THU424 A Diagnostic Predictive Model For Secondary Osteoporosis In Patients With Fragility Fracture: A Retrospective Cohort Study In A Tertiary Care Hospital

Abstract

Abstract Disclosure: P. Phudphong: None. M. Phimphilai: None. W. Manosroi: None. N. Adulkasem: None. T. Kaewchur: None. Introduction: Although primary osteoporosis is the leading etiology of osteoporosis in asymptomatic elderly presenting with fragility fractures, secondary osteoporosis can be accounted for one-third of patients. Establishing whether a fragility fracture is secondary to a specific cause of osteoporosis is crucial for treatment outcomes. This study aimed to develop a simple screening tool for secondary osteoporosis in the elderly who are presented with fragility fractures. Methods: A retrospective cohort study of 456 patients diagnosed with non-traumatic hip and clinical vertebral fractures between January 2017 and July 2022 was conducted. Demographic, clinical, biochemical, and final diagnostic data were retrieved. Potential predictors for secondary osteoporosis were identified via multivariate logistic regression analysis. Subsequently, we developed a predictive model for secondary osteoporosis using the identified potential predictors. Results: This study included 343 females and 113 males with a mean age of 76.9±11.0 years. One hundred and twenty-one patients (26.5%) were diagnosed with secondary osteoporosis. Vitamin D deficiency (71.9%) was the most common cause of secondary osteoporosis, followed by glucocorticoid-induced osteoporosis (23.9%) and primary hyperparathyroidism (9.9%). The developed prediction model for secondary osteoporosis demonstrated an acceptable discriminative ability with an AuROC of 0.75 (95%CI 0.69 to 0.81) using the patient’s age, body mass index (BMI), corrected serum calcium, serum phosphate, thyroid stimulating hormone (TSH) level, and BMI-based FRAX score. With a cut-off level of 0.22, the proposed predictive model revealed a sensitivity of 74.4% and a specificity of 65.8%. Finally, the developed prediction model was derived into a web-based screening tool available at: https://www.calconic.com/calculator-widgets/secondary-osteoporosis-screening-tool/62f7c112d5da86001f8e3a25?layouts=true. Conclusion: A predictive model for screening secondary osteoporosis was constructed using simple clinical and biochemical parameters. This newly developed predictive model may provide clinicians with guidance to perform further advanced investigations for secondary causes of osteoporosis. Presentation: Thursday, June 15, 2023