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Murphy MC, Mosler AB, Rio EK, Coventry M, Raj IS, Chivers PT, Arendt-Nielsen L, Alfieri FM, Bjurström MF, Larsen DB, Chang WJ, Olesen AE, Hertel E, Holm PM, Graven-Nielsen T, de Paula Gomes CAF, Henriksen M, Klinedinst NJ, Mathew J, Drewes AM, Nunes GS, O'Leary H, Østerås H, Ozturk O, Pozsgai M, Rampazo ÉP, Rasmussen S, Rice D, Sánchez-Romero EA, Irani A, Stausholm MB, Hince D, Petersen KKS. Can quantitative sensory testing predict treatment outcomes in hip and knee osteoarthritis? A systematic review and meta-analysis of individual participant data. Pain 2025:00006396-990000000-00887. [PMID: 40310871 DOI: 10.1097/j.pain.0000000000003627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2024] [Accepted: 03/13/2025] [Indexed: 05/03/2025]
Abstract
ABSTRACT An individual participant data (IPD) meta-analysis can assess the predictive value of data on outcomes at the individual level, offering a potential tool for developing personalized pain management. Pretreatment quantitative sensory testing (QST) may stratify patient groups, which are then linked to treatment outcomes. Our objective was to determine if measures of QST at baseline are related to treatment outcomes (at any time point) for pain and disability in lower-limb osteoarthritis. We performed a systematic review with an IPD meta-analysis. Searches were conducted in 9 databases until May 5, 2023 for intervention studies that measured baseline QST and longitudinal measures of participant-reported pain and disability. We performed a 2-stage approach to analyse longitudinal data. Individual models were fitted to each study and combined using random effects multivariate meta-analytic models. Study quality was assessed using the Joanna Briggs Institute checklist, and certainty of the evidence was assessed using GRADE. We identified 3082 records and included 1 hip and 28 knee datasets consisting of 2522 participants from 40 studies. Local warm detection thresholds (P = 0.024) predicted knee osteoarthritis pain outcomes (very-low certainty). Local warm detection thresholds (P = 0.030), remote cold detection thresholds (P = 0.05), and remote pressure tolerance thresholds (P = 0.007) predicted knee osteoarthritis disability outcomes (very-low certainty). Other QST variables were associated with hip and knee osteoarthritis pain and disability levels (eg, pressure pain thresholds), but this relationship did not change over time. This review finds that mechanism-based, QST methodologies do not consistently predict pain or disability on an individual level in hip or knee osteoarthritis.
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Affiliation(s)
- Myles C Murphy
- Nutrition and Health Innovation Research Institute, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Institute for Health Research, The University of Notre Dame Australia, Fremantle, WA, Australia
| | - Andrea B Mosler
- Nutrition and Health Innovation Research Institute, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- La Trobe Sport and Exercise Medicine Research Centre, La Trobe University, Bundoora, VIC, Australia
| | - Ebonie K Rio
- La Trobe Sport and Exercise Medicine Research Centre, La Trobe University, Bundoora, VIC, Australia
- Victorian Institute of Sport, Melbourne, VIC, Australia
- The Australian Ballet, Melbourne, VIC, Australia
| | - Molly Coventry
- Nutrition and Health Innovation Research Institute, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Isaac Selva Raj
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- School of Allied Health, Murdoch University, Murdoch, WA, Australia
- Centre for Healthy Ageing, Murdoch University, Murdoch, WA, Australia
| | - Paola T Chivers
- Nutrition and Health Innovation Research Institute, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Institute for Health Research, The University of Notre Dame Australia, Fremantle, WA, Australia
| | - Lars Arendt-Nielsen
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg, Denmark
- Mech-Sense, Department of Gastroenterology, Aalborg University Hospital, Aalborg, Denmark
- Steno Diabetes Center North Denmark, Clinical Institute, Aalborg University Hospital, Aalborg, Denmark
| | - Fabio Marcon Alfieri
- Postgraduate Program in Health Promotion, Adventist University Center of São Paulo, São Paulo, Brazil
| | | | - Dennis Boye Larsen
- Mech-Sense, Department of Gastroenterology, Aalborg University Hospital, Aalborg, Denmark
