ArticleInternational journal of spine surgery2020
Decision Tree-based Modelling for Identification of Predictors of Blood Loss and Transfusion Requirement After Adult Spinal Deformity Surgery.
Article in International journal of spine surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Algorithmic fairness reporting in artificial intelligence for spinal deformity: a systematic review.Spine deformity · 2026Review
- Impact of adjunctive spine surgery on multilevel spinal fusion in the management of adult spinal deformity: A single centre propensity score-matched analysis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Predictors of blood loss, operative time, and length of stay in adult spinal deformity surgery: a retrospective cohort study in Southeastern United States.Asian spine journal · 2025Article
- Artificial Intelligence in Patient Blood Management: A Systematic Review of Predictive, Diagnostic, and Decision Support Applications.Journal of clinical medicine · 2025Review
- Blood transfusion and mortality after spine osteotomy: a nationwide population-based retrospective cohort study.Scientific reports · 2025Article
- Assessing blood volume returned with use of intraoperative cell salvage in adult spinal deformity correction.Spine deformity · 2025Article
- AI and machine learning in paediatric spine deformity surgery.Bone & joint open · 2025Article
- Tailored resection of spinal dumbbell schwannomas using transforaminal and modified epidural trans dural sleeve approaches with hemilaminectomy.Frontiers in surgery · 2025Article
- Mapping the landscape of machine learning models used for predicting transfusions in surgical procedures: a scoping review.BMC medical informatics and decision making · 2024Article
- Risk factors for allogeneic red blood cell transfusion in adult spinal deformity surgery.Asian spine journal · 2024Article
- Personalizing adult spinal deformity surgery through multimodal artificial intelligence.Acta orthopaedica et traumatologica turcica · 2024Review
- Machine learning in transfusion medicine: A scoping review.Transfusion · 2024Article
- A novel predictive model of perioperative blood transfusion requirement in tuberculous spondylitis patients undergoing posterior decompression and instrumentation.International orthopaedics · 2023Review
- Prediction of red blood cell transfusion after orthopedic surgery using an interpretable machine learning framework.Frontiers in surgery · 2023Article
- An Artificial Neural Network Model for the Prediction of Perioperative Blood Transfusion in Adult Spinal Deformity Surgery.Journal of clinical medicine · 2022Article
- AI MSK clinical applications: spine imaging.Skeletal radiology · 2022Review
- Emerging Technologies in the Treatment of Adult Spinal Deformity.Neurospine · 2021Article
- Assessment of Clinical Decision Support System Efficiency in Spinal Neurosurgery for Personalized Minimally Invasive Technologies Used on Lumbar Spine.Sovremennye tekhnologii v meditsine · 2021Article
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Authors and funding
5 authors.
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Abstract
backgroundMultilevel fusions and complex osteotomies to restore global alignment in adult spinal deformity (ASD) surgery can lead to increased operative time and blood loss. In this regard, we assessed factors predictive of perioperative blood product transfusion in patients undergoing long posterior spinal fusion for ASD.
methodsA single-institution retrospective review was conducted on 909 patients with ASD, age > 18 years, who underwent surgery for ASD with greater than 4 levels fused. Using conditional inference tree analysis, a machine learning methodology, we sought to predict the combination of variables that best predicted increased risk for intraoperative percent blood volume lost and perioperative blood product transfusion.
resultsAmong the 909 patients included in the study, 377 (41.5%) received red blood cell (RBC) transfusion. The conditional inference tree analysis identified greater than 13 levels fused, American Society of Anesthesiologists (ASA) score > 1, a history of hypertension, 3-column osteotomy, pelvic fixation, and operative time > 8 hours, as significant risk factors for perioperative RBC transfusion. The best predictors for the subgroup with the highest risk for intraoperative percent blood volume lost (subgroup mean: 53.1% ± 42.9%) were greater than 13 levels fused, ASA score > 1, preoperative hemoglobin < 13.6 g/dL, 3-column osteotomy, posterior column osteotomy, and pelvic fixation. Patients who underwent major blood transfusion intraoperatively had significantly longer length of stay (8.5 days) versus those who did not (6.1 days) (
conclusionsUsing a supervised learning technique, this study demonstrates that greater than 13 levels fused, ASA score > 1, 3-column osteotomy, and pelvic fixation are consistent risk factors for increased intraoperative percent blood volume lost and perioperative RBC transfusion. The addition of having a preoperative hemoglobin < 13.6 g/dL or undergoing a posterior column osteotomy conferred the highest risk for intraoperative blood loss. This information can assist spinal deformity surgeons in identifying at-risk individuals and allocating healthcare resources. LEVEL OF EVIDENCE: 3.
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