Evidence map›Paper›PMID 28248946›Full record

ReviewNature reviews. Urology2017

New and developing diagnostic technologies for urinary tract infections.

Michael Davenport, Kathleen E Mach, Linda M Dairiki Shortliffe, Niaz Banaei, Tza-Huei Wang, Joseph C Liao

Abstract readReview
In one paragraph

Review in Nature reviews. Urology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 134 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
134citing papers in PubMed, 2 pooled it
–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

134 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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74 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

6 authors.

Michael DavenportDepartment of Urology, Stanford University School of Medicine, 300 Pasteur Drive S-287, Stanford, California 94305 USA.
Kathleen E MachDepartment of Urology, Stanford University School of Medicine, 300 Pasteur Drive S-287, Stanford, California 94305 USA.
Linda M Dairiki ShortliffeDepartment of Urology, Stanford University School of Medicine, 300 Pasteur Drive S-287, Stanford, California 94305 USA.
Niaz BanaeiDepartment of Pathology, Stanford University School of Medicine, 3375 Hillview Avenue, Palo Alto, California 94304 USA.
Tza-Huei WangDepartments of Mechanical and Biomedical Engineering, Johns Hopkins University, 3400 N. Charles Street, Baltimore, Maryland 21218, USA.
Joseph C LiaoDepartment of Urology, Stanford University School of Medicine, 300 Pasteur Drive S-287, Stanford, California 94305 USA.

Funding

A Droplet-based single cell platform for pathogen identification and ASTR01AI117032 · NIAID · JOHNS HOPKINS UNIVERSITY · PI LIAO, JOSEPH C, WANG, TZA-HUEI JEFF · 2015 to 2019
$5.7M
An Integrated Diagnostic Biochip for Point of Care Pathogen IdentificationU01AI082457 · NIAID · PALO ALTO VETERANS INSTIT FOR RESEARCH · PI LIAO, JOSEPH C · 2009 to 2013
$3.7M
NIAID NIH HHS R01 AI117032NIAID NIH HHS U01 AI082457
6 · The paper itself

Abstract

Timely and accurate identification and determination of the antimicrobial susceptibility of uropathogens is central to the management of UTIs. Urine dipsticks are fast and amenable to point-of-care testing, but do not have adequate diagnostic accuracy or provide microbiological diagnosis. Urine culture with antimicrobial susceptibility testing takes 2-3 days and requires a clinical laboratory. The common use of empirical antibiotics has contributed to the rise of multidrug-resistant organisms, reducing treatment options and increasing costs. In addition to improved antimicrobial stewardship and the development of new antimicrobials, novel diagnostics are needed for timely microbial identification and determination of antimicrobial susceptibilities. New diagnostic platforms, including nucleic acid tests and mass spectrometry, have been approved for clinical use and have improved the speed and accuracy of pathogen identification from primary cultures. Optimization for direct urine testing would reduce the time to diagnosis, yet these technologies do not provide comprehensive information on antimicrobial susceptibility. Emerging technologies including biosensors, microfluidics, and other integrated platforms could improve UTI diagnosis via direct pathogen detection from urine samples, rapid antimicrobial susceptibility testing, and point-of-care testing. Successful development and implementation of these technologies has the potential to usher in an era of precision medicine to improve patient care and public health.

Indexed as

Anti-Bacterial AgentsClinical Laboratory TechniquesDrug Resistance, BacterialHumansMedical Laboratory ScienceMicrofluidic Analytical TechniquesPolymerase Chain ReactionUrinalysisUrinary Tract InfectionsAnti-Bacterial Agents

Identifiers

PMID28248946
PMCPMC5473291

What OpenQuestion holds

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LicenceTDM
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.