On-road assessment of fitness-to-drive in persons with MS with cognitive impairment: A prospective study
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment is common in multiple sclerosis (MS). In other populations, cognitive impairment is known to affect fitness-to-drive. Few studies have focused on fitness-to-drive in MS and no studies have solely focused on the influence of cognitive impairment. OBJECTIVE: To assess fitness-to-drive in persons with MS with cognitive impairment and low physical disability. METHODS: Persons with MS, aged 18-59 years with EDSS ⩽ 4.0, impaired processing speed, and impairment on at least one measure of memory or executive function, were recruited. Cognition was assessed using the Minimal Assessment of Cognitive Function battery. A formal on-road driving assessment was conducted. Chi-square analysis examined the association between the fitness-to-drive (pass/fail) and the neuropsychological test results (normal/impaired). Bayesian statistics predicting failure of the on-road assessment were calculated. RESULTS: ( df = 1, N = 36) = 3.956; p = 0.047) with a sensitivity of 100%, but low specificity (35.7%) due to false positives (18/25). CONCLUSION: In persons with MS and impaired processing speed, impairment on the BVMTR-IR should lead clinicians to address fitness-to-drive.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".