Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study
BackgroundDry eye disease (DED) is one of the most common ocular surface diseases. Numerous patients with DED remain undiagnosed and inadequately treated, experiencing various subjective symptoms and a decrease in quality of life and work productivity. A mobile health smartph...
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| Language: | English |
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JMIR Publications
2023-03-01
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| Series: | JMIR Research Protocols |
| Online Access: | https://www.researchprotocols.org/2023/1/e45218 |
| _version_ | 1797734325854142464 |
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| author | Ken Nagino Yuichi Okumura Masahiro Yamaguchi Jaemyoung Sung Masashi Nagao Kenta Fujio Yasutsugu Akasaki Tianxiang Huang Kunihiko Hirosawa Masao Iwagami Akie Midorikawa-Inomata Keiichi Fujimoto Atsuko Eguchi Yukinobu Okajima Koji Kakisu Yuto Tei Takefumi Yamaguchi Daisuke Tomida Masaki Fukui Yukari Yagi-Yaguchi Yuichi Hori Jun Shimazaki Shuko Nojiri Yuki Morooka Alan Yee Maria Miura Mizu Ohno Takenori Inomata |
| author_facet | Ken Nagino Yuichi Okumura Masahiro Yamaguchi Jaemyoung Sung Masashi Nagao Kenta Fujio Yasutsugu Akasaki Tianxiang Huang Kunihiko Hirosawa Masao Iwagami Akie Midorikawa-Inomata Keiichi Fujimoto Atsuko Eguchi Yukinobu Okajima Koji Kakisu Yuto Tei Takefumi Yamaguchi Daisuke Tomida Masaki Fukui Yukari Yagi-Yaguchi Yuichi Hori Jun Shimazaki Shuko Nojiri Yuki Morooka Alan Yee Maria Miura Mizu Ohno Takenori Inomata |
| author_sort | Ken Nagino |
| collection | DOAJ |
| description |
BackgroundDry eye disease (DED) is one of the most common ocular surface diseases. Numerous patients with DED remain undiagnosed and inadequately treated, experiencing various subjective symptoms and a decrease in quality of life and work productivity. A mobile health smartphone app, namely, the DEA01, has been developed as a noninvasive, noncontact, and remote screening device, in the context of an ongoing paradigm shift in the health care system, to facilitate a diagnosis of DED.
ObjectiveThis study aimed to evaluate the capabilities of the DEA01 smartphone app to facilitate a DED diagnosis.
MethodsIn this multicenter, open-label, prospective, and cross-sectional study, the test method will involve using the DEA01 smartphone app to collect and evaluate DED symptoms, based on the Japanese version of the Ocular Surface Disease Index (J-OSDI), and to measure the maximum blink interval (MBI). The standard method will then involve a paper-based J-OSDI evaluation of subjective symptoms of DED and tear film breakup time (TFBUT) measurement in an in-person encounter. We will allocate 220 patients to DED and non-DED groups, based on the standard method. The primary outcome will be the sensitivity and specificity of the DED diagnosis according to the test method. Secondary outcomes will be the validity and reliability of the test method. The concordance rate, positive and negative predictive values, and the likelihood ratio between the test and standard methods will be assessed. The area under the curve of the test method will be evaluated using a receiver operating characteristic curve. The internal consistency of the app-based J-OSDI and the correlation between the app-based J-OSDI and paper-based J-OSDI will be assessed. A DED diagnosis cutoff value for the app-based MBI will be determined using a receiver operating characteristic curve. The app-based MBI will be assessed to determine a correlation between a slit lamp–based MBI and TFBUT. Adverse events and DEA01 failure data will be collected. Operability and usability will be assessed using a 5-point Likert scale questionnaire.
ResultsPatient enrollment will start in February 2023 and end in July 2023. The findings will be analyzed in August 2023, and the results will be reported from March 2024 onward.
ConclusionsThis study may have implications in identifying a noninvasive, noncontact route to facilitate a diagnosis of DED. The DEA01 may enable a comprehensive diagnostic evaluation within a telemedicine setting and facilitate early intervention for undiagnosed patients with DED confronting health care access barriers.
