A review of nearly two decades in an autologous blood programme: the rise and fall of activity
Bibliographic record
Abstract
Autologous blood donation (ABD) has been widely recommended. Data from one of the oldest hospital-based programmes in Canada describe both activities and drawbacks. Data were compared over the nearly two decades of activity that peaked in 1996. A 5-year review of recent activity showed that of the 2410 patients referred for consideration, 1823 (75.64%) were accepted into the programme. Surgical services requested 5825 units of autologous blood. Of these, 3147 units were donated by 1536 patients, 803 units were transfused in the operating room and 558 units were given postoperatively. In total, only 1361 units (43.25%) were transfused. The mean age of the patients was 58 years (median 61 years and mode 69 years). The haemoglobin concentrations before donation were significantly higher, averaging 145.2 g L(-1) before donation and 114.9 g L(-1) immediately before surgery, whereas at the time of discharge, the haemoglobin concentration averaged 126.2 g L(-1) (P = 0.0001) in transfused patients. Data from this well-established ABD programme indicate less than 50% overall utilization. The activity in the programme increased until 1996 following which it dropped progressively. The low haemoglobin concentration after surgery is of concern and should foster a transfusion algorithm for these patients.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".