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Pain-Track: a time-series approach for the description and analysis of the burden of pain
OBJECTIVE: To present the Pain-Track, a novel framework for the description and analysis of the pain experience based on its temporal evolution, around which intensity and other attributes of pain (texture, anatomy), interventions and clinical symptoms can be registered. This time-series approach ca...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8180079/ https://www.ncbi.nlm.nih.gov/pubmed/34090484 http://dx.doi.org/10.1186/s13104-021-05636-2 |
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author | Alonso, Wladimir J. Schuck-Paim, Cynthia |
author_facet | Alonso, Wladimir J. Schuck-Paim, Cynthia |
author_sort | Alonso, Wladimir J. |
collection | PubMed |
description | OBJECTIVE: To present the Pain-Track, a novel framework for the description and analysis of the pain experience based on its temporal evolution, around which intensity and other attributes of pain (texture, anatomy), interventions and clinical symptoms can be registered. This time-series approach can provide valuable insight on the expected evolution of the pain typically associated with different medical conditions and on time-varying (risk) factors associated with the temporal dynamics of pain. RESULTS: We illustrate the use of the framework to explore hypotheses on the temporal profile of the pain associated with an acute injury (bone fracture), and the magnitude of the pain burden it represents. We also show that, by focusing on the critical dimensions of the pain experience (intensity and time), the approach can help map different conditions to a common scale directly relating to the experiences of those who endure them (time in pain), providing the basis for the quantification of the burden of pain inflicted upon individuals or populations. An electronic version for data entry and interpretation is also presented. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13104-021-05636-2. |
format | Online Article Text |
id | pubmed-8180079 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81800792021-06-07 Pain-Track: a time-series approach for the description and analysis of the burden of pain Alonso, Wladimir J. Schuck-Paim, Cynthia BMC Res Notes Research Note OBJECTIVE: To present the Pain-Track, a novel framework for the description and analysis of the pain experience based on its temporal evolution, around which intensity and other attributes of pain (texture, anatomy), interventions and clinical symptoms can be registered. This time-series approach can provide valuable insight on the expected evolution of the pain typically associated with different medical conditions and on time-varying (risk) factors associated with the temporal dynamics of pain. RESULTS: We illustrate the use of the framework to explore hypotheses on the temporal profile of the pain associated with an acute injury (bone fracture), and the magnitude of the pain burden it represents. We also show that, by focusing on the critical dimensions of the pain experience (intensity and time), the approach can help map different conditions to a common scale directly relating to the experiences of those who endure them (time in pain), providing the basis for the quantification of the burden of pain inflicted upon individuals or populations. An electronic version for data entry and interpretation is also presented. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13104-021-05636-2. BioMed Central 2021-06-05 /pmc/articles/PMC8180079/ /pubmed/34090484 http://dx.doi.org/10.1186/s13104-021-05636-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Note Alonso, Wladimir J. Schuck-Paim, Cynthia Pain-Track: a time-series approach for the description and analysis of the burden of pain |
title | Pain-Track: a time-series approach for the description and analysis of the burden of pain |
title_full | Pain-Track: a time-series approach for the description and analysis of the burden of pain |
title_fullStr | Pain-Track: a time-series approach for the description and analysis of the burden of pain |
title_full_unstemmed | Pain-Track: a time-series approach for the description and analysis of the burden of pain |
title_short | Pain-Track: a time-series approach for the description and analysis of the burden of pain |
title_sort | pain-track: a time-series approach for the description and analysis of the burden of pain |
topic | Research Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8180079/ https://www.ncbi.nlm.nih.gov/pubmed/34090484 http://dx.doi.org/10.1186/s13104-021-05636-2 |
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