Evidence map›Paper›PMID 30619863›Full record

ArticleFrontiers in medicine2018

Comparing Two Automated Techniques for the Primary Screening-Out of Urine Culture.

María Isabel Millán-Lou, Juan Manuel García-Lechuz, María Angeles Ruiz-Andrés, Concepción López, María José Aldea, P Egido, María José Revillo, Antonio Rezusta

Abstract read
In one paragraph

Article in Frontiers in medicine, 2018. 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

8 authors.

María Isabel Millán-LouServicio de Microbiología, Hospital Universitario Miguel-Servet, Zaragoza, Spain.
Juan Manuel García-LechuzServicio de Microbiología, Hospital Universitario Miguel-Servet, Zaragoza, Spain.
María Angeles Ruiz-AndrésServicio de Microbiología, Hospital Universitario Miguel-Servet, Zaragoza, Spain.
Concepción LópezServicio de Microbiología, Hospital Universitario Miguel-Servet, Zaragoza, Spain.
María José AldeaServicio de Microbiología, Hospital Universitario Miguel-Servet, Zaragoza, Spain.
P EgidoServicio de Microbiología, Hospital Universitario Miguel-Servet, Zaragoza, Spain.
María José RevilloServicio de Microbiología, Hospital Universitario Miguel-Servet, Zaragoza, Spain.
Antonio RezustaServicio de Microbiología, Hospital Universitario Miguel-Servet, Zaragoza, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urinary tract infection is the most common human infection with a high morbidity. In primary care and hospital services, conventional urine culture is a key part of infection diagnosis but results take at least 24 h. Therefore, a rapid and reliable screening method is still needed to discard negative samples as quickly as possible and to reduce the laboratory workload. In this aspect, this study aims to compare the diagnostic performance between Sysmex UF-1000i and FUS200 systems in comparison to urine culture as the gold standard. From March to June 2016, 1,220 urine samples collected at the clinical microbiology laboratory of the "Miguel Servet" hospital were studied in parallel with both analysers, and some technical features were evaluated to select the ideal equipment. The most balanced cut-off values taking into account bacteria or leukocyte counts were 138 bacteria/μL or 119.8 leukocyte/μL for the UF-1000i (95.3% SE and 70.4% SP), and 5.7 bacteria/μL or 4.3 leukocyte/μL for the FUS200 (95.8% SE and 44.4% SP). The reduction of cultured plates was 37.4% with the FUS200 and 58.3% with the UF-1000i. This study shows that both techniques improve the workflow in the laboratory, but the UF-1000i has the highest specificity at any sensitivity and the FUS200 needs a shorter processing time.

Indexed as

automated screening systemsFUS200microbiological diagnosticsUF-1000iurinary tract infection

Identifiers

PMID30619863
PMCPMC6302016

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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.