Generation and optimization of the self‐administered pediatric bleeding questionnaire and its validation as a screening tool for von Willebrand disease
Bibliographic record
Abstract
OBJECTIVE: Our objective was to generate, optimize, and validate a self-administered pediatric bleeding questionnaire (Self-PBQ) as a screening tool for von Willebrand disease (VWD) in children referred to the hematology clinic for the first time. STUDY DESIGN: The Self-PBQ was generated by combining the validated expert-administered PBQ and the International Society on Thrombosis and Hemostasis (ISTH) bleeding assessment tool (BAT). Medical terminology was translated into lay language requiring a grade 4 reading level. In Phase 1, the Self-PBQ was optimized and the level of agreement between the Self-PBQ and the expert-administered PBQ was determined. Phase 2 established the normal range of bleeding scores (BSs) of the Self-PBQ. Phase 3 examined the Self-PBQ as a screening tool for first-time referrals to the hematology clinic. RESULTS: The Self-PBQ is a reliable surrogate for the expert-administered PBQ with an excellent intraclass correlation (ICC) of 0.917. The Self-PBQ was scored with the PBQ and the ISTH-BAT scoring systems, for which its normal BS ranges are -1 to 2 or 0 to 2, respectively. A positive Self-PBQ BS (≥3) had a sensitivity of 78%, a specificity of 37%, a positive predictive value of 0.18, and a negative predictive value of 0.91 for identifying VWD in children being investigated by a hematologist for a bleeding disorder. CONCLUSION: The Self-PBQ generates comparable BSs to the expert-administered PBQ and is a reliable, reasonably sensitive screening tool to incorporate into the assessment of children presenting to a hematologist for the investigation of an inherited bleeding disorder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".