Kinematics and paraspinal muscle activation patterns during walking differ between patients with lumbar spinal stenosis and controls

Walking stress-induced changes in gait patterns and muscle activity: Patients with lumbar spinal stenosis versus asymptomatic controls

INTRODUCTION

Patients with symptomatic lumbar spinal stenosis (sLSS) are often limited in their walking range because of worsening symptoms, which is thought to induce changes in the gait pattern. The aim of this study was to determine whether changes in gait pattern and muscle activity in these patients are elicited by a walking stress and differ from asymptomatic controls.

METHODS

Twenty patients with sLSS and 19 asymptomatic controls performed a 30-minute walking stress. Gait was assessed using seven inertial sensors and sagittal joint range of motion (ROM) was calculated during different phases of gait. Muscle activation of the gluteus medius, erector spinae and multifidus muscles was measured by surface electromyography (EMG) and integrated EMGs (normalized to the maximum during gait) were calculated. Differences between groups and time points (beginning and end) were assessed using mixed factorial analysis of variance.

RESULTS

Patients had less knee extension ROM in terminal stance, less knee flexion ROM in swing and less overall hip flexion/extension ROM than controls (p ≤ 0.03). There were no functionally relevant changes in these parameters during the walking stress. The integrated EMG was greater in all muscles in patients than in controls and increased in both groups during the walking stress in the paraspinal but not in the gluteus medius muscle. There was no interaction between group and time for any of the parameters.

CONCLUSION

Differences in gait pattern and muscle activity between patients with sLSS and controls are generally present, but are not amplified by a walking stress.

The cross-sectional area of gluteal muscle on multiaxial CT scan as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease

PURPOSE

This study examined the predictive value of the gluteal muscle index (GMI) for diagnosing sarcopenia in patients with degenerative lumbar disease (DLD), highlighting the need for effective diagnostic markers in this population.

METHODS

This prospective observational study included 202 elderly patients scheduled for lumbar spine surgery. Muscle indices for psoas, paraspinal, and gluteal muscles were measured using multiaxial computed tomography. Sarcopenia was diagnosed per the 2019 Asian Working Group for Sarcopenia (AWGS) criteria. Statistical analysis comprised univariate and multivariate logistic regression to identify predictors of sarcopenia.

RESULTS

Of patients, 77% were diagnosed with sarcopenia. The GMI and psoas muscle index (PMI) were identified as significant predictors of sarcopenia in the univariate analysis. Multivariate analysis confirmed their predictive value, with higher indices correlating with a reduced risk of sarcopenia (GMI odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.92-0.97; PMI OR = 0.95, 95% CI = 0.92-0.98, both P < .001).

CONCLUSION

The GMI serves as a reliable predictor of sarcopenia in elderly patients undergoing lumbar spine surgery for DLD, suggesting a significant role of gluteal muscles in diagnosing sarcopenia. Incorporating GMI into clinical assessments is critical to better manage and diagnose sarcopenia in this population.

The Application of Surface Electromyography Technology in Evaluating Paraspinal Muscle Function

Surface electromyography (sEMG) has emerged as a valuable tool for assessing muscle activity in various clinical and research settings. This review focuses on the application of sEMG specifically in the context of paraspinal muscles. The paraspinal muscles play a critical role in providing stability and facilitating movement of the spine. Dysfunctions or alterations in paraspinal muscle activity can lead to various musculoskeletal disorders and spinal pathologies. Therefore, understanding and quantifying paraspinal muscle activity is crucial for accurate diagnosis, treatment planning, and monitoring therapeutic interventions. This review discusses the clinical applications of sEMG in paraspinal muscles, including the assessment of low back pain, spinal disorders, and rehabilitation interventions. It explores how sEMG can aid in diagnosing the potential causes of low back pain and monitoring the effectiveness of physical therapy, spinal manipulative therapy, and exercise protocols. It also discusses emerging technologies and advancements in sEMG techniques that aim to enhance the accuracy and reliability of paraspinal muscle assessment. In summary, the application of sEMG in paraspinal muscles provides valuable insights into muscle function, dysfunction, and therapeutic interventions. By examining the literature on sEMG in paraspinal muscles, this review offers a comprehensive understanding of the current state of research, identifies knowledge gaps, and suggests future directions for optimizing the use of sEMG in assessing paraspinal muscle activity.

