Recommendations on multidisciplinary management of elective surgery in people with haemophilia
Bibliographic record
Abstract
Planning and undertaking elective surgery in people with haemophilia (PWH) is most effective with the involvement of a specialist and experienced multidisciplinary team (MDT) at a haemophilia treatment centre. However, despite extensive best practice guidelines for surgery in PWH, there may exist a gap between guidelines and practical application. For this consensus review, an expert multidisciplinary panel comprising surgeons, haematologists, nurses, physiotherapists and a dental expert was assembled to develop practical approaches to implement the principles of multidisciplinary management of elective surgery for PWH. Careful preoperative planning is paramount for successful elective surgery, including dental examinations, physical assessment and prehabilitation, laboratory testing and the development of haemostasis and pain management plans. A coordinator may be appointed from the MDT to ensure that critical tasks are performed and milestones met to enable surgery to proceed. At all stages, the patient and their parent/caregiver, where appropriate, should be consulted to ensure that their expectations and functional goals are realistic and can be achieved. The planning phase should ensure that surgery proceeds without incident, but the surgical team should be ready to handle unanticipated events. Similarly, the broader MDT must be made aware of events in surgery that may require postoperative plans to be changed. Postoperative rehabilitation should begin soon after surgery, with attention paid to management of haemostasis and pain. Surgery in patients with inhibitors requires even more careful preparation and should only be undertaken by an MDT experienced in this area, at a specialized haemophilia treatment centre with a comprehensive care model.
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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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.022 | 0.010 |
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".