Trial RegistrationJapan Registry of Clinical Trials jRCTs032220524; https://jrct.niph.go.jp/latest-detail/jRCTs032220524
International Registered Report Identifier (IRRID)PRR1-10.2196/45218 |
| first_indexed | 2024-03-12T12:42:39Z |
| format | Article |
| id | doaj.art-b27924c66e484652b646b16b6d87587d |
| institution | Directory Open Access Journal |
| issn | 1929-0748 |
| language | English |
| last_indexed | 2024-03-12T12:42:39Z |
| publishDate | 2023-03-01 |
| publisher | JMIR Publications |
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| series | JMIR Research Protocols |
| spelling | doaj.art-b27924c66e484652b646b16b6d87587d2023-08-28T23:45:04ZengJMIR PublicationsJMIR Research Protocols1929-07482023-03-0112e4521810.2196/45218Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional StudyKen Naginohttps://orcid.org/0000-0002-0317-6074Yuichi Okumurahttps://orcid.org/0000-0002-5521-5469Masahiro Yamaguchihttps://orcid.org/0000-0002-2971-9321Jaemyoung Sunghttps://orcid.org/0000-0002-9441-3687Masashi Nagaohttps://orcid.org/0000-0002-8909-4650Kenta Fujiohttps://orcid.org/0000-0002-8472-0800Yasutsugu Akasakihttps://orcid.org/0000-0001-9527-0115Tianxiang Huanghttps://orcid.org/0000-0001-8867-1367Kunihiko Hirosawahttps://orcid.org/0000-0001-6775-3697Masao Iwagamihttps://orcid.org/0000-0001-7079-0640Akie Midorikawa-Inomatahttps://orcid.org/0000-0002-6054-5710Keiichi Fujimotohttps://orcid.org/0000-0003-0420-0782Atsuko Eguchihttps://orcid.org/0000-0002-5540-055XYukinobu Okajimahttps://orcid.org/0000-0003-0845-4587Koji Kakisuhttps://orcid.org/0000-0003-0535-3035Yuto Teihttps://orcid.org/0000-0002-1525-018XTakefumi Yamaguchihttps://orcid.org/0000-0002-2546-2813Daisuke Tomidahttps://orcid.org/0000-0002-6361-3600Masaki Fukuihttps://orcid.org/0000-0002-3948-5338Yukari Yagi-Yaguchihttps://orcid.org/0000-0002-7980-7741Yuichi Horihttps://orcid.org/0000-0002-3781-7976Jun Shimazakihttps://orcid.org/0000-0002-0435-3095Shuko Nojirihttps://orcid.org/0000-0003-0422-8152Yuki Morookahttps://orcid.org/0000-0002-0461-2659Alan Yeehttps://orcid.org/0000-0002-5613-9613Maria Miurahttps://orcid.org/0000-0002-2600-2085Mizu Ohnohttps://orcid.org/0000-0002-1835-7038Takenori Inomatahttps://orcid.org/0000-0003-3435-1055 BackgroundDry eye disease (DED) is one of the most common ocular surface diseases. Numerous patients with DED remain undiagnosed and inadequately treated, experiencing various subjective symptoms and a decrease in quality of life and work productivity. A mobile health smartphone app, namely, the DEA01, has been developed as a noninvasive, noncontact, and remote screening device, in the context of an ongoing paradigm shift in the health care system, to facilitate a diagnosis of DED. ObjectiveThis study aimed to evaluate the capabilities of the DEA01 smartphone app to facilitate a DED diagnosis. MethodsIn this multicenter, open-label, prospective, and cross-sectional study, the test method will involve using the DEA01 smartphone app to collect and evaluate DED symptoms, based on the Japanese version of the Ocular Surface Disease Index (J-OSDI), and to measure the maximum blink interval (MBI). The standard method will then involve a paper-based J-OSDI evaluation of subjective symptoms of DED and tear film breakup time (TFBUT) measurement in an in-person encounter. We will allocate 220 patients to DED and non-DED groups, based on the standard method. The primary outcome will be the sensitivity and specificity of the DED diagnosis according to the test method. Secondary outcomes will be the validity and reliability of the test method. The concordance rate, positive and negative predictive values, and the likelihood ratio between the test and standard methods will be assessed. The area under the curve of the test method will be evaluated using a receiver operating characteristic curve. The internal consistency of the app-based J-OSDI and the correlation between the app-based J-OSDI and paper-based J-OSDI will be assessed. A DED diagnosis cutoff value for the app-based MBI will be determined using a receiver operating characteristic curve. The app-based MBI will be assessed to determine a correlation between a slit lamp–based MBI and TFBUT. Adverse events and DEA01 failure data will be collected. Operability and usability will be assessed using a 5-point Likert scale questionnaire. ResultsPatient enrollment will start in February 2023 and end in July 2023. The findings will be analyzed in August 2023, and the results will be reported from March 2024 onward. ConclusionsThis study may have implications in identifying a noninvasive, noncontact route to facilitate a diagnosis of DED. The DEA01 may enable a comprehensive diagnostic evaluation within a telemedicine setting and facilitate early intervention for undiagnosed patients with DED confronting health care access barriers. Trial RegistrationJapan Registry of Clinical Trials jRCTs032220524; https://jrct.niph.go.jp/latest-detail/jRCTs032220524 International Registered Report Identifier (IRRID)PRR1-10.2196/45218https://www.researchprotocols.org/2023/1/e45218 |
| spellingShingle | Ken Nagino Yuichi Okumura Masahiro Yamaguchi Jaemyoung Sung Masashi Nagao Kenta Fujio Yasutsugu Akasaki Tianxiang Huang Kunihiko Hirosawa Masao Iwagami Akie Midorikawa-Inomata Keiichi Fujimoto Atsuko Eguchi Yukinobu Okajima Koji Kakisu Yuto Tei Takefumi Yamaguchi Daisuke Tomida Masaki Fukui Yukari Yagi-Yaguchi Yuichi Hori Jun Shimazaki Shuko Nojiri Yuki Morooka Alan Yee Maria Miura Mizu Ohno Takenori Inomata Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study JMIR Research Protocols |
| title | Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study |
| title_full | Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study |
| title_fullStr | Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study |
| title_full_unstemmed | Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study |
| title_short | Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study |
| title_sort | diagnostic ability of a smartphone app for dry eye disease protocol for a multicenter open label prospective and cross sectional study |
| url | https://www.researchprotocols.org/2023/1/e45218 |
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