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Quantitative Sensory Testing to Predict Postoperative Pain
PURPOSE OF REVIEW: We review the relevance of quantitative sensory testing (QST) in light of acute and chronic postoperative pain and associated challenges. RECENT FINDINGS: Predicting the occurrence of acute and chronic postoperative pain with QST can help identify patients at risk and allows proac...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808998/ https://www.ncbi.nlm.nih.gov/pubmed/33443676 http://dx.doi.org/10.1007/s11916-020-00920-5 |
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author | Braun, Matthias Bello, Corina Riva, Thomas Hönemann, Christian Doll, Dietrich Urman, Richard D. Luedi, Markus M. |
author_facet | Braun, Matthias Bello, Corina Riva, Thomas Hönemann, Christian Doll, Dietrich Urman, Richard D. Luedi, Markus M. |
author_sort | Braun, Matthias |
collection | PubMed |
description | PURPOSE OF REVIEW: We review the relevance of quantitative sensory testing (QST) in light of acute and chronic postoperative pain and associated challenges. RECENT FINDINGS: Predicting the occurrence of acute and chronic postoperative pain with QST can help identify patients at risk and allows proactive preventive management. Generally, central QST testing, such as temporal summation of pain (TSP) and conditioned pain modulation (CPM), appear to be the most promising modalities for reliable prediction of postoperative pain by QST. Overall, QST testing has the best predictive value in patients undergoing orthopedic procedures. SUMMARY: Current evidence underlines the potential of preoperative QST to predict postoperative pain in patients undergoing elective surgery. Implementing QST in routine preoperative screening can help advancing traditional pain therapy toward personalized perioperative pain medicine. |
format | Online Article Text |
id | pubmed-7808998 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-78089982021-01-21 Quantitative Sensory Testing to Predict Postoperative Pain Braun, Matthias Bello, Corina Riva, Thomas Hönemann, Christian Doll, Dietrich Urman, Richard D. Luedi, Markus M. Curr Pain Headache Rep Acute Pain Medicine (R Urman, Section Editor) PURPOSE OF REVIEW: We review the relevance of quantitative sensory testing (QST) in light of acute and chronic postoperative pain and associated challenges. RECENT FINDINGS: Predicting the occurrence of acute and chronic postoperative pain with QST can help identify patients at risk and allows proactive preventive management. Generally, central QST testing, such as temporal summation of pain (TSP) and conditioned pain modulation (CPM), appear to be the most promising modalities for reliable prediction of postoperative pain by QST. Overall, QST testing has the best predictive value in patients undergoing orthopedic procedures. SUMMARY: Current evidence underlines the potential of preoperative QST to predict postoperative pain in patients undergoing elective surgery. Implementing QST in routine preoperative screening can help advancing traditional pain therapy toward personalized perioperative pain medicine. Springer US 2021-01-14 2021 /pmc/articles/PMC7808998/ /pubmed/33443676 http://dx.doi.org/10.1007/s11916-020-00920-5 Text en © The Author(s) 2021 Open Access This 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/. |
spellingShingle | Acute Pain Medicine (R Urman, Section Editor) Braun, Matthias Bello, Corina Riva, Thomas Hönemann, Christian Doll, Dietrich Urman, Richard D. Luedi, Markus M. Quantitative Sensory Testing to Predict Postoperative Pain |
title | Quantitative Sensory Testing to Predict Postoperative Pain |
title_full | Quantitative Sensory Testing to Predict Postoperative Pain |
title_fullStr | Quantitative Sensory Testing to Predict Postoperative Pain |
title_full_unstemmed | Quantitative Sensory Testing to Predict Postoperative Pain |
title_short | Quantitative Sensory Testing to Predict Postoperative Pain |
title_sort | quantitative sensory testing to predict postoperative pain |
topic | Acute Pain Medicine (R Urman, Section Editor) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808998/ https://www.ncbi.nlm.nih.gov/pubmed/33443676 http://dx.doi.org/10.1007/s11916-020-00920-5 |
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