Platelet Transfusion Threshold in Patients With Upper Gastrointestinal Bleeding
Bibliographic record
Abstract
BACKGROUND: There exists uncertainty as to the optimal platelet values when managing patients with nonvariceal upper gastrointestinal (GI) bleeding. GOALS AND STUDY: A systematic review was carried out to determine the optimal approach when managing patients with thrombocytopenia in the setting of nonvariceal upper GI bleeding. RESULTS: Eighteen of 803 potential articles were selected and reviewed, including 4 randomized controlled trials and 6 cohort studies. The only empirical clinical data available pertained to the management of hematology or oncology patients. There was no high-level evidence that determined the proper threshold of platelet transfusion specifically in GI bleeding. We were, therefore, limited to include principally consensus opinions, recommendations, and guidelines for platelet transfusion trigger as they apply to the treatment (including prophylaxis) of bleeding in general, with a paucity of data addressing major bleeding, let alone bleeding from a gastroenterologic origin. Randomized clinical trials were individually underpowered in allowing definitive conclusions, even though resulting recommendations were supported by similarly underpowered retrospective and prospective observational studies. CONCLUSIONS: There exist a paucity of data to recommend optimal therapeutic platelet count targets in patients with active GI bleeding. Based principally on expert opinion recommendations, we propose a count of 50×10/L. Some professional associations have suggested in very specific clinical settings (postcardiopulmonary bypass surgery or central nervous system trauma) a higher value of up to 100×10/L. Properly designed randomized trials are required to more precisely address this important clinical question.
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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 | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".