Perioperative replacement therapy in haemophilia B: An appeal to “B” more precise
Bibliographic record
Abstract
INTRODUCTION: Haemophilia B is caused by a deficiency of coagulation factor IX (FIX) and characterized by bleeding in muscles and joints. In the perioperative setting, patients are treated with FIX replacement therapy to secure haemostasis. Targeting of specified FIX levels is challenging and requires frequent monitoring and adjustment of therapy. AIM: To evaluate perioperative management in haemophilia B, including monitoring of FIX infusions and observed FIX levels, whereby predictors of low and high FIX levels were assessed. METHODS: undergoing elective, minor or major surgical procedures between 2000 and 2015 were included. Data were collected on patient, surgical and treatment characteristics. Observed FIX levels were compared to target levels as recommended by guidelines. RESULTS: [IQR 0.10-0.39]. Clinically relevant bleeding complications (necessity of a second surgical intervention or red blood cell transfusion) occurred in 7 procedures (2.7%). CONCLUSION: This study demonstrates that targeting of FIX levels in the perioperative setting is complex and suboptimal, but although this bleeding is minimal. Alternative dosing strategies taking patient and surgical characteristics as well as pharmacokinetic principles into account may help to optimize and individualize treatment.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".