Analysis of risk factors and predictive efficacy of senile osteoporosis fracture based on biochemical indicators of bone metabolism

Abstract

Osteoporosis (OS) is characterized by low bone mass and altered bone microarchitecture. Patients with OS are at significantly increased risk for fragility fractures, which ultimately suffer fractures. Biochemical indicators of bone metabolism are important for assessing the risk of fracture occurrence. In this study, we aimed to investigate the risk factors for osteoporotic fracture in the elderly based on bone metabolism biochemical indexes and to analyze their predictive efficacy through relevant bone metabolism biochemical indexes. Methods: A total of 254 elderly OS patients diagnosed and treated in our hospital during May 2019 to April 2022 was randomly picked, of which 100 patients were finally enrolled. Patients were divided into OS fracture group and non-fracture group according to whether they had OS fracture. The contents of bone mineral density (BMD) and bone metabolism biochemical indexes, including Dickkopf1 (DKK-1), sclerostin (SOST), osteoprotegerin (OPG), osteopontin (OPN), osteocalcin (BGP) and 25 hydroxyvitamin D (25 (OH) D) were detected in lumbar L2č4 and left femoral greater trochanter. The correlation between bone metabolism and BMD was evaluated using Pearson analysis. The risk factors of OS fracture were analyzed using Multivariate logistic regression analysis. The predictive value of biochemical indexes of bone metabolism on the risk of OS fracture was analyzed using ROC curve. Results: The OS fracture group had a higher proportion of patients with age and lack of sunlight compared to the non-fracture group (P < 0.05). Patients in the OS fracture group exhibited lower BMD in lumbar L2č4 and left femoral greater trochanter compared to the non-fracture group (P < 0.05). At 14 weeks and 16 weeks after surgery, levels of DKK-1, SOST and OPN were higher in the OS fracture group than these in the non-fracture group, while levels of OPG, BGP and 25 (OH) D were lower (P < 0.05). BMD in lumbar L2č4, BMD in femoral greater trochanter, OPG, BGP and 25 (OH) D were the protective factors (P < 0.05), and the age, lack of sunlight, DKK-1, SOST and OPN were the risk factors for OS fractures (P < 0.05). BMD in lumbar L2č4 was negatively correlated with DKK1, SOST and OPN (P < 0.05), and positively correlated with BGP and 25 (OH) D (P < 0.05). 25 (OH) D was positively correlated with femoral greater trochanter BMD (P < 0.05). OPG, OPN, BGP and 25 (OH) D had predictive value for OS fracture occurrence, with respective areas under the curve (AUC) of 0.709, 0.761, 0.720 and 0.730. When all indicators were combined, the AUC increased to 0.940 (P < 0.05), signifying high predictive value for OS fractures. Conclusion: Biochemical bone metabolism indicators were closely correlated with the risk of OS fracture and had a high predictive value as influencing factors for OS fracture occurrence. Therefore, an accurate combination of biochemical indices may help reduce the risk of fracture in the elderly, enabling the development of targeted treatment plans for elderly fracture patients.

Keywords

• bone metabolism
• osteoporotic fracture in the elderly
• risk prediction
• predictive efficacy