Association between preoperative hemoglobin levels after iron supplementation and perioperative blood transfusion requirements in children undergoing scoliosis surgery
Bibliographic record
Abstract
BACKGROUND AND AIMS: In this study, we assessed the association between preoperative hemoglobin and red blood cell transfusion in children undergoing spine surgery after the implementation of our preoperative iron supplementation protocol. METHOD: We performed a retrospective analysis of patients who underwent posterior spinal fusion surgery between January 2013 and December 2017 and received preoperative iron supplementation. We used uni- and multivariable logistic regression to determine the association between preoperative hemoglobin level and red blood cell transfusion in patients receiving iron supplementation. RESULTS: A total of 382 patients treated with preoperative oral iron were included. Of these, 175 (45.5%) patients were transfused intraoperatively. Multivariable logistic regression analysis revealed nonidiopathic etiology of the scoliosis (OR 4.178 [95% CI: 2.277-7.668], P < .001), the Cobb angle (OR 1.025 [95% CI: 1.010-1.040], P = .001), and number of vertebrae fused (OR 1.169 [95% CI: 1.042-1.312], P = .008) were associated with red blood cell transfusion. In addition, patients with a preoperative hemoglobin ≥ 140 g/L (OR 0.157 [95% CI: 0.046-0.540], P = .003), and hemoglobin between 130 and 140 g/L (OR 0.195 [95% CI: 0.057-0.669], P = .009) were less likely to be transfused compared with patients with preoperative hemoglobin between 120 and 130 g/L (OR 0.294 [95% CI: 0.780-1.082], P = .066) or <120 g/L (reference). CONCLUSION: Our study suggests that higher preoperative hemoglobin levels (>130 g/L) are associated with a reduced need for red blood cell transfusion in pediatric patients who have received iron supplementation before undergoing posterior spinal fusion in our institution. The effect of iron supplementation, the optimal dosing, and duration of supplemental iron therapy remains unclear at this time.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".