A Global Survey of Ergonomics Practice Patterns and Rates of Musculoskeletal Pain Among Urologists Performing Retrograde Intrarenal Surgery
Bibliographic record
Abstract
Purpose: Retrograde intrarenal surgery (RIRS) requires urologists to adopt an awkward body posture for long durations. Few urologists receive training in ergonomics despite the availability of ergonomic best practices utilized by other surgical specialties. We characterize ergonomic practice patterns and rates of musculoskeletal (MSK) pain among urologists performing RIRS. Methods: A web-based survey was distributed through the Endourological Society, the European Association of Urology, and social media. Surgeon anthropometrics and ergonomic factors were compared with ergonomic best practices. Pain was assessed with the Nordic Musculoskeletal Questionnaire (NMQ). Results: Overall, 519 of 526 participants completed the survey (99% completion rate). Ninety-three percent of urologists consider ergonomic factors when performing RIRS to reduce fatigue (68%), increase performance (64%), improve efficiency (59%), and reduce pain (49%). Only 16% received training in ergonomics. Residents/fellows had significantly lower confidence in ergonomic techniques compared with attending surgeons with any career length. Adherence to proper ergonomic positioning for modifiable factors was highly variable. On the NMQ, 12-month rates of RIRS-associated pain in ≥1 body part, pain limiting activities of daily living (ADLs), and pain requiring medical evaluation were 81%, 51%, and 29%, respectively. Annual case volume >150 cases (odds ratio [OR] 0.55 [0.35–0.87]) and higher adherence to proper ergonomic techniques (OR 0.67 [0.46–0.97]) were independently associated with lower odds of pain. Limitations include a predominantly male cohort, which hindered the ability to assess gender disparities in pain and ergonomic preferences. Conclusions: Adherence to ergonomic best practices during RIRS is variable and may explain high rates of MSK pain among urologists. These results underscore the importance of utilizing proper ergonomic techniques and may serve as a framework for establishing ergonomic guidelines for RIRS.
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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 | 0.003 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".