Evidence map›Paper›PMID 37811113›Full record

ArticleAnnals of medicine and surgery (2012)2023

Prediction of the bacterial shape in urinary tract infections with the Sysmex UF-1000i analyser: technical note.

Noussaiba Benhamza, Adnane Aarab, Soumya Farih, Abderrazak Saddari, Loubna Yacoubi, Elmostapha Benaissa, Yassine Ben Lahlou, Mostafa Elouennass, Adil Maleb

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Article in Annals of medicine and surgery (2012), 2023. 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
0.2field-weighted citation impact, top 40% of its field
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, 1 citations in OpenAlex.

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

9 authors at 3 institutions in 2 countries.

Noussaiba BenhamzaLaboratory of Microbiology, Mohamed VI Teaching Hospital.
Adnane AarabLaboratory of Microbiology, Mohamed VI Teaching Hospital.
Soumya FarihLaboratory of Microbiology, Mohamed VI Teaching Hospital.
Abderrazak SaddariLaboratory of Microbiology, Mohamed VI Teaching Hospital.
Loubna YacoubiLaboratory of Microbiology, Mohamed VI Teaching Hospital.
Elmostapha BenaissaDepartment of Bacteriology, Mohammed V Teaching Military Hospital.
Yassine Ben LahlouDepartment of Bacteriology, Mohammed V Teaching Military Hospital.
Mostafa ElouennassEpidemiology and Bacterial Resistance Research Team/BIO-INOVA Centre, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco.
Adil MalebLaboratory of Microbiology, Mohamed VI Teaching Hospital.
Mohamed I University · MAMilitary Hospital · PKMohammed V University · MA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The aim of our study was to explore the utility of the Sysmex UF-1000i analyzer as a rapid screening tool for urinary tract infections (UTI) and its ability to predict bacterial shape in order to help physicians choose the appropriate empiric treatment. Materials and methods: This is a retrospective study, including 1023 urine cytobacteriological examinations. Urines were processed according to the recommendations of the medical microbiology reference system (REMIC). Using the Sysmex Uf-1000i analyzer, the authors evaluated bacteria forward scatter (B_FSC) and fluorescent light scatter (B_FLH) in a preliminary discrimination step for UTI caused by bacilli or cocci bacteria. Results: The authors got 1023 positive samples. Comparing baccili and cocci bacteria, the authors observed a statistically significant difference for B_FSC but not for B_FLH. The values of B_FLH are very close for the four categories of microorganisms compared (bacilli, cocci, bacilli-cocci association, and yeasts). For these same categories, tests show different values for the B_FSC. A separate analysis of the B_FSC values for bacilli shows that their distribution is relatively homogeneous and exhibits a peak between 20 and 30 ch. Conclusion: Dimensional parameters of bacteria generated by UF-1000i could be a rapid and useful tool for predicting the bacterial shape causing UTI.

Indexed as

B_FSCmorphology discrimination UTIUF-1000iurinary tract infections

Identifiers

PMID37811113
PMCPMC10552994
OpenAlexW4387324597

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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.