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  • TEAMS: An Algorithm for Fusion Level Selection in Idiopathic Adolescent Scoliosis Surgery

    Final Number:

    Ryan Gregory Nazar MD

    Study Design:

    Subject Category:

    Meeting: Section on Disorders of the Spine and Peripheral Nerves 2016 Annual Meeting

    Introduction: The purpose of this study is to review the literature to determine guidelines for selection of fusion levels in adolescent idiopathic scoliosis (AIS). The mnemonic TEAMS is introduced as an algorithm for decision making when trying to determine fusion levels and includes: Type of curve, End of cobb angle, Avoiding kyphotic apex, Mobile disc segment below fusion, Stable zone of Harrington for end points.

    Methods: We conducted systematic review of publications evaluating the surgical treatment of AIS for the period of 1950 to 2015.

    Results: A total of 6 classification systems of AIS curves types were identified; highlighting pertinent and significant contributions that determine correct fusion level selection as well as identifying limitations and potential improvements (Table 1). Classification and treatment has changed over time as evident in Table 1 because our understanding of correct fusion level determination in AIS has evolved over time. Table 2 demonstrates a natural evolution of important concepts that have been realized in AIS management that were categorized into the general concepts for selecting fusion level. Most of the literature on this subject comes from level 4 studies that are case series. In order to simplify understanding of a complex topic, determine guidelines for fusion levels, and provide a framework for future concepts that emerge; we categorized current understanding and parameters based upon our literature review to create the mnemonic TEAMS (Table 3)

    Conclusions: The TEAMS mnemonic provides a simple guide to understanding and determining fusion levels for AIS based upon a balanced curve correction and leaving the maximum number of mobile vertebral segments. Residents, fellows, and spine surgeons can benefit from the decision-making algorithm presented here. Further research is needed to evaluate the long-term outcomes, versatility, reliability, and accuracy of our method for defining the vertebrae to be included for arthrodesis.

    Patient Care: The evolution of classification systems and concepts through time demonstrated by Tables 1 and 2 only helps to support that selection of fusion for thoracic and thoracolumbar/lumbar curves in AIS is a concept that is critically debated and difficult to apply in practice. Our study reviews the literature serving as an introduction to determining which patients should undergo selective fusion and which vertebrae should be included in that fusion. In order to simplify understanding of a complex topic, determine guidelines for fusion levels, and provide a framework for future concepts that emerge; we categorized current understanding and parameters based upon our literature review to create the mnemonic TEAMS.

    Learning Objectives: By the conclusion of this session, participants should be able to: 1) Discuss the selection of fusion levels in AIS. 2) Identify curve types as structural or non-structural; rigid, semi-rigid, or flexible. 3) Apply the TEAMS algorithm to case examples

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