Evidence map›Paper›PMID 39421091›Full record

ReviewCureus2024

Parkinson's Disease Treatment: A Bibliometric Analysis.

Billy McBenedict, Wilhelmina N Hauwanga, Gustavo Ienaco, Dulci Petrus, Syeda Sukaina Kazmi, Jonatha Machado Lima, Barakat B Onabanjo, Asaju Felix, Sujood Awadelseed, Shivadeva Selvamani and 2 more

Abstract readReview
In one paragraph

Review in Cureus, 2024. 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. Review
  2. Review
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

12 authors.

Billy McBenedictNeurosurgery, Fluminense Federal University, Niterói, BRA.
Wilhelmina N HauwangaFamily Medicine, Faculty of Medicine, Federal University of the State of Rio de Janeiro, Rio de Janeiro, BRA.
Gustavo IenacoMedicine, Fluminense Federal University, Niterói, BRA.
Dulci PetrusFamily Health, Directorate of Special Programs, Ministry of Health and Social Services, Windhoek, NAM.
Syeda Sukaina KazmiMedicine, Ziauddin University, Karachi, PAK.
Jonatha Machado LimaNeurosurgery, Fluminense Federal University, Niterói, BRA.
Barakat B OnabanjoNeurosurgery, Fluminense Federal University, Niterói, BRA.
Asaju FelixGeneral Practice, Dorset County Hospital, Dorchester, GBR.
Sujood AwadelseedNeurosurgery, Fluminense Federal University, Niterói, BRA.
Shivadeva SelvamaniMedicine, International Medical University, Kuala Lumpur, MYS.
Phoh Wen CherFamily Medicine, International Medical University, Kuala Lumpur, MYS.
Bruno Lima PessôaNeurosurgery, Fluminense Federal University, Niterói, BRA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by motor symptoms like bradykinesia, tremor, rigidity, and postural instability. Patients also experience non-motor symptoms that greatly affect their quality of life. The global prevalence of PD is increasing, especially among the elderly, necessitating effective treatment strategies. This review provides an overview of the current treatment modalities for PD, including pharmacological and surgical interventions, and employs a bibliometric analysis to evaluate the trends and impact of scientific research in this field. A comprehensive search of the Web of Science Core Collection (WoSCC) database was conducted on July 12, 2024, yielding 3,724 publications related to PD treatment. Bibliometric analysis was performed using Biblioshiny and VOSviewer to assess publication trends, impact, and collaborative networks. Metrics such as the number of publications, citations, h-index, and country/institutional contributions were analyzed to identify key areas of focus and influential research in PD treatment. The analysis revealed a significant increase in PD research output from 2000 onwards, peaking between 2011 and 2016. The United States led in research production, followed by China, Canada, and the United Kingdom. Key researchers included Lang AE, Okun MS, and Lozano AM, with the University of Toronto, University of California System, and Harvard University being the top contributing institutions. The study identified major trends in pharmacological treatments, such as dopamine replacement therapy and deep brain stimulation (DBS) as the most common surgical intervention. Bibliometric analysis highlighted significant international collaborations and identified influential studies shaping the current understanding and treatment of PD. This bibliometric analysis elucidated the trends and impacts of scientific contributions, emphasizing the prolific output from leading countries and institutions in relation to the treatment of Parkinson's disease. Take-home messages for the conclusion of our study are as follows: (1) this study found a substantial increase in Parkinson's disease (PD) research output from 2000 onwards, peaking around 2017-2018, (2) noted a decline in publication output post-2020, (3) the United States had the highest research output, followed by significant contributions from countries like China, Canada, and the United Kingdom, (4) international collaborations played a vital role in advancing PD research, (5) key researchers in the field were Lang AE, Okun MS, and Lozano AM, (6) and established institutions like the University of Toronto, Johns Hopkins University and Harvard University made substantial contributions to the field, emphasizing the role of leading academic centers in driving PD research.

Indexed as

bibliometric analysisdeep brain stimulationneurodegenerative disordersparkinson's diseaseresearch trends

Identifiers

PMID39421091
PMCPMC11486509

What OpenQuestion holds

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LicenceCC BY
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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.