Clinical evaluation of bleeds and response to haemostatic treatment in patients with acquired haemophilia: A global expert consensus statement
Bibliographic record
Abstract
BACKGROUND: Acquired haemophilia (AH) is a rare bleeding disorder with significant morbidity and mortality. Most patients initially present to physicians without experience of the disease, delaying diagnosis and potentially worsening outcomes. Existing guidance in AH is limited to clinical opinion of few experts and does not address monitoring bleeds in specific anatomical locations. AIM: Derive consensus from a large sample of experts around the world in monitoring bleeding patients with AH. METHODS: Using the Delphi methodology, a structured survey, designed to derive consensus on how to monitor bleeding patients with AH, was developed by a steering committee for completion by a group of haematologists with an interest in AH. Consensus was defined as ≥75% agreement with a given survey statement. After three rounds of survey refinement, a final list of consensus statements was compiled. RESULTS: Thirty-six global specialists in AH participated. The participants spanned 20 countries and had treated a median of 12.0 (range, 1-50) patients with AH within the preceding 5 years. Consensus was achieved in all items after three survey rounds. In addition to statements on general management of bleeding patients, consensus statements in the following areas were presented: urinary tract, gastrointestinal tract, muscles, skin, joints, nose, pharynx, mouth, intracranial and postpartum. CONCLUSIONS: Here, we present consensus statements derived from a broad sample of global specialists to address monitoring of location-specific bleeds and evaluating efficacy of bleeding treatment in patients with AH. These statements could be applied in practice by treating physicians and validated by individual population surveys.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".