Characteristics and Risk Factors Associated with Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application

Takenori Inomata, Masao Iwagami, Masahiro Nakamura, Tina Shiang, Yusuke Yoshimura, Keiichi Fujimoto, Yuichi Okumura, Atsuko Eguchi, Nanami Iwata, Maria Miura, Satoshi Hori, Yoshimune Hiratsuka, Miki Uchino, Kazuo Tsubota, Reza Dana, Akira Murakami

研究成果: Article

1 引用 (Scopus)

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Importance: The incidence of dry eye disease has increased; the potential for crowdsource data to help identify undiagnosed dry eye in symptomatic individuals remains unknown. Objective: To assess the characteristics and risk factors associated with diagnosed and undiagnosed symptomatic dry eye using the smartphone app DryEyeRhythm. Design, Setting, and Participants: A cross-sectional study using crowdsourced data was conducted including individuals in Japan who downloaded DryEyeRhythm and completed the entire questionnaire; duplicate users were excluded. DryEyeRhythm was released on November 2, 2016; the study was conducted from November 2, 2016, to January 12, 2018. Exposures: DryEyeRhythm data were collected on demographics, medical history, lifestyle, subjective symptoms, and disease-specific symptoms, using the Ocular Surface Disease Index (100-point scale; scores 0-12 indicate normal, healthy eyes; 13-22, mild dry eye; 23-32, moderate dry eye; 33-100, severe dry eye symptoms), and the Zung Self-Rating Depression Scale (total of 20 items, total score ranging from 20-80, with ≥40 highly suggestive of depression). Main Outcomes and Measures: Multivariate-adjusted logistic regression analysis was used to identify risk factors for symptomatic dry eye and to identify risk factors for undiagnosed symptomatic dry eye. Results: A total of 21394 records were identified in our database; 4454 users, included 899 participants (27.3%) with diagnosed and 2395 participants (72.7%) with undiagnosed symptomatic dry eye, completed all questionnaires and their data were analyzed. A total of 2972 participants (66.7%) were women; mean (SD) age was 27.9 (12.6) years. The identified risk factors for symptomatic vs no symptomatic dry eye included younger age (odds ratio [OR], 0.99; 95% CI, 0.987-0.999, P =.02), female sex (OR, 1.99; 95% CI, 1.61-2.46; P <.001), pollinosis (termed hay fever on the questionnaire) (OR, 1.35; 95% CI, 1.18-1.55; P <.001), depression (OR, 1.78; 95% CI, 1.18-2.69; P =.006), mental illnesses other than depression or schizophrenia (OR, 1.87; 95% CI, 1.24-2.82; P =.003), current contact lens use (OR, 1.27; 95% CI, 1.09-1.48; P =.002), extended screen exposure (OR, 1.55; 95% CI, 1.25-1.91; P <.001), and smoking (OR, 1.65; 95% CI, 1.37-1.98; P <.001). The risk factors for undiagnosed vs diagnosed symptomatic dry eye included younger age (OR, 0.96; 95% CI, 0.95-0.97; P <.001), male sex (OR, 0.55; 95% CI, 0.42-0.72; P <.001), as well as absence of collagen disease (OR, 95% CI, 0.23; 0.09-0.60; P =.003), mental illnesses other than depression or schizophrenia (OR, 0.50; 95% CI, 0.36-0.69; P <.001), ophthalmic surgery other than cataract surgery and laser-assisted in situ keratomileusis (OR, 0.41; 95% CI, 0.27-0.64; P <.001), and current (OR, 0.64; 95% CI, 0.54-0.77; P <.001) or past (OR, 0.45; 95% CI, 0.34-0.58; P <.001) contact lens use. Conclusions and Relevance: This study's findings suggest that crowdsourced research identified individuals with diagnosed and undiagnosed symptomatic dry eye and the associated risk factors. These findings could play a role in earlier prevention or more effective interventions for dry eye disease.

元の言語English
ジャーナルJAMA Ophthalmology
DOI
出版物ステータスAccepted/In press - 2019 1 1

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Odds Ratio
Eye Diseases
Depression
Seasonal Allergic Rhinitis
Contact Lenses
Sex Ratio
Smartphone
Crowdsourcing
Schizophrenia
Collagen Diseases
Laser In Situ Keratomileusis
Cataract
Life Style
Japan
Cross-Sectional Studies
Logistic Models
Smoking
Regression Analysis
Demography
Outcome Assessment (Health Care)

ASJC Scopus subject areas

  • Ophthalmology

これを引用

Inomata, T., Iwagami, M., Nakamura, M., Shiang, T., Yoshimura, Y., Fujimoto, K., ... Murakami, A. (受理済み/印刷中). Characteristics and Risk Factors Associated with Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application. JAMA Ophthalmology. https://doi.org/10.1001/jamaophthalmol.2019.4815

Characteristics and Risk Factors Associated with Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application. / Inomata, Takenori; Iwagami, Masao; Nakamura, Masahiro; Shiang, Tina; Yoshimura, Yusuke; Fujimoto, Keiichi; Okumura, Yuichi; Eguchi, Atsuko; Iwata, Nanami; Miura, Maria; Hori, Satoshi; Hiratsuka, Yoshimune; Uchino, Miki; Tsubota, Kazuo; Dana, Reza; Murakami, Akira.

