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The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis
BACKGROUND: Neuromodulation 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 psychia...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531015/ https://www.ncbi.nlm.nih.gov/pubmed/33071769 http://dx.doi.org/10.3389/fninf.2020.00036 |
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author | Hedges, David M. Hegman, John C. Brown, Jefferson R. Wilburn, Jack T. Chapman, Brian E. Butson, Christopher R. |
author_facet | Hedges, David M. Hegman, John C. Brown, Jefferson R. Wilburn, Jack T. Chapman, Brian E. Butson, Christopher R. |
author_sort | Hedges, David M. |
collection | PubMed |
description | BACKGROUND: Neuromodulation 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. OBJECTIVE: In 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. METHODS: This 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. RESULTS: The 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. CONCLUSION: Ultimately, we believe that widespread adoption of the INR platform will improve population health research in neuromodulation therapy. |
format | Online Article Text |
id | pubmed-7531015 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75310152020-10-17 The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis Hedges, David M. Hegman, John C. Brown, Jefferson R. Wilburn, Jack T. Chapman, Brian E. Butson, Christopher R. Front Neuroinform Neuroscience BACKGROUND: Neuromodulation 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. OBJECTIVE: In 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. METHODS: This 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. RESULTS: The 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. CONCLUSION: Ultimately, we believe that widespread adoption of the INR platform will improve population health research in neuromodulation therapy. Frontiers Media S.A. 2020-09-18 /pmc/articles/PMC7531015/ /pubmed/33071769 http://dx.doi.org/10.3389/fninf.2020.00036 Text en Copyright © 2020 Hedges, Hegman, Brown, Wilburn, Chapman and Butson. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Hedges, David M. Hegman, John C. Brown, Jefferson R. Wilburn, Jack T. Chapman, Brian E. Butson, Christopher R. The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis |
title | The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis |
title_full | The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis |
title_fullStr | The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis |
title_full_unstemmed | The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis |
title_short | The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis |
title_sort | international neuromodulation registry: an informatics framework supporting cohort discovery and analysis |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531015/ https://www.ncbi.nlm.nih.gov/pubmed/33071769 http://dx.doi.org/10.3389/fninf.2020.00036 |
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