Evidence map›Paper›PMID 12149332›Full record

ArticleJournal of clinical microbiology2002

Fluorescent amplified fragment length polymorphism probabilistic database for identification of bacterial isolates from urinary tract infections.

Yankuba Kassama, Paul J Rooney, Royston Goodacre

Abstract readEvaluation Study
In one paragraph

Article in Journal of clinical microbiology, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yankuba KassamaInstitute of Biological Sciences, University of Wales, Aberystwyth, Ceredigion, SY23 3DD, United Kingdom.
Paul J Rooney
Royston Goodacre

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability of the fluorescent amplified fragment length polymorphism (FAFLP) technique to identify bacterial isolates from urinary tract infections (UTIs) was investigated. FAFLP was carried out using the single primer combination MseI plus CT and EcoRI plus 0, and information-rich FAFLP profiles were generated from all 69 UTI isolates studied, which comprised both gram-negative and gram-positive bacteria encompassing eight genera. The genetic relatedness of these 69 bacteria was determined by cluster analysis, and this revealed eight main groups corresponding to the eight bacterial genera. Finer discrimination on the same dendrogram showed species and subspecies differentiations, thus demonstrating the potential of FAFLP for describing a wide diversity range within microbial populations. The interpretation of FAFLP profiles is often complicated because it relies upon the investigator interpreting dendrograms; this process may be subjective if the tree is complicated, particularly if it includes polytomies (unresolved nodes). Therefore, we have developed a method based on Bayes' theorem for the identification of bacteria against an FAFLP probabilistic identification matrix. Thus, FAFLP is suitable for the objective identification of causal agents of UTI, and the procedure offers great potential in the clinical laboratory.

Indexed as

Bacterial Typing TechniquesDatabases, FactualModels, StatisticalPolymorphism, Restriction Fragment LengthBacterial InfectionsCluster AnalysisDNA, BacterialFluorescenceGram-Negative BacteriaGram-Positive BacteriaHumansUrinary Tract InfectionsDNA, Bacterial

Identifiers

PMID12149332
PMCPMC120626

What OpenQuestion holds

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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.