FRI0208 The Impact of A Referral Model for Axial Spondyloarthritis in Young Patients with Chronic Low Back Pain, the Design of an Impact Study

2014 ◽  
Vol 73 (Suppl 2) ◽  
pp. 458.1-458
Author(s):  
L. Van Hoeven ◽  
Y. Vergouwe ◽  
M. Hazes ◽  
A. Weel
2001 ◽  
Author(s):  
FP Torres ◽  
D Ybañez-García ◽  
P Pérez-Caballero ◽  
M Morales ◽  
A Llópis

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0131963 ◽  
Author(s):  
Lonneke van Hoeven ◽  
Yvonne Vergouwe ◽  
P. D. M. de Buck ◽  
Jolanda J. Luime ◽  
Johanna M. W. Hazes ◽  
...  

2020 ◽  
Vol 33 (5) ◽  
pp. 785-791 ◽  
Author(s):  
Nuray Alaca ◽  
Hande Kaba ◽  
Ayce Atalay

BACKGROUND AND OBJECTIVES: Low back pain (LBP) is one of the leading forms of chronic pain and is among the leading causes of pain and disability. In this study, we investigated the associations between the severity of disability and fear of movement and pain beliefs as well as the impact of the fear of movement and pain beliefs on the quality of life in patients with chronic LBP. METHODS: A total of 89 patients (42.29 ± 16.05 years) with chronic low back pain were included in the study. The instruments used in the assessments include the Visual Analogue Scale (VAS), the Oswestry Disability Index (ODI), the Tampa Kinesiophobia Scale (TKS), the Pain Belief Questionnaire (PBQ), and the SF 36-Short Form. Patients were assigned into three groups by disability severity based on ODI scores. Statistical analysis was performed using SPSS 15. RESULTS: No statistically significant intergroup differences were found in TKS and PBQ scores (p> 0.05). A positive correlation was found between TKS scores, age (r: 0.227/p< 0.05), PBQ organic (r: -0.250/p< 0.05) scores. CONCLUSIONS: Our study revealed high levels of kinesiophobia and similar pain beliefs, independent of the severity level of disability. We believe that cognitive-behavioral therapy that may reduce fear-avoidance behaviors and convert negative pain beliefs into positive ones should be added to rehabilitation procedures for LBP.


GeroScience ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 251-269 ◽  
Author(s):  
Gerold Ebenbichler ◽  
Richard Habenicht ◽  
Sara Ziegelbecker ◽  
Josef Kollmitzer ◽  
Patrick Mair ◽  
...  

AbstractThe impact of aging on the back muscles is not well understood, yet may hold clues to both normal aging and chronic low back pain (cLBP). This study sought to investigate whether the median frequency (MF) surface electromyographic (SEMG) back muscle fatigue method—a proxy for glycolytic muscle metabolism—would be able to detect age- and sex-specific differences in neuromuscular and muscle metabolic functions in individuals with cLBP in a reliable way, and whether it would be as sensitive as when used on healthy individuals. With participants seated on a dynamometer (20° trunk anteflexion), paraspinal SEMG activity was recorded bilaterally from the multifidus (L5), longissimus (L2), and iliolumbalis (L1) muscles during isometric, sustained back extensions loaded at 80% of maximum from 117 younger (58 females) and 112 older (56 female) cLBP individuals. Tests were repeated after 1–2 days and 6 weeks. Median frequency, the SEMG variable indicating neuromuscular fatigue, was analyzed. Maximum back extensor strength was comparable between younger and older participants. Significantly less MF-SEMG back muscle fatigue was observed in older as compared to younger, and in older female as compared to older male cLBP individuals. Relative reliability was excellent, but absolute reliability appeared large for this SEMG-fatigue measure. Findings suggest that cLBP likely does not mask the age-specific diagnostic potential of the MF-SEMG back extensor fatigue method. Thus, this method possesses a great potential to be further developed into a valuable biomarker capable of detecting back muscle function at risk of sarcopenia at very early stages.


2014 ◽  
Vol 66 (3) ◽  
pp. 446-453 ◽  
Author(s):  
Lonneke van Hoeven ◽  
Jolanda Luime ◽  
Huub Han ◽  
Yvonne Vergouwe ◽  
Angelique Weel

2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Toshinaga Tsuji ◽  
Ko Matsudaira ◽  
Hiroki Sato ◽  
Jeffrey Vietri

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