Evidence map›Paper›PMID 36313023›Full record

ArticleFrontiers in aging neuroscience2022

Monocytohigh-density lipoprotein ratio has a high predictive value for the diagnosis of multiple system atrophy and the differentiation from Parkinson's disease.

Lijuan Jiang, Zhen Zhong, Juan Huang, Hetao Bian, Wei Huang

Abstract 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 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  18. Inflammation in multiple system atrophy.Frontiers in immunology · 2023
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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

5 authors.

Lijuan JiangDepartment of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Zhen ZhongDepartment of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Juan HuangDepartment of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Hetao BianDepartment of Neurology, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China.
Wei HuangDepartment of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: Inflammation is closely related to the pathogenesis of multiple system atrophy (MSA). As markers of inflammation, the monocyte to high-density lipoprotein ratio (MHR), neutrophil to lymphocyte ratio (NLR), and red cell distribution width to platelet ratio (RPR) have been proven to be associated with a large variety of diseases. The aim of this study was to explore the association between inflammatory markers (MHR, NLR, and RPR) and MSA, and the difference between MSA and Parkinson's disease (PD) was further compared by these inflammatory markers. Materials and methods: This study was divided into three groups: 47 patients with MSA, 125 patients with PD, and 124 healthy controls. The corresponding laboratory indicators of subjects were collected and analyzed to obtain MHR, NLR, and RPR values. Results: Compared with healthy controls, the MHR, NLR, and RPR were higher in the MSA group ( Conclusion: There may be peripheral inflammation in patients with MSA. Compared with NLR and RPR, MHR has higher predictive value for the diagnosis and differential diagnosis of MSA.

Indexed as

monocyte to high-density lipoprotein ratiomultiple system atrophyneutrophil to lymphocyte ratioParkinson’s diseaseperipheral inflammationred cell distribution width to platelet ratio

Identifiers

PMID36313023
PMCPMC9607904

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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.