Evidence map›Paper›PMID 40527913›Full record

ArticleNPJ Parkinson's disease2025

Wrist accelerometry and machine learning sensitively capture disease progression in prodromal Parkinson's disease.

Anoopum S Gupta, Siddharth Patel

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ Parkinson's disease, 2025. 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. 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

2 authors.

Anoopum S GuptaDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. agupta@mgh.harvard.edu.
Siddharth PatelDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Funding

A Computational Approach for Quantifying Motor Behaviors in Spinocerebellar Ataxias to Improve Early Detection of Motor Signs and Precisely Estimate Disease Severity and Disease ChangeR01NS117826 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI GUPTA, ANOOPUM SATYAWAN · 2021 to 2025
$2.7M
Development of Real-World Motor Outcome Measures in Ataxia-TelangiectasiaR01NS134597 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Anoopum Satyawan Gupta · 2024 to 2026
$1.9M
NINDS NIH HHS NS117826NINDS NIH HHS R01 NS117826NINDS NIH HHS R01 NS134597
6 · The paper itself

Abstract

Sensitive motor measures are needed to support trials in Parkinson's disease (PD). Wrist sensor data was collected continuously at home from 269 individuals with PD (106 with prodromal PD). Submovements were smaller, slower, and less variable in PD and prodromal PD. A machine-learned composite measure captured disease progression in prodromal PD more sensitively than the MDS-UPDRS Part III motor score. Wearable sensor-based measures may be useful in upcoming clinical trials.

Identifiers

PMID40527913
PMCPMC12174331

What OpenQuestion holds

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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.