Evidence map›Paper›PMID 35517901›Full record

ArticleInfection and drug resistance2022

Carbapenem Resistant

Jie Qin, Chengyun Zou, Jianmin Tao, Tian Wei, Li Yan, Yufei Zhang, Haiying Wang

Abstract 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 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Antimicrobial Susceptibility ofAntibiotics (Basel, Switzerland) · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Predictors of Mortality, Drug Resistance, and Determinants among Carbapenem-ResistantThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2024
    Article
  15. Article
  16. Review
  17. Machine Learning Techniques for Antimicrobial Resistance Prediction ofComputational intelligence and neuroscience · 2023
    Article
  18. Evolving trends amongFrontiers in public health · 2023
    Article
  19. Article
  20. Detection of Antibiotic Resistance Genes inInfection and drug resistance · 2022
    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

7 authors.

Jie QinDepartment of Clinical Laboratory, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.ORCID 0000-0002-5000-5817
Chengyun ZouDepartment of Medical Technology, Yueyang Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.
Jianmin TaoDepartment of Clinical Laboratory, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.
Tian WeiDepartment of Clinical Laboratory, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.
Li YanDepartment of Clinical Laboratory, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.
Yufei ZhangDepartment of Medical Technology, Yueyang Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.ORCID 0000-0003-0449-9446
Haiying WangDepartment of Clinical Laboratory, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The prevalence and clinical impact on mortality of carbapenem-resistant Methods: A retrospective study of 600 elderly inpatients infected with Results: Of 600 Conclusion: The study revealed high rates of CRPA, MDR PA among the hospitalized elderly patient with

Indexed as

carbapenem-resistantinfectionmortalityPseudomonas aeruginosarisk factors

Identifiers

PMID35517901
PMCPMC9064054

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.