Related Experiment Video
Updated: Apr 17, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
Published on: May 10, 2019
Overlapping Sanders scores challenge age-based AIS/JIS classifications
Matthew Weintraub1, Omar Taha1, Mehdi M Elfilali2
1Department of Orthopedics, Columbia University Irving Medical Center, New York, USA.
Purpose:
The current classification of idiopathic scoliosis relies on chronological age cutoffs to differentiate juvenile (JIS) from adolescent (AIS) subtypes. However, age-based distinctions may not reliably reflect physiological maturity, a critical factor for predicting curve progression and guiding treatment. This study investigates skeletal maturity differences across the traditional JIS-AIS age threshold using the Sanders maturity scale (SMS).
Methods:
A retrospective review was conducted using a multicenter pediatric spine registry. Patients aged 7-13 years with idiopathic scoliosis and documented SMS scores were included. SMS distributions were analyzed across age bands surrounding the JIS-AIS cutoff (9-10 vs. 10-11 years). Demographic and anthropometric data evaluated factors associated with skeletal maturity variation.
Results:
Among 637 patients (86% female and 14% male), there was a 50% overlap in SMS scores between 9-10 and 10-11-year-olds, with many AIS-classified patients exhibiting skeletal immaturity similar to JIS counterparts. SMS stages 3-5 were associated with greater height, weight, and BMI than stages 1-2 within the same age range. Female and non-Caucasian patients were more likely to show advanced skeletal maturity. These findings underscore significant heterogeneity in growth potential near the age-based diagnostic boundary.
Conclusion:
Chronological age alone does not reliably reflect skeletal maturity or growth risk in idiopathic scoliosis patients. The Sanders Maturity Scale offers a more precise, physiology-based alternative to age-based classification and should be considered in diagnostic, prognostic, and treatment frameworks. Transitioning toward skeletal maturity-based classification could enhance treatment individualization, improve clinical trial stratification, and optimize patient outcomes.
More Related Videos
11:29Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools
Published on: June 20, 2020
09:00Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
Published on: August 16, 2024
Related Concept Videos
Sieve Analysis and Grading Curves
Types of Aggregate Grading
Well-graded aggregates include a complete range of necessary size fractions that fit together to create a dense matrix with minimal voids, represented by a smooth, continuous gradation curve. This type of grading ensures good...
Aggregates Classification
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
Measures of Intelligence
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
Classification of Systems-II
Introduction to z Scores
z scores...