Is homologous blood transfusion a risk factor for infection after hip replacement?
Bibliographic record
Abstract
OBJECTIVES: To assess the risk of postoperative infection associated with blood transfusion in patients who undergo primary total hip arthroplasty. DESIGN: A retrospective cohort study. SETTING: Victoria General Hospital, Halifax, (a tertiary-care centre). PATIENTS: All patients who underwent primary total hip replacement between 1990 and 1995 (N = 1206). INTERVENTIONS: Hip replacement with or without perioperative blood transfusion. OUTCOME MEASURES: The rate of postoperative infection, the number of blood transfusions, patient age and sex, duration of surgery and the surgeon who performed the procedure. Victoria General Hospital medical records, the transfusion services record and the Dalhousie University Hip Study databases were integrated and analyzed using a standard statistical package. RESULTS: The incidence of infection postoperative was 9.9% overall, 8.4% in patients receiving no transfusion, and 14% in those receiving homologous transfusion (p = 0.035). There were no infections in the 11 patients who received an autologous blood transfusion. Significant predictors of postoperative infection were sex, age and duration surgery; these were not confounding variables multivariate analysis). Neither the operating surgeon nor the blood product transfused affected the infection rate. CONCLUSIONS: These findings suggest an increased risk of postoperative infection in patients who undergo primary hip replacement and receive homologous blood transfusions perioperatively.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".