Evidence map›Paper›PMID 39367337›Full record

ReviewInternational journal of emergency medicine2024

Bibliometric analysis of depression in post-stroke patients.

Dehao Zheng, Sydney Vaughn, Murdoc Gould, Latha Ganti

Abstract readReview
In one paragraph

Review in International journal of emergency medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Dehao ZhengTrinity Preparatory School, Winter Park, Fl, USA.
Sydney VaughnBrown University, Providence, Rhode Island, USA.
Murdoc GouldBirkbeck, University College London, London, UK.
Latha GantiOrlando College of Osteopathic Medicine, Winter, FL, 34787, USA. lganti@ocom.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionStroke is a life-threatening condition that increasingly damages cerebral tissue over time and can lead to serious post-effects, including depression, which can hinder a patient's recovery from stroke and reduce quality of life. This paper aims to analyze the global research landscape of post-stroke depression (PSD) between the years 1900 to 2024 using bibliometric analysis.

methodsThe data used in this analysis was collected from the Web of Science Core Collection (WoSCC). An advanced search was performed using the keywords, "stroke" and "depression," on July 8th, 2024. From the Web of Science, bibliometric data was then extracted and analyzed in VOSviewer through four categories: countries, number of publications, keywords, and journals.

resultsThe bibliometric analysis resulted in 2,289 publications from the year 1900 to 2024. A gradual increase in the number of publications on post-stroke depression over the study period was observed. China was found to be the leading country for publications and funding on PSD, with the United States following in second. The top keywords included: "stroke," "depression," and "poststroke depression." The Journal of Stroke had the highest number of publications on depression in post-stroke patients.

conclusionThis study provides an overview of the current trends in articles published on PSD. Depression is an important topic to be considered in post-stroke patients due to its negative effects on post-stroke recovery and reduced quality of life, necessitating a call to attention and support for future research in this field. With continued research efforts led by the United States and China, improved treatments for patients with post-stroke depression can be implemented.

Indexed as

Bibliometric analysisPost-stroke depression

Identifiers

PMID39367337
PMCPMC11452956

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.