Critical bleeding in adults and children with immune thrombocytopenia: a multicenter cohort study
Bibliographic record
Abstract
ABSTRACT: Critical bleeding in patients with immune thrombocytopenia (ITP) is a life-threatening hematologic emergency. This study aimed to describe the frequency, management, and outcomes of critical bleeds among adults and children with ITP. We conducted a retrospective cohort study of patients with ITP who presented to the emergency room with a platelet count <20 × 109/L across 7 centers in the United States and Canada between 2010 and 2019. Of 1226 patients (n = 296 adults; n = 930 children), 28 (2.3%) had critical bleeds (adults, n = 15 [median age, 68 years]; children, n = 13 [median age, 11 years]). Of patients with critical bleeds, 12 adults (80.0%) and 6 children (46.2%) had intracranial hemorrhage (ICH). For adults, the common interventions used to treat critical bleeds were platelet transfusions (n = 11 [73.3%]), corticosteroids (n = 10 [66.7%]), and IV immunoglobulin (n = 8 [53.3%]), and for children, common interventions were IV immunoglobulin (n = 10 [76.9%]), corticosteroids (n = 8 [61.5%]), platelet transfusions (n = 8 [61.5%]), thrombopoietin receptor agonists (n = 4 [30.8%]), and antifibrinolytic agents (n = 4 [30.8%]). For both adults and children, the most common treatment combination was corticosteroids, IV immunoglobulin, and platelet transfusion (n = 6 [40.0%] vs n = 6 [46.2%]). The median time from presentation to first treatment was 6.9 hours for adults and 3.5 hours for children. Overall, 9 patients (32.1%) with critical ITP bleeds died, including 7 adults (46.7%) and 2 children (15.4%). Critical bleeding in patients with ITP was rare but frequently fatal, especially among older adults with ICH and when treatments were delayed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".