Variability of joint hypermobility in children: a meta-analytic approach to set cut-off scores

Cylie M Williams1, James J Welch2, Mark Scheper3,4,5,6

  • 1School of Primary and Allied Health Care, Monash University, 47-49 Moorooduc Hwy, Frankston, VIC, 3199, Australia. cylie.williams@monash.edu.

PubMed

Insights

A Beighton score of 6 or more is recommended to identify generalized joint hypermobility in children. This research analyzed global data to establish a new evidence-based threshold for pediatric hypermobility assessment.

Area of Science:

  • Pediatric Rheumatology
  • Clinical Assessment
  • Joint Hypermobility Syndromes

Background:

  • Current international consensus on defining generalized joint hypermobility (GJH) in children relies on expert opinion.
  • Establishing an evidence-based cut-off for the Beighton score in pediatric populations is crucial for accurate diagnosis.

Purpose of the Study:

  • To determine the global prevalence of Beighton scores in children.
  • To provide a data-driven recommendation for the Beighton score cut-off to identify GJH in children.

Main Methods:

  • Systematic literature search of AMED, OVID Medline, Embase, and CINAHL databases (inception to April 2024).
  • Inclusion of studies reporting Beighton scores in children up to 18 years from the general population.
  • Extraction of data on participant demographics, Beighton scores, and author-defined hypermobility cut-offs.

Main Results:

  • Analysis of 37 articles involving 28,868 participants.
  • A Beighton score cut-off of ≥6 yielded a prevalence of 6% in males and 13% in females across reporting studies.
  • Limited data availability precluded further sub-analyses by age, pubertal status, or ethnicity.

Conclusions:

  • A minimum Beighton score of 6 or more is recommended as the working threshold for identifying GJH in children.
  • A threshold of 7 or greater may be more appropriate for childhood hypermobility assessment, particularly in females.

Related Concept Videos

Functional Classification of Joints01:09

Functional Classification of Joints

Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
4.0K
Variability: Analysis01:11

Variability: Analysis

Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
140
Structural Classification of Joints01:20

Structural Classification of Joints

Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
3.3K
Kendall's Coefficient of Concordance01:20

Kendall's Coefficient of Concordance

Kendall's Coefficient of Concordance (W), also known as Kendall's W, is a non-parametric statistical measure used to assess the agreement or concordance between multiple raters or judges when they rank a set of items. It is often used when you have ordinal data (ranks) and you want to see if there is consistency or consensus among the raters. It is widely applied in research areas such as psychology, medicine, and social sciences, where multiple judges are asked to rank or rate subjects...
323