Evidence map›Paper›PMID 36345539›Full record

ArticleInfection and drug resistance2022

Analysis of the Distribution and Drug Resistance of Pathogens in Patients with Urinary Tract Infection in the Eastern Chongming Area of Shanghai from 2018 to 2020.

Jing Li, Feifei Jiang, An Xie, Yufeng Jiang

Open access · goldAbstract read
In one paragraph

Article in Infection and drug resistance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Global prevalence of fluoroquinolone resistance inFrontiers in cellular and infection microbiology · 2026
    Pooled it
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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

4 authors at 2 institutions in 1 country.

Jing LiDepartment of Urology, Chongming Branch of Shanghai Tenth People's Hospital, Shanghai, Tongji University School of Medicine, Shanghai, 202157, People's Republic of China.
Feifei JiangDepartment of Clinical Laboratory, Chongming Branch of Shanghai Tenth People's Hospital, Shanghai, Tongji University School of Medicine, Shanghai, 202157, People's Republic of China.
An XieDepartment of Nosocomial Infection Control, Chongming Branch of Shanghai Tenth People's Hospital, Shanghai, Tongji University School of Medicine, Shanghai, 202157, People's Republic of China.
Yufeng JiangDepartment of Urology, Chongming Branch of Shanghai Tenth People's Hospital, Shanghai, Tongji University School of Medicine, Shanghai, 202157, People's Republic of China.
Shanghai Tenth People's Hospital · CNTongji University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The aim of this study was to clarify the distribution and drug resistance of pathogens causing urinary tract infection (UTI) and to provide a scientific reference for the rational application of antibiotics. Patients and Methods: The results of bacterial identification and drug sensitivity analysis of midstream urine samples in our hospital from January 2018 to December 2020 were retrospectively analyzed. The data were analyzed using WHONET 5.6 and SPSS 26.0 (IBM) software. Results: In all, 1786 pathogens were isolated from 13,141 midstream urine culture samples. Of these, 1093 (61.2%) were gram-negative bacteria, mainly Conclusion: The pathogens that cause UTIs in patients are diverse, with the most common being

Indexed as

antibiotic resistanceantimicrobial agentmidstream urine culturepathogenic bacteria distributionurinary tract infections

Identifiers

PMID36345539
PMCPMC9636864
OpenAlexW4308012305

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.