Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT04422288 |
| Other study ID # |
NUVA.MSK1901 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
May 15, 2020 |
| Est. completion date |
October 1, 2022 |
Study information
| Verified date |
February 2024 |
| Source |
NuVasive |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial 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.
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.
