Red cell concentrates from teen male donors contain poor‐quality biologically older cells
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Donor factors influence the quality characteristics of red cell concentrates (RCCs) and the lesions that develop in these heterogeneous blood products during hypothermic storage. Teen male donors' RCCs contain elevated levels of biologically old red blood cells (RBCs). The aim of this study was to interrogate the quality of units of different donor ages and sexes to unravel the complex interplay between donor characteristics, long-term cold storage and, for the first time, RBC biological age. MATERIALS AND METHODS: RCCs from teen males, teen females, senior males and senior females were density-separated into less-dense/young (Y-RBCs) and dense/old RBCs (O-RBCs) throughout hypothermic storage for testing. The unseparated and density-separated cells were tested for haematological parameters, stress (oxidative and osmotic) haemolysis and oxygen affinity (p50). RESULTS: The O-RBCs obtained from teen donor samples, particularly males, had smaller mean corpuscular volumes and higher mean corpuscular haemoglobin concentrations. While biological age did not significantly affect oxygen affinity, biologically aged O-RBCs from stored RCCs exhibited increased oxidative haemolysis and decreased osmotic fragility, with teenage male RCCs exhibiting the highest propensity to haemolyse. CONCLUSION: Previously, donor age and sex were shown to have an impact on the biological age distribution of RBCs within RCCs. Herein, we demonstrated that RBC biological age, particularly O-RBCs, which are found more prevalently in male teens, to be a driving factor of several aspects of poor blood product quality. This study emphasizes that donor factors should continue to be considered for their potential impacts on transfusion outcomes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".