건성안 설문의 상관관계 및 관련요인 분석을 통한 의사결정나무모형 개발

Purpose: This study analyzed the correlation between prolonged COVID-19-related factors and dry eyes and developed a decision tree model that can identify the characteristics according to the grade of dry eyes. Methods: Dry Eye Questionnaire-5 (DEQ-5) and the Ocular surface disease index (OSDI) questionnaire were used to assess the subjective symptoms of adults in their 20s and 30s. An analysis of factors related to dry eyes due to prolonged COVID- 19 was conducted by a self-prepared questionnaire. Descriptive statistics, including frequency distributions, means, and standard deviations, were used to analyze data; the Pearson correlation coefficient was used to identify the correlation between the questionnaire answers. The relevance, priority, and reference point of answer variables according to the OSDI grade were analyzed by the ordinal logistic regression and decision tree model. Results: The highest positive correlation was found between “ocular fatigue score” and “ocular dryness score,” and one unit increase in “maskwearing time,” “ocular fatigue score,” and “DEQ-5 score” significantly increased the probability of having a higher OSDI grade. Based on the decision tree model, it was found that the OSDI grade was highly correlated in the order of ocular dryness score, ocular fatigue score, DEQ-5 score, and mask-wearing time, and the related factors' reference value could be set for each grade of dry eyes. Conclusions: Results from the questionnaire-based surveys on subjective symptoms and related factors associated with prolonged COVID-19 could effectively predict the grading of dry eyes. Therefore, if the reliability of the subjective symptoms-based questionnaire answers is secured, it can be used as a reference value for predicting and diagnosing dry eyes.