Measurement of factor XIII for the diagnosis and management of deficiencies: insights from a retrospective review of 10 years of data on consecutive samples and patients
Bibliographic record
Abstract
Background: Factor XIII (FXIII) deficiency is a challenge in the diagnosis of rare bleeding disorders with inherited and acquired causes. Objectives: We evaluated consecutive cases tested for FXIII deficiency for insights on diagnosis. Methods: With ethics approval, we retrospectively reviewed FXIII tests performed between 2013 and 2023 and local patient records for insights into causes and presentations of FXIII deficiency. Results: < .05). Most FXIII deficiencies were acquired (92%), and although several were autoimmune, most were from consumption, major bleeds, or severe infections or had uncertain significance, with bleeding sometimes attributable to other causes. Conclusion: Congenital and acquired FXIII deficiency are associated with bleeding. Local practices were changed to ensure that FXIII:Act is used to screen for FXIII deficiency and that deficient patients have FXIII:Act and FXIII-A:Ag quantified and compared.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".