Spastic Ataxia Composite ( <scp>SPAXCOM</scp> ): A Scale to Evaluate the Progression of Subjects with Spasticity and Ataxia
Bibliographic record
Abstract
BACKGROUND: Current clinical scales that track disease progression are more tailored to spasticity or ataxia, with limited sensitivity to change. OBJECTIVES: The aim was to develop a sensitive and valid scale specifically geared towards optimized sensitivity to change and adapted to patients presenting with both spasticity and ataxia. METHODS: Longitudinal data from 127 spastic paraplegia type 7 (SPG7) and 112 autosomal recessive spastic ataxia Charlevoix-Saguenay (ARSACS) patients were collected within the multicenter PROSPAX study. Sensitivity to change over 2 years of 30 items from the Scale for the Rating and Assessment of Ataxias (SARA), Spastic Paraplegia Rating Scale (SPRS), and the Activities of Daily Living subscale of the Friedreich's Ataxia Rating Scale (FARS-ADL) was evaluated. Items that demonstrated the highest sensitivity to change were used to build the Spastic Ataxia Composite scale (SPAXCOM). RESULTS: With seven items, the SPAXCOM showed an effect size of 0.71, higher than reference scales (SARA: 0.43, SPRS: 0.42, FARS-ADL: 0.27). The SPAXCOM had a similar sensitivity to change for both genotypes and was more sensitive in participants with a SARA lower than 10 and within the intermediate disease stage (FARS-Disease Staging: 2-3.5). The SPAXCOM showed a high correlation with disease duration (r = 0.67 [0.60; 0.72]) and disease stage (r = 0.86 [0.83; 0.89]). Perception of improvement, stagnation, and worsening were associated with a mean yearly SPAXCOM change of 0.44 (-0.14; 1.01), 0.61 (0.19; 1.03), and 1.22 (0.96; 1.49), respectively. CONCLUSION: The SPAXCOM is more sensitive to change and homogeneous across genotypes than the reference scales, allowing a reduction of the required sample size in future clinical trials. © 2025 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".