Predicting osteoporotic fractures post-vertebroplasty: a machine learning approach with a web-based calculator.

PURPOSE: The aim of this study was to develop and validate a machine learning (ML) model for predicting the risk of new osteoporotic vertebral compression fracture (OVCF) in patients who underwent percutaneous vertebroplasty (PVP) and to create a user-friendly web-based calculator for clinical use. METHODS: A retrospective analysis of patients undergoing percutaneous vertebroplasty: A retrospective analysis of patients treated with PVP between June 2016 and June 2018 at Liuzhou People's Hospital was performed. The independent variables of the model were screened using Boruta and modelled using 9 algorithms. Model performance was assessed using the area under the receiver operating characteristic curve (ROC_AUC), and clinical utility was assessed by clinical decision curve analysis (DCA). The best models were analysed for interpretability using SHapley Additive exPlanations (SHAP) and the models were deployed visually using a web calculator. RESULTS: Training and test groups were split using time. The SVM model performed best in both the training group tenfold cross-validation (CV) and validation group AUC, with an AUC of 0.77. DCA showed that the model was beneficial to patients in both the training and test sets. A network calculator developed based on the SHAP-based SVM model can be used for clinical risk assessment ( https://nicolazhang.shinyapps.io/refracture_shap/ ). CONCLUSIONS: The SVM-based ML model was effective in predicting the risk of new-onset OVCF after PVP, and the network calculator provides a practical tool for clinical decision-making. This study contributes to personalised care in spinal surgery.

Clinical analysis of different anesthesia methods for pulmonary infection after perioperative operation.

The purpose is to explore the effect of different anesthesia methods on pulmonary infection after the operation. 120 patients who underwent surgery from January 2015 to August 2018 were selected in three groups: group A (n=40), group B (n=40), and group C (n=40). Group A was given inhalation anesthesia, group B was given total intravenous anesthesia, and group C was given epidural block combined with general anesthesia. In addition to lung imaging examination, the postoperative parameters of patients such as leukocyte count and mean arterial pressure were recorded. Through image analysis, the case of pulmonary infection after epidural block combined with general anesthesia was 1, while that of inhalation anesthesia and intravenous injection was 7 and 8. In terms of the fluctuation of heart rate and mean arterial pressure, patients in group C had lower levels of heart rate and mean arterial pressure, while patients in groups A and B had higher levels of these parameters. There was no significant difference between inhalation anesthesia and intravenous injection for pulmonary infection after the operation. Thus, it can be concluded that the negative effects of epidural block combined with general anesthesia are much less than those of the other two anesthesia methods, which has the smallest effect on pulmonary infection after the operation. Therefore, the epidural block combined with general anesthesia has the smallest effect on pulmonary infection after the operation. This study is of great significance, and more anesthesia methods can be further studied in subsequent works.