Prophylactic platelet transfusions
Bibliographic record
Abstract
PURPOSE OF REVIEW: For decades, prophylactic platelet transfusions have been a standard practice for treatment-related thrombocytopenia in patients with hematologic malignancies, although evidence supporting this practice was limited. Two recent randomized controlled studies were carried out to challenge this practice by comparing prophylactic to therapeutic-only platelet transfusion strategies. This review compares and contrasts the study findings to provide further insight into the study conclusions and their application to practice. RECENT FINDINGS: Past studies exploring platelet transfusion in this patient population focused on identifying the optimal platelet threshold for transfusions and the minimum effective dose to achieve hemostasis. Balancing increased demand with limited supply has further necessitated determining if a therapeutic-only approach is as efficacious. This is especially pertinent given improved prognosis of hematologic malignancies because of novel therapies and better diagnostic technologies. Two large randomized controlled studies showed that therapeutic-only strategy reduces platelet utilization, but possibly at an increased risk of high-grade bleeding in certain patient groups. SUMMARY: The majority of this adult patient population should continue to receive prophylactic platelet transfusions to prevent high-grade bleeding. Stable autologous stem cell transplant patients appear to be at a lower risk of thrombocytopenia-related bleeding and are candidates for therapeutic-only platelet transfusions in expert centers with careful monitoring.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".