Effects of lumbar extensor muscle strengthening and neuromuscular control retraining on disability in patients with chronic low back pain: a protocol for a randomised controlled trial

Neuromuscular Control and Resistance Training for People With Chronic Low Back Pain: A Randomized Controlled Trial

OBJECTIVE: To determine if adding lumbar neuromuscular control retraining exercises to a 12-week program of strengthening exercises had greater effect for improving disability than 12 weeks of strengthening exercises alone in people with chronic low back pain (LBP). DESIGN: Single-center, participant- and assessor-blinded, comparative effectiveness randomized controlled trial. METHODS: Sixty-nine participants (31 females; 29 males; mean age: 46.5 years) with nonspecific chronic LBP were recruited for a 12-week program involving lumbar extension neuromuscular retraining in addition to resistance exercises (intervention) or 12 weeks of resistance exercises alone (control). The primary outcome measure was the Oswestry Disability Index. Secondary outcome measures included the Numeric Rating Scale, Tampa Scale for Kinesiophobia, Pain Self-Efficacy Questionnaire, and the International Physical Activity Questionnaire. Outcomes were measured at baseline, 6 weeks, and 12 weeks. RESULTS: Forty-three participants (22 control, 21 intervention) completed all outcome measures at 6 and 12 weeks. Fourteen participants were lost to follow-up, and 12 participants discontinued due to COVID-19 restrictions. Both groups demonstrated clinically important changes in disability, pain intensity, and kinesiophobia. The difference between groups with respect to disability was imprecise and not clinically meaningful (mean difference, -4.4; 95% CI: -10.2, 1.4) at 12 weeks. Differences in secondary outcomes at 6 or 12 weeks were also small with wide confidence intervals. CONCLUSIONS: Adding lumbar neuromuscular control retraining to a series of resistance exercises offered no additional benefit over resistance exercises alone over a 12-week period. J Orthop Sports Phys Ther 2024;54(5):1-10. Epub 18 March 2024. doi:10.2519/jospt.2024.12349.

Regression-Based Machine Learning for Predicting Lifting Movement Pattern Change in People with Low Back Pain

Machine learning (ML) algorithms are crucial within the realm of healthcare applications. However, a comprehensive assessment of the effectiveness of regression algorithms in predicting alterations in lifting movement patterns has not been conducted. This research represents a pilot investigation using regression-based machine learning techniques to forecast alterations in trunk, hip, and knee movements subsequent to a 12-week strength training for people who have low back pain (LBP). The system uses a feature extraction algorithm to calculate the range of motion in the sagittal plane for the knee, trunk, and hip and 12 different regression machine learning algorithms. The results show that Ensemble Tree with LSBoost demonstrated the utmost accuracy in prognosticating trunk movement. Meanwhile, the Ensemble Tree approach, specifically LSBoost, exhibited the highest predictive precision for hip movement. The Gaussian regression with the kernel chosen as exponential returned the highest prediction accuracy for knee movement. These regression models hold the potential to significantly enhance the precision of visualisation of the treatment output for individuals afflicted with LBP.

Impaired Lumbar Extensor Force Control Is Associated with Increased Lifting Knee Velocity in People with Chronic Low-Back Pain

The ability of the lumbar extensor muscles to accurately control static and dynamic forces is important during daily activities such as lifting. Lumbar extensor force control is impaired in low-back pain patients and may therefore explain the variances in lifting kinematics. Thirty-three chronic low-back pain participants were instructed to lift weight using a self-selected technique. Participants also performed an isometric lumbar extension task where they increased and decreased their lumbar extensor force output to match a variable target force within 20-50% lumbar extensor maximal voluntary contraction. Lifting trunk and lower limb range of motion and angular velocity variables derived from phase plane analysis in all planes were calculated. Lumbar extensor force control was analyzed by calculating the Root-Mean-Square Error (RMSE) between the participants' force and the target force during the increasing (RMSEA), decreasing (RMSED) force portions and for the overall force error (RMSET) of the test. The relationship between lifting kinematics and RMSE variables was analyzed using multiple linear regression. Knee angular velocity in the sagittal and coronal planes were positively associated with RMSEA (R2 = 0.10, β = 0.35, p = 0.046 and R2 = 0.21, β = 0.48, p = 0.004, respectively). Impaired lumbar extensor force control is associated with increased multiplanar knee movement velocity during lifting. The study findings suggest a potential relationship between lumbar and lower limb neuromuscular function in people with chronic low-back pain.

