ARSACS in a young Indian adult: a case report on autosomal recessive spastic ataxia presentation
Bibliographic record
Abstract
This case report elucidates the intricate clinical trajectory and diagnostic odyssey of a 26- year-old Indian male presenting with Autosomal Recessive Spastic Ataxia of Charlevoix- Saguenay (ARSACS). The patient‘s history with a progressive array of symptoms, including falls, balance impairments, dysarthria, and muscle cramps, exhibited heightened severity at the age of 15. Remarkably, despite the challenges imposed by these symptoms, the patient maintained a degree of independence in his daily activities. The definitive diagnosis was established through a comprehensive clinical evaluation, imaging studies, and genetic analysis, which disclosed a SACS mutation (p.Lys2931AsnfsTer22). Neurological examination brought to light bilateral lower limb spasticity, toe muscle weakness, absent ankle reflexes, and discernible cerebellar signs. Magnetic Resonance Imaging (MRI) revealed characteristic linear transverse hypointensities in the pons and superior vermis, indicative of cerebellar atrophy. Ophthalmic evaluation further fortified the diagnosis with findings of retinal nerve fibre layer thickening and foveal hypoplasia. This case underscores the intrinsic heterogeneity in the clinical presentation of ARSACS and accentuates the critical importance of a multidisciplinary approach for precision in diagnosis. The molecular validation achieved through genetic testing, particularly the identification of a SACS mutation, serves as an indispensable foundation for comprehending the observed phenotype. Recognition of ARSACS assumes paramount significance for informed counselling, effective management, and potential therapeutic interventions. Subsequent research endeavours are warranted to unravel the underlying pathophysiological mechanisms and augment our comprehension of this rare neurological condition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".