Evidence map›Paper›PMID 33071769›Full record

ArticleFrontiers in neuroinformatics2020

The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis.

David M Hedges, John C Hegman, Jefferson R Brown, Jack T Wilburn, Brian E Chapman, Christopher R Butson

Abstract read
In one paragraph

Article in Frontiers in neuroinformatics, 2020. 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.

No citing paper in PubMed yet.

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

6 authors.

David M HedgesScientific Computing and Imaging (SCI) Institute, The University of Utah, Salt Lake City, UT, United States.
John C HegmanScientific Computing and Imaging (SCI) Institute, The University of Utah, Salt Lake City, UT, United States.
Jefferson R BrownScientific Computing and Imaging (SCI) Institute, The University of Utah, Salt Lake City, UT, United States.
Jack T WilburnScientific Computing and Imaging (SCI) Institute, The University of Utah, Salt Lake City, UT, United States.
Brian E ChapmanDepartment of Biomedical Informatics, The University of Utah, Salt Lake City, UT, United States.
Christopher R ButsonScientific Computing and Imaging (SCI) Institute, The University of Utah, Salt Lake City, UT, United States.

Funding

TRD - VisualizationP41GM103545 · NIGMS · UNIVERSITY OF UTAH · PI JOHNSON, CHRISTOPHER R., MACLEOD, ROB S. · 2012 to 2019
$9.7M
Mobile Decision Support System for Nurse Management of Neuromodulation TherapyR01NR014852 · NINR · UNIVERSITY OF UTAH · PI BUTSON, CHRISTOPHER R, OKUN, MICHAEL S · 2015 to 2019
$2.9M
From genomics to natural language processing: A protected environment for research computing in the health scienceS10OD021644 · OD · UNIVERSITY OF UTAH · PI CHEATHAM, THOMAS E. · 2017 to 2017
$494k
NIGMS NIH HHS P41 GM103545NIH HHS S10 OD021644NINR NIH HHS R01 NR014852
6 · The paper itself

Abstract

backgroundNeuromodulation therapies, such as deep brain stimulation (DBS), spinal cord stimulation (SCS), responsive neurostimulation (RNS), transcranial magnetic stimulation (TMS), transcranial direct stimulation (tDCS), and vagus nerve stimulation (VNS) are used to treat neurological and psychiatric conditions for patients who have failed to benefit from other treatment approaches. Although generally effective, seemingly similar cases often have very different levels of effectiveness. While there is ongoing interest in developing predictors, it can be difficult to aggregate the necessary data from limited cohorts of patients at individual treatment centers.

objectiveIn order to increase the predictive power in neuromodulation studies, we created an informatics platform called the International Neuromodulation Registry (INR). The INR platform has a data flow process that will allow researchers to pool data across multiple centers to enable population health research.

methodsThis custom informatics platform has a Neo4j graph database and includes a harmonization process that allows data from different studies to be aggregated and compared. Users of the INR can download deidentified patient imaging, patient demographic data, device settings, and medical rating scales. The INR supports complex network analysis and patient timeline visualization.

resultsThe INR currently houses and allows visualization of deidentified imaging and clinical data from hundreds of patients with a wide range of diagnoses and neuromodulation therapies.

conclusionUltimately, we believe that widespread adoption of the INR platform will improve population health research in neuromodulation therapy.

Indexed as

deep brain stimulationgraph databaseresponsive neurostimulationspinal cord stimulationtranscranial magnetic stimulation

Identifiers

PMID33071769
PMCPMC7531015

What OpenQuestion holds

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LicenceCC BY
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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.