Surgical ergonomics: how and where to start?
Bibliographic record
Abstract
The field of ergonomics is dedicated to understanding the interactions between humans and elements of a system, with one of the core tenets of ergonomic approaches being the need to fit the environment to workers.It includes physical, cognitive, and organizational ergonomics that are all needed to create safe and efficient work environment (Figure 1).In the fast paced and high-stakes operating room (OR) environment, this principle is often forgotten.Surgeons, anaesthetists, and nurses alike tend to adapt their cognitive and physical work to a sometimes hostile work environment.Poor ergonomics in the OR can lead to musculoskeletal disorders, absenteeism, modification in clinical practice, reduced career longevity, and burn out, in addition to downstream repercussions on the risk of intra-operative complications, patient safety, and sustainability of the healthcare workforce (Figure 2).1-4 One of the main protective factors against poor ergonomics is awareness of optimal practices.5 This review will present key principles for optimal ergonomics in the OR. Personal equipmentThis aspect is one that can be more easily controlled by individuals in the OR.• Shoes: Well adapted footwear can prevent complaints related to lower extremity discomfort from prolonged standing, such as sore feet, lower limb oedema, muscle fatigue and low back pain.Shoes should allow for toe freedom, arch support, and have a 1-2.5cm heel (flat shoes increase strain on the Achilles tendon).6• Stockings: Knee-high compression stockings of 15-20 mmHg are suggested to reduce lower extremity muscle pain, fatigue, and oedema.• Loupes: Because forward head posture increases loading on the cervical spine by up to 20 kg, it is crucial to wear well-fitted loupes if they are needed.Neck flexion with loupes should not exceed 25 degrees to prevent spine and neck strain.Good posture without extensive flexion of the lower and especially cervical spine is important in decreasing musculoskeletal injuries (Figure 3).Consider trying high declination loupes or exoscopes.• Led aprons: Wearing a lead apron increases body temperature by up to 1˚C, impacts on body mechanics, and adds strain to trapezoid and temporalis muscles and the lumbar spine.7 Wearing a well-fitted apron including a vest and kilt/skirt is recommended over a single apron.In addition, weight-reliever aprons and back-aids such as exoskeletons exist, if needed 8
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".