| | - Wei-Ju Chang
- School of Health Sciences, University of New South Wales, Syndey, New South Wales, Australia
| | - Anne Estrup Olesen
- Department of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark
- Department of Clinical Pharmacology, Aalborg University Hospital, Aalborg, Denmark
| | - Emma Hertel
- Centre for Mathematical Modeling of Knee Osteoarthritis (MathKOA), Department of Materials and Production, Aalborg University, Aalborg, Denmark
| | - Paetur Mikal Holm
- The Research and Implementation Unit PROgrez, Department of Physiotherapy and Occupational Therapy, Næstved-Slagelse-Ringsted Hospitals, Region Zealand, Denmark
- Center for Surgery, National Hospital of Faroe Islands, Tórshavn, Faroe Islands
- Faculty of Health Sciences, University of Faroe Islands, Tórshavn, Faroe Islands
| | - Thomas Graven-Nielsen
- Steno Diabetes Center North Denmark, Clinical Institute, Aalborg University Hospital, Aalborg, Denmark
| | | | - Marius Henriksen
- Bispebjerg Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark
| | | | - Jerin Mathew
- Department of Anatomy, University of Otago, Dunedin, Ōtepoti, New Zealand
| | - Asbjørn Mohr Drewes
- Mech-Sense, Department of Gastroenterology, Aalborg University Hospital, Aalborg, Denmark
| | - Guilherme S Nunes
- Department of Physiotherapy and Rehabilitation, Federal University of Santa Maria, Santa Maria, Brazil
| | - Helen O'Leary
- School of Allied Health, Faculty of Education and Health Sciences, University of Limerick, Limerick, Ireland
| | - Håvard Østerås
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ozgul Ozturk
- Department of Physiotherapy and Rehabilitation, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey
| | | | | | - Sten Rasmussen
- Department of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark
| | - David Rice
- Health and Rehabilitation Research Institute, School of Clinical Sciences, Auckland University of Technology, Auckland, NewZealand
- Department of Anaesthesiology and Perioperative Medicine, Health New Zealand Te Whatu Ora Waitematā, Auckland, New Zealand
| | - Eleuterio A Sánchez-Romero
- Interdisciplinary Research Group on Musculoskeletal Disorders, Faculty of Sport Sciences, Universidad Europea de Madrid, Villaviciosa de Odón, Spain
| | - Anushka Irani
- Division of Rheumatology, Mayo Clinic, FL, United States
- Nuffield Department of Clinical Neurosciences, University of Oxford, London, United Kingdom
| | - Martin Bjørn Stausholm
- Department of Global Public Health and Primary Care, Faculty of Medicine, University of Bergen, Bergen, Norway
- Department of Physical and Occupational Therapy, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Dana Hince
- Institute for Health Research, The University of Notre Dame Australia, Fremantle, WA, Australia
| | - Kristian Kjær-Staal Petersen
- Steno Diabetes Center North Denmark, Clinical Institute, Aalborg University Hospital, Aalborg, Denmark
- Department of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark
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Deng Y, Yang Y, Zhu F, Liu W, Chen J, Xu G. Analgesic efficacy and safety of methylene blue combined with cocktail for periarticular infiltration following total knee arthroplasty: a prospective, randomized, controlled study. Perioper Med (Lond) 2025; 14:9. [PMID: 39833953 PMCID: PMC11748522 DOI: 10.1186/s13741-025-00493-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2024] [Accepted: 01/13/2025] [Indexed: 01/22/2025] Open
Abstract
OBJECTIVE This study aims to explore the analgesic effects and safety of periarticular injections of methylene blue (MB) combined with a cocktail formulation following total knee arthroplasty (TKA). METHODS A total of 70 patients undergoing total knee arthroplasty were selected and divided into two groups based on the cocktail formula used for periarticular infiltration, including the methylene blue group (M group, n = 35) and the control group (C group, n = 35). Both groups underwent spinal anesthesia. At the end of the surgery, the M group received a 0.05% methylene blue combined cocktail for periarticular infiltration block, while the C group received a conventional cocktail infiltration block. Postoperatively, both groups used intravenous patient-controlled analgesia. Then, the rest and movement Numeric Rating Scale (NRS) scores, postoperative sufentanil consumption, postoperative