Machine Learning Derived Lifting Technique in People without Low Back Pain

This paper presents a method for determining the number of lifting techniques used by healthy individuals through the analysis of kinematic data collected from 115 participants utilizing an motion capture system. The technique utilizes a combination of feature extraction and Ward's method to analyse the range of motion in the sagittal plane of the knee, hip, and trunk. The findings identified five unique lifting techniques in people without low back pain. The multivariate analysis of variance statistical analysis reveals a significant difference in the range of motion in the trunk, hip and knee between each cluster for healthy people (F (12, 646) = 125.720, p < 0.0001).Clinical Relevance- This information can assist healthcare professionals in choosing effective treatments and interventions for those with occupational lower back pain by focusing rehabilitation on specific body parts associated with problematic lifting techniques, such as the trunk, hip, or knee, which may lead to improved pain and disability outcomes, exemplifying precision medicine.

Machine Learning Derived Lifting Techniques and Pain Self-Efficacy in People with Chronic Low Back Pain

This paper proposes an innovative methodology for finding how many lifting techniques people with chronic low back pain (CLBP) can demonstrate with camera data collected from 115 participants. The system employs a feature extraction algorithm to calculate the knee, trunk and hip range of motion in the sagittal plane, Ward’s method, a combination of K-means and Ensemble clustering method for classification algorithm, and Bayesian neural network to validate the result of Ward’s method and the combination of K-means and Ensemble clustering method. The classification results and effect size show that Ward clustering is the optimal method where precision and recall percentages of all clusters are above 90, and the overall accuracy of the Bayesian Neural Network is 97.9%. The statistical analysis reported a significant difference in the range of motion of the knee, hip and trunk between each cluster, F (9, 1136) = 195.67, p < 0.0001. The results of this study suggest that there are four different lifting techniques in people with CLBP. Additionally, the results show that even though the clusters demonstrated similar pain levels, one of the clusters, which uses the least amount of trunk and the most knee movement, demonstrates the lowest pain self-efficacy.

Electromyography of the Multifidus Muscle in Horses Trotting During Therapeutic Exercises

Thoracolumbar pain has been identified in both human and equine patients. Rehabilitation and conditioning programs have focused specifically on improving trunk and abdominal muscle function (1–5). Equine exercise programs routinely incorporate ground poles and training devices for the similar goals of increasing spinal and core stability and strength (6–8). The multifidus muscle has been an area of focus due to atrophy associated with disease (9). To date, there have been no reports on the activity of the multifidus muscle in horses in relation to therapeutic exercises. Our objectives were to use electromyography to determine the average work performed and peak muscle activity of the multifidus in horses trotting, trotting over ground poles, trotting while wearing a resistance band-based training device and trotting while wearing the training device over ground poles. We hypothesized that ground poles and the training device would each increase average work performed and peak multifidus muscle activity. Right and left cranial thoracic locations showed significant increased muscle work and peak activation when horses were trotted over ground poles versus without. The peak activation was significantly greater in horses trotting over poles in both lumbar regions, but there was no significant change in peak activation in either location due to the training device. When the influence of the training device was investigated without ground poles, left caudal thoracic muscle work and peak activity, and right lumbar muscle work were significantly lower when using the training device, as compared to without. When the training device was combined with trotting over ground poles, both left and right caudal thoracic regions showed significantly lower muscle work and peak activity when the device was used. There was no significant difference between with and without the device in either left or right lumbar muscle work. In conclusion, implementing ground poles can be an effective strategy to increase the activation of the multifidus muscle, however, caution should be taken when incorporating the use of a resistance band training device as muscle work and peak activation were significantly reduced in most locations. Further study should be performed in regards to the training device to determine its effects on epaxial musculature.

Reliability of lumbar multifidus and iliocostalis lumborum thickness and echogenicity measurements using ultrasound imaging

Purpose

To establish the test-retest and inter-rater reliability of lumbar multifidus (LM) and iliocostalis lumborum (IL) muscle thickness and echogenicity as derived using ultrasound imaging.

Methods

Ultrasound images of the LM and IL were collected from 11 healthy participants on two occasions, 1 week apart, by two independent assessors. Measures of LM and IL thickness and echogenicity were subject to test-retest and inter-rater reliability, which was assessed by calculation of an F statistic, the interclass correlation coefficient (ICC), the standard error of measurement, 95% confidence intervals and Bland-Altman plots. This study was given approval by The University of Melbourne Behavioural and Social Sciences Human Ethics Sub-Committee (ref: 1749845).

Results

Assessors A and B showed good to excellent test-retest reliability for LM thickness (ICC_3,3 A: 0.89 and B: 0.98), LM echogenicity (ICC_3,3 A: 0.93 and B: 0.95) and IL echogenicity (ICC_3,3 A: 0.87 and B: 0.83). Test-retest reliability for IL thickness was poor for Assessor A but excellent for Assessor B. Both assessors demonstrated excellent inter-rater reliability for LM thickness and echogenicity (ICC_2,3: 0.79 and 0.94), but poor reliability for IL thickness and echogenicity (ICC_2,3: 0.00 and 0.39).

