DryEyeRhythm: A reliable and valid smartphone application for the diagnosis assistance of dry eye
DryEyeRhythm: A reliable and valid smartphone application for the diagnosis assistance of dry eye
复制标题
DOI：
10.1016/j.jtos.2022.04.005
复制
发表时间：
2022-04-28
期刊：
影响因子：
6.4
通讯作者：
Murakami, Akira
中科院分区：
文献类型：
--
作者：
Okumura, Yuichi;Inomata, Takenori;Murakami, Akira
目的：未被诊断或治疗不充分的干眼病（DED）降低了生活质量。我们的目的是调查的可靠性，有效性和可行性的DryEyeRhythm智能手机应用程序（应用程序）的诊断辅助DED.Methods：这项前瞻性，横断面，观察性，单中心研究招募了82名参与者（42与DED）年龄>= 20岁（2020年7月至2021年5月）。排除有眼睑疾病、上睑下垂、精神疾病、帕金森病或任何其他影响眨眼的疾病病史的患者。参与者接受了DED检查，包括日本版的眼表疾病指数（J-OSDI）和最大眨眼间隔（MBI）。我们分析了他们基于应用程序的J-OSDI和MBI结果。内部一致性信度和同时效度分别采用Cronbach’s α系数和Pearson’s检验进行评价。通过比较基于临床的J-OSDI和MBI的结果来评估基于应用程序的DED诊断的判别效度。结果：基于应用程序的J-OSDI具有较好的内部一致性（Cronbach's alpha = 0.874）。基于app的J-OSDI和MBI与基于临床的J-OSDI和MBI呈正相关（r = 0.891和r = 0.329）。基于应用程序的J-OSDI和MBI的判别有效性在DED队列中产生了显著更高的总分（8.6 +/- 9.3 vs. 28.4 +/- 14.9，P < 0.001; 19.0 +/- 11.1 vs. 13.2 +/- 9.3，P < 0.001）。应用程序的阳性和阴性预测值分别为91.3%和69.1%。曲线下的面积（95%置信区间）为0.910（0.846-0.973）与同时使用的应用程序为基础的J-OSDI和MBI.Conclusions：DryEyeRhythm应用程序是一种新型的，非侵入性的，可靠的，有效的工具，用于评估DED。
Purpose: Undiagnosed or inadequately treated dry eye disease (DED) decreases the quality of life. We aimed to investigate the reliability, validity, and feasibility of the DryEyeRhythm smartphone application (app) for the diagnosis assistance of DED.Methods: This prospective, cross-sectional, observational, single-center study recruited 82 participants (42 with DED) aged >= 20 years (July 2020-May 2021). Patients with a history of eyelid disorder, ptosis, mental disease, Parkinson's disease, or any other disease affecting blinking were excluded. Participants underwent DED examinations, including the Japanese version of the Ocular Surface Disease Index (J-OSDI) and maximum blink interval (MBI). We analyzed their app-based J-OSDI and MBI results. Internal consistency reliability and concurrent validity were evaluated using Cronbach's alpha coefficients and Pearson's test, respectively. The discriminant validity of the app-based DED diagnosis was assessed by comparing the results of the clinical-based J-OSDI and MBI. The app feasibility and screening performance were evaluated using the precision rate and receiver operating characteristic curve analysis.Results: The app-based J-OSDI showed good internal consistency (Cronbach's alpha = 0.874). The app-based J-OSDI and MBI were positively correlated with their clinical-based counterparts (r = 0.891 and r = 0.329, respectively). Discriminant validity of the app-based J-OSDI and MBI yielded significantly higher total scores for the DED cohort (8.6 +/- 9.3 vs. 28.4 +/- 14.9, P < 0.001; 19.0 +/- 11.1 vs. 13.2 +/- 9.3, P < 0.001). The app's positive and negative predictive values were 91.3% and 69.1%, respectively. The area under the curve (95% confidence interval) was 0.910 (0.846-0.973) with concurrent use of the app-based J-OSDI and MBI.Conclusions: DryEyeRhythm app is a novel, non-invasive, reliable, and valid instrument for assessing DED.