Driving restrictions after implantable cardioverter defibrillator implantation: an evidence-based approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: Little evidence is available regarding restrictions from driving following implantable cardioverter defibrillator (ICD) implantation or following first appropriate or inappropriate shock. The purpose of the current analysis was to provide evidence for driving restrictions based on real-world incidences of shocks (appropriate and inappropriate). METHODS AND RESULTS: A total of 2786 primary and secondary prevention ICD patients were included. The occurrence of shocks was noted during a median follow-up of 996 days (inter-quartile range, 428-1833 days). With the risk of harm (RH) formula, using the incidence of sudden cardiac incapacitation, the annual RH to others posed by a driver with an ICD was calculated. Based on Canadian data, the annual RH to others of 5 in 100 000 (0.005%) was used as a cut-off value. In both primary and secondary prevention ICD patients with private driving habits, no restrictions to drive directly following implantation, or an inappropriate shock are warranted. However, following an appropriate shock, these patients are at an increased risk to cause harm to other road users and therefore should be restricted to drive for a period of 2 and 4 months, respectively. In addition, all ICD patients with professional driving habits have a substantial elevated risk to cause harm to other road users during the complete follow-up after both implantation and shock and should therefore be restricted to drive permanently. CONCLUSION: The current analysis provides a clinically applicable tool for guideline committees to establish evidence-based driving restrictions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it