:: JAMA Ophthalmology, 01.01.2019.

研究成果: Article

Inomata, T, Iwagami, M, Nakamura, M, Shiang, T, Yoshimura, Y, Fujimoto, K, Okumura, Y, Eguchi, A, Iwata, N, Miura, M, Hori, S, Hiratsuka, Y, Uchino, M, Tsubota, K, Dana, R & Murakami, A 2019, 'Characteristics and Risk Factors Associated with Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application', JAMA Ophthalmology. https://doi.org/10.1001/jamaophthalmol.2019.4815
Inomata, Takenori ; Iwagami, Masao ; Nakamura, Masahiro ; Shiang, Tina ; Yoshimura, Yusuke ; Fujimoto, Keiichi ; Okumura, Yuichi ; Eguchi, Atsuko ; Iwata, Nanami ; Miura, Maria ; Hori, Satoshi ; Hiratsuka, Yoshimune ; Uchino, Miki ; Tsubota, Kazuo ; Dana, Reza ; Murakami, Akira. / Characteristics and Risk Factors Associated with Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application. :: JAMA Ophthalmology. 2019.
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title = "Characteristics and Risk Factors Associated with Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application",
abstract = "Importance: The incidence of dry eye disease has increased; the potential for crowdsource data to help identify undiagnosed dry eye in symptomatic individuals remains unknown. Objective: To assess the characteristics and risk factors associated with diagnosed and undiagnosed symptomatic dry eye using the smartphone app DryEyeRhythm. Design, Setting, and Participants: A cross-sectional study using crowdsourced data was conducted including individuals in Japan who downloaded DryEyeRhythm and completed the entire questionnaire; duplicate users were excluded. DryEyeRhythm was released on November 2, 2016; the study was conducted from November 2, 2016, to January 12, 2018. Exposures: DryEyeRhythm data were collected on demographics, medical history, lifestyle, subjective symptoms, and disease-specific symptoms, using the Ocular Surface Disease Index (100-point scale; scores 0-12 indicate normal, healthy eyes; 13-22, mild dry eye; 23-32, moderate dry eye; 33-100, severe dry eye symptoms), and the Zung Self-Rating Depression Scale (total of 20 items, total score ranging from 20-80, with ≥40 highly suggestive of depression). Main Outcomes and Measures: Multivariate-adjusted logistic regression analysis was used to identify risk factors for symptomatic dry eye and to identify risk factors for undiagnosed symptomatic dry eye. Results: A total of 21394 records were identified in our database; 4454 users, included 899 participants (27.3{\%}) with diagnosed and 2395 participants (72.7{\%}) with undiagnosed symptomatic dry eye, completed all questionnaires and their data were analyzed. A total of 2972 participants (66.7{\%}) were women; mean (SD) age was 27.9 (12.6) years. The identified risk factors for symptomatic vs no symptomatic dry eye included younger age (odds ratio [OR], 0.99; 95{\%} CI, 0.987-0.999, P =.02), female sex (OR, 1.99; 95{\%} CI, 1.61-2.46; P <.001), pollinosis (termed hay fever on the questionnaire) (OR, 1.35; 95{\%} CI, 1.18-1.55; P <.001), depression (OR, 1.78; 95{\%} CI, 1.18-2.69; P =.006), mental illnesses other than depression or schizophrenia (OR, 1.87; 95{\%} CI, 1.24-2.82; P =.003), current contact lens use (OR, 1.27; 95{\%} CI, 1.09-1.48; P =.002), extended screen exposure (OR, 1.55; 95{\%} CI, 1.25-1.91; P <.001), and smoking (OR, 1.65; 95{\%} CI, 1.37-1.98; P <.001). The risk factors for undiagnosed vs diagnosed symptomatic dry eye included younger age (OR, 0.96; 95{\%} CI, 0.95-0.97; P <.001), male sex (OR, 0.55; 95{\%} CI, 0.42-0.72; P <.001), as well as absence of collagen disease (OR, 95{\%} CI, 0.23; 0.09-0.60; P =.003), mental illnesses other than depression or schizophrenia (OR, 0.50; 95{\%} CI, 0.36-0.69; P <.001), ophthalmic surgery other than cataract surgery and laser-assisted in situ keratomileusis (OR, 0.41; 95{\%} CI, 0.27-0.64; P <.001), and current (OR, 0.64; 95{\%} CI, 0.54-0.77; P <.001) or past (OR, 0.45; 95{\%} CI, 0.34-0.58; P <.001) contact lens use. Conclusions and Relevance: This study's findings suggest that crowdsourced research identified individuals with diagnosed and undiagnosed symptomatic dry eye and the associated risk factors. These findings could play a role in earlier prevention or more effective interventions for dry eye disease.",
author = "Takenori Inomata and Masao Iwagami and Masahiro Nakamura and Tina Shiang and Yusuke Yoshimura and Keiichi Fujimoto and Yuichi Okumura and Atsuko Eguchi and Nanami Iwata and Maria Miura and Satoshi Hori and Yoshimune Hiratsuka and Miki Uchino and Kazuo Tsubota and Reza Dana and Akira Murakami",
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journal = "JAMA Ophthalmology",
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T1 - Characteristics and Risk Factors Associated with Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application

