Bibliographic record
Abstract
We aimed to collate guidelines for preoperative marking in orthopaedic surgery, identify areas of convergence and difference and relate them to previous work on guideline effectiveness. We performed a systematic search of Medline and Google using ‘correct site’, ‘wrong site’, ‘marking’, ‘surgery’, ‘orthopaedics’ and ‘guidelines’. Orthopaedic societies and bodies, personal knowledge and unindexed conference abstracts were also used. We found nine guidelines from ten institutions in seven different countries; UK National Patient Safety Agency/Royal College of Surgeons of England, Australian College of Surgeons, JCAHO (USA), Canadian Orthopaedic Association, Veterans Health Association (USA), Copenhagen Hospital Corporation, German Coalition for Patient Safety, American Academy of Orthopaedic Surgeons and the New Zealand Orthopaedic Association. We identified four ‘core-steps’ common to the majority of guidelines. Firstly, using indelible pen. Secondly, the operating surgeon should mark the patient. Thirdly, the patient should be involved in confirming side/site. Finally, a ‘time-out’ before starting the procedure. Only one of the ‘core steps’ is carried out in theatre. The others are carried out before theatre emphasising the importance of accurately identifying and marking early in the patient’s journey. Common sense suggests guidelines should be simple, user friendly and quick to complete. Making guidelines compatible with existing values and not deviating from existing routines are recognised to increase their use. Guidelines issued by practitioners’ own professional bodies are likely to have more impact than those from outside the profession. However increasing the number of items a guideline contains does not necessarily make it better or safer. The four core steps we identified are the basis for any marking guideline. It is reasonable to assume that incorporating the guidance into clinical orthopaedic practice will further improve safety. Future work should focus on establishing the relative impact of each guideline aspect.
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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 | 0.016 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.027 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".