老年视力障碍患者社会衰弱风险预测模型的构建及验证

doi:10.3761/j.issn.0254-1769.2026.19.011

摘要/Abstract

摘要：

目的分析老年视力障碍患者社会衰弱的影响因素，构建风险预测列线图模型，为早期识别高危人群提供参考。方法采用便利抽样法，选取2025年12月至2026年4月在江西省某三级甲等医院就诊的350例老年视力障碍患者为调查对象，将其按7∶3比例随机分为训练集和验证集，在训练集中采用单因素分析、LASSO回归筛选候选预测因子，对2种方法的交集变量进行多因素Logistic回归构建预测模型，绘制列线图。采用受试者操作特征曲线下面积、校准曲线、Hosmer-Lemeshow检验和决策曲线分析评价模型效能。结果最终纳入344例。老年视力障碍患者社会衰弱发生率为32.56%，家庭人均月收入、社会支持得分、视功能相关生存质量得分是社会衰弱的影响因素，构建的列线图模型训练集受试者操作特征曲线下面积为0.955，验证集受试者操作特征曲线下面积为0.960；Hosmer-Lemeshow检验结果显示，训练集χ²=13.046，P=0.110，验证集χ²=1.571，P=0.666；决策曲线分析显示，模型在阈值概率5%~90%内临床净获益良好。结论该研究构建的列线图模型具有良好的预测效能，可用于老年视力障碍患者社会衰弱的早期筛查。

关键词: 老年人, 视力障碍, 社会衰弱, 风险预测模型, 护理

Abstract:

Objective To analyze the influencing factors of social frailty in older adults with visual impairment，construct a risk prediction nomogram model，and provide a reference for early identification of high-risk populations. Methods Using convenience sampling，data of 350 older adults with visual impairment who visited a tertiary hospital in Jiangxi Province from December 2025 to April 2026 were retrospectively collected. The cohort was randomly divided into a training set and a validation set at a 7∶3 ratio. In the training set，univariate analysis and LASSO regression were used to screen candidate predictors. The intersection variables of the 2 methods were included in multivariable Logistic regression to construct the prediction model，and a nomogram was plotted. Model performance was evaluated using the area under the receiver operating characteristic curve，calibration curve，Hosmer-Lemeshow test，and decision curve analysis. Results A total of 344 cases were ultimately included. The incidence rate of social frailty in older adults with visual impairment was 32.56%. Per capita monthly household income，social support score，and visual function-related quality of life score were the influencing factors of social frailty. The area under the curve of the constructed nomogram model was 0.955 in the training set and 0.960 in the validation set. The Hosmer-Lemeshow test showed that χ²=13.046，P=0.110 for the training set，and χ²=1.571，P=0.666 for the validation set. Decision curve analysis showed that the model had a good clinical net benefit in the threshold probability range of 5%-90%. Conclusion The nomogram model constructed in this study has good predictive performance and can be used for early screening of social frailty in older adults with visual impairment.

Key words: Aged, Visual Impairment, Social Frailty, Risk Prediction Model, Nursing Care

晏康容, 唐浪娟, 吴利, 谢方婷, 缪洪艳, 刘子悦, 莫妮. 老年视力障碍患者社会衰弱风险预测模型的构建及验证[J]. 中华护理杂志, 2026, 61(19): 2669-2675.

YAN Kangrong, TANG Langjuan, WU Li, XIE Fangting, MIAO Hongyan, LIU Ziyue, MO Ni. Construction and internal validation of a risk prediction nomogram for social frailty in older adults with visual impairment[J]. Chinese Journal of Nursing, 2026, 61(19): 2669-2675.

图/表 5

表1 训练集中老年视力障碍患者社会衰弱影响因素的单因素分析[n=241，例（百分比，%）]

Table 1 Univariate analysis of factors associated with social frailty in the training set[n=241，case（percentage，%）]

表2 分类变量赋值情况

Table 2 Coding scheme of categorical variables

表3 老年视力障碍患者社会衰弱多因素Logistic回归分析结果（n=241）

Table 3 Multivariable logistic regression analysis of social frailty in older adults with visual impairment（n=241）

图1 老年视力障碍患者社会衰弱风险预测列线图

Figure 1 Nomogram for predicting the risk of social frailty in older adults with visual impairment

图2 训练集与验证集受试者操作特征曲线

Figure 2 ROC curves of the social frailty prediction model in the training and validation sets

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