Symptom-based stratification algorithm for heterogeneous symptoms of dry eye disease: a feasibility study
Symptom-based stratification algorithm for heterogeneous symptoms of dry eye disease: a feasibility study
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DOI：
10.1038/s41433-023-02538-4
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发表时间：
2023-04-15
期刊：
影响因子：
3.9
通讯作者：
Kobayashi, Hiroyuki
中科院分区：
文献类型：
--
作者：
Nagino, Ken;Inomata, Takenori;Kobayashi, Hiroyuki
本研究于2015年12月至2021年10月在日本一所大学医院进行，研究对象和方法包括接受过干眼病综合检查并完成日本版眼表疾病指数(J-OSDI)的受试者。使用先前建立的基于症状的DED分层算法，将被诊断为DED的患者分层到七个群组。结果共纳入426例患者(中位年龄[四分位数范围]；63[48-72]岁；357例(83.8%)女性)。其中，291名(68.3%)的参与者被诊断为DED，并成功地分成了7个组。J-OSDI总分在第1组最高(61.4[52.2-75.0])，其次是第5组(44.1[38.8-47.9])。泪膜破裂时间以第1组最短(1.5[1.1~2.1])，第3组次之(1.6[1.0~2.5])。本研究中分层整群的J-OSDI总分与上一项研究中确定的整群的J-OSDI总分存在显著相关性(r=0.991，P<；0.001)。结论采用先前建立的面向普通人群的算法成功地对就诊的DED患者进行了分层，揭示了他们看似异质性和多变性的临床特征的规律。这一结果对推广针对个别患者的治疗干预措施，以及未来实施基于智能手机的临床数据收集具有重要意义。
Background/objectiveTo test the feasibility of a dry eye disease (DED) symptom stratification algorithm previously established for the general population among patients visiting ophthalmologists.Subject/methodsThis retrospective cross-sectional study was conducted between December 2015 and October 2021 at a university hospital in Japan; participants who underwent a comprehensive DED examination and completed the Japanese version of the Ocular Surface Disease Index (J-OSDI) were included. Patients diagnosed with DED were stratified into seven clusters using a previously established symptom-based stratification algorithm for DED. Characteristics of the patients in stratified clusters were compared.ResultsIn total, 426 participants were included (median age [interquartile range]; 63 [48-72] years; 357 (83.8%) women). Among them, 291 (68.3%) participants were diagnosed with DED and successfully stratified into seven clusters. The J-OSDI total score was highest in cluster 1 (61.4 [52.2-75.0]), followed by cluster 5 (44.1 [38.8-47.9]). The tear film breakup time was the shortest in cluster 1 (1.5 [1.1-2.1]), followed by cluster 3 (1.6 [1.0-2.5]). The J-OSDI total scores from the stratified clusters in this study and those from the clusters identified in the previous study showed a significant correlation (r = 0.991, P < 0.001).ConclusionsThe patients with DED who visited ophthalmologists were successfully stratified by the previously established algorithm for the general population, uncovering patterns for their seemingly heterogeneous and variable clinical characteristics of DED. The results have important implications for promoting treatment interventions tailored to individual patients and implementing smartphone-based clinical data collection in the future.