Variability in International Society on Thrombosis and Haemostasis-Scientific and Standardization Committee endorsed Bleeding Assessment Tool (ISTH-BAT) score with normal aging in healthy females: contributory factors and clinical significance
Bibliographic record
Abstract
BACKGROUND: Bleeding assessment tools are key screening tests used in the evaluation of patients with suspected inherited bleeding disorders. The International Society on Thrombosis and Haemostasis-Scientific and Standardization Committee endorsed Bleeding Assessment Tool (ISTH-BAT) has differing reference ranges for adult males (0-3), adult females (0-5), and children (0-2), reflecting differing bleeding symptoms and exposure to hemostatic challenges in these healthy population subgroups. Age is known to markedly impact bleeding score in individuals with von Willebrand disease. However, the influence of age on bleeding score in healthy adult controls is poorly understood. OBJECTIVES: We aimed to assess variability in ISTH-BAT score with age among healthy control females. METHODS: We used the legacy "Merging Project" dataset of normal healthy controls upon which current ISTH-BAT normal ranges are based. We included women, totaling 646 individuals. The normal range (middle 95th percentile) of total ISTH-BAT and grouped subdomain scores between age quartiles was assessed. RESULTS: The normal range of ISTH-BAT scores increased with age, ranging from 0 to 4 in the youngest quartile (age range, 18-30) to 0 to 6 in the oldest (age range, 52-88). This increased variability with aging was related both to high menorrhagia domain scores in older women and an increase in postprocedural bleeding with accumulated exposure to hemostatic challenges. CONCLUSIONS: Cumulatively, our data highlight that normal aging leads to increased variability in bleeding scores in healthy adult females. Further refinement of the ISTH-BAT with age-adjusted reference ranges may improve the sensitivity and specificity of the tool among females.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".