Assessment and Reporting of Driving Fitness in Patients with Dementia in Clinical Practice: Data from SveDem, the Swedish Dementia Registry
Bibliographic record
Abstract
BACKGROUND: Driving constitutes a very important aspect of daily life and is dependent on cognitive functions such as attention, visuo-spatial skills and memory, which are often compromised in dementia. Therefore, the driving fitness of patients with dementia needs to be addressed by physicians and those that are deemed unfit should not be allowed to continue driving. OBJECTIVE: We aimed at investigating to what extent physicians assess driving fitness in dementia patients and determinant factors for revoking of their licenses. METHODS: This study includes 15113 patients with newly diagnosed dementia and driver's license registered in the Swedish Dementia Registry (SveDem). The main outcomes were reporting to the licensing authority and making an agreement about driving eligibility with the patients. RESULTS: Physicians had not taken any action in 16% of dementia patients, whereas 9% were reported to the authority to have their licenses revoked. Males (OR = 3.04), those with an MMSE score between 20-24 (OR = 1.35) and 10-19 (OR = 1.50), patients with frontotemporal (OR = 3.09) and vascular dementia (OR = 1.26) were more likely to be reported to the authority. CONCLUSION: For the majority of patients with dementia, driving fitness was assessed. Nevertheless, physicians did not address the issue in a sizeable proportion of dementia patients. Type of dementia, cognitive status, age, sex and burden of comorbidities are independent factors associated with the assessment of driving fitness in patients with dementia. Increased knowledge on how these factors relate to road safety may pave the way for more specific guidelines addressing the issue of driving in patients with dementia.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".