Evidence map›Paper›PMID 28271057›Full record

ArticleFrontiers in pediatrics2017

The Need for Improved Detection of Urinary Tract Infections in Young Children.

Tracy E Bunting-Early, Nader Shaikh, Lynn Woo, Christopher S Cooper, T Ernesto Figueroa

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

5 authors.

Tracy E Bunting-EarlyOutcomes Positive, Inc. , Newark, DE , USA.
Nader ShaikhChildren's Hospital of Pittsburgh , Pittsburgh, PA , USA.
Lynn WooRainbow Babies and Children's Hospital , Cleveland, OH , USA.
Christopher S CooperUniversity of Iowa Children's Hospital , Iowa City, IA , USA.
T Ernesto FigueroaNemours/Alfred I. duPont Hospital for Children , Wilmington, DE , USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesAn estimated 400,000 urinary tract infections (UTIs) are diagnosed annually in children aged <3 years in the United States; yet >50% of febrile UTIs may be missed in this population. Here, we explored possible barriers to diagnosing febrile UTIs in very young children through social research of community pediatricians.

methodsFollowing qualitative interviews, a quantitative survey was developed that included a high-risk case for febrile UTI, presented before prompting for the topic of the survey, to gauge practice of delayed testing. Factors associated with delay were explored using univariate logistic regression. The final survey link was sent to three populations

resultsOf the 218 evaluable responses, 59.6% of physicians would initially test urine in the high-risk case patient, while 21.6% would choose to continue fever reducer and follow-up in 2 days. In the knowledge-based questions, 67.5, 34.0, and 35.6% of respondents identified the correct prevalences in total population, Caucasian girls, and uncircumcised boys, respectively. Many pediatricians (59.5%) believed that delays in detection are common in clinical practice. Physicians who chose to delay testing were more likely to be female, in practice for <25 years, to underestimate prevalence of febrile UTIs and have greater number of children seen per week (all

conclusionOur findings support the need for improved communication and education about prevalence in higher risk populations, outcomes associated with delayed diagnosis, and optimal skills for collection of urine in young patients.

Indexed as

detectiondiagnosisfeverpediatriciansprevalencesurvey researchurinary tract infectionsyoung children

Identifiers

PMID28271057
PMCPMC5319447

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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.