A SYSTEMATIC REVIEW OF THE RISK OF MOTOR VEHICLE COLLISION AND DEMENTIA
Bibliographic record
Abstract
Guidelines that physicians use to assess fitness to drive for dementia are limited in their currency, applicability, and rigor of development. We performed a systematic review to determine the risk of motor vehicle collisions or driving impairment caused by dementia. Seven literature databases retrieved 12,860 search results: we included nine studies in this analysis, involving 378 participants with dementia and 416 healthy controls. We found medium to large effects of dementia on driving abilities in six of the seven recent studies that examined driving impairment. Persons with dementia were more likely to fail a road test than healthy controls (RR: 10.77, 95% CI: 3.00–38.62, z=3.65, p<0.001), with no significant heterogeneity (χ2=1.50, p=0.68, I2=0%). Even mild stages of dementia place patients at substantially higher risk of failing a performance-based road test and of demonstrating impaired driving abilities on the road.
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".