Evaluating stability of human spine in static tasks: a combined <i>in vivo</i>-computational study

Ghezelbash, Farshid; Shahvarpour, Ali; Larivière, Christian; Shirazi‐Adl, A.

doi:10.1080/10255842.2021.2004399

Cited by 4 publications

(4 citation statements)

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“…This test assesses the role of the stabilizing muscles of the lumbar spine in a neutral posture, in which passive tissue stiffness plays a minimal role [ 54 ]. Raising the load above the body’s center of mass (shoulder height) increases the challenge to spine stability (by increasing the potential energy of the system), as evidenced by increased trunk muscle activation with higher loads [ 55 , 56 ]. This is further challenged when the supported load is held away from the body, as not only is dorsal trunk muscle activation increased to counteract the net moment in flexion (also producing added spine compression), but there is also an increase in abdominal muscle activation that can only be attributed to maintaining lumbar stability [ 55 , 57 ].…”

Section: Discussionmentioning

confidence: 99%

“…Raising the load above the body’s center of mass (shoulder height) increases the challenge to spine stability (by increasing the potential energy of the system), as evidenced by increased trunk muscle activation with higher loads [ 55 , 56 ]. This is further challenged when the supported load is held away from the body, as not only is dorsal trunk muscle activation increased to counteract the net moment in flexion (also producing added spine compression), but there is also an increase in abdominal muscle activation that can only be attributed to maintaining lumbar stability [ 55 , 57 ]. Our original hypothesis was that patients with poorer lumbar spine stabilization would have difficulty performing this test (scores below 0.75/1) and would benefit from the lumbar stabilization exercise program.…”

Section: Discussionmentioning

confidence: 99%

“…However, it is the patients with higher scores who benefited. Moving the load forward induces an automatic co-contraction of the trunk muscles [ 57 ], which would contribute to maintaining lumbar stability [ 55 ]. This test, therefore, may not elicit pain related to lumbar instability, but might elicit pain from other causes such as spinal compression.…”

Section: Discussionmentioning

confidence: 99%

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Derivation of clinical prediction rules for identifying patients with non-acute low back pain who respond best to a lumbar stabilization exercise program at post-treatment and six-month follow-up

et al. 2022

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Low back pain (LBP) remains one of the most common and incapacitating health conditions worldwide. Clinical guidelines recommend exercise programs after the acute phase, but clinical effects are modest when assessed at a population level. Research needs to determine who is likely to benefit from specific exercise interventions, based on clinical presentation. This study aimed to derive clinical prediction rules (CPRs) for treatment success, using a lumbar stabilization exercise program (LSEP), at the end of treatment and at six-month follow-up. The eight-week LSEP, including clinical sessions and home exercises, was completed by 110 participants with non-acute LBP, with 100 retained at the six-month follow-up. Physical (lumbar segmental instability, motor control impairments, posture and range of motion, trunk muscle endurance and physical performance tests) and psychological (related to fear-avoidance and home-exercise adherence) measures were collected at a baseline clinical exam. Multivariate logistic regression models were used to predict clinical success, as defined by ≥50% decrease in the Oswestry Disability Index. CPRs were derived for success at program completion (T8) and six-month follow-up (T34), negotiating between predictive ability and clinical usability. The chosen CPRs contained four (T8) and three (T34) clinical tests, all theoretically related to spinal instability, making these CPRs specific to the treatment provided (LSEP). The chosen CPRs provided a positive likelihood ratio of 17.9 (T8) and 8.2 (T34), when two or more tests were positive. When applying these CPRs, the probability of treatment success rose from 49% to 96% at T8 and from 53% to 92% at T34. These results support the further development of these CPRs by proceeding to the validation stage.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Derivation of clinical prediction rules for identifying patients with non-acute low back pain who respond best to a lumbar stabilization exercise program at post-treatment and six-month follow-up

et al. 2022

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“…Interestingly, this test was selected in the clinical prediction rules predicting the treatment success after a lumbar stabilization exercise programme at the end of the 8‐week treatment as well as at the 6‐month follow‐up (Larivière, Rabhi, et al, 2022). In healthy participants (no LBP), moving the load forward induces an automatic co‐contraction of back and abdominal muscles (Larivière et al, 2019), which would contribute to preserving lumbar stability (Ghezelbash et al, 2022). This is especially true for deeper abdominals (IO and TrA), comparatively to EO, as substantiated in a surface electromyographic (EMG) study (Larivière et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

