Modeling to Predict Factor VIII Levels Associated with Zero Bleeds in Patients with Severe Hemophilia A Initiated on Tertiary Prophylaxis
Bibliographic record
Abstract
BACKGROUND: Factor VIII (FVIII) trough levels > 1 IU/dL in patients with severe hemophilia A receiving regular prophylaxis may optimize bleed protection. OBJECTIVES: In this post hoc analysis of patients receiving tertiary prophylaxis for approximately 1 year, the relationship between estimated FVIII levels and reported bleeds was investigated to predict the potential for zero bleeds. METHODS: Sixty-three patients (median [range] age, 28 [7-59] years) with severe hemophilia A (229 bleeds) were included. FVIII levels at time of each bleed were estimated from single-dose individual pharmacokinetics. The highest estimated FVIII level at which patients experienced a bleed was considered the "potentially effective trough level" for that bleed type. Kaplan-Meier estimates of proportions of patients with no bleeds above certain estimated FVIII levels were determined. Those not experiencing a bleed in the trial were assumed to have a bleed at 0 IU/dL (pragmatic approach) or at their median trough level (conservative approach). RESULTS: Kaplan-Meier estimates based on pragmatic approach predicted zero all bleeds, joint bleeds, and spontaneous joint bleeds in 1 year in 40, 43, and 63% of patients, respectively, when the potentially effective trough FVIII level was set at 1 IU/dL. Between 1 and 10 IU/dL, every 1 IU/dL rise in estimated FVIII level was associated with an additional 2% of patients having zero all bleeds. CONCLUSION: This post hoc analysis confirms benefits with trough levels of approximately 1 to 3 IU/dL in most patients starting tertiary prophylaxis; prophylaxis with higher trough levels may help patients to achieve zero bleeds.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".