Muscle activity and rehabilitation in spinal stenosis (MARSS) after conservative therapy and surgical decompression with or without fusion: Protocol for a partially randomized patient preference trial on rehabilitation timing

Background

Patients affected by lumbar spinal stenosis (LSS) suffer from a multifactorial degeneration of the lumbar spine resulting in narrowing of the neuroforamina and spinal canal, leading to various functional limitations. It remains unclear whether LSS patients after surgery would benefit from early post-operative rehabilitation, or if a delayed rehabilitation would be more advantageous. The purpose of this partially randomized patient preference trial is to evaluate the impact of post-operative rehabilitation timing as well as surgical intervention type on psychometric properties and functional outcomes in patients with LSS.

Methods

Data for this patient preference trial are collected before and after surgical (decompression only or decompression and fusion) and rehabilitative interventions as well as six, 12 and 24 months after completing rehabilitation. The study participants are patients diagnosed with LSS who are at least 18 years old. After a medical check-up, participants will complete patient-reported outcome measures (PAREMO-20, SIBAR, FREM-8, SF-12, SFI, ODI) and different functional assessments (functional reach test, loaded reach test, handgrip strength, standing balance control, 6-min walk test).

Ethics and dissemination

The results of this study will be published through peer-reviewed publications and scientific contributions at national and international conferences. This research has been approved by the Institutional Review Board of Martin Luther University Halle-Wittenberg (reference number: 2022-128).

Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study

Elderly patients often have more than one disease that affects walking behavior. An objective tool to identify which disease is the main cause of functional limitations may aid clinical decision making. Therefore, we investigated whether gait patterns could be used to identify degenerative diseases using machine learning. Data were extracted from a clinical database that included sagittal joint angles and spatiotemporal parameters measured using seven inertial sensors, and anthropometric data of patients with unilateral knee or hip osteoarthritis, lumbar or cervical spinal stenosis, and healthy controls. Various classification models were explored using the MATLAB Classification Learner app, and the optimizable Support Vector Machine was chosen as the best performing model. The accuracy of discrimination between healthy and pathologic gait was 82.3%, indicating that it is possible to distinguish pathological from healthy gait. The accuracy of discrimination between the different degenerative diseases was 51.4%, indicating the similarities in gait patterns between diseases need to be further explored. Overall, the differences between pathologic and healthy gait are distinct enough to classify using a classical machine learning model; however, routinely recorded gait characteristics and anthropometric data are not sufficient for successful discrimination of the degenerative diseases.

The role of muscle degeneration and spinal balance in the pathophysiology of lumbar spinal stenosis: Study protocol of a translational approach combining in vivo biomechanical experiments with clinical and radiological parameters

OBJECTIVE

To describe a study protocol for investigating the functional association between posture, spinal balance, ambulatory biomechanics, paraspinal muscle fatigue, paraspinal muscle quality and symptoms in patients with symptomatic lumbar spinal stenosis (sLSS) before and 1-year after elective surgical intervention.

DESIGN

Single-centre prospective, experimental, multimodal (clinical, biomechanical, radiological) study with three instances of data collection: baseline (study visit 1), 6-month follow-up (remote) and 1-year follow-up (study visit 2). Both study visits include an in vivo experiment aiming to elicit paraspinal muscle fatigue for postural assessment in a non-fatigued and fatigued state.

EXPERIMENTAL PROTOCOL

At baseline and 1-year follow-up, 122 patients with sLSS will be assessed clinically, perform the back-performance scale assessment and complete several patient-reported outcome measure (PROMs) questionnaires regarding overall health, disease-related symptoms and kinesiophobia. Posture and biomechanical parameters (joint kinematics, kinetics, surface electromyography, back curvature) will be recorded using an optoelectronic system and retroreflective markers during different tasks including overground walking and movement assessments before and after a modified Biering-Sørensen test, used to elicit paraspinal muscle fatigue. Measurements of muscle size and quality and the severity of spinal stenosis will be obtained using magnetic resonance imaging (MRI) and sagittal postural alignment data from EOS radiographies. After each study visit, physical activity level will be assessed during 9 days using a wrist-worn activity monitor. In addition, physical activity level and PROMs will be assessed remotely at 6-month follow-up.

CONCLUSION

The multimodal set of data obtained using the study protocol described in this paper will help to expand our current knowledge on the pathophysiology, biomechanics, and treatment outcome of degenerative sLSS. The results of this study may contribute to defining and/or altering patient treatment norms, surgery indication criteria and post-surgery rehabilitation schedules.

TRIAL REGISTRATION

The protocol was approved by the regional ethics committee and has been registered at clinicaltrials.gov (NCT05523388).