Evidence map›Paper›PMID 40093420›Full record

ArticlePeerJ2025

Clinical, molecular, and resistance features of

Yan Liu, Yuan Xie, Lei Liu, Jie Wang, Wenjing Li, Chengfan Yang, Shuhua Lu

Abstract read
In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

2 citing papers in PubMed.

  1. Article
  2. 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.

Yan Liu *Clinical Laboratory, Affiliated Hospital of Jining Medical University, Jining, Shandong, China.
Yuan Xie *Clinical Laboratory, Affiliated Hospital of Jining Medical University, Jining, Shandong, China.
Lei LiuShandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China.
Jie WangClinical Laboratory, Affiliated Hospital of Jining Medical University, Jining, Shandong, China.
Wenjing LiInstitute of Cerebrovascular Disease, Xianyang Hospital of Yan'an University, Xianyang, China.
Chengfan YangClinical Medicine, Jining Medical University, Jining, Shandong, China.
Shuhua LuClinical Laboratory, Affiliated Hospital of Jining Medical University, Jining, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Listeriosis, caused by Methods: This study included non-perinatal patients with listeriosis from four tertiary centers in Shandong, China. Data on demographics, clinical characteristics, and outcomes were collected retrospectively over 8 years (2015-2022). Results: Among 292,254 non-perinatal patients, 27 listeriosis cases were identified, resulting in an incidence of nine cases per 100,000 admissions. Patients had a median age of 56 years, with 66.7% having comorbidities. Fever was the most common symptom (88.9%), and 44.4% had central nervous system involvement. Most patients (26/24; 96.3%) received antibiotics, 37.0% received monotherapy and 59.3% combination therapy. The mortality rate was 22.2%. The antimicrobial susceptibility test showed that 25 strains were sensitive to most antibiotics. Multilocus sequence typing revealed nine sequence types (ST), predominantly ST8 (44.4%), and serogroup 1/2a is the most common serogroup (66.7%). Conclusions: This study provides valuable insights into the clinical and molecular features of

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialListeria monocytogenesListeriosisAdultAgedAged, 80 and overChinaFemaleHumansIncidenceMaleMicrobial Sensitivity TestsMiddle AgedMultilocus Sequence TypingRetrospective StudiesAnti-Bacterial AgentsInfectionListeria monocytogenesListeriosisMolecular featureNon-perinatal patients

Identifiers

PMID40093420
PMCPMC11908440

What OpenQuestion holds

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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.