Comparing bleed frequency and factor concentrate use between haemophilia A and B patients
Bibliographic record
Abstract
Haemorrhagic manifestations in patients with haemophilia A and B are considered quite similar for comparable level of factor deficiency. We investigated the bleeding frequency and factor usage between HA and HB patients with comparable disease severities. We collected data on frequency of bleeds and factor concentrate utilization over 3 years, from January 2001 to December 2003. Information was gathered from home infusion logs recorded by patients or their parents, and treatment records from the Hemophilia Clinic or the Hospital Emergency Department. Data were available on 58 patients with severe HA (FVIII < 0.01 U mL(-1)), 10 with moderate HA (FVIII < 0.05 U mL(-1)), 15 with severe HB, and five with moderate HB who required treatment for episodic bleeds, postoperative haemostasis and for primary or secondary prophylaxis. The HA patients bled more frequently than HB patients (14.4 vs. 8.63 bleeds/patient/year), but used similar amounts of concentrate per year. HA patients underwent surgical procedures 3.2 times more frequently than HB patients to correct musculoskeletal complications. A total of 21,363,409 IU of recombinant FVIII was used by patients with HA (104,722 IU/patient/year) and 6,430, 960 IU of recombinant factor IX, by patients with HB (107,182 IU/patient/year). The difference in factor concentrate usage is not statistically significant (P > 0.05). The decrease in bleed frequency in haemophilia B indicates that the conclusions from randomized trials of prophylaxis in HA may not be accurately applied to HB.
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 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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".