Exploring the components of bleeding outcomes in transfusion trials for patients with hematologic malignancy
Bibliographic record
Abstract
Clinically significant bleeding in patients with hematologic malignancies is a heterogeneous composite outcome currently defined as World Health Organization (WHO) bleeding Grades 2, 3, and 4. However, the clinical significance of some minor bleeds categorized as WHO Grades 1 and 2 remains controversial. We analyzed the number and frequency of individual signs and symptoms of WHO Grades 1 and 2 bleeds and explored their association with more severe incident bleeds graded as WHO Grades 3 and 4. STUDY DESIGN AND METHODS: We aggregated daily bleeding assessment data from three randomized controlled trials conducted in patients with hematologic malignancies that used bleeding as an outcome. Cox proportional hazard regression analysis was used to identify signs and symptoms categorized as WHO Grades 1 and 2 bleeds that were associated with more severe bleeds (Grades 3 and 4). RESULTS: We collected data from 315 patients (n = 5476 daily bleeding assessments; 3383 [61.8%] with a bleed documented). A total of 98.3% (3326/3383) were Grade 1 and 2 bleeds and 1.7% (57/3383) were Grades 3 and 4. Grade 1 and 2 bleeds were composed of 20 different bleeding signs and symptoms. Hematuria (hazard ratio, 16.1; 95% confidence interval, 4.4-59.2; P < .0001) was associated with incident Grade 3 or 4 bleeds. CONCLUSION: In patients with hematologic malignancy, only hematuria (microscopic and/or macroscopic) was associated with more severe incident bleeds. This findings require validation in independent data sets.
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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 | 0.090 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".