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Classical microbiology techniques are relatively slow in comparison to other analytical techniques, in many cases due to the need to culture the microorganisms. Furthermore, classical approaches are difficult with unculturable microorganisms. More recently, the emergence of molecular biology techniques, particularly those on antibodies and nucleic acid probes combined with amplification techniques, has provided speediness and specificity to microbiological diagnosis. Flow cytometry (FCM) allows single- or multiple-microbe detection in clinical samples in an easy, reliable, and fast way. Microbes can be identified on the basis of their peculiar cytometric parameters or by means of certain fluorochromes that can be used either independently or bound to specific antibodies or oligonucleotides. FCM has permitted the development of quantitative procedures to assess antimicrobial susceptibility and drug cytotoxicity in a rapid, accurate, and highly reproducible way. Furthermore, this technique allows the monitoring of in vitro antimicrobial activity and of antimicrobial treatments ex vivo. The most outstanding contribution of FCM is the possibility of detecting the presence of heterogeneous populations with different responses to antimicrobial treatments. Despite these advantages, the application of FCM in clinical microbiology is not yet widespread, probably due to the lack of access to flow cytometers or the lack of knowledge about the potential of this technique. One of the goals of this review is to attempt to mitigate this latter circumstance. We are convinced that in the near future, the availability of commercial kits should increase the use of this technique in the clinical microbiology laboratory.

Indexed as

Flow CytometryInfectionsMicrobiological TechniquesHumansLaboratoriesMicrobial Sensitivity Tests

Identifiers

PMID10755996
PMCPMC100149

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.