Evidence map›Paper›PMID 36437996›Full record

ArticleFrontiers in aging neuroscience2022

Subtyping of early-onset Parkinson's disease using cluster analysis: A large cohort study.

Zhou Zhou, Xiaoxia Zhou, Yaqin Xiang, Yuwen Zhao, Hongxu Pan, Juan Wu, Qian Xu, Yase Chen, Qiying Sun, Xinyin Wu and 8 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 16% of its field
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

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Influence of the level of education on cognitive function in Parkinson's disease.Journal of neural transmission (Vienna, Austria : 1996) · 2026
    Article
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  4. Review
  5. The combination ofQuantitative imaging in medicine and surgery · 2024
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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

18 authors at 3 institutions in 1 country.

Zhou ZhouDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Xiaoxia ZhouDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Yaqin XiangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Yuwen ZhaoDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Hongxu PanDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Juan WuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Qian XuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Yase ChenDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Qiying SunDepartment of Geriatrics, Xiangya Hospital, Central South University, Changsha, China.
Xinyin WuDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Jianping ZhuHunan KeY Health Technology Co., Ltd., Changsha, China.
Xuehong WuHunan KeY Health Technology Co., Ltd., Changsha, China.
Jianhua LiHunan Creator Information Technology Co., Ltd., Changsha, China.
Xinxiang YanDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Jifeng GuoDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Beisha TangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Lifang LeiDepartment of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China.
Zhenhua LiuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Central South University · CNXiangya Hospital Central South University · CNHunan Provincial Science and Technology Department · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Increasing evidence suggests that early-onset Parkinson's disease (EOPD) is heterogeneous in its clinical presentation and progression. Defining subtypes of EOPD is needed to better understand underlying mechanisms, predict disease course, and eventually design more efficient personalized management strategies. Objective: To identify clinical subtypes of EOPD, assess the clinical characteristics of each EOPD subtype, and compare the progression between EOPD subtypes. Materials and methods: A total of 1,217 patients were enrolled from a large EOPD cohort of the Parkinson's Disease & Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC) between January 2017 and September 2021. A comprehensive spectrum of motor and non-motor features were assessed at baseline. Cluster analysis was performed using data on demographics, motor symptoms and signs, and other non-motor manifestations. In 454 out of total patients were reassessed after a mean follow-up time of 1.5 years to compare progression between different subtypes. Results: Three subtypes were defined: mild motor and non-motor dysfunction/slow progression, intermediate and severe motor and non-motor dysfunction/malignant. Compared to patients with mild subtype, patients with the severe subtype were more likely to have rapid eye movement sleep behavior disorder, wearing-off, and dyskinesia, after adjusting for age and disease duration at baseline, and showed a more rapid progression in Unified Parkinson's Disease Rating Scale (UPDRS) total score ( Conclusion: We identified three different clinical subtypes (mild, intermediate, and severe) using cluster analysis in a large EOPD cohort for the first time, which is important for tailoring therapy to individuals with EOPD.

Indexed as

cluster analysisearly-onset Parkinson’s diseaseheterogeneousPD-MDCNCsubtype

Identifiers

PMID36437996
PMCPMC9692000
OpenAlexW4308937496

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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.