The clinical use of platelet transfusions: A systematic literature review and meta‐analysis on behalf of the International Collaboration for Transfusion Medicine Guidelines
Bibliographic record
Abstract
BACKGROUND: Platelets are frequently transfused, but supply and potential harms highlight the importance of appropriate use. STUDY DESIGN AND METHODS: Our systematic review (SR) followed a predefined protocol. Eligible studies included SRs, randomized controlled trials (RCTs), and matched cohort observational studies between 1946 and March 2025. Populations included were hypoproliferative thrombocytopenia, periprocedural prophylaxis, cardiovascular surgery, consumptive thrombocytopenia, and intracranial hemorrhage. The intervention was restrictive versus liberal platelet transfusion strategies on outcomes of mortality and bleeding. Duplicate screening and data extraction occurred. Meta-analysis used Mantel-Haenszel method of random effects model. RESULTS: Twenty-one RCTs, 24 observational studies, and 20 SRs were included. The evidence quality varied. For hypoproliferative thrombocytopenia, 11 RCTs were analyzed, with 9 RCTs at moderate risk of bias (ROB). Two RCTs were identified for dengue, with high ROB for bleeding. One RCT was identified each in cardiovascular surgery, intracranial hemorrhage, and periprocedural prophylaxis. Meta-analyses indicated no significant effect for outcomes of mortality or bleeding by strategy, but confidence intervals (CIs) were wide. Effect estimates were 1.32 [0.93, 1.86] for all-cause mortality in hypoproliferative thrombocytopenia, 0.80 [0.38, 1.70] in cardiovascular surgery, and 0.69 [0.47, 1.03] in critically ill neonates or dengue patients. DISCUSSION: A consistent lack of benefit with liberal platelet transfusion was observed across analyzed populations, although wide confidence intervals do not exclude clinically meaningful impacts. Important research gaps are highlighted in areas where the RCT data is limited.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".