Prevalence and Risk Factors for Cervical and Lumbar Spondylosis in Interventional Electrophysiologists
Bibliographic record
Abstract
UNLABELLED: INTRODUCTION: The volume and complexity of interventional electrophysiology procedures have increased greatly over the last 20 years. Anecdotal reports from Canada and elsewhere have suggested an important prevalence of neck and back problems in interventional electrophysiologists. METHODS AND RESULTS: To quantify the scope of neck and back problems, we surveyed 70 interventional electrophysiologists in Canada using an electronic survey with in person and email reminders. We also surveyed an age- and gender-matched group of noninterventional cardiologists. We received responses from a total of 58 of 70 interventional electrophysiologists (response rate 82.8%). There was a significantly higher prevalence of cervical spondylosis among electrophysiologists compared to matched noninterventional cardiologists (20.7% compared to 5.5%, P = 0.033). There was a trend for increased prevalence of lumbar spondylosis (25.9% compared to 16.7%, P = 0.298). Among electrophysiologists, those with cervical spondylosis were older (49.83 ± 10.48 years compared to 44.57 ± 9.20, P = 0.092) and had worked in the specialty for longer in comparison to unaffected physicians (19.67 ± 10.06 years compared to 13.37 ± 8.97 years, P = 0.039). All other variables including gender, height, weight, BMI, type of lead, weekly average lead time, and % of time standing in electrophysiology laboratory were not different. On multivariable analysis there were no independent predictors of disease. CONCLUSIONS: There is a significant increased prevalence of cervical spondylosis among interventional electrophysiologists. Programs to improve ergonomics and minimize time spent wearing lead are needed. The same vigilance that is used to ensure radiation safety in the laboratory should be applied to create ergonomic safety.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".