scholarly journals XGBoost, a Machine Learning Method, Predicts Neurological Recovery in Patients with Cervical Spinal Cord Injury

2020 ◽  
Vol 1 (1) ◽  
pp. 8-16
Author(s):  
Tomoo Inoue ◽  
Daisuke Ichikawa ◽  
Taro Ueno ◽  
Maxwell Cheong ◽  
Takashi Inoue ◽  
...  
Keyword(s):  
Machine Learning ◽  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Cervical Spinal Cord ◽  
Cervical Spinal Cord Injury ◽  
Neurological Recovery ◽  
Machine Learning Method ◽  
Learning Method ◽  
Cord Injury

scholarly journals Intramedullary Lesion Length has a Negative Effect on Neurological Recovery in Cervical Spinal Cord Injury Patients with AIS Grades A-C

2016 ◽  
Vol 6 (1_suppl) ◽  
pp. s-0036-1582936-s-0036-1582936
Author(s):  
Bizhan Aarabi ◽  
Charles Sansur ◽  
David Ibrahimi ◽  
David Hersh ◽  
Elizabeth Le ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Cervical Spinal Cord ◽  
Cervical Spinal Cord Injury ◽  
Neurological Recovery ◽  
Lesion Length ◽  
Intramedullary Lesion ◽  
Cord Injury ◽  
Negative Effect

scholarly journals Window of opportunity for surgical decompression in patients with acute traumatic cervical spinal cord injury

2020 ◽  
Vol 32 (5) ◽  
pp. 633-641 ◽  
Author(s):  
Marko Jug ◽  
Nataša Kejžar ◽  
Matej Cimerman ◽  
Fajko F. Bajrović
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Cervical Spinal Cord ◽  
Surgical Decompression ◽  
Cervical Spinal Cord Injury ◽  
Neurological Recovery ◽  
Optimal Timing ◽  
Neurological Improvement ◽  
Severity Of Injury ◽  
Cord Injury

OBJECTIVEThe objective of this prospective study was to determine the optimal timing for surgical decompression (SD) in patients with acute traumatic cervical spinal cord injury (tSCI) within the first 24 hours of injury.METHODSIn successive patients with fracture and/or dislocation of the subaxial cervical spine and American Spinal Injury Association Impairment Scale (AIS) grades A–C, receiver operating characteristic curve analysis was used to determine the optimal timing for SD within the first 24 hours of cervical tSCI to obtain a neurological recovery of at least two AIS grades. Multivariate logistic regression was used to model significant neurological recovery with time to SD, degree of spinal canal compromise (SCC), and severity of injury.RESULTSIn this cohort of 64 patients, the optimal timing for SD to obtain a significant neurological improvement was within 4 hours of injury (95% confidence interval 4–9 hours). Increasing the delay from injury to SD or the degree of SCC significantly reduced the likelihood of significant neurological improvement. Due to the strong correlation with SCC, the severity of injury was a marginally significant predictor of neurological recovery.CONCLUSIONSThese findings indicate that in patients with acute cervical tSCI and AIS grades A–C, the optimal timing for SD is within the first 4–9 hours of injury, depending on the degree of SCC and the severity of injury. Further studies are required to better understand the interrelationships among the timing of SD, injury severity, and degree of SCC in these patients.

Determining the short-term neurological prognosis for acute cervical spinal cord injury using machine learning

2022 ◽  
Vol 96 ◽  
pp. 74-79
Author(s):  
Sho Okimatsu ◽  
Satoshi Maki ◽  
Takeo Furuya ◽  
Takayuki Fujiyoshi ◽  
Mitsuhiro Kitamura ◽  
...  
Keyword(s):  
Machine Learning ◽  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Cervical Spinal Cord ◽  
Cervical Spinal Cord Injury ◽  
Short Term ◽  
Cord Injury ◽  
Neurological Prognosis

scholarly journals An Inertial Measurement Unit-Based Wireless System for Shoulder Motion Assessment in Patients with Cervical Spinal Cord Injury: A Validation Pilot Study in a Clinical Setting

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1057
Author(s):  
Riccardo Bravi ◽  
Stefano Caputo ◽  
Sara Jayousi ◽  
Alessio Martinelli ◽  
Lorenzo Biotti ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Clinical Setting ◽  
Cervical Spinal Cord ◽  
Wearable Sensors ◽  
Cervical Spinal Cord Injury ◽  
Measurement Unit ◽  
Innovative Technology ◽  
Inertial Measurement ◽  
Cord Injury

Residual motion of upper limbs in individuals who experienced cervical spinal cord injury (CSCI) is vital to achieve functional independence. Several interventions were developed to restore shoulder range of motion (ROM) in CSCI patients. However, shoulder ROM assessment in clinical practice is commonly limited to use of a simple goniometer. Conventional goniometric measurements are operator-dependent and require significant time and effort. Therefore, innovative technology for supporting medical personnel in objectively and reliably measuring the efficacy of treatments for shoulder ROM in CSCI patients would be extremely desirable. This study evaluated the validity of a customized wireless wearable sensors (Inertial Measurement Units—IMUs) system for shoulder ROM assessment in CSCI patients in clinical setting. Eight CSCI patients and eight healthy controls performed four shoulder movements (forward flexion, abduction, and internal and external rotation) with dominant arm. Every movement was evaluated with a goniometer by different testers and with the IMU system at the same time. Validity was evaluated by comparing IMUs and goniometer measurements using Intraclass Correlation Coefficient (ICC) and Limits of Agreement (LOA). inter-tester reliability of IMUs and goniometer measurements was also investigated. Preliminary results provide essential information on the accuracy of the proposed wireless wearable sensors system in acquiring objective measurements of the shoulder movements in CSCI patients.

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