Evidence map›Paper›PMID 39193522›Full record

ArticleFrontiers in neuroscience2024

Metabolite profile in hereditary spastic paraplegia analyzed using magnetic resonance spectroscopy: a cross-sectional analysis in a longitudinal study.

Domenico Montanaro, Marinela Vavla, Francesca Frijia, Alessio Coi, Alessandra Baratto, Rosa Pasquariello, Cristina Stefan, Andrea Martinuzzi

Abstract read
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Article in Frontiers in neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Domenico MontanaroU.O. Dipartimentale e Servizio Autonomo di Risonanza Magnetica, Dipartimento di Neuroscienze dell'Età Evolutiva, IRCCS Fondazione Stella Maris, Pisa, Italy.
Marinela VavlaChild and Adolescent Neuropsychiatric Unit, Department of Women's and Children's Health, University Hospital of Padua, Padova, Italy.
Francesca FrijiaBioengineering Unit, Fondazione Toscana G. Monasterio, Pisa, Italy.
Alessio CoiUnit of Epidemiology of Rare Diseases and Congenital Anomalies, Institute of Clinical Physiology, National Research Council, Pisa, Italy.
Alessandra BarattoDepartment of Radiology, S. Maria dei Battuti Hospital- Conegliano, Treviso, Italy.
Rosa PasquarielloU.O. Dipartimentale e Servizio Autonomo di Risonanza Magnetica, Dipartimento di Neuroscienze dell'Età Evolutiva, IRCCS Fondazione Stella Maris, Pisa, Italy.
Cristina StefanDepartment of Neurorehabilitation, IRCCS E. Medea Scientific Institute, Conegliano, Italy.
Andrea MartinuzziDepartment of Neurorehabilitation, IRCCS E. Medea Scientific Institute, Conegliano, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hereditary Spastic Paraplegias (HSP) are genetic neurodegenerative disorders affecting the corticospinal tract. No established neuroimaging biomarker is associated with this condition. Methods: A total of 46 patients affected by HSP, genetically and clinically evaluated and tested with SPRS scores, and 46 healthy controls (HC) matched by age and gender underwent a single-voxel Magnetic Resonance Spectroscopy sampling (MRS) of bilateral pre-central and pre-frontal regions. MRS data were analyzed cross-sectionally (at T Results: Statistically significant data showed that T Conclusion: This pilot study indicates that brain MRS is a valuable approach that could potentially serve as an objective biomarker in HSP.

Indexed as

conditional inference tree methodcross sectional analysisishereditary spastic paraplegias (HSP)longitudinal analysismagnetic resonance spectroscopy (MRS)pre-frontalSPRS

Identifiers

PMID39193522
PMCPMC11347332

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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.