Device Profile of the Mobi-C Artificial Cervical Disc: an Overview of Its Safety and Efficacy
Expert review of medical devices(2025)
Department of Neurological Surgery
Abstract
INTRODUCTION:The Mobi-C Cervical Disc Replacement is a motion preserving alternative to anterior cervical discectomy and fusion in properly indicated patients. In 2013, Mobi-C became the first cervical disc in the United States approved to treat more than one level of the cervical spine. The FDA determined Mobi-C to be statistically superior to fusion at two levels, based on the primary endpoint of a prospective, concurrently controlled and randomized multicenter clinical trial. AREAS COVERED:The history of Mobi-C and cervical disc arthroplasty is discussed. The unique biomechanics and structure of Mobi-C, the clinical results, the long term follow-up, the disc's biomechanics, and cost-effectiveness research are described. The competitive landscape is overviewed. EXPERT OPINION:The evidence in this article supports the use of the Mobi-C cervical disc prosthesis as a viable alternative to fusion surgery in selected patients. Mobi-C has a relatively long track record compared to most other cervical disc prostheses. Thus far, Mobi-C is a very good option for preserving cervical motion based on long term follow-up, for achieving favorable clinical outcomes, and for maintaining patient safety. The Mobi-C cervical disc prosthesis is generally viewed positively, supported by clinical experience and research findings.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined