Nephrology Department, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, Guangdong, China.
Nuclear Medicine, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, Guangdong, China.
Ren Fail. 2024 Dec;46(2):2361802. doi: 10.1080/0886022X.2024.2361802. Epub 2024 Jun 14.
BACKGROUND: Osteoporosis in pre-dialysis chronic kidney disease (CKD) patients has been overlooked, and the risk factors of osteoporosis in these patients have not been adequately studied. OBJECTIVE: To identify risk factors for osteoporosis in pre-dialysis CKD patients and develop predictive models to estimate the likelihood of osteoporosis. METHODS: Dual-energy X-ray absorptiometry was used to measure bone mineral density, and clinical examination results were collected from 326 pre-dialysis CKD patients. Binary logistic regression was employed to explore the risk factors associated with osteoporosis and develop predictive models. RESULTS: In this cohort, 53.4% ( = 174) were male, 46.6% ( = 152) were female, and 21.8% ( = 71) were diagnosed with osteoporosis. Among those diagnosed with osteoporosis, 67.6% ( = 48) were female and 32.4% ( = 23) were male. Older age and low 25-(OH)-Vitamin D levels were identified as risk factors for osteoporosis in males. For females, older age, being underweight, higher bone alkaline phosphatase (NBAP), and advanced CKD (G5) were significant risk factors, while higher iPTH was protective. Older age, being underweight, and higher NBAP were risk factors for osteoporosis in the G1-4 subgroup. In the G5 subgroup, older age and higher NBAP increased the risk, while high 25-(OH)-Vitamin D or iPTH had protective effects. Nomogram models were developed to assess osteoporosis risk in pre-dialysis patients based on gender and renal function stage. CONCLUSION: Risk factors for osteoporosis vary by gender and renal function stages. The nomogram clinical prediction models we constructed may aid in the rapid screening of patients at high risk of osteoporosis.
背景: 透析前慢性肾脏病(CKD)患者的骨质疏松症一直被忽视,这些患者的骨质疏松症危险因素尚未得到充分研究。
目的: 确定透析前 CKD 患者骨质疏松症的危险因素,并建立预测模型来估计骨质疏松症的可能性。
方法: 使用双能 X 射线吸收法测量骨矿物质密度,并从 326 名透析前 CKD 患者中收集临床检查结果。采用二元逻辑回归分析探讨与骨质疏松症相关的危险因素,并建立预测模型。
结果: 在该队列中,53.4%( = 174)为男性,46.6%( = 152)为女性,21.8%( = 71)被诊断为骨质疏松症。在诊断为骨质疏松症的患者中,67.6%( = 48)为女性,32.4%( = 23)为男性。年龄较大和 25-(OH)-维生素 D 水平较低被确定为男性骨质疏松症的危险因素。对于女性,年龄较大、体重不足、骨碱性磷酸酶(NBAP)较高和 CKD 进展(G5)是显著的危险因素,而较高的 iPTH 则具有保护作用。年龄较大、体重不足和 NBAP 较高是 G1-4 亚组骨质疏松症的危险因素。在 G5 亚组中,年龄较大和 NBAP 较高增加了风险,而较高的 25-(OH)-维生素 D 或 iPTH 具有保护作用。我们基于性别和肾功能分期开发了诺莫图模型来评估透析前患者的骨质疏松症风险。
结论: 骨质疏松症的危险因素因性别和肾功能分期而异。我们构建的诺莫图临床预测模型可能有助于快速筛选骨质疏松症高危患者。
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