Perioperative Anemia Management in Patients Undergoing Gynaecologic Procedures: A 12-Year Multisite Study
Bibliographic record
Abstract
OBJECTIVES: Perioperative anemia is a risk factor for adverse outcomes in surgery. The purpose of this study was to characterize perioperative red blood cell (RBC) transfusion and intravenous (IV) iron use in patients undergoing gynaecologic procedures. METHODS: This was a retrospective cohort study using data from a multihospital database in Ontario, Canada. Patients aged ≥15 years who underwent gynaecologic surgery with a hospital admission between April 1, 2010 and March 31, 2022 at 3 academic hospitals were identified. The primary outcomes were perioperative (90 days before to 30 days after surgery) RBC transfusion and IV iron utilization in patients undergoing gynaecologic surgery. Secondary outcomes included hospital length of stay, intensive care unit admission, and in-hospital mortality. RESULTS: Of the 5572 patients in our cohort, 27.6% had preoperative anemia and 18.7% received RBC transfusion during the perioperative period. A perioperative RBC transfusion was administered to 29.7% of patients with underlying malignancy and to 7.8% of patients without a diagnosis of malignancy. Of the 60 patients with hemoglobin <80 g/L, 91.7% had an RBC transfusion. Regarding iron therapy, 0.6% of patients received IV iron during the perioperative period. In our cohort, preoperative anemia was associated with increased intensive care unit admissions and hospital length of stay, with patients with hemoglobin <80 g/L at the highest risk. CONCLUSIONS: Preoperative anemia was common in this gynaecologic surgery cohort and was associated with adverse clinical outcomes. Our results highlight the importance of implementing an institutional patient blood management program.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".