Evidence map›Paper›PMID 38343821›Full record

ArticleResearch square2024

Quantitative DigitoGraphy: a Comprehensive Real-Time Remote Monitoring System for Parkinson's Disease.

Shannon L Hoffman, Paul Schmiedmayer, Aryaman S Gala, Kevin B Wilkins, Laura Parisi, Shreesh Karjagi, Aarushi S Negi, Simon Revlock, Christopher Coriz, Jeremy Revlock and 2 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 2 countries.

Shannon L HoffmanDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA.
Paul SchmiedmayerStanford Byers Center for Biodesign, Stanford University, Stanford, CA.ORCID 0000-0002-8607-9148
Aryaman S GalaDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA.
Kevin B WilkinsDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA.
Laura ParisiDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA.
Shreesh KarjagiDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA.ORCID 0009-0000-5793-8022
Aarushi S NegiDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA.
Simon RevlockFastlane Creations, Encinitas, CA.
Christopher CorizDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA.
Jeremy RevlockDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA.
Vishnu RaviStanford Byers Center for Biodesign, Stanford University, Stanford, CA.ORCID 0000-0003-0359-1275
Helen Bronte-StewartDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA.
Stanford University · USStanford Medicine · USSensor Creations (United States) · US

Funding

Stanford Alzheimer's Disease Research CenterAdmin Supp: Developing iPSC models for AD and PDP30AG066515 · NIA · STANFORD UNIVERSITY · PI ELIZABETH MORMINO · 2020 to 2026
$29.0M
Neurodegeneration and Brain Function in Aging with HIV and Parkinson's DiseaseR01AA023165 · NIAAA · SRI INTERNATIONAL · PI SCHULTE, TILMAN · 2014 to 2017
$3.0M
NIAAA NIH HHS R01 AA023165NIA NIH HHS P30 AG066515
6 · The paper itself

Abstract

People with Parkinson's disease (PWP) face critical challenges, including lack of access to neurological care, inadequate measurement and communication of motor symptoms, and suboptimal medication management and compliance. We have developed QDG-Care: a comprehensive connected care platform for Parkinson's disease (PD) that delivers validated, quantitative metrics of all motor signs in PD in real time, monitors the effects of adjusting therapy and medication adherence and is accessible in the electronic health record. In this article, we describe the design and engineering of all components of QDG-Care, including the development and utility of the QDG Mobility and Tremor Severity Scores. We present the preliminary results and insights from the first at-home trial using QDG-Care. QDG technology has enormous potential to improve access to, equity of, and quality of care for PWP, and improve compliance with complex time-critical medication regimens. It will enable rapid "Go-NoGo" decisions for new therapeutics by providing high-resolution data that require fewer participants at lower cost and allow more diverse recruitment.

Identifiers

PMID38343821
PMCPMC10854288
OpenAlexW4391151359

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.