Effect of changing the age criteria for blood donors
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The upper age limit for allogeneic blood donation varies among countries and blood operators. We assessed the impact of the removal of the upper age limit for donation in Canada from December 2004 to January 2006. MATERIALS AND METHODS: Starting in December 2004, regular donors were permitted to continue whole blood or apheresis donation past their 71st birthday, provided an annual external medical assessment was performed by their family physician. Regular donors aged from 70 to 74 were sent a letter about the change in criteria, and encouraged to continue donations. Rates of donor adverse reactions and deferrals were calculated for these donors and donors in other age groups. RESULTS: In the 13-month period following implementation of the new criteria, 961 (54%) of regular donors who had received a letter initiated a medical inquiry, and 862 inquiries were completed and returned to Canadian Blood Services. In 98% of cases, the donors' family physician approved ongoing donation. Of the 659 donors who presented to donate, 93% successfully donated. There was only one moderate/severe donor reaction out of 3137 donor attendances for donors aged 71 and older. This rate was not statistically different from the rate in the overall donor population. No donors were deferred for high-risk activities or had positive infectious disease test results. CONCLUSION: Regular blood donors may safely continue to donate past their 71st birthday. Extra steps in the donation process, such as an external medical inquiry, may not be necessary.
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".