Factors Associated With Perioperative Transfusion in Lower Extremity Revision Arthroplasty Under a Restrictive Blood Management Protocol
Bibliographic record
Abstract
INTRODUCTION: Approximately 37% of patients undergoing lower extremity revision total joint arthroplasty (TJA) receive allogeneic blood transfusions (ABTs), which are associated with increased risk of morbidity and death. It is important to identify patient factors associated with needing ABT because the health of higher-risk patients can be optimized preoperatively and their need for ABT can be minimized. Our goal was to identify the patient and surgical factors independently associated with perioperative ABT in revision TJA. METHODS: We included all 251 lower extremity revision TJA cases performed at our academic tertiary care center from January 1, 2016, to December 31, 2018. We assessed the following factors for associations with perioperative ABT: patient age, sex, race, body mass index, preoperative hemoglobin level, and infection status (ie, infection as indication for revision TJA); use of vasopressors, tranexamic acid (TXA), surgical drains, tourniquets, and intraoperative cell salvage; and procedure type (hip versus knee), procedure complexity (according to the number of components revised), and surgical time. Multivariable regression was used to identify factors independently associated with perioperative ABT. RESULTS: The following characteristics were independently associated with greater odds of perioperative ABT: preoperative hemoglobin level (odds ratio [OR], 1.8; 95% confidence interval [CI], 1.5 to 2.2), infectious indication for revision (OR, 3.6; 95% CI, 1.3 to 9.7), and procedure complexity. TXA use was a negative predictor of ABT (OR, 0.47; 95% CI, 0.23 to 0.98). Compared with polyethylene liner exchanges, single-component revisions (OR, 14; 95% CI, 3.6 to 56) and dual-component revisions (OR, 7.8; 95% CI, 2.3 to 26) were associated with greater odds of ABT. DISCUSSION: Patients with preoperative anemia, those undergoing revision TJA because of infection, those who did not receive TXA, and those undergoing more complex TJA procedures may have greater odds of requiring ABT. We recommend preoperative optimization of the health of these patients to reduce the need for ABT. LEVEL OF EVIDENCE: Level III, prognostic study.
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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 | 0.006 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".