Pragmatic, double-blind, randomised trial evaluating the impact of red blood cell donor sex on recipient mortality in an academic hospital population: the innovative Trial Assessing Donor Sex (iTADS) protocol
Bibliographic record
Abstract
INTRODUCTION: With over 1 million units of blood transfused each year in Canada, their use has a significant clinical and economic impact on our health system. Adequate screening of blood donors is important to ensure the safety and clinical benefit of blood products. Some adverse transfusion reactions have been shown to be related to donor factors (eg, lung injury), whereas other adverse outcomes have been theoretically related to donor factors (mortality and infection). Our clinical trial will test whether male donor blood leads to a greater benefit for transfusion recipients compared with female donor blood. METHODS AND ANALYSIS: We have designed a pragmatic, double-blind, randomised trial that will allocate transfusion recipients to receive either male-only or female-only donor transfusions. We will enrol 8850 adult patients requiring at least one transfusion at four sites over an approximate 2-year period. Randomisation and allocation will occur in the blood bank prior to release of the units of blood for transfusion. Our primary outcome is mortality. An intent-to-treat analysis will be applied using all randomised and transfused patients. The principal analysis will be a survival analysis comparing the time from randomisation to death between patients allocated to male donor red blood cells (RBCs) and female donor RBCs. ETHICS AND DISSEMINATION: Approval has been obtained from research ethics boards of all involved institutions, as well as from privacy offices of Canadian Blood Services, Institute for Clinical Evaluative Science and The Ottawa Hospital Data Warehouse. Our findings will be published in peer-reviewed journals and presented at relevant stakeholder conferences and meetings. TRIAL REGISTRATION NUMBER: NCT03344887; Pre-results.
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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 | 0.022 | 0.033 |
| Meta-epidemiology (narrow) | 0.007 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".