Allogeneic Red Blood Cell Transfusion Is an Independent Risk Factor for the Development of Postoperative Bacterial Infection
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background and Objectives: Allogeneic red blood cell transfusions may exert immunomodulatory effects in recipients including an increased rate of postoperative bacterial infection. It is controversial whether allogeneic transfusion is an independent predictor for the development of postoperative bacterial infection. Methods: We analysed a prospectively collected database of 1,349 patients undergoing colorectal surgery in 11 centres across Canada. The primary outcome was the development of either a postoperative wound infection or intraabdominal sepsis in transfused and nontransfused patients. The effect of allogeneic transfusion on postoperative infection was evaluated with adjustment for all the confounding factors in a multiple regression analysis. Results: The 282 patients who received a total of 832 allogeneic units had a significantly higher frequency of wound infections and intra‐abdominal sepsis than the patients who were not transfused (25.9 vs. 14.2%, p = 0.001). A significant dose‐response relationship between transfusion and infectior, rate was demonstrated. Multiple regression analysis identified allogeneic transfusion as a statistically significant independent predictor for postoperative bacterial infection (OR 1.18, 95% CI 1.05–1.33, p = 0.007). Other independent predictors were anastomotic leak, repeat operation, patient age and preoperative haemoglobin level. The mortality rate was also significantly higher in the transfused group. Conclusion: These data support the hypothesis that allogeneic red cell transfusion is an independent risk factor for the development of postoperative bacterial infection in patients undergoing colorectal surgery. This association provides further reason to minimise exposure to allogeneic transfusions in the perioperative setting.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.006 | 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 it