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Observational Study
. 2023 Aug 21;13(1):13583.
doi: 10.1038/s41598-023-40968-y.

Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis

Kenta Fujio  1   2 , Ken Nagino  1   2   3 , Tianxiang Huang  1   2 , Jaemyoung Sung  1 , Yasutsugu Akasaki  1   2 , Yuichi Okumura  1   2 , Akie Midorikawa-Inomata  3 , Keiichi Fujimoto  1   2 , Atsuko Eguchi  3 , Maria Miura  1   2 , Shokirova Hurramhon  1 , Alan Yee  1 , Kunihiko Hirosawa  1   2 , Mizu Ohno  1   2 , Yuki Morooka  1   2 , Akira Murakami  1   2 , Hiroyuki Kobayashi  3 , Takenori Inomata  4   5   6   7
Affiliations
Observational Study

Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis

Kenta Fujio et al. Sci Rep. .

Abstract

The coronavirus disease (COVID-19) pandemic has emphasized the paucity of non-contact and non-invasive methods for the objective evaluation of dry eye disease (DED). However, robust evidence to support the implementation of mHealth- and app-based biometrics for clinical use is lacking. This study aimed to evaluate the reliability and validity of app-based maximum blink interval (MBI) measurements using DryEyeRhythm and equivalent traditional techniques in providing an accessible and convenient diagnosis. In this single-center, prospective, cross-sectional, observational study, 83 participants, including 57 with DED, had measurements recorded including slit-lamp-based, app-based, and visually confirmed MBI. Internal consistency and reliability were assessed using Cronbach's alpha and intraclass correlation coefficients. Discriminant and concurrent validity were assessed by comparing the MBIs from the DED and non-DED groups and Pearson's tests for each platform pair. Bland-Altman analysis was performed to assess the agreement between platforms. App-based MBI showed good Cronbach's alpha coefficient, intraclass correlation coefficient, and Pearson correlation coefficient values, compared with visually confirmed MBI. The DED group had significantly shorter app-based MBIs, compared with the non-DED group. Bland-Altman analysis revealed minimal biases between the app-based and visually confirmed MBIs. Our findings indicate that DryEyeRhythm is a reliable and valid tool that can be used for non-invasive and non-contact collection of MBI measurements, which can assist in accessible DED detection and management.

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Conflict of interest statement

The DryEyeRhythm app was created using Apple’s Research Kit (Cupertino, CA, USA) along with OHAKO, Inc. (Tokyo, Japan) and Medical Logue, Inc. (Tokyo, Japan). T.I., Y.O., and A.M.I are the owners of InnoJin, Inc., Tokyo, Japan, which helped develop DryEyeRhythm. T.I. received grants from Johnson & Johnson Vision Care, SEED Co., Ltd., Novartis Pharma K.K., and Kowa Company, Ltd., outside the submitted work, as well as personal fees from Santen Pharmaceutical Co., Ltd. and InnoJin, Inc. Y.O. and A. M. I. reported receiving personal fees from InnoJin, Inc. The remaining authors declare no competing interests.

Figures

Figure 1
Figure 1
Flowchart of the study indicating the number of participants at each. CFS, corneal fluorescein staining; TFBUT, tear film breakup time; MBI, maximum blink interval.
Figure 2
Figure 2
Bland–Altman plot for the app-based and visually confirmed maximum blink interval (MBI). The x-axis of the Bland–Altman plot represents average MBI values, and the y-axis represents differences between two of the different MBI measurement methods. The central line indicates the mean difference (bias) between the MBI values, whereas the superior and inferior lines indicate the upper and lower 95% limits of agreement, respectively. Differences between app-based and visually confirmed MBIs are displayed for (a) iOS and (b) Android. Differences in app-based MBI based on the operating systems are shown in (c). Differences between app-based and slit-lamp-based MBIs are displayed for (d) iOS and (e) Android. MBI, maximum blink interval; iOS, iPhone Operating System.
Figure 3
Figure 3
Illustration showing the process of DryEyeRhythm application-based maximum blink interval (MBI) measurement. (a) Representative illustration of MBI measurement using the DryEyeRhythm app. (b) Prior to the app-based MBI measurement, instructional information on the procedure is displayed to the user. (c) The user must align their face with the displayed guideline during the 3-s countdown before MBI measurement. (d) MBI measurement screen: measurements are obtained with the face aligned to the guideline. (e) Measurement completion screen: once the app detects a blink, the MBI is displayed to the user and the measurement is complete.
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References

    1. Stapleton F, et al. TFOS DEWS II epidemiology report. Ocul. Surf. 2017;15:334–365. doi: 10.1016/j.jtos.2017.05.003. - DOI - PubMed
    1. Inomata T, et al. Changes in distribution of dry eye disease by the new 2016 diagnostic criteria from the Asia dry eye society. Sci. Rep. 2018;8:1918. doi: 10.1038/s41598-018-19775-3. - DOI - PMC - PubMed
    1. Wolffsohn JS, et al. TFOS lifestyle: Impact of the digital environment on the ocular surface. Ocul. Surf. 2023;28:213–252. doi: 10.1016/j.jtos.2023.04.004. - DOI - PubMed
    1. Midorikawa-Inomata A, et al. Reliability and validity of the Japanese version of the Ocular Surface Disease Index for dry eye disease. BMJ Open. 2019;9:e033940. doi: 10.1136/bmjopen-2019-033940. - DOI - PMC - PubMed
    1. Okumura Y, et al. DryEyeRhythm: A reliable and valid smartphone application for the diagnosis assistance of dry eye. Ocul. Surf. 2022;25:19–25. doi: 10.1016/j.jtos.2022.04.005. - DOI - PubMed

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