Conclusions

Inter-rater and test-retest reliability was excellent for LM but was less reliable for measures of the IL muscle.

Thoracolumbar Slope Is Useful Parameter for Evaluating HealthRelated Quality of Life and Sagittal Imbalance Aggravation in Adult Spinal Deformity: A Prospective Observational Cohort Study

Objective

The purpose of the present study was to evaluate the natural course of primary degenerative sagittal imbalance (PDSI), its aggravating factors, and health-related quality of life (HRQoL) associated with various spinal alignment parameters (SAPs) in patients with PDSI who have not undergone surgery.

Methods

One hundred three participants volunteered to participate. The SAPs, including T1 pelvic angle (T1PA), thoracolumbar tilt, and thoracolumbar slope (TLS), were measured on whole-spine standing radiographs. The back and lumbar muscle volumes were measured. To determine HRQoL at baseline and at 2-year follow-up, face-to-face questionnaires were administered, which included visual analogue scale of the back and leg, physical component summary/mental component summary of 36-item Short Form Health Survey, Oswestry Disability Index (ODI), and Mini-Mental State Examination.

Results

Overall HRQoL measures had improved after 2 years of follow-up compared to baseline. PDSI aggravation was observed in 18 participants (26.1%). TLS, sagittal vertical axis (SVA), and T1PA were strongly correlated with each other. TLS, SVA, and T1PA were correlated with ODI score. Among them, TLS was most highly correlated with ODI score. TLS greater than -3.5° was a predicting factor for PDSI aggravation (p=0.034; 95% confidence interval, 1.173–63.61; odds ratio, 8.636).

Conclusion

The present study implied that PDSI does not necessarily worsen with aging. TLS is an appropriate parameter for assessing the clinical situation in patients with PDSI. Furthermore, a TLS greater than -3.5° predicts PDSI aggravation; thus, TLS may be a useful parameter for predicting prognosis in PDSI.

Posterior-Chain Resistance Training Compared to General Exercise and Walking Programmes for the Treatment of Chronic Low Back Pain in the General Population: A Systematic Review and Meta-Analysis

BACKGROUND

While chronic exercise training has been demonstrated to be an effective non-pharmacological treatment for chronic low back pain (CLBP), there has been a relative lack of evidence or clinical guidelines for whether a posterior chain resistance training programme provides any benefits over general exercise (GE).

OBJECTIVES

To determine if chronic posterior chain resistance training (PCRT), defined as exercise programmes of ≥6 weeks duration focused on the thoracic, lumbar and hip extensor musculature, is more effective than GE in improving pain, level of disability, muscular strength and the number of adverse events in recreationally active and sedentary individuals with CLBP.

METHODS

Four electronic databases were systematically searched from 25 September 2019 until 30 August 2020. Using the Joanna Briggs Institute (JBI) Critical Appraisal Tools checklist for randomized controlled trials (RCTs), articles were critically appraised and compared against the inclusion/exclusion criteria. Standardized mean difference (SMD), risk difference (RD) and confidence interval (CI) were calculated using Review Manager 5.3.

RESULTS

Eight articles were included, with a total of 408 participants (203 PCRT, 205 GE). Both PCRT and GE were effective in improving a number of CLBP-related outcomes, but these effects were often significantly greater in PCRT than GE, especially with greater training durations (i.e. 12-16 weeks compared to 6-8 weeks). Specifically, when compared to GE, PCRT demonstrated a greater reduction in pain (SMD = - 0.61 (95% CI - 1.21 to 0.00), p = 0.05; I2 = 74%) and level of disability (SMD = - 0.53 (95% CI - 0.97 to - 0.09), p = 0.02; I2 = 52%), as well as a greater increase in muscle strength (SMD = 0.67 (95% CI 0.21 to 1.13), p = 0.004; I2 = 0%). No differences in the number of adverse events were reported between PCRT and GE (RD = - 0.02 (95% CI - 0.10 to 0.05), p = 0.57; I2 = 72%).

CONCLUSION

Results of the meta-analysis indicated that 12-16 weeks of PCRT had a statistically significantly greater effect than GE on pain, level of disability and muscular strength, with no significant difference in the number of adverse events for recreationally active and sedentary patients with CLBP. Clinicians should strongly consider utilizing PCRT interventions for 12-16 weeks with patients with CLBP to maximize their improvements in pain, disability and muscle strength. Future research should focus on comparing the efficacy and adverse events associated with specific PCRT exercise training and movement patterns (i.e. deadlift, hip lift) in treating this population.

TRIAL REGISTRATION

PROSPERO CRD42020155700 .