Evidence map›Paper›PMID 31214847›Full record

ReviewCurrent neurology and neuroscience reports2019

Structural Imaging in Parkinson's Disease: New Developments.

Stéphane Prange, Elise Metereau, Stéphane Thobois

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current neurology and neuroscience reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
3.0field-weighted citation impact, top 9% 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

24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 38 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Stéphane PrangeInstitut des Sciences Cognitives Marc Jeannerod, Université de Lyon, CNRS, UMR 5229, F-69675, Bron, France.
Elise MetereauInstitut des Sciences Cognitives Marc Jeannerod, Université de Lyon, CNRS, UMR 5229, F-69675, Bron, France.
Stéphane ThoboisInstitut des Sciences Cognitives Marc Jeannerod, Université de Lyon, CNRS, UMR 5229, F-69675, Bron, France. stephane.thobois@chu-lyon.fr.
Centre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewTo review the advances in structural imaging for the diagnosis, prognosis, and treatment of Parkinson's disease (PD) during the last 5 years. RECENT

findingsStructural imaging using high-field MRI (≥ 3 T) and new MR sequences sensitive to iron and nigral pigments have achieved to assess in vivo pathological surrogates useful for PD diagnosis (notably decreased nigral neuromelanin and loss of dorsal nigral hyperintensity, increased nigral iron content, diffusivity, and free-water), prodromal diagnosis (decreased neuromelanin signal in the locus coeruleus), and PD progression (with increasing nigral iron content (increasing R2* rate) and nigral damage (increasing free-water)). Additionally, evaluation of atrophy in small monoaminergic nuclei is useful for prognosis, including cholinergic basal forebrain nuclei atrophy for cognitive impairment. New advances in multimodal structural imaging improve diagnosis, prognosis, and prediction of invasive treatment outcome in PD, and may further benefit from machine learning and large scale longitudinal studies to better identify prognostic subtypes.

Indexed as

AgedAtrophyBasal GangliaBrainCognitive DysfunctionDisease ProgressionFemaleHumansIronLongitudinal StudiesMagnetic Resonance ImagingMaleMelaninsMiddle AgedParkinson DiseaseSubstantia NigraIronMelaninsneuromelaninMachine learningMRINeuromelaninParkinson’s diseaseProdromal diagnosis

Identifiers

PMID31214847
OpenAlexW2952350023

What OpenQuestion holds

Textmetadata
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.