Proximal Junctional Kyphosis, Spino-pelvic Alignment, Thoracolumbar Spinal Fusion
Conditions
Brief summary
Spinal posture and imbalance are known to be related to increased muscle expenditure, with narrow cone of economy of muscle effort defining the most comfortable postures. Therefore, it is hypothesized that predicting the posture of the lowest muscle effort available for a patient with a given spinal alignment and body properties will correspond to the posture the patient will most likely assume. Based on established musculoskeletal models, a model application was configured to allow prediction of this optimal posture. This study aims to assess the validity of this approach and the value of using biomechanical modeling for pre-operative planning.
Detailed description
The objective of this study is to validate a novel method of post-operative posture prediction - a full-body biomechanical model based on an established technology and physiological reasoning. Specifically, the model ability to predict postoperative global sagittal alignment, including compensatory and reciprocal changes, from pre-operative radiographic imaging and the information about planned posture correction will be evaluated. This will be realized by comparing model-predicted radiographic measures and overall balance to follow-up patient radiographs. Having demonstrated model validity to predict postoperative posture will allow to use this method for simulating various what-if scenarios to empower surgical planning by predicting expected outcomes. This can be used to optimizing preoperative planning, which has a potential to substantially improved surgery predictability and patient outcomes. Furthermore, validated model will allow scientific investigation of the principles governing human posture and biomechanics of the pathological spine. Generated scientific knowledge of biomechanical factors influencing sagittal posture and surgery outcomes (e.g. number of levels fused, amount and distribution of posture correction, etc.) can lead to improvements in clinical management of spinal disorders.
Interventions
None listed
Sponsors
NuVasive
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Inclusion criteria
1. Male or female patients 2. Any ethnicity 3. At least 18 years of age 4. Has undergone a thoracolumbar spinal fusion procedure
Exclusion criteria
1. Patient has had a prior spinal surgery in the thoracic and/or lumbar spine; 2. Patient presents scoliosis greater or equal to 20° T4-T12 Cobb angle; 3. Patient has been diagnosed with idiopathic adolescent scoliosis (treated or untreated); 4. Patient has other implants that obstruct the spine and/or pelvis in the lateral view; 5. Patient presents any of the following complications: pseudoarthrosis, instrumentation failure, instrumentation pull-out and/or requires a revision surgery at any time following the primary surgery and prior to 3 months post-op; 6. Patient is a prisoner.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Difference between model-predicted and observed postural measures - Thoracic Kyphosis (TK) | 3 months | The simulation-predicted posture will be compared against the posture observed at follow-up, using the thoracic kyphosis (TK) angle. |
| Difference between model-predicted and observed postural measures - Lumbar Lordosis (LL) | 3 Months | The simulation-predicted posture will be compared against the posture observed at follow-up, using the LL - lumbar lordosis (LL) angle. |
| Difference between model-predicted and observed postural measures - T1 Pelvic Angle (TPA) | 3 Months | The simulation-predicted posture will be compared against the posture observed at follow-up, using the T1 pelvic angle (TPA). |
| Difference between model-predicted and observed postural measures - Pelvic Incidence-Lumbar Lordosis Mismatch (∆PILL) | 3 Months | The simulation-predicted posture will be compared against the posture observed at follow-up, using the pelvic incidence-lumbar lordosis mismatch (∆PILL). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Model sensitivity and specificity in predicting posture imbalance | 3 months | A McNemar's test (a paired Chi-squared test) will be used to test the null hypothesis that the balance prediction is due to chance, allowing to assess if the model predictive power is better than random. |
Countries
United States
Outcome results
None listed