The relationship between clinical examination measures and ultrasound measures of fascia thickness surrounding trunk muscles or lumbar multifidus fatty infiltrations: An exploratory study

et al. 2022

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Patients with chronic low back pain (CLBP) exhibit remodelling of the lumbar soft tissues such as muscle fatty infiltrations (MFI) and fibrosis of the lumbar multifidus (LuM) muscles, thickness changes of the thoracolumbar fascia (TLF) and perimuscular connective tissues (PMCT) surrounding the abdominal lateral wall muscles. Rehabilitative ultrasound imaging (RUSI) parameters such as thickness and echogenicity are sensitive to this remodelling. This experimental laboratory study aimed to explore whether these RUSI parameters (LuM echogenicity and fascia thicknesses), hereafter called dependent variables (DV) were linked to independent variables (IV) such as (1) other RUSI parameters (trunk muscle thickness and activation) and (2) physical and psychological measures. RUSI measures, as well as a clinical examination comprising physical tests and psychological questionnaires, were collected from 70 participants with LBP. The following RUSI dependent variables (RUSI‐DV), measures of passive tissues were performed bilaterally: (1) LuM echogenicity (MFI/fibrosis) at three vertebral levels (L3/L4, L4/L5 and L5/S1); (2) TLF posterior layer thickness, and (3) PMCT thickness of the fasciae between subcutaneous tissue thickness (STT) and external oblique (PMCTSTT/EO), between external and internal oblique (PMCTEO/IO), between IO and transversus abdominis (PMCTIO/TrA) and between TrA and intra‐abdominal content (PMCTTrA/IA). RUSI measures of trunk muscle's function (thickness and activation), also called measures of active muscle tissues, were considered as independent variables (RUSI‐IV), along with physical tests related to lumbar stability (n = 6), motor control deficits (n = 7), trunk muscle endurance (n = 4), physical performance (n = 4), lumbar posture (n = 2), and range of motion (ROM) tests (n = 6). Psychosocial measures included pain catastrophizing, fear‐avoidance beliefs, psychological distress, illness perceptions and concepts related to adherence to a home‐based exercise programme (physical activity level, self‐efficacy, social support, outcome expectations). Six multivariate regression models (forward stepwise selection) were generated, using RUSI‐DV measures as dependent variables and RUSI‐IV/physical/psychosocial measures as independent variables (predictors). The six multivariate models included three to five predictors, explaining 63% of total LuM echogenicity variance, between 41% and 46% of trunk superficial fasciae variance (TLF, PMCTSTT/EO) and between 28% and 37% of deeper abdominal wall fasciae variance (PMCTEO/IO, PMCTIO/TrA and PMCTTrA/IA). These variables were from RUSI‐IV (LuM thickness at rest, activation of IO and TrA), body composition (percent fat) and clinical physical examination (lumbar and pelvis flexion ROM, aberrant movements, passive and active straight‐leg raise, loaded‐reach test) from the biological domain, as well as from the lifestyle (physical activity level during sports), psychological (psychological distress—cognitive subscale, fear‐avoidance beliefs during physical ac...

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Effect of personalized spinal profile on its biomechanical response in an EMG-assisted optimization musculoskeletal model of the trunk

Larivière,

Eskandari,

Mecheri

et al. 2024

Journal of Biomechanics

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Evaluating stability of human spine in static tasks: a combined in vivo-computational study

Cited by 4 publications

References 65 publications

Derivation of clinical prediction rules for identifying patients with non-acute low back pain who respond best to a lumbar stabilization exercise program at post-treatment and six-month follow-up

Derivation of clinical prediction rules for identifying patients with non-acute low back pain who respond best to a lumbar stabilization exercise program at post-treatment and six-month follow-up

The relationship between clinical examination measures and ultrasound measures of fascia thickness surrounding trunk muscles or lumbar multifidus fatty infiltrations: An exploratory study

Effect of personalized spinal profile on its biomechanical response in an EMG-assisted optimization musculoskeletal model of the trunk

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