Zhao Yue, Wang Aiping
The First Afliated Hospital of China Medical University, Shenyang, Liaoning Province, China.
Int J Nurs Sci. 2023 Jun 20;10(3):383-390. doi: 10.1016/j.ijnss.2023.06.010. eCollection 2023 Jul.
This study aimed to determine the risk factors that affect visual impairment in older adults for developing and evaluating a visual impairment risk prediction model.
In this hospital-based unmatched case-control design study, we enrolled 586 participants (411 in the training set and 175 in the internal test set) from the ophthalmology clinic and physical examination center of a teaching hospital in Liaoning Province, China, from June to December 2020. Visual impairment was defined as best-corrected visual acuity <6/18 (The WHO definition). Possible influencing factors of visual impairment were assessed, including demographic factors, socioeconomic factors, disease and medication factors, and lifestyle. A visual impairment risk prediction model was developed using binary logistic regression analysis. The area under the ROC curve (AUC) was used to evaluate the effectiveness of the proposed prediction model.
Six independent influencing factors of visual impairment in older adults were identified: age, systolic blood pressure, physical activity scores, diabetes, self-reported ocular disease history, and education level. A visual impairment risk prediction model for older adults was developed, showing powerful predictive ability in the training set and internal test set with AUCs of 0.87 (95%CI 0.83-0.90) and 0.81 (95%CI 0.74-0.88), respectively.
The risk prediction model for visual impairment in older adults had high predictive power. Identifying older adults at risk for developing visual impairment can help healthcare workers to adopt appropriate targeted programs for early education and intervention to prevent or delay visual impairment and prevent injuries due to visual impairment in older adults.
本研究旨在确定影响老年人视力损害的风险因素，以开发和评估视力损害风险预测模型。
在这项基于医院的非匹配病例对照设计研究中，我们于2020年6月至12月从中国辽宁省一家教学医院的眼科诊所和体检中心招募了586名参与者（训练集411名，内部测试集175名）。视力损害定义为最佳矫正视力<6/18（世界卫生组织定义）。评估了视力损害的可能影响因素，包括人口统计学因素、社会经济因素、疾病和药物因素以及生活方式。使用二元逻辑回归分析开发了视力损害风险预测模型。ROC曲线下面积（AUC）用于评估所提出预测模型的有效性。
确定了老年人视力损害的六个独立影响因素：年龄、收缩压、身体活动评分、糖尿病、自我报告的眼部疾病史和教育水平。开发了老年人视力损害风险预测模型，在训练集和内部测试集中显示出强大的预测能力，AUC分别为0.87（95%CI 0.83 - 0.90）和0.81（95%CI 0.74 - 0.88）。
老年人视力损害风险预测模型具有较高的预测能力。识别有视力损害风险的老年人可以帮助医护人员采取适当的针对性方案进行早期教育和干预，以预防或延缓视力损害，并防止老年人因视力损害而受伤。
