Quantifying Pain Location and Intensity with Multimodal Pain Body Diagrams.


Journal

Journal of visualized experiments : JoVE
ISSN: 1940-087X
Titre abrégé: J Vis Exp
Pays: United States
ID NLM: 101313252

Informations de publication

Date de publication:
07 07 2023
Historique:
medline: 25 7 2023
pubmed: 24 7 2023
entrez: 24 7 2023
Statut: epublish

Résumé

To quantify an individual's subjective pain severity, standardized pain rating scales such as the numeric rating scale (NRS), visual analog scale (VAS), or McGill pain questionnaire (MPQ) are commonly used to assess pain on a numerical scale. However, these scales are often biased and fail to capture the complexity of pain experiences. In contrast, clinical practice often requires patients to report areas of pain by drawing on a body diagram, which is an effective but qualitative tool. The method presented here extracts quantifiable metrics from pain body diagrams (PBDs) which are validated against the NRS, VAS, and MPQ pain scales. By using a novel pressure-hue transformation on a digital tablet, different drawing pressures applied with a digital stylus can be represented as different hues on a PBD. This produces a visually intuitive diagram of hues ranging from green to blue to red, representing mild to moderate to most painful regions, respectively. To quantify each PBD, novel pain metrics were defined: (1) PBD mean intensity, which equals the sum of each pixel's hue value divided by the number of colored pixels, (2) PBD coverage, which equals the number of colored pixels divided by the total number of pixels on the body, and (3) PBD sum intensity, which equals the sum of all pixels' hue values. Using correlation and information theory analyses, these PBD metrics were shown to have high concordance with standardized pain metrics, including NRS, VAS and MPQ. In conclusion, PBDs can provide novel spatial and quantitative information that can be repeatedly measured and tracked over time to comprehensively characterize a participant's pain experience.

Identifiants

pubmed: 37486137
doi: 10.3791/65334
doi:

Types de publication

Journal Article Video-Audio Media Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NINDS NIH HHS
ID : UH3 NS115631
Pays : United States

Auteurs

Jereen Kwong (J)

Anesthesiology (Division of Pain Management), University of California, San Francisco.

Joanna Lin (J)

Neurological Surgery and UCSF Weill Institute of Neurosciences, University of California, San Francisco.

Ryan Leriche (R)

Neurological Surgery and UCSF Weill Institute of Neurosciences, University of California, San Francisco.

Thomas A Wozny (TA)

Neurological Surgery and UCSF Weill Institute of Neurosciences, University of California, San Francisco.

Ana Shaughnessy (A)

Neurological Surgery and UCSF Weill Institute of Neurosciences, University of California, San Francisco.

Ashlyn Schmitgen (A)

Neurological Surgery and UCSF Weill Institute of Neurosciences, University of California, San Francisco.

Prasad Shirvalkar (P)

Anesthesiology (Division of Pain Management) and Neurological Surgery and UCSF Weill Institute of Neurosciences, University of California, San Francisco; Prasad.Shirvalkar@ucsf.edu.

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