ArticleBMC musculoskeletal disorders2022
Blood transfusion risk prediction in spinal tuberculosis surgery: development and assessment of a novel predictive nomogram.
Article in BMC musculoskeletal disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Development and evaluation of a nomogram model for predicting prolonged hospitalization after spinal tuberculosis focus decompression, fusion, and internal fixation surgery.European journal of medical research · 2026Article
- Development and validation of machine learning models for distal instrumentation-related problems in patients with degenerative lumbar scoliosis based on preoperative CT and MRI.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 · 2025Article
- Prediction model for cytomegalovirus infection following hematopoietic stem cell transplantation in patients with β-thalassemia major.SAGE open medicine · 2025Article
- Deep Learning for Discrimination of Early Spinal Tuberculosis from Acute Osteoporotic Vertebral Fracture on CT.Infection and drug resistance · 2025Article
- Machine learning-enabled prediction of prolonged length of stay in hospital after surgery for tuberculosis spondylitis patients with unbalanced data: a novel approach using explainable artificial intelligence (XAI).European journal of medical research · 2024Article
- Ultra-restrictive red blood cell transfusion strategies in extensively burned patients.Scientific reports · 2024Article
- Cerebrospinal Fluid Leakage Combined with Blood Biomarkers Predicts Poor Wound Healing After Posterior Lumbar Spinal Fusion: A Machine Learning Analysis.International journal of general medicine · 2024Article
- A practical nomogram for predicting amputation rates in acute compartment syndrome patients based on clinical factors and biochemical blood markers.BMC musculoskeletal disorders · 2023Article
- Predictive modeling of perioperative blood transfusion in lumbar posterior interbody fusion using machine learning.Frontiers in physiology · 2023Article
- Using Machine Learning to Predict Surgical Site Infection After Lumbar Spine Surgery.Infection and drug resistance · 2023Article
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20 authors.
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Abstract
objectiveThe present study attempted to predict blood transfusion risk in spinal tuberculosis surgery by using a novel predictive nomogram.
methodsThe study was conducted on the clinical data of 495 patients (167 patients in the transfusion group and 328 patients in the non-transfusion group) who underwent spinal tuberculosis surgery in our hospital from June 2012 to June 2021. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression analyses were used to screen out statistically significant parameters, which were included to establish a novel predictive nomogram model. The receiver operating characteristic (ROC) curve, calibration curves, C-index, and decision curve analysis (DCA) were used to evaluate the model. Finally, the nomogram was further assessed through internal validation.
resultsThe C-index of the nomogram was 0.787 (95% confidence interval: 74.6%-.82.8%). The C-value calculated by internal validation was 0.763. The area under the curve (AUC) of the predictive nomogram was 0.785, and the DCA was 0.01-0.79.
conclusionA nomogram with high accuracy, clinical validity, and reliability was established to predict blood transfusion risk in spinal tuberculosis surgery. Surgeons must prepare preoperative surgical strategies and ensure adequate availability of blood before surgery.
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