Does Left Ventricular Assist Device Implantation Affect Driving Patterns in Patients With End-Stage Heart Failure?
Bibliographic record
Abstract
Background In 2012, the Canadian Society of Cardiology indicated that patients supported with left ventricular assist device (LVAD) may drive a private vehicle 2 months after implantation, provided they are deemed clinically stable. Objective evidence supporting this recommendation is limited. We sought to compare data regarding driving habits in our patients following LVAD implantation. Methods A standard questionnaire addressing driving patterns before and after LVAD implantation was sent to all living patients who had received an LVAD between January 2010 and January 2014. Ninety-four of 124 patients responded (average age 58 years, 69.2% men, 77.7% bridge to transplant). Results Prior to LVAD, all were living at home, 33% were employed, and 93% were driving. Sixty-nine percent indicated they drove after LVAD implantation; they were younger (56 vs 62 years, p=0.02) and had providers recommendation (p=0.004). Four of seven patients who had not driven before started driving (p Conclusions Most patients returned to driving after LVAD implantation. A minority had LVAD-associated alarms that were easily addressed. We suggest inclusion of driving habits in registries to provide clarity on the safety of driving while being supported with LVAD.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".