Preoperative anemia increases the risk of red blood cell transfusion and prolonged hospital length of stay in children undergoing spine arthrodesis surgery
Bibliographic record
Abstract
BACKGROUND: Preoperative anemia is an important modifiable risk factor for red blood cell (RBC) transfusion in a variety of surgical populations. The primary objective of this study was to examine the association between preoperative anemia and i) transfusion of RBCs within 72 hours of surgery and ii) postoperative clinical outcomes in children undergoing spine arthrodesis surgery. STUDY DESIGN AND METHODS: We assembled a retrospective cohort of children included in the American College of Surgeons National Quality Improvement Program Pediatric database who underwent spine arthrodesis surgery from 2012 to 2016. Anemia was defined using age- and sex-specific hematocrit thresholds. Data collected included demographic and surgical characteristics, RBC transfusion within 72 hours, and 30-day postoperative outcomes (postoperative mechanical ventilation, infection, readmission, hospital length of stay, mortality). Multivariable logistic regression analyses were used to identify independent predictors of RBC transfusion and postoperative outcomes. RESULTS: We included 9,095 patients in the analysis. Preoperative anemia was present in 14% (n = 1,233) of the population and 67% (n = 6,135) of patients were transfused. Our multivariable logistic regression showed anemia, surgical time > 350 minutes, > 7 vertebral levels fused, neuromuscular disease, and cerebral palsy were all independent predictors of RBC transfusion. Preoperative anemia was also associated with prolonged hospital LOS (adjusted OR: 1.31, 95%CI: 1.11-1.54, p = 0.002). CONCLUSIONS: In this study of 9,095 children undergoing spine surgery, preoperative anemia was associated with an increased risk of RBC transfusion and prolonged LOS. Further studies are needed to determine if treatment of preoperative anemia can effectively reduce intraoperative RBC transfusion.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".