Digital Gait Outcomes for Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS): Discriminative, Convergent, and Ecological Validity in a Multicenter Study (PROSPAX).
Bibliographic record
Abstract
With treatment trials on the horizon, this study aimed to identify candidate digital-motor gait outcomes for autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS), capturable by wearable sensors with multicenter validity, and ideally also ecological validity during free walking outside laboratory settings.Cross-sectional multicenter study (four centers), with gait assessments in 36 subjects (18 ARSACS patients; 18 controls) using three body-worn sensors (Opal, APDM) in laboratory settings and free walking in public spaces. Sensor gait measures were analyzed for discriminative validity from controls, and for convergent (ie, clinical and patient relevance) validity by correlations with SPRSmobility (primary outcome) and Scale for the Assessment and Rating of Ataxia (SARA), Spastic Paraplegia Rating Scale (SPRS), and activities of daily living subscore of the Friedreich Ataxia Rating Scale (FARS-ADL) (exploratory outcomes).Of 30 hypothesis-based digital gait measures, 14 measures discriminated ARSACS patients from controls with large effect sizes (|Cliff's δ| > 0.8) in laboratory settings, with strongest discrimination by measures of spatiotemporal variability Lateral Step Deviation (δ = 0.98), SPcmp (δ = 0.94), and Swing CV (δ = 0.93). Large correlations with the SPRSmobility were observed for Swing CV (Spearman's ρ = 0.84), Speed (ρ = -0.63), and Harmonic Ratio V (ρ = -0.62). During supervised free walking in a public space, 11/30 gait measures discriminated ARSACS from controls with large effect sizes. Large correlations with SPRSmobility were here observed for Swing CV (ρ = 0.78) and Speed (ρ = -0.69), without reductions in effect sizes compared with laboratory settings.We identified a promising set of digital-motor candidate gait outcomes for ARSACS, applicable in multicenter settings, correlating with patient-relevant health aspects, and with high validity also outside laboratory settings, thus simulating real-life walking with higher ecological validity. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".