Risk Factors Influencing Transfusion Rates in DIEP Flap Breast Reconstruction
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Bibliographic record
Abstract
BACKGROUND: As the popularity of deep inferior epigastric perforator (DIEP) flap breast reconstruction grows, there remains little information on the transfusion rate of this more technically challenging procedure. The purpose of this study was to examine the perioperative blood loss and patient characteristics of women undergoing DIEP flap breast reconstruction in an attempt to identify independent risk factors that predict increased blood loss and transfusion requirements. METHODS: A retrospective chart review identified 144 patients who underwent DIEP flap breast reconstruction performed at Queen Elizabeth II Health Sciences Center between January of 2002 and July of 2009. Intraoperative blood loss, hemoglobin and hematocrit drop, length of hospital stay, incidence of perioperative blood transfusions, and complications were reviewed. This study assessed the effects of older age, obesity, bilateral reconstruction, immediate reconstruction, tamoxifen treatment, and length of surgery on the incidence of perioperative blood transfusion and complications. RESULTS: A total of 18.8 percent of patients required perioperative blood transfusions. These patients were older and more obese, underwent more immediate and bilateral reconstructions, and had longer mean operative times and hospital stays. Patients who underwent lengthy bilateral DIEP reconstructions were at increased risk of receiving a perioperative blood transfusion (bilateral: relative risk, 2.4; odds ratio, 4.4; long surgery: relative risk, 3.9; odds ratio, 7.3). Blood transfusion recipients had an increased risk and greater odds of experiencing any postoperative complication (relative risk, 2.3; odds ratio, 3.4). CONCLUSIONS: Bilateral reconstruction and length of surgery were the only factors to significantly increase the risk of perioperative blood transfusion. Patients receiving blood transfusions had an increased risk of experiencing a postoperative complication.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it