Hepatic encephalopathy and driving safety: A survey of patient counseling and regulatory reporting by health care professionals in British Columbia, Canada
Bibliographic record
Abstract
Background: Hepatic encephalopathy (HE) is a neuropsychiatric syndrome resulting from liver dysfunction, leading to significant cognitive and motor impairments. These impairments can severely affect daily activities, including driving. This research explores the public safety issue of HE and driving safety, focusing on the knowledge and practices of health care professionals. Methods: An electronic survey was distributed across various institutions in British Columbia, Canada, targeting 191 health care professionals, including attending physicians, residents, nurse practitioners, medical students, and fellows from various specialties. The survey assessed the training received, frequency of discussions about driving safety, and actions taken regarding advising patients to stop driving. Results: This study revealed significant gaps in addressing driving safety protocols by health care providers among patients with HE. Only 19.9% of professionals routinely ask their patients about driving, and few engage in specific discussions about driving safety. Internal medicine and gastroenterology specialists, who are most likely to care for patients with HE, reported low practices of screening for and educating about HE and driving safety. Conclusions: The findings underscore the need for increased awareness and proactive discussions among health care providers regarding driving safety in patients with HE. Implementing routine assessments and discussions in HE management protocols can enhance patient safety. Future research should focus on developing standardized guidelines and evaluating the effectiveness of interventions in reducing driving-related risks.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".