PP12.14 – 2319: Reliability of phenotypic early onset ataxia recognition

Abstract

Objective In absence of a “golden detection standard”, identification of early onset ataxia (EOA) relies on phenotypic ataxia recognition. In children, this process is complex for several reasons: 1. physiologically immature motor behavior may “overlap” with signs of initiating ataxia; 2. EOA often involves “mixed” phenotypes (i.e. concurrent with other movement disorders) and 3. movement disorders are phenotyped by specialists of diverse backgrounds. Insight in phenotypic EOA recognition may help to improve the diagnostic yield of innovative genetic techniques and may contribute to the inclusion of high quality patient data in international databases. This study aimed to investigate the inter-observer agreement on phenotypic EOA recognition and to explore whether SARA (Scale for Assessment and Rating of Ataxia) can provide a discriminative marker for EOA recognition. Methods Seven movement disorder specialists independently phenotyped motor behavior of 40 patients (mean age 15 years, range 5–34 years) in whom ataxic features were described (medical records; University Medical Center Groningen; 1998–2012). We determined Fleiss Kappa (FK) and Cohen's Kappa's according to observer-subgroups (pediatric-neurology, adult-neurology, genetics, and trainees). We compared %SARA-subscores (subscore/total score x 100%) between “indisputable” (primary ataxia recognition by at least six observers) and “mixed” (ataxia recognition, unfulfilling “indisputable” criteria) EOA phenotypes. Results Phenotypic EOA recognition was statistically significant, but of moderate strength (FK=0.414). Pediatric neurologists revealed the highest intergroup agreement (with all observer-subgroups; p Conclusion Among movement disorder professionals from different disciplines, inter-observer agreement on phenotypic EOA recognition is statistically significant, but of moderate strength. SARA gait-subscores can provide a supportive discriminative marker between EOA phenotypes. Phenotypic insight may hopefully contribute to the inclusion of uniform, high quality data in international EOA databases.