inflammatory markers, and the occurrence of adverse reactions such as wound infection and poor wound healing were compared after postoperative 24 h, 48 h, 72 h, and 7-day, 14-day, 28-day between the two groups. RESULTS The rest and during movement, NRS scores at postoperative 24 h, 48 h, 72 h, 7-day, 14-day, and 28-day were significantly lower in the C group compared with the M group (P < 0.05). The total sufentanil consumption at postoperative 72 h was less in the M group (98.9 ± 11.3 µg) compared to the C group (129.1 ± 12.3 µg) (P < 0.01). It also showed a lower IL-6 in the M group at postoperative 24 h and 72 h (P < 0.05). However, there were no significant differences in CRP levels between the two groups at 24 h and 72 h post-surgery (P > 0.05), and neither group experienced complications such as wound infection or poor wound healing. CONCLUSION Methylene blue combined with a cocktail can be safely used for local infiltration after knee arthroplasty, which reduces postoperative opioid consumption and suppresses the release of inflammatory factors. Moreover, it synergistically enhanced the local anesthetic analgesia and provided sustained pain relief for at least 4 weeks.
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Affiliation(s)
- Yijiang Deng
- Department of Anesthesiology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Department of Anesthesiology, Affiliated Hospital of Panzhihua University, Sichuan, China
| | - Yong Yang
- Department of Orthopedics, Affiliated Hospital of Panzhihua University, Sichuan, China
| | - Feng Zhu
- Department of Anesthesiology, Affiliated Hospital of Panzhihua University, Sichuan, China
| | - Wenzhi Liu
- Department of Anesthesiology, Affiliated Hospital of Panzhihua University, Sichuan, China
| | - Jiarui Chen
- Department of Anesthesiology, Affiliated Hospital of Panzhihua University, Sichuan, China
| | - Guangmin Xu
- Department of Anesthesiology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
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Chen Y, Wang E, Sites BD, Cohen SP. Integrating mechanistic-based and classification-based concepts into perioperative pain management: an educational guide for acute pain physicians. Reg Anesth Pain Med 2024; 49:581-601. [PMID: 36707224 DOI: 10.1136/rapm-2022-104203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 01/13/2023] [Indexed: 01/28/2023]
Abstract
Chronic pain begins with acute pain. Physicians tend to classify pain by duration (acute vs chronic) and mechanism (nociceptive, neuropathic and nociplastic). Although this taxonomy may facilitate diagnosis and documentation, such categories are to some degree arbitrary constructs, with significant overlap in terms of mechanisms and treatments. In clinical practice, there are myriad different definitions for chronic pain and a substantial portion of chronic pain involves mixed phenotypes. Classification of pain based on acuity and mechanisms informs management at all levels and constitutes a critical part of guidelines and treatment for chronic pain care. Yet specialty care is often siloed, with advances in understanding lagging years behind in some areas in which these developments should be at the forefront of clinical practice. For example, in perioperative pain management, enhanced recovery protocols are not standardized and tend to drive treatment without consideration of mechanisms, which in many cases may be incongruent with personalized medicine and mechanism-based treatment. In this educational document, we discuss mechanisms and classification of pain as it pertains to commonly performed surgical procedures. Our goal is to provide a clinical reference for the acute pain physician to facilitate pain management decision-making (both diagnosis and therapy) in the perioperative period.
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Affiliation(s)
- Yian Chen
- Anesthesiology, Stanford University School of Medicine, Stanford, California, USA
| | - Eric Wang
- Anesthesiology and Critical Care Medicine, The Johns Hopkins Hospital, Baltimore, Maryland, USA
| | - Brian D Sites
- Anesthesiology and Orthopaedics, Dartmouth College Geisel School of Medicine, Hanover, New Hampshire, USA
| | - Steven P Cohen
- Anesthesiology, Neurology, Physical Medicine & Rehabilitation and Psychiatry & Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
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