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Published on: September 18, 2020
Normative values and phenotypic performance profiles in the modified closed kinetic chain upper extremity stability
Akshitha Rajasekhar1, Rifna Kousar1, Ravi Ramadevarapura Honnahalagegowda1
1Institute of Physiotherapy, Srinivas University City campus Pandeshwar, Mangaluru, Karnataka, India.
Abstract:
BackgroundThe closed kinetic chain upper extremity stability test (CKCUEST) is widely used to assess shoulder stability. The modified CKCUEST (mCKCUEST) incorporates height-normalized hand spacing (50%) to account for individual anthropometric variations and improve biomechanical validity.ObjectiveTo establish normative reference values for mCKCUEST performance in healthy Indian adults and to define diagnostic thresholds and performance phenotypes using percentile classification, ROC analysis, and clustering techniques.MethodsA cross-sectional study was conducted among 517 physically active participants (53.6% females) aged 18-28 years. Each participant completed three mCKCUEST trials. Mean, relative (touches/meter), and power scores were calculated. Percentile ranks were stratified by sex. ROC analysis assessed discriminatory cut-offs, while k-means clustering was used to identify phenotypic subgroups. An adaptation index (Trial 3-Trial 1) was computed to evaluate neuromuscular responsiveness.ResultsThe mean mCKCUEST score was 17.6 ± 2.3 repetitions with a relative score of 10.5 ± 1.5 touches/meter and a power score of 56.2 ± 11.9. Males performed better than females in Trials 2 and 3 (p < 0.001). No significant correlations were observed between anthropometric variables and performance outcomes. K-means clustering revealed three distinct performance phenotypes, including one with low baseline scores but high neuromuscular adaptability. BMI-based stratification showed most participants were in the normal range (72.5%).ConclusionThis study provides normative benchmarks for mCKCUEST in healthy Indian adults. The integration of percentile norms, BMI stratification, and adaptation-based phenotypes enhances individualized interpretation in clinical and performance assessment settings.
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