摘要
目的本研究旨在基于世界卫生组织口腔健康标准及入院基线资料构建老年口腔疾病患者发生衰弱的预测模型,辅助临床早期识别高风险人群并实施干预。方法收集2021年6月至2024年6月内于金堂县第二人民医院口腔科就诊的老年口腔疾病患者302例,应用Fried衰弱表型评估衰弱状态,采用多因素Logistic回归筛选独立预测因子并构建预测模型。结果与无衰弱组比较,衰弱前期/衰弱组心率、心力衰竭比例、白细胞计数、口腔颌面部疼痛和口腔功能障碍比例更高,血脂异常比例、血红蛋白水平更低(P<0.05)。多因素Logistic回归分析显示,较高的心率(OR=1.032,95%CI:1.019~1.044,P<0.001)、心力衰竭(OR=2.340,95%CI:1.403~3.904,P=0.001)、较高的白细胞计数(OR=1.031,95%CI:1.002~1.061,P=0.035)、口腔颌面部疼痛(OR=1.818,95%CI:1.022~3.234,P=0.042)及口腔功能障碍(OR=2.565,95%CI:1.436~4.582,P=0.001)是老年口腔疾病患者发生衰弱的独立危险因素。所构建模型曲线下面积为0.741,具有良好预测性能,经校准和决策曲线验证具临床实用价值。结论本模型有助于临床早期识别老年口腔疾病患者中的衰弱高风险个体,为精准干预提供依据,尚需进一步验证其外部适用性。
Objective This study aimeds to develop a predictive model for frailty in elderly patients with oral diseases based on the World Health Organization(WHO)oral health standards and baseline admission data.The model is intended to support the early recognition of high-risk populations in clinical settings and facilitate timely intervention strategies.Methods A total of 302 elderly patients with oral diseases who attended the Department of Stomatology at the Second People's Hospital of Jintang County between June 2021 and June 2024 were included in the study.The Fried frailty phenotype was utilized to evaluate their frailty status.Multivariate Logistic regression analysis was conducted to identify independent predictors and develop a predictive model.Results Compared with the non-frail group,the pre-frail/frail group showed higher heart rate,proportion of heart failure,white blood cell count,prevalence of oral and maxillofacial pain,and oral dysfunction,but lower rates of dyslipidemia and hemoglobin levels(P<0.05).Multivariate Logistic regression analysis indicated that higher heart rate(OR=1.032,95%CI:1.019-1.044,P<0.001),heart failure(OR=2.340,95%CI:1.403-3.904,P=0.001),elevated white blood cell count(OR=1.031,95%CI:1.002-1.061,P=0.035),orofacial pain(OR=1.818,95%CI:1.022-3.234,P=0.042),and oral functional impairment(OR=2.565,95%CI:1.436-4.582,P=0.001)were significantly associated with frailty in elderly patients with oral diseases.The area under the curve of the constructed model was 0.741,indicating good predictive performance.Calibration and decision curve analyses demonstrated favorable clinical utility.Conclusion The proposed model may facilitate early identification of elderly oral disease patients at high risk of frailty and provide a basis for tailored interventions.Further validation in external populations is warranted.
作者
易发均
黄维
胡兴周
YI Fajun;HUANG Wei;HU Xingzhou(Department of Stomatology,Jintang County Second People's Hospital,Chengdu 610404,China;Department of Cardiology,Jintang County Second People's Hospital,Chengdu 610404,China)
出处
《中华老年口腔医学杂志》
2025年第6期438-443,共6页
Chinese Journal of Geriatric Dentistry
