ArticleBMC microbiology2017
Article in BMC microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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.
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.
Who cites it
21 citing papers in PubMed, 33 citations in OpenAlex.
- Article
- Metabolic interactions between bacterial co-isolates from catheter-associated urinary tract infections.Scientific reports · 2026Article
- Metabolomics strategy for diagnosing urinary tract infections.Nature communications · 2025Article
- Urinary Tract Infections Detection with Molecular Biomarkers.Biomolecules · 2024Review
- Gut microbiome and metabolome to discover pathogenic bacteria and probiotics in ankylosing spondylitis.Frontiers in immunology · 2024Article
- The distinct transcriptome of virulence-associated phylogenetic group B2Microbiology spectrum · 2023Article
- Bacteria-Infected Artificial Urine Characterization Based on a Combined Approach Using an Electronic Tongue Complemented withBiosensors · 2023Article
- What is the Diagnostic Accuracy of Novel Urine Biomarkers for Urinary Tract Infection?Biomarker insights · 2023Review
- Quantitative NMR Methods in Metabolomics.Handbook of experimental pharmacology · 2023Article
- Metabolomics of infectious diseases in the era of personalized medicine.Frontiers in molecular biosciences · 2023Review
- Rapid Fluorescence Sensor Guided Detection of Urinary Tract Bacterial Infections.International journal of nanomedicine · 2022Article
- Paper and thread as media for the frugal detection of urinary tract infections (UTIs).Analytical and bioanalytical chemistry · 2022Review
- Short-Chain Fatty Acid and FFAR2 Activation - A New Option for Treating Infections?Frontiers in cellular and infection microbiology · 2021Review
- Diagnostic Value of the Fimbriae Distribution Pattern in Localization of Urinary Tract Infection.Frontiers in medicine · 2021Article
- NMR-Based Metabolomics.Advances in experimental medicine and biology · 2021Article
- Integrative Metabolomics to Identify Molecular Signatures of Responses to Vaccines and Infections.Metabolites · 2020Review
- Malodorous biogenic amines in Escherichia coli-caused urinary tract infections in women-a metabolomics approach.Scientific reports · 2020Article
- Metabolomic study of soft corals from the Colombian Caribbean: PSYCHE andScientific reports · 2020Article
- Biomarkers in urinary tract infections - which ones are suitable for diagnostics and follow-up?GMS infectious diseases · 2020Review
- Rapid Growth and Metabolism of Uropathogenic Escherichia coli in Relation to Urine Composition.Clinical microbiology reviews · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUrinary tract infection (UTI) is one of the most common diagnoses in girls and women, and to a lesser extent in boys and men younger than 50 years. Escherichia coli, followed by Klebsiella spp. and Proteus spp., cause 75-90% of all infections. Infection of the urinary tract is identified by growth of a significant number of a single species in the urine, in the presence of symptoms. Urinary culture is an accurate diagnostic method but takes several hours or days to be carried out. Metabolomics analysis aims to identify biomarkers that are capable of speeding up diagnosis.
methodsUrine samples from 51 patients with a prior diagnosis of Escherichia coli-associated UTI, from 21 patients with UTI caused by other pathogens (bacteria and fungi), and from 61 healthy controls were analyzed. The
resultsOrthogonal Partial Least Squares-discriminant Analysis (OPLS-DA) showed good separation (R
conclusionsAcetate and trimethylamine were identified as optimal candidates for biomarkers for UTI diagnosis. The conclusions support the possibility of a fast diagnostic test for Escherichia coli-associated UTI using acetate and trimethylamine concentrations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.