There is growing evidence for the idea that in back pain patients, pain-related fear (fear of pain/physical activity/(re)injury) may be more disabling than pain itself. A number of questionnaires have been developed to quantify pain-related fears, including the Fear-Avoidance Beliefs Questionnaire (FABQ), the Tampa Scale for Kinesiophobia (TSK), and the Pain Anxiety Symptoms Scale (PASS). A total of 104 patients, presenting to a rehabilitation center or a comprehensive pain clinic with chronic low back pain were studied in three independent studies aimed at (1) replicating that pain-related fear is more disabling than pain itself (2) investigating the association between pain-related fear and poor behavioral performance and (3) investigating whether pain-related fear measures are better predictors of disability and behavioral performance than measures of general negative affect or general negative pain beliefs (e.g. pain catastrophizing). All three studies showed similar results. Highest correlations were found among the pain-related fear measures and measures of self-reported disability and behavioral performance. Even when controlling for sociodemographics, multiple regression analyses revealed that the subscales of the FABQ and the TSK were superior in predicting self-reported disability and poor behavioral performance. The PASS appeared more strongly associated with pain catastrophizing and negative affect, and was less predictive of pain disability and behavioral performance. Implications for chronic back pain assessment, prevention and treatment are discussed.

Pain-related fear is more diaabling than pain itself: evidence on the role of pain-related fear in chronic low-back pain disability

Background: Lumbar disc herniation (LDH) is among the most common causes of lower back pain and sciatica. The causes of LDH have not been fully elucidated but most likely involve a complex combination of mechanical and biological processes. Magnetic resonance imaging (MRI) is a tool most frequently used for LDH because it can show abnormal soft tissue areas around the spine. Deep learning models may be trained to recognize images with high speed and accuracy to diagnose LDH. Although the deep learning model requires huge numbers of image datasets to train and establish the best model, this study processed enhanced medical image features for training the small-scale deep learning dataset. Methods: We propose automatic detection to assist the initial LDH exam for lower back pain. The subjects were between 20 and 65 years old with at least 6 months of work experience. The deep learning method employed the YOLOv3 model to train and detect small object changes such as LDH on MRI. The dataset images were processed and combined with labeling and annotation from the radiologist's diagnosis record. Results: Our method proves the possibility of using deep learning with a small-scale dataset with limited medical images. The highest mean average precision (mAP) was 92.4% at 550 images with data augmentation (550-aug), and the YOLOv3 LDH training was 100% with the best average precision at 550-aug among all datasets. This study used data augmentation to prevent under- or overfitting in an object detection model that was trained with the small-scale dataset. Conclusions: The data augmentation technique plays a crucial role in YOLOv3 training and detection results. This method displays a high possibility for rapid initial tests and auto-detection for a limited clinical dataset.

Lumbar Disc Herniation Automatic Detection in Magnetic Resonance Imaging Based on Deep Learning.

Effects of a 16-week Pilates exercises training program for isometric trunk extension and flexion strength.

Is Interferential Current Before Pilates Exercises More Effective Than Placebo in Patients With Chronic Nonspecific Low Back Pain?: A Randomized Controlled Trial

Acute effects of proprioceptive neuromuscular facilitation exercises on the postural strategy in patients with chronic low back pain.

Chronic low back represents one of the major causes of disability worldwide. Our narrative review has the purpose of highlighting the evidence supporting the different rehabilitative techniques described for its management. In total, 26 studies were found suitable to be included in the review (14 articles about pilates, six about McKenzie (MK), one article about Feldenkrais, three about Global Postural Rehabilitation (GPR) and two about Proprioceptive Neuromuscular Facilitation). The effect of exercise therapy was examined for each single study through changes in the main clinical outcomes (pain, disability,) quality of life (QoL) and psychological aspects and the targeted aspects of physical function (muscle strength, mobility, muscular activity and flexibility). All the techniques are effective for the study groups with respect to the control groups in reducing pain and disability and improving the QoL and maintaining benefits at follow-up; pilates, Back School, MK and Feldenkrais methods reduce pain and are more efficient than a pharmacological or instrumental approach in reducing disability and improving all psychological aspects also. GPR shows long lasting results for the last outcome. To date, it is difficult to affirm the superiority of one approach over another. Further high quality research is needed to confirm the effect of these techniques, together with the use of more appropriate evaluation measures.

/pdf/chronic-low-back-pain-and-postural-rehabilitation-exercise-a-302pdn8mkp.pdf

Chronic low back pain and postural rehabilitation exercise: a literature review.

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Chronic low back pain and postural rehabilitation exercise: a literature review.