Efficacy of Manual Therapy on Facilitatory Nociception and Endogenous Pain Modulation in Older Adults with Knee Osteoarthritis: A Case Series

Romero, Eleuterio A. Sánchez; González-Zamorano, Yeray; Arribas-Romano, Alberto; Martínez-Pozas, Oliver; Espinar, Elena Fernández; Pedersini, Paolo; Pérez, José Luis Alonso; Fernández‐Carnero, Josué

doi:10.3390/app11041895

Cited by 28 publications

(25 citation statements)

References 44 publications

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“…Osteoarthritic changes were also apparent in active duty soldiers younger than 20 years of age [ 9 ]. In the early stages of the disease, there were multiple methods of treatment including surgical and conservative treatment [ 10 , 11 , 12 , 13 ]. Nevertheless, at the end stage of the disease, total knee arthroplasty (TKA) is the gold standard of treatment.…”

Section: Introductionmentioning

confidence: 99%

Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part I: Femoral-Tibial Joint

Karpiński

Krakowski

Jonak

et al. 2022

Sensors

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Osteoarthritis (OA) is a chronic, progressive disease which has over 300 million cases each year. Some of the main symptoms of OA are pain, restriction of joint motion and stiffness of the joint. Early diagnosis and treatment can prolong painless joint function. Vibroarthrography (VAG) is a cheap, reproducible, non-invasive and easy-to-use tool which can be implemented in the diagnostic route. The aim of this study was to establish diagnostic accuracy and to identify the most accurate signal processing method for the detection of OA in knee joints. In this study, we have enrolled a total of 67 patients, 34 in a study group and 33 in a control group. All patients in the study group were referred for surgical treatment due to intraarticular lesions, and the control group consisted of healthy individuals without knee symptoms. Cartilage status was assessed during surgery according to the International Cartilage Repair Society (ICRS) and vibroarthrography was performed one day prior to surgery in the study group. Vibroarthrography was performed in an open and closed kinematic chain for the involved knees in the study and control group. Signals were acquired by two sensors placed on the medial and lateral joint line. Using the neighbourhood component analysis (NCA) algorithm, the selection of optimal signal measures was performed. Classification using artificial neural networks was performed for three variants: I—open kinetic chain, II—closed kinetic chain, and III—open and closed kinetic chain. Vibroarthrography showed high diagnostic accuracy in determining healthy cartilage from cartilage lesions, and the number of repetitions during examination can be reduced only to closed kinematic chain.

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Section: Introductionmentioning

confidence: 99%

Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part I: Femoral-Tibial Joint

Karpiński

Krakowski

Jonak

et al. 2022

Sensors

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“…Various methods of treatment, including conservative and surgical measures have been proposed for the treatment of OA [ 11 , 12 , 13 , 14 ]. The end stage disease is indicated for arthroplasty.…”

Section: Introductionmentioning

confidence: 99%

Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint

Karpiński

Krakowski

Jonak

et al. 2022

Sensors

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Cartilage loss due to osteoarthritis (OA) in the patellofemoral joint provokes pain, stiffness, and restriction of joint motion, which strongly reduces quality of life. Early diagnosis is essential for prolonging painless joint function. Vibroarthrography (VAG) has been proposed in the literature as a safe, noninvasive, and reproducible tool for cartilage evaluation. Until now, however, there have been no strict protocols for VAG acquisition especially in regard to differences between the patellofemoral and tibiofemoral joints. The purpose of this study was to evaluate the proposed examination and acquisition protocol for the patellofemoral joint, as well as to determine the optimal examination protocol to obtain the best diagnostic results. Thirty-four patients scheduled for knee surgery due to cartilage lesions were enrolled in the study and compared with 33 healthy individuals in the control group. VAG acquisition was performed prior to surgery, and cartilage status was evaluated during the surgery as a reference point. Both closed (CKC) and open (OKC) kinetic chains were assessed during VAG. The selection of the optimal signal measures was performed using a neighborhood component analysis (NCA) algorithm. The classification was performed using multilayer perceptron (MLP) and radial basis function (RBF) neural networks. The classification using artificial neural networks was performed for three variants: I. open kinetic chain, II. closed kinetic chain, and III. open and closed kinetic chain. The highest diagnostic accuracy was obtained for variants I and II for the RBF 9-35-2 and MLP 10-16-2 networks, respectively, achieving a classification accuracy of 98.53, a sensitivity of 0.958, and a specificity of 1. For variant III, a diagnostic accuracy of 97.79 was obtained with a sensitivity and specificity of 0.978 for MLP 8-3-2. This indicates a possible simplification of the examination protocol to single kinetic chain analyses.

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“…Consequently, hands-on care is recommended for a range of musculoskeletal (MSK) conditions, including low back pain (LBP), neck pain, headaches, carpal tunnel syndrome and hip and knee osteoarthritis ( Deyle et al, 2000 ; Akalin et al, 2002 ; MacDonald et al, 2006 ; Rubinstein et al, 2011 ; Gross et al, 2015 ; Cerritelli et al, 2017 ). A significant body of evidence demonstrates that hands-on techniques in MSK care have a particularly important role on pain modulation ( Deyle et al, 2000 ; Bialosky et al, 2009 ; Vigotsky and Bruhns, 2015 ; Cerritelli et al, 2017 ; Geri et al, 2019 ; Sánchez-Romero et al, 2021 ). Therefore, the hand plays a crucial role in delivering MSK care through the sense of touch.…”

Section: Introductionmentioning

confidence: 99%

Therapeutic Alliance as Active Inference: The Role of Therapeutic Touch and Biobehavioural Synchrony in Musculoskeletal Care

McParlin¹,

Cerritelli²,

Rossettini³

et al. 2022

Front. Behav. Neurosci.

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Touch is recognised as crucial for survival, fostering cooperative communication, accelerating recovery, reducing hospital stays, and promoting overall wellness and the therapeutic alliance. In this hypothesis and theory paper, we present an entwined model that combines touch for alignment and active inference to explain how the brain develops “priors” necessary for the health care provider to engage with the patient effectively. We appeal to active inference to explain the empirically integrative neurophysiological and behavioural mechanisms that underwrite synchronous relationships through touch. Specifically, we offer a formal framework for understanding – and explaining – the role of therapeutic touch and hands-on care in developing a therapeutic alliance and synchrony between health care providers and their patients in musculoskeletal care. We first review the crucial importance of therapeutic touch and its clinical role in facilitating the formation of a solid therapeutic alliance and in regulating allostasis. We then consider how touch is used clinically – to promote cooperative communication, demonstrate empathy, overcome uncertainty, and infer the mental states of others – through the lens of active inference. We conclude that touch plays a crucial role in achieving successful clinical outcomes and adapting previous priors to create intertwined beliefs. The ensuing framework may help healthcare providers in the field of musculoskeletal care to use hands-on care to strengthen the therapeutic alliance, minimise prediction errors (a.k.a., free energy), and thereby promote recovery from physical and psychological impairments.

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Efficacy of Manual Therapy on Facilitatory Nociception and Endogenous Pain Modulation in Older Adults with Knee Osteoarthritis: A Case Series

Cited by 28 publications

References 44 publications

Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part I: Femoral-Tibial Joint

Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part I: Femoral-Tibial Joint

Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint

Therapeutic Alliance as Active Inference: The Role of Therapeutic Touch and Biobehavioural Synchrony in Musculoskeletal Care

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