Journey Through Autosomal-Recessive Spastic Ataxia of Charlevoix–Saguenay: Insights From a Case Series of Seven Patients–A Single-Center Study and Review of an Indian Cohort
Bibliographic record
Abstract
OBJECTIVE: In this study, we describe the clinical and investigative profiles of 7 cases of autosomal-recessive spastic ataxia of Charlevoix-Saguenay (ARSACS). METHODS: We performed a retrospective chart review of genetically proven cases of ARSACS from our database. Additionally, we reviewed the literature for reported cases of ARSACS from India. RESULTS: All 7 patients experienced disease onset within the first decade of life. According to the available data, all patients had walking difficulty (7/7), spastic ataxia (7/7), classical neuroimaging findings (7/7), sensory‒motor demyelinating polyneuropathy (6/6), abnormal evoked potentials (5/5), and a thickened retinal nerve fiber layer (3/3). Exome sequencing revealed 8 unique pathogenic/likely pathogenic variants (6 novel) in the SACS gene. An additional 21 cases (18 families) of ARSACS that could be identified from India had similar clinical and investigational findings. The most common c.8793delA variant may have a founder effect. CONCLUSION: Our series adds to the previously reported cases of ARSACS from India and expands the genetic spectrum by adding 6 novel variants.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".