Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis
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...
| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-40968-y |
| _version_ | 1797576739577135104 |
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| author | Kenta Fujio Ken Nagino Tianxiang Huang Jaemyoung Sung Yasutsugu Akasaki Yuichi Okumura Akie Midorikawa-Inomata Keiichi Fujimoto Atsuko Eguchi Maria Miura Shokirova Hurramhon Alan Yee Kunihiko Hirosawa Mizu Ohno Yuki Morooka Akira Murakami Hiroyuki Kobayashi Takenori Inomata |
| author_facet | Kenta Fujio Ken Nagino Tianxiang Huang Jaemyoung Sung Yasutsugu Akasaki Yuichi Okumura Akie Midorikawa-Inomata Keiichi Fujimoto Atsuko Eguchi Maria Miura Shokirova Hurramhon Alan Yee Kunihiko Hirosawa Mizu Ohno Yuki Morooka Akira Murakami Hiroyuki Kobayashi Takenori Inomata |
| author_sort | Kenta Fujio |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T21:57:59Z |
| format | Article |
| id | doaj.art-f483d397cb364990bd05154d942956b0 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-10T21:57:59Z |
| publishDate | 2023-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-f483d397cb364990bd05154d942956b02023-11-19T13:05:06ZengNature PortfolioScientific Reports2045-23222023-08-0113111010.1038/s41598-023-40968-yClinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosisKenta Fujio0Ken Nagino1Tianxiang Huang2Jaemyoung Sung3Yasutsugu Akasaki4Yuichi Okumura5Akie Midorikawa-Inomata6Keiichi Fujimoto7Atsuko Eguchi8Maria Miura9Shokirova Hurramhon10Alan Yee11Kunihiko Hirosawa12Mizu Ohno13Yuki Morooka14Akira Murakami15Hiroyuki Kobayashi16Takenori Inomata17Department of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Hospital Administration, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Hospital Administration, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineDepartment of Hospital Administration, Juntendo University Graduate School of MedicineDepartment of Ophthalmology, Juntendo University Graduate School of MedicineAbstract 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.https://doi.org/10.1038/s41598-023-40968-y |
| spellingShingle | Kenta Fujio Ken Nagino Tianxiang Huang Jaemyoung Sung Yasutsugu Akasaki Yuichi Okumura Akie Midorikawa-Inomata Keiichi Fujimoto Atsuko Eguchi Maria Miura Shokirova Hurramhon Alan Yee Kunihiko Hirosawa Mizu Ohno Yuki Morooka Akira Murakami Hiroyuki Kobayashi Takenori Inomata Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis Scientific Reports |
| title | Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis |
| title_full | Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis |
| title_fullStr | Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis |
| title_full_unstemmed | Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis |
| title_short | Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis |
| title_sort | clinical utility of maximum blink interval measured by smartphone application dryeyerhythm to support dry eye disease diagnosis |
| url | https://doi.org/10.1038/s41598-023-40968-y |
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