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Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB(3)P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh
As a member of the Back Pain Consortium (BACPAC), the University of Pittsburgh Mechanistic Research Center's research goal is to phenotype chronic low back pain using biological, biomechanical, and behavioral domains using a prospective, observational cohort study. Data will be collected from 1...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403299/ https://www.ncbi.nlm.nih.gov/pubmed/36715642 http://dx.doi.org/10.1093/pm/pnad009 |
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author | Vo, Nam V Piva, Sara R Patterson, Charity G McKernan, Gina P Zhou, Leming Bell, Kevin M Anderst, William Greco, Carol M Schneider, Michael J Delitto, Anthony Dicianno, Brad E Darwin, Jessa Sowa, Gwendolyn A |
author_facet | Vo, Nam V Piva, Sara R Patterson, Charity G McKernan, Gina P Zhou, Leming Bell, Kevin M Anderst, William Greco, Carol M Schneider, Michael J Delitto, Anthony Dicianno, Brad E Darwin, Jessa Sowa, Gwendolyn A |
author_sort | Vo, Nam V |
collection | PubMed |
description | As a member of the Back Pain Consortium (BACPAC), the University of Pittsburgh Mechanistic Research Center's research goal is to phenotype chronic low back pain using biological, biomechanical, and behavioral domains using a prospective, observational cohort study. Data will be collected from 1,000 participants with chronic low back pain according to BACPAC-wide harmonized and study-specific protocols. Participation lasts 12 months with one required in person baseline visit, an optional second in person visit for advanced biomechanical assessment, and electronic follow ups at months 1, 2, 3, 4, 5, 6, 9, and 12 to assess low back pain status and response to prescribed treatments. Behavioral data analysis includes a battery of patient-reported outcomes, social determinants of health, quantitative sensory testing, and physical activity. Biological data analysis includes omics generated from blood, saliva, and spine tissue. Biomechanical data analysis includes a physical examination, lumbopelvic kinematics, and intervertebral kinematics. The statistical analysis includes traditional unsupervised machine learning approaches to categorize participants into groups and determine the variables that differentiate patients. Additional analysis includes the creation of a series of decision rules based on baseline measures and treatment pathways as inputs to predict clinical outcomes. The characteristics identified will contribute to future studies to assist clinicians in designing a personalized, optimal treatment approach for each patient. |
format | Online Article Text |
id | pubmed-10403299 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-104032992023-08-05 Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB(3)P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh Vo, Nam V Piva, Sara R Patterson, Charity G McKernan, Gina P Zhou, Leming Bell, Kevin M Anderst, William Greco, Carol M Schneider, Michael J Delitto, Anthony Dicianno, Brad E Darwin, Jessa Sowa, Gwendolyn A Pain Med Original Research Article As a member of the Back Pain Consortium (BACPAC), the University of Pittsburgh Mechanistic Research Center's research goal is to phenotype chronic low back pain using biological, biomechanical, and behavioral domains using a prospective, observational cohort study. Data will be collected from 1,000 participants with chronic low back pain according to BACPAC-wide harmonized and study-specific protocols. Participation lasts 12 months with one required in person baseline visit, an optional second in person visit for advanced biomechanical assessment, and electronic follow ups at months 1, 2, 3, 4, 5, 6, 9, and 12 to assess low back pain status and response to prescribed treatments. Behavioral data analysis includes a battery of patient-reported outcomes, social determinants of health, quantitative sensory testing, and physical activity. Biological data analysis includes omics generated from blood, saliva, and spine tissue. Biomechanical data analysis includes a physical examination, lumbopelvic kinematics, and intervertebral kinematics. The statistical analysis includes traditional unsupervised machine learning approaches to categorize participants into groups and determine the variables that differentiate patients. Additional analysis includes the creation of a series of decision rules based on baseline measures and treatment pathways as inputs to predict clinical outcomes. The characteristics identified will contribute to future studies to assist clinicians in designing a personalized, optimal treatment approach for each patient. Oxford University Press 2023-01-30 /pmc/articles/PMC10403299/ /pubmed/36715642 http://dx.doi.org/10.1093/pm/pnad009 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the American Academy of Pain Medicine. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Article Vo, Nam V Piva, Sara R Patterson, Charity G McKernan, Gina P Zhou, Leming Bell, Kevin M Anderst, William Greco, Carol M Schneider, Michael J Delitto, Anthony Dicianno, Brad E Darwin, Jessa Sowa, Gwendolyn A Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB(3)P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh |
title | Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB(3)P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh |
title_full | Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB(3)P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh |
title_fullStr | Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB(3)P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh |
title_full_unstemmed | Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB(3)P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh |
title_short | Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB(3)P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh |
title_sort | toward the identification of distinct phenotypes: research protocol for the low back pain biological, biomechanical, and behavioral (lb(3)p) cohort study and the bacpac mechanistic research center at the university of pittsburgh |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403299/ https://www.ncbi.nlm.nih.gov/pubmed/36715642 http://dx.doi.org/10.1093/pm/pnad009 |
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