Intracranial bleeding in haemophilia beyond the neonatal period – the role of CT imaging in suspected intracranial bleeding
Bibliographic record
Abstract
We conducted a review of a single institutional experience of patients with haemophilia presenting with suspected intracranial haemorrhage (ICH) who underwent computed tomographic (CT) neuro-imaging. We found that over a 9-year period (1996-2004) 43 patients with haemophilia presented 73 times with suspected ICH: 10 presented multiple times (range: 2-9 times). The median age at presentation was 3.5 years (range: 0.5-17). Preceding trauma occurred in most (62/73; 85%) episodes. ICH was confirmed in 11 of the 73 (16%) episodes in eight patients. Patients with severe haemophilia accounted for a disproportionate number of episodes of suspected (60/73; 82%) and of confirmed ICH (10/11; 91%). All ICH occurred in patients not on prophylaxis; five occurred in three inhibitor-positive patients. Altered consciousness at presentation was present in 10/11 (91%) cases of confirmed ICH but only in 5/62 (8%) (ICH-negative) episodes. The positive and negative predictive values of altered consciousness to predict/rule out an ICH was 67% and 98%, respectively. The following were associated with an increased risk of presenting with suspected ICH and of having a confirmed ICH: (i) having severe haemophilia; (ii) not being on prophylaxis; (iii) having an inhibitor; and (iv) presenting with an altered level of consciousness. Patients without any of these features may not need to undergo CT imaging when presenting with suspected ICH. Ideally a prospective study to evaluate this hypothesis should be conducted.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".