Evidence map›Paper›PMID 31997098›Full record

ArticleEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology2020

Modeling the risk of fluoroquinolone resistance in non-severe community-onset pyelonephritis.

Antoine Leforestier, Marie-Anne Vibet, Nicolas Gentet, François Javaudin, Quentin Le Bastard, Emmanuel Montassier, Eric Batard

Abstract read
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In one paragraph

Article in European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 99% of its field
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 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Global prevalence of fluoroquinolone resistance inFrontiers in cellular and infection microbiology · 2026
    Pooled it
  2. Fluoroquinolone Resistance inMicroorganisms · 2024
    Review
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 at 4 institutions in 1 country.

Antoine LeforestierEmergency Department, Centre Hospitalier Départemental Vendée, La Roche-sur-Yon, France.
Marie-Anne VibetEE1701 Microbiotes Hôtes Antibiotiques et Résistances bactériennes, Université de Nantes, Nantes, France.
Nicolas GentetEmergency Department, CHU Nantes, Nantes, France.
François JavaudinEE1701 Microbiotes Hôtes Antibiotiques et Résistances bactériennes, Université de Nantes, Nantes, France.
Quentin Le BastardEE1701 Microbiotes Hôtes Antibiotiques et Résistances bactériennes, Université de Nantes, Nantes, France.
Emmanuel MontassierEE1701 Microbiotes Hôtes Antibiotiques et Résistances bactériennes, Université de Nantes, Nantes, France.
Eric BatardEE1701 Microbiotes Hôtes Antibiotiques et Résistances bactériennes, Université de Nantes, Nantes, France. eric.batard@univ-nantes.fr.ORCID http://orcid.org/0000-0002-1927-228X
Centre Hospitalier Universitaire de Nantes · FRCentre d'Investigation Clinique de Nantes · FRCNR de la Résistance aux Antibiotiques · FRRoche (France) · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Estimating whether the individual probability of being infected by a fluoroquinolone resistant isolate is higher than 10% may help to choose the empirical treatment of pyelonephritis. We aimed to model the risk of fluoroquinolone resistance in women with community-onset pyelonephritis. Women with non-severe community-onset pyelonephritis were prospectively recruited in 4 French emergency departments of 2 districts. Adjusted odds ratios (aOR) and 95% confidence intervals were estimated through multivariate logistic regression. Among 190 patients, 19 (10%) were infected by a fluoroquinolone resistant isolate. Fluoroquinolone resistance was more frequent in district #2 (17%) than in district #1 (3%). Independent risk factors for fluoroquinolone resistance were district (adjusted OR, 7.0 (2.2-31.9)), and in the 6 previous months, urinary tract infection (UTI, aOR, 3.9 (1.3-11.5)) and vesical catheterization (aOR, 4.7 (0.5-33.3)). A specific model was derived to identify district #2 patients with a low (10% or lower) probability of being infected by a fluoroquinolone resistant isolate. Independent risk factors were residency in long-term care facility (aOR, 3.3 (0.7-13.5)), and in the 6 previous months, UTI (adjusted OR, 3.1 (0.9-10.7)) and home nursing care (aOR, 3.4 (0.6-17.0)). For 63 (67%) patients, the predicted probability of fluoroquinolone resistance was 0.10; among these patients, 6 (10%) actually had a fluoroquinolone resistant isolate. Locally derived predictive models may be used to identify patients with a low probability of fluoroquinolone resistance and guide the empirical antimicrobial therapy of non-severe community-onset pyelonephritis.

Indexed as

Drug ResistanceModels, StatisticalAdultAgedAnti-Bacterial AgentsBacteriaCommunity-Acquired InfectionsEmergency Service, HospitalFemaleFluoroquinolonesHumansMiddle AgedProspective StudiesPyelonephritisRisk FactorsAnti-Bacterial AgentsFluoroquinolonesCommunity-onsetFluoroquinolonesPredictionPyelonephritisResistance

Identifiers

PMID31997098
OpenAlexW3004152954

What OpenQuestion holds

Textmetadata
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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.