Pain Trajectories in Knee Osteoarthritis—A Systematic Review and Best Evidence Synthesis on Pain Predictors

Different profiles of pain progression have been reported in patients with knee osteoarthritis (OA), but the determinants of this heterogeneity are still to be sought. The aim of this systematic review was to analyze all studies providing information about knee OA pain trajectories to delineate, acc...

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Main Authors: Davide Previtali, Luca Andriolo, Giorgio Di Laura Frattura, Angelo Boffa, Christian Candrian, Stefano Zaffagnini, Giuseppe Filardo
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Journal of Clinical Medicine
Subjects:
Online Access:https://www.mdpi.com/2077-0383/9/9/2828
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author Davide Previtali
Luca Andriolo
Giorgio Di Laura Frattura
Angelo Boffa
Christian Candrian
Stefano Zaffagnini
Giuseppe Filardo
author_facet Davide Previtali
Luca Andriolo
Giorgio Di Laura Frattura
Angelo Boffa
Christian Candrian
Stefano Zaffagnini
Giuseppe Filardo
author_sort Davide Previtali
collection DOAJ
description Different profiles of pain progression have been reported in patients with knee osteoarthritis (OA), but the determinants of this heterogeneity are still to be sought. The aim of this systematic review was to analyze all studies providing information about knee OA pain trajectories to delineate, according to patients’ characteristics, an evidence-based evolution pattern of this disabling disease, which is key for a more personalized and effective management of knee OA. A literature search was performed on PubMed, Web of Science, Cochrane Library, and grey literature databases. The Cochrane Collaboration’s tool for assessing risk of bias was used, and a best-evidence synthesis was performed to define the predictors of pain evolution. Seven articles on 7747 patients affected by knee OA (mainly early/moderate) were included. Daily knee OA pain trajectories were unstable in almost half of the patients. In the mid-term, knee OA had a steady pain trajectory in 85% of the patients, 8% experienced pain reduction, while 7% experienced pain worsening. Low education, comorbidities, and depression were patient-related predictors of severe/worsening knee OA pain. Conversely, age, alcohol, smoking, pain coping strategies, and medications were unrelated to pain evolution. Conflicting/no evidence was found for all joint-related factors, such as baseline radiographic severity.
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spelling doaj.art-212f0e7177774365ba9cd71c7b350e332023-11-20T12:06:53ZengMDPI AGJournal of Clinical Medicine2077-03832020-09-0199282810.3390/jcm9092828Pain Trajectories in Knee Osteoarthritis—A Systematic Review and Best Evidence Synthesis on Pain PredictorsDavide Previtali0Luca Andriolo1Giorgio Di Laura Frattura2Angelo Boffa3Christian Candrian4Stefano Zaffagnini5Giuseppe Filardo6Orthopaedic and Traumatology Unit, Ospedale Regionale di Lugano, EOC, 6900 Lugano, SwitzerlandClinica Ortopedica e Traumatologica 2, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, ItalyOrthopaedic and Traumatology Unit, Ospedale Regionale di Lugano, EOC, 6900 Lugano, SwitzerlandClinica Ortopedica e Traumatologica 2, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, ItalyOrthopaedic and Traumatology Unit, Ospedale Regionale di Lugano, EOC, 6900 Lugano, SwitzerlandClinica Ortopedica e Traumatologica 2, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, ItalyOrthopaedic and Traumatology Unit, Ospedale Regionale di Lugano, EOC, 6900 Lugano, SwitzerlandDifferent profiles of pain progression have been reported in patients with knee osteoarthritis (OA), but the determinants of this heterogeneity are still to be sought. The aim of this systematic review was to analyze all studies providing information about knee OA pain trajectories to delineate, according to patients’ characteristics, an evidence-based evolution pattern of this disabling disease, which is key for a more personalized and effective management of knee OA. A literature search was performed on PubMed, Web of Science, Cochrane Library, and grey literature databases. The Cochrane Collaboration’s tool for assessing risk of bias was used, and a best-evidence synthesis was performed to define the predictors of pain evolution. Seven articles on 7747 patients affected by knee OA (mainly early/moderate) were included. Daily knee OA pain trajectories were unstable in almost half of the patients. In the mid-term, knee OA had a steady pain trajectory in 85% of the patients, 8% experienced pain reduction, while 7% experienced pain worsening. Low education, comorbidities, and depression were patient-related predictors of severe/worsening knee OA pain. Conversely, age, alcohol, smoking, pain coping strategies, and medications were unrelated to pain evolution. Conflicting/no evidence was found for all joint-related factors, such as baseline radiographic severity.https://www.mdpi.com/2077-0383/9/9/2828kneeosteoarthritispaintrajectoriespredictorsevolution
spellingShingle Davide Previtali
Luca Andriolo
Giorgio Di Laura Frattura
Angelo Boffa
Christian Candrian
Stefano Zaffagnini
Giuseppe Filardo
Pain Trajectories in Knee Osteoarthritis—A Systematic Review and Best Evidence Synthesis on Pain Predictors
Journal of Clinical Medicine
knee
osteoarthritis
pain
trajectories
predictors
evolution
title Pain Trajectories in Knee Osteoarthritis—A Systematic Review and Best Evidence Synthesis on Pain Predictors
title_full Pain Trajectories in Knee Osteoarthritis—A Systematic Review and Best Evidence Synthesis on Pain Predictors
title_fullStr Pain Trajectories in Knee Osteoarthritis—A Systematic Review and Best Evidence Synthesis on Pain Predictors
title_full_unstemmed Pain Trajectories in Knee Osteoarthritis—A Systematic Review and Best Evidence Synthesis on Pain Predictors
title_short Pain Trajectories in Knee Osteoarthritis—A Systematic Review and Best Evidence Synthesis on Pain Predictors
title_sort pain trajectories in knee osteoarthritis a systematic review and best evidence synthesis on pain predictors
topic knee
osteoarthritis
pain
trajectories
predictors
evolution
url https://www.mdpi.com/2077-0383/9/9/2828
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