Evidence map›Paper›PMID 40025442›Full record

SynthesisBMC psychiatry2025

Quantitative analysis of literature on diagnostic biomarkers of Schizophrenia: revealing research hotspots and future prospects.

Liuyin Jin, Linman Wu, Jing Zhang, Wenxin Jia, Han Zhou, Shulan Jiang, Pengju Jiang, Yingfang Li, Yang Li

Abstract readSystematic Review
In one paragraph

Synthesis in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 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

9 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. 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

9 authors.

Liuyin Jin *The Second People'S Hospital of Lishui, Lishui, China.
Linman Wu *Nanchong Mental Health Center of Sichuan Province, Nanchong, China.
Jing ZhangThe Second People'S Hospital of Lishui, Lishui, China.
Wenxin JiaThe Second People'S Hospital of Lishui, Lishui, China.
Han ZhouSchool of Mental Health, Wenzhou Medical University, Wenzhou, China.
Shulan JiangSchool of Mental Health, Wenzhou Medical University, Wenzhou, China.
Pengju JiangThe Second People'S Hospital of Lishui, Lishui, China.
Yingfang LiThe Second People'S Hospital of Lishui, Lishui, China.
Yang LiThe Second People'S Hospital of Lishui, Lishui, China. 18857806945@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSchizophrenia (SCZ) is a complex mental disorder characterized by a wide range of symptoms and cognitive impairments. The search for reliable biomarkers for SCZ has gained increasing attention in recent years, as they hold the potential to improve early diagnosis and intervention strategies. To understand the research trends and collaborations in this field, a comprehensive Bibliometric analysis of SCZ and biomarkers research was conducted.

methodsA systematic search of the Web of Science Core Collection was performed to retrieve relevant articles published from January 2000 to July 2023. The search focused on SCZ and biomarkers. Bibliometric tools, including CiteSpace, VOSviewer, and R package Bibliometrix, were utilized to perform data extraction, quantitative analysis, and visualization.

resultsThe search focused on SCZ and biomarkers, and a total of 2935 articles were included in the analysis. The analysis revealed a gradual increase in the number of publications related to SCZ and biomarkers over the years, indicating a growing research focus in this area. Collaboration and research activity were found to be concentrated in the United States and Western European countries. Among the top ten most active journals, "Schizophrenia Research" emerged as the journal with the highest number of publications and citations related to SCZ and biomarkers. Recent studies published in this journal have highlighted the potential use of facial expressions as a diagnostic biomarker for SCZ, suggesting that facial expression analysis using big data may hold promise for future diagnosis and interventions. Furthermore, the analysis of key research keywords identified inflammatory factors, DNA methylation changes, and glutamate alterations as potential biomarkers for SCZ diagnosis.

conclusionThis Bibliometric analysis provides valuable insights into the current state of research on SCZ and biomarkers. The identification of reliable biomarkers for SCZ could have significant implications for early diagnosis and interventions, potentially leading to improved outcomes for individuals affected by this challenging mental disorder. Further research and collaborations in this field are encouraged to advance our understanding of SCZ and enhance diagnostic and therapeutic approaches.

Indexed as

BibliometricsBiomarkersBiomedical ResearchSchizophreniaHumansBiomarkersBibliometricsBiomarkersCiteSpaceSCZVOSviewer

Identifiers

PMID40025442
PMCPMC11872302

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.