Evidence map›Paper›PMID 26965031›Full record

Trial reportThe British journal of general practice : the journal of the Royal College of General Practitioners2016

Predicting antibiotic prescription after symptomatic treatment for urinary tract infection: development of a model using data from an RCT in general practice.

Ildikó Gágyor, Jörg Haasenritter, Jutta Bleidorn, Warren McIsaac, Guido Schmiemann, Eva Hummers-Pradier, Wolfgang Himmel

Abstract readComparative StudyRandomized Controlled Trial
In one paragraph

Trial report in The British journal of general practice : the journal of the Royal College of General Practitioners, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  13. Variations in presentation, management, and patient outcomes of urinary tract infection: a prospective four-country primary care observational cohort study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2017
    Observational
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

7 authors.

Ildikó GágyorDepartment of General Practice, Göttingen University Medical Center, Göttingen, Germany.
Jörg HaasenritterDepartment of General Practice/Family Medicine, Philipps University Marburg, Marburg, Germany.
Jutta BleidornInstitute of General Practice, Hannover Medical School, Hannover, Germany.
Warren McIsaacRay D Wolfe Department of Family Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada.
Guido SchmiemannInstitute for Public Health and Nursing Research, Department for Health Services Research, University of Bremen, Bremen, Germany.
Eva Hummers-PradierDepartment of General Practice, Göttingen University Medical Center, Göttingen, Germany.
Wolfgang HimmelDepartment of General Practice, Göttingen University Medical Center, Göttingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUncomplicated urinary tract infection (UTI) is often treated with antibiotics, resulting in increasing resistance levels. A randomised controlled trial showed that two-thirds of females with UTI treated symptomatically recovered without subsequent antibiotic treatment.

aimTo investigate whether there are differences between females with a UTI who were subsequently prescribed antibiotics and those who recovered with symptomatic treatment only, and to develop a model to predict those who can safely and effectively be treated symptomatically. DESIGN AND

settingThis is a subgroup analysis of females assigned to ibuprofen in a UTI trial in general practices.

methodMultiple logistic regression analysis was used to select variables for a prediction model, The discriminative value of the model was estimated by the area under the receiver operator curve (AUC) and the effects of different thresholds were calculated within the model predicting antibiotic prescription and need for follow-up visits.

resultsOf the 235 females in the ibuprofen group, 79 were subsequently prescribed antibiotics within 28 days of follow-up. The final model included five predictors: urgency/frequency, impaired daily activities, and positive dipstick test results for erythrocytes, leucocytes, and nitrite. The AUC was 0.73 (95% CI = 0.67 to 0.80). A reasonable threshold for antibiotic initiation would result in 58% of females presenting with UTI being treated with antibiotics. Of the remaining females, only 6% would return to the practice because of symptomatic treatment failure.

conclusionThe present model revealed moderately good accuracy and could be the basis for a decision aid for GPs and females to find the treatment option that fits best.

Indexed as

General PracticeAdultAnti-Infective Agents, UrinaryAnti-Inflammatory Agents, Non-SteroidalArea Under CurveDouble-Blind MethodDrug Resistance, MicrobialFemaleFollow-Up StudiesHumansIbuprofenMiddle AgedPractice Guidelines as TopicPractice Patterns, Physicians'Treatment OutcomeUrinary Tract InfectionsAnti-Infective Agents, UrinaryAnti-Inflammatory Agents, Non-SteroidalIbuprofenfamily practiceibuprofenprediction modelurinary anti-infective agentsurinary tract infections

Identifiers

PMID26965031
PMCPMC4809706

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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.