Predicting postoperative gait in cerebral palsy

Autor: Bernadette Dorizzi, A C Omar Galarraga, Eric Desailly, N. Khouri, Vincent Vigneron
Přispěvatelé: Informatique, Biologie Intégrative et Systèmes Complexes (IBISC), Université d'Évry-Val-d'Essonne (UEVE), UNAM, Fondation Ellen Poidatz, Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Centre National de la Recherche Scientifique (CNRS), CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Informatique, Biologie Intégrative et Systèmes Complexes ( IBISC ), Université d'Évry-Val-d'Essonne ( UEVE ), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux ( SAMOVAR ), Institut Mines-Télécom [Paris]-Télécom SudParis ( TSP ) -Centre National de la Recherche Scientifique ( CNRS )
Rok vydání: 2017
Předmět:
Male
medicine.medical_specialty
Adolescent
Biophysics
Physical examination
[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing
Kinematics
Single-event multilevel surgery
Cerebral palsy
Clinical gait analysis
Machine Learning
03 medical and health sciences
0302 clinical medicine
Outcome Assessment
Health Care
Preoperative Care
Humans
Medicine
Orthopedic Procedures
Orthopedics and Sports Medicine
Child
Physical Examination
Gait Disorders
Neurologic
Retrospective Studies
Orthodontics
Principal Component Analysis
medicine.diagnostic_test
business.industry
Cerebral Palsy
Rehabilitation
Outcome prediction
030229 sport sciences
medicine.disease
Gait
Confidence interval
Sagittal plane
Biomechanical Phenomena
Transverse plane
medicine.anatomical_structure
Lower Extremity
Coronal plane
Linear Models
Physical therapy
Female
business
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Algorithms
030217 neurology & neurosurgery
Zdroj: Gait & Posture
Gait & Posture, 2017, 52, pp.45--51. ⟨10.1016/j.gaitpost.2016.11.012⟩
Gait and Posture
Gait and Posture, Elsevier, 2017, 52, pp.45--51. ⟨10.1016/j.gaitpost.2016.11.012⟩
Gait and Posture, Elsevier, 2017, 52, pp.45--51. 〈10.1016/j.gaitpost.2016.11.012〉
ISSN: 0966-6362
1879-2219
Popis: International audience; In this work, postoperative lower limb kinematics are predicted with respect to preoperative kinematics, physical examination and surgery data. Data of 115 children with cerebral palsy that have undergone single-event multilevel surgery were considered. Preoperative data dimension was reduced utilizing principal component analysis. Then, multiple linear regressions with 80% confidence intervals were performed between postoperative kinematics and bilateral preoperative kinematics, 36 physical examination variables and combinations of 9 different surgical procedures. The mean prediction errors on test vary from 4° (pelvic obliquity and hip adduction) to 10° (hip rotation and foot progression), depending on the kinematic angle. The unilateral mean sizes of the confidence intervals vary from 5° to 15°. Frontal plane angles are predicted with the lowest errors, however the same performance is achieved when considering the postoperative average signals. Sagittal plane angles are better predicted than transverse plane angles, with statistical differences with respect to the average postoperative kinematics for both plane's angles except for ankle dorsiflexion. The mean prediction errors are smaller than the variability of gait parameters in cerebral palsy. The performance of the system is independent of the preoperative state severity of the patient. Even if the system is not yet accurate enough to define a surgery plan, it shows an unbiased estimation of the most likely outcome, which can be useful for both the clinician and the patient. More patients’ data are necessary for improving the precision of the model in order to predict the kinematic outcome of a large number of possible surgeries and gait patterns.
Databáze: OpenAIRE
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