Z Liu1, X Zhang1, H Liu2, D Wang3. 1. Department of Orthopedics, Affiliated Hospital of Beihua University, Jilin, 132000, China. 2. Department of Orthopedics, Baicheng Central Hospital, Jilin, China. 3. Department of Orthopedics, Affiliated Hospital of Beihua University, Jilin, 132000, China. 1098039263@qq.com.
Abstract
In clinical practice, it was found that some patients experienced short-term recurrent pain (SRP) in the original site after PVP treatment. This study was designed to develop and validate a nomogram for predicting the potential risks of SRP after PVP, which may help to provide a painless postoperative experience and personalized health management for patients with OVCF. INTRODUCTION: With the aging of China's population, the incidence of osteoporotic vertebral compression fractures (OVCF) has increased significantly. Percutaneous vertebroplasty (PVP) has been widely accepted due to its minimally invasive, rapid, and effective characteristics. However, it has been found that some patients have short-term recurrent pain (SRP) in the original site after surgery in practical clinical work. METHODS: We retrospectively reviewed the clinical data of OVCF patients who were treated with PVP in our center from January 1st, 2019, to December 30th, 2020. A total of 296 patients were enrolled in the study cohort, and patients were randomly divided into the training set (70%) and validation set (30%). Univariate and multivariate logistic regression analyses were used to determine the risk factors of SRP, and a nomogram predictive model was established accordingly. The model was evaluated by calibration curve, receiver operation characteristic (ROC) curve, and decision curve analysis (DCA). RESULTS: Among the 296 patients, 83 (27.85%) patients experienced SRP after surgery. The independent risk factors included fracture segments (OR: 14.148, 95%CI: 1.532-130.661; p < 0.019), number of surgical vertebrae (OR: 7.896, 95%CI: 3.007-20.729; p < 0.001; (OR: 12.563, 95%CI: 2.223-70.993; p = 0.004), and smoking (OR: 3.833, 95%CI: 1.219-12.052; p = 0.022). The AUC of the prediction model was 0.819 in the training set and 0.794 in the validation set. The calibration curve and DCA indicated the good performance of this nomogram. CONCLUSION: The nomogram prediction model had satisfactory accuracy and clinical utility, which may benefit clinical decision-making for the treatment of OVCF and strengthen patient education.
In clinical practice, it was found that some patients experienced short-term recurrent pain (SRP) in the original site after PVP treatment. This study was designed to develop and validate a nomogram for predicting the potential risks of SRP after PVP, which may help to provide a painless postoperative experience and personalized health management for patients with OVCF. INTRODUCTION: With the aging of China's population, the incidence of osteoporotic vertebral compression fractures (OVCF) has increased significantly. Percutaneous vertebroplasty (PVP) has been widely accepted due to its minimally invasive, rapid, and effective characteristics. However, it has been found that some patients have short-term recurrent pain (SRP) in the original site after surgery in practical clinical work. METHODS: We retrospectively reviewed the clinical data of OVCF patients who were treated with PVP in our center from January 1st, 2019, to December 30th, 2020. A total of 296 patients were enrolled in the study cohort, and patients were randomly divided into the training set (70%) and validation set (30%). Univariate and multivariate logistic regression analyses were used to determine the risk factors of SRP, and a nomogram predictive model was established accordingly. The model was evaluated by calibration curve, receiver operation characteristic (ROC) curve, and decision curve analysis (DCA). RESULTS: Among the 296 patients, 83 (27.85%) patients experienced SRP after surgery. The independent risk factors included fracture segments (OR: 14.148, 95%CI: 1.532-130.661; p < 0.019), number of surgical vertebrae (OR: 7.896, 95%CI: 3.007-20.729; p < 0.001; (OR: 12.563, 95%CI: 2.223-70.993; p = 0.004), and smoking (OR: 3.833, 95%CI: 1.219-12.052; p = 0.022). The AUC of the prediction model was 0.819 in the training set and 0.794 in the validation set. The calibration curve and DCA indicated the good performance of this nomogram. CONCLUSION: The nomogram prediction model had satisfactory accuracy and clinical utility, which may benefit clinical decision-making for the treatment of OVCF and strengthen patient education.
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