Evidence map›Paper›PMID 34126937›Full record

ArticleBMC infectious diseases2021

Antibiotic prescriptions and risk factors for antimicrobial resistance in patients hospitalized with urinary tract infection: a matched case-control study using the French health insurance database (SNDS).

Marion Opatowski, Christian Brun-Buisson, Mehdi Touat, Jérôme Salomon, Didier Guillemot, Philippe Tuppin, Laurence Watier

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 7% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
  2. Spatial pattern and risk factors of resistance to important antibiotics amongAntimicrobial stewardship & healthcare epidemiology : ASHE · 2026
    Article
  3. Article
  4. Article
  5. Association between postdischarge antibiotic use andAntimicrobial stewardship & healthcare epidemiology : ASHE · 2025
    Article
  6. Article
  7. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Marion OpatowskiEpidemiology and Modeling of bacterial Evasion to Antibacterials Unit (EMEA), Institut Pasteur, 25-28, Rue du Dr. Roux, 75724, Paris Cedex 15, France.ORCID http://orcid.org/0000-0002-0484-0846
Christian Brun-BuissonEpidemiology and Modeling of bacterial Evasion to Antibacterials Unit (EMEA), Institut Pasteur, 25-28, Rue du Dr. Roux, 75724, Paris Cedex 15, France.ORCID http://orcid.org/0000-0001-5909-576X
Mehdi TouatEpidemiology and Modeling of bacterial Evasion to Antibacterials Unit (EMEA), Institut Pasteur, 25-28, Rue du Dr. Roux, 75724, Paris Cedex 15, France.ORCID http://orcid.org/0000-0002-2340-5604
Jérôme SalomonEpidemiology and Modeling of bacterial Evasion to Antibacterials Unit (EMEA), Institut Pasteur, 25-28, Rue du Dr. Roux, 75724, Paris Cedex 15, France.ORCID http://orcid.org/0000-0002-3749-4337
Didier GuillemotEpidemiology and Modeling of bacterial Evasion to Antibacterials Unit (EMEA), Institut Pasteur, 25-28, Rue du Dr. Roux, 75724, Paris Cedex 15, France.ORCID http://orcid.org/0000-0002-8497-1765
Philippe TuppinFrench National Health Insurance (Cnam), 50 Avenue du Pr-André-Lemierre, 75986, Paris Cedex 20, France.ORCID http://orcid.org/0000-0001-5698-9215
Laurence WatierEpidemiology and Modeling of bacterial Evasion to Antibacterials Unit (EMEA), Institut Pasteur, 25-28, Rue du Dr. Roux, 75724, Paris Cedex 15, France. laurence.watier@inserm.fr.ORCID http://orcid.org/0000-0002-4057-1102
Inserm · FRConservatoire National des Arts et Métiers · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntibiotic resistance is increasing among urinary pathogens, resulting in worse clinical and economic outcomes. We analysed factors associated with antibiotic-resistant bacteria (ARB) in patients hospitalized for urinary tract infection, using the comprehensive French national claims database.

methodsHospitalized urinary tract infections were identified from 2015 to 2017. Cases (due to ARB) were matched to controls (without ARB) according to year, age, sex, infection, and bacterium. Healthcare-associated (HCAI) and community-acquired (CAI) infections were analysed separately; logistic regressions were stratified by sex.

resultsFrom 9460 cases identified, 6468 CAIs and 2855 HCAIs were matched with controls. Over a 12-months window, the risk increased when exposure occurred within the last 3 months. The following risk factors were identified: antibiotic exposure, with an OR reaching 3.6 [2.8-4.5] for men with CAI, mostly associated with broad-spectrum antibiotics; surgical procedure on urinary tract (OR 2.0 [1.5-2.6] for women with HCAI and 1.3 [1.1-1.6] for men with CAI); stay in intensive care unit > 7 days (OR 1.7 [1.2-2.6] for men with HCAI). Studied co-morbidities had no impact on ARB.

conclusionsThis study points out the critical window of 3 months for antibiotic exposure, confirms the impact of broad-spectrum antibiotic consumption on ARB, and supports the importance of prevention during urological procedures, and long intensive care unit stays.

Indexed as

Drug Resistance, BacterialAgedAged, 80 and overAnti-Bacterial AgentsCase-Control StudiesDrug PrescriptionsFemaleFranceHospitalizationHumansInsurance, HealthMaleMiddle AgedRisk FactorsUrinary Tract InfectionsAnti-Bacterial AgentsAdministrative claims databaseAntimicrobial resistanceMedico-administrative databaseRisk factors, antibiotic consumptionSNDSUrinary tract infections

Identifiers

PMID34126937
PMCPMC8201676
OpenAlexW3170775068

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.