Safety and efficacy of unmodified whole blood vs. buffy coat‐depleted red cell concentrates in autologous transfusion of elective orthopaedic surgery patients
Bibliographic record
Abstract
Storing autologous blood as whole blood (WB) has been proposed for increasing the cost-effectiveness of preoperative autologous blood donation programmes. However, experimental data suggest that autologous leucocytes might lead to immunomodulation similar to the effect attributed to allogeneic leucocytes. In a retrospective analysis, the postoperative outcome of 120 patients undergoing elective orthopaedic surgery and having donated up to two units of autologous WB (AWB) was compared with that of a control group of 52 patients, whose autologous donation had been processed into buffy coat-depleted red cell concentrates (RCC). At least one autologous unit, but no allogeneic units, had been transfused in all analysed patients. Donation schemes were equally efficacious in both groups. There was no significant difference in postoperative infection rates between the two groups. Overall rates were 7.7% in the RCC group and 8.3% in the WB group. Surgical, thromboembolic and other recorded complications, length of postoperative hospital stay and days of the use of antibiotics were also not significantly different between the two groups. The results of this study suggest that transfusion of up to two units of unmodified AWB is as efficacious as the transfusion of autologous RCC and does not negatively influence the postoperative outcome in elective orthopaedic surgery.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".