Perioperative Transfusion Practices in Adults Having Noncardiac Surgery
Bibliographic record
Abstract
Surgical patients are often transfused to manage bleeding and anemia. Best practices for red blood cell (RBC) transfusion administration in patient having noncardiac surgery remains controversial and a robust evaluation and description of perioperative transfusion practices is lacking. We characterized perioperative hemoglobin concentrations and transfusion practices from the prospective VISION cohort which included 39,222 patients aged ≥45 years who had inpatient noncardiac surgery. Variations in transfusion practices were analyzed using hierarchical mixed models, and associations with mortality and complications were evaluated using a nested frailty survival model. Within the cohort, 16.1% (n = 6296) were given perioperative RBC transfusions, with the fraction declining from 20% to 13% over the 6-year study period. The proportion of patients transfused varied by surgery type from 6.4% for low-risk operations (i.e., minor surgery) to 31.5% for orthopedic surgeries. Variations were largely associated with patient hemoglobin concentrations, but also with center (range: 3.7%-27.3%) and country (0.4%-25.3%). Even after adjusting for baseline hemoglobin, comorbidities and type of surgery, both center and country were significant sources of variation in transfusion practices. Among transfused participants, 60.4% (n = 3728/6170) had at least 1 hemoglobin concentration ≤80g/L and 86.0% (n = 5305/6170) had at least 1 hemoglobin concentration ≤90g/L, suggesting that relatively restrictive transfusion strategies were used in most. The proportion of patients receiving at least 1 RBC transfusion declined from 20% to 13% over 6 years. However, there was considerable unexplained variation in transfusion practices.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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 teacher head, 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".