Chen Shijie, Li Lin, He Liangyu, Xiong Shanshan, Du Na, Chen Huifang, Hou Lili, Zeng Changjuan
Clinical Research Unit, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, Shanghai, 200011, China.
Heliyon. 2023 Oct 11;9(10):e20638. doi: 10.1016/j.heliyon.2023.e20638. eCollection 2023 Oct.
To construct a risk assessment model for forecasting the likelihood of myopia in elementary school students.
A cross-sectional study.
This study utilized convenient sampling and questionnaire survey to collect data from eligible elementary students and their parents during the coronavirus disease 2019 (COVID-19) pandemic period from March to December 2020. The data were divided into training and testing sets in a 7:3 ratio. Lasso regression was employed to screen variables for inclusion in the model to establish a generalized linear model, with a nomogram model as the final result.
The study included 1139 elementary students, comprising 54.5 % male and 45.5 % female participants. A total of 37 variables were obtained, which were analyzed using lasso regression. Cross-validation revealed that the best lambda value was 0.04201788. Five variables affecting myopia were identified: three risk and two protective factors. The three risk factors were student age (OR = 1.32), family location (urban vs. rural, OR = 2.33), and parents' occupation (compared with farmer: worker, OR = 2.03; teacher, OR = 1.62; medical worker, OR = 5.64; self-employed, OR = 1.78; civil servant, OR = 1.65; company employee, OR = 1.45; service industries, OR = 3.38; and others, OR = 3.20). The two protective factors were eye distance score (OR = 0.83) and eye health exercise score (OR = 0.95). The model was verified and showed good accuracy with an AUC of 0.778 and Brier score of 0.122 in addition to satisfactory clinical effects.
The model effectively predicted the risk of myopia in elementary school students during the COVID-19 pandemic. Using this model, high-risk groups can be identified to provide a foundation for early intervention and follow-up, thereby reducing the incidence of myopia in this population.
构建一个预测小学生近视可能性的风险评估模型。
一项横断面研究。
本研究采用便利抽样和问卷调查的方法，于2020年3月至12月新冠疫情期间收集符合条件的小学生及其家长的数据。数据按7:3的比例分为训练集和测试集。采用Lasso回归筛选纳入模型的变量，以建立广义线性模型，最终结果为列线图模型。
本研究纳入1139名小学生，其中男性占54.5%，女性占45.5%。共获得37个变量，使用Lasso回归进行分析。交叉验证显示最佳λ值为0.04201788。确定了五个影响近视的变量：三个危险因素和两个保护因素。三个危险因素分别为学生年龄（OR = 1.32）、家庭所在地（城市与农村，OR = 2.33）以及父母职业（与农民相比：工人，OR = 2.03；教师，OR = 1.62；医务人员，OR = 5.64；个体经营者，OR = 1.78；公务员，OR = 1.65；公司员工，OR = 1.45；服务业，OR = 3.38；其他，OR = 3.20）。两个保护因素为眼距得分（OR = 0.83）和眼保健操得分（OR = 0.95）。该模型经过验证，除临床效果满意外，AUC为0.778，Brier评分为0.122，显示出良好的准确性。
该模型有效预测了新冠疫情期间小学生的近视风险。利用该模型可识别高危人群，为早期干预和随访提供依据，从而降低该人群的近视发病率。
