Periprocedural hemostatic prophylaxis and outcomes in bleeding disorder of unknown cause
Bibliographic record
Abstract
Background: Bleeding disorder of unknown cause (BDUC) is a diagnostic category encompassing patients with a clear bleeding phenotype but without identifiable abnormality on hemostatic testing. The optimal management of hemostasis in BDUC patients prior to invasive procedures and childbirth is uncertain. Objectives: Our objective was to characterize periprocedural hemostatic prophylaxis and bleeding outcomes in patients with BDUC. Methods: We conducted a retrospective cohort study of adult patients with BDUC at 2 academic medical centers. Following diagnosis of BDUC, subsequent surgical procedures and childbirths were analyzed using a combination of registry data and manual chart review. Results: We identified 127 patients with mean age of 39.9 years (SD = 16.6); the majority of patients were female (91.3%). Forty-eight major procedures, 70 minor procedures, and 19 childbirths were analyzed. Antifibrinolytic monotherapy was advised for 57% of major procedures, 59% of minor procedures, and 67% of childbirths. Perioperative platelet transfusion was recommended in 26% of major procedures and 9% of minor procedures in combination with other hemostatic agents. Major or clinically relevant nonmajor bleeding occurred in 4.1% (4/98) of procedures with prophylaxis and 10% (2/20) of procedures without prophylaxis. Postpartum hemorrhage occurred in 26% (5/19) of deliveries. Conclusion: In this multiinstitution experience, we found overall low rates of hemostatic complications in procedures completed with hemostatic prophylaxis, although preventing hemorrhage in childbirth and gynecologic procedures remain unmet needs.
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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 | 0.001 | 0.004 |
| 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 | 0.000 | 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".