Evidence map›Paper›PMID 34140784›Full record

ArticleInfection and drug resistance2021

Microbial Spectrum and Resistance Patterns in Ocular Infections: A 15-Year Review in East China.

Chunhong Liu, Baixing Ding, Jian Ji, Zhujian Wang, Huiwen Chen, Wenjun Cao

Open access · goldAbstract read
In one paragraph

Article in Infection and drug resistance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 32% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
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

6 authors at 2 institutions in 1 country.

Chunhong Liu *Clinical Laboratory, Eye & ENT Hospital, Fudan University, Shanghai, People's Republic of China.
Baixing Ding *Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, People's Republic of China.
Jian JiClinical Laboratory, Eye & ENT Hospital, Fudan University, Shanghai, People's Republic of China.
Zhujian WangClinical Laboratory, Eye & ENT Hospital, Fudan University, Shanghai, People's Republic of China.
Huiwen ChenClinical Laboratory, Eye & ENT Hospital, Fudan University, Shanghai, People's Republic of China.
Wenjun CaoClinical Laboratory, Eye & ENT Hospital, Fudan University, Shanghai, People's Republic of China.
Eye & ENT Hospital of Fudan University · CNFudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo report antibiotic resistance rates and trends of common ocular isolates collected over a 15-year period.

methodsWe collected 3533 isolates from July 1, 2005 to July 31, 2020. Antibiotic sensitivity was determined according to the guidelines of the Clinical and Laboratory Standards Institute. Chi-squared (

resultsAmong the 3533 isolates, the predominant pathogens were the staphylococcal species. Methicillin resistance was observed in 381

conclusionStaphylococci were the most common microorganisms responsible for causing ocular infections. Antibiotic resistance was high among staphylococci, with nearly half of these isolates were resistant to methicillin and these had a high probability of concurrent resistance among MR staphylococci to other antibiotics. Overall, ocular resistance did not significantly change during the 15-year study period. We conclude that continued surveillance of antibiotic resistance provides critical data to guide antibiotic selection.

Indexed as

antibiotic resistancemethicillinocular isolatestaphylococci

Identifiers

PMID34140784
PMCPMC8203601
OpenAlexW3168001300

What OpenQuestion holds

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LicenceCC BY-NC
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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.