Seizure Attacks While Driving: Quality of Life in Persons with Epilepsy
Bibliographic record
Abstract
OBJECTIVE: To study the effect on quality of life (QOL) of a seizure attack while driving in persons with epilepsy (PWE). METHODS: From four provincial and eight university hospitals in Thailand, we enrolled epileptic patients who drove a car or motorcycle or used to drive. The SF-36 questionnaire was used to evaluate QOL. The mean SF-36 score for all dimensions was calculated and compared with patients who either had or did not have a seizure attack while driving and in those who either had or had not been involved in a traffic accident while driving. RESULTS: We had 245 adult PWE who drove a car or motorcycle or used to drive. Of these, 69 cases (28%) had a seizure attack whilst driving. Over half (36/69; 57%) had had seizure-related accidents, most of which were mild but about 20% needed hospitalization. PWE having a seizure attack while driving had a significantly lower QOL in four of the eight categories compared with patients who had not. PWE who had a seizure-related accident had a significantly lower mean value in the vitality category than those who did not. CONCLUSIONS: Seizure attacks while driving diminished QOL in PWE even though they only suffered minor injuries. Driving as a QOL issue should be discussed with patients. A good public transportation system would ease the need 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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".