Development and validation of a predictive model for spinal fracture risk in osteoporosis patients

作     者：Xu-Miao Lin Zhi-Cai Shi 

作者机构：Department of OrthopedicsChanghai HospitalShanghai 200433China 

出 版 物：《World Journal of Clinical Cases》 (世界临床病例杂志)

年 卷 期：2023年第11卷第20期

页      面：4824-4832页

核心收录：

学科分类：1002[医学-临床医学] 100210[医学-外科学(含：普外、骨外、泌尿外、胸心外、神外、整形、烧伤、野战外)] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学] 

主　　题：Spinal osteoporosis Fracture risk prediction Bone mineral density Vertebral trabecular alterations Previous vertebral fractures 

摘      要：BACKGROUND Spinal osteoporosis is a prevalent health condition characterized by the thinning of bone tissues in the spine,increasing the risk of *** its high incidence,especially among older populations,it is critical to have accurate and effective predictive models for fracture ***,clinicians have relied on a combination of factors such as demographics,clinical attributes,and radiological characteristics to predict fracture risk in these ***,these models often lack precision and fail to include all potential risk *** is a need for a more comprehensive,statistically robust prediction model that can better identify high-risk individuals for early *** To construct and validate a model for forecasting fracture risk in patients with spinal *** The medical records of 80 patients with spinal osteoporosis who were diagnosed and treated between 2019 and 2022 were retrospectively *** patients were selected according to strict criteria and categorized into two groups:Those with fractures(n=40)and those without fractures(n=40).Demographics,clinical attributes,biochemical indicators,bone mineral density(BMD),and radiological characteristics were collected and compared.A logistic regression analysis was employed to create an osteoporotic fracture risk-prediction *** area under the receiver operating characteristic curve(AUROC)was used to evaluate the model’s *** Factors significantly associated with fracture risk included age,sex,body mass index(BMI),smoking history,BMD,vertebral trabecular alterations,and prior vertebral *** final risk-prediction model was developed using the formula:(logit[P]=-3.75+0.04×age-1.15×sex+0.02×BMI+0.83×smoking history+2.25×BMD-1.12×vertebral trabecular alterations+1.83×previous vertebral fractures).The AUROC of the model was 0.93(95%CI:0.88-0.96,P0.001),indicating strong discriminatory *** The fracture risk-pr