AU - Inomata, Takenori

AU - Iwagami, Masao

AU - Nakamura, Masahiro

AU - Shiang, Tina

AU - Yoshimura, Yusuke

AU - Fujimoto, Keiichi

AU - Okumura, Yuichi

AU - Eguchi, Atsuko

AU - Iwata, Nanami

AU - Miura, Maria

AU - Hori, Satoshi

AU - Hiratsuka, Yoshimune

AU - Uchino, Miki

AU - Tsubota, Kazuo

AU - Dana, Reza

AU - Murakami, Akira

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Importance: The incidence of dry eye disease has increased; the potential for crowdsource data to help identify undiagnosed dry eye in symptomatic individuals remains unknown. Objective: To assess the characteristics and risk factors associated with diagnosed and undiagnosed symptomatic dry eye using the smartphone app DryEyeRhythm. Design, Setting, and Participants: A cross-sectional study using crowdsourced data was conducted including individuals in Japan who downloaded DryEyeRhythm and completed the entire questionnaire; duplicate users were excluded. DryEyeRhythm was released on November 2, 2016; the study was conducted from November 2, 2016, to January 12, 2018. Exposures: DryEyeRhythm data were collected on demographics, medical history, lifestyle, subjective symptoms, and disease-specific symptoms, using the Ocular Surface Disease Index (100-point scale; scores 0-12 indicate normal, healthy eyes; 13-22, mild dry eye; 23-32, moderate dry eye; 33-100, severe dry eye symptoms), and the Zung Self-Rating Depression Scale (total of 20 items, total score ranging from 20-80, with ≥40 highly suggestive of depression). Main Outcomes and Measures: Multivariate-adjusted logistic regression analysis was used to identify risk factors for symptomatic dry eye and to identify risk factors for undiagnosed symptomatic dry eye. Results: A total of 21394 records were identified in our database; 4454 users, included 899 participants (27.3%) with diagnosed and 2395 participants (72.7%) with undiagnosed symptomatic dry eye, completed all questionnaires and their data were analyzed. A total of 2972 participants (66.7%) were women; mean (SD) age was 27.9 (12.6) years. The identified risk factors for symptomatic vs no symptomatic dry eye included younger age (odds ratio [OR], 0.99; 95% CI, 0.987-0.999, P =.02), female sex (OR, 1.99; 95% CI, 1.61-2.46; P <.001), pollinosis (termed hay fever on the questionnaire) (OR, 1.35; 95% CI, 1.18-1.55; P <.001), depression (OR, 1.78; 95% CI, 1.18-2.69; P =.006), mental illnesses other than depression or schizophrenia (OR, 1.87; 95% CI, 1.24-2.82; P =.003), current contact lens use (OR, 1.27; 95% CI, 1.09-1.48; P =.002), extended screen exposure (OR, 1.55; 95% CI, 1.25-1.91; P <.001), and smoking (OR, 1.65; 95% CI, 1.37-1.98; P <.001). The risk factors for undiagnosed vs diagnosed symptomatic dry eye included younger age (OR, 0.96; 95% CI, 0.95-0.97; P <.001), male sex (OR, 0.55; 95% CI, 0.42-0.72; P <.001), as well as absence of collagen disease (OR, 95% CI, 0.23; 0.09-0.60; P =.003), mental illnesses other than depression or schizophrenia (OR, 0.50; 95% CI, 0.36-0.69; P <.001), ophthalmic surgery other than cataract surgery and laser-assisted in situ keratomileusis (OR, 0.41; 95% CI, 0.27-0.64; P <.001), and current (OR, 0.64; 95% CI, 0.54-0.77; P <.001) or past (OR, 0.45; 95% CI, 0.34-0.58; P <.001) contact lens use. Conclusions and Relevance: This study's findings suggest that crowdsourced research identified individuals with diagnosed and undiagnosed symptomatic dry eye and the associated risk factors. These findings could play a role in earlier prevention or more effective interventions for dry eye disease.

AB - Importance: The incidence of dry eye disease has increased; the potential for crowdsource data to help identify undiagnosed dry eye in symptomatic individuals remains unknown. Objective: To assess the characteristics and risk factors associated with diagnosed and undiagnosed symptomatic dry eye using the smartphone app DryEyeRhythm. Design, Setting, and Participants: A cross-sectional study using crowdsourced data was conducted including individuals in Japan who downloaded DryEyeRhythm and completed the entire questionnaire; duplicate users were excluded. DryEyeRhythm was released on November 2, 2016; the study was conducted from November 2, 2016, to January 12, 2018. Exposures: DryEyeRhythm data were collected on demographics, medical history, lifestyle, subjective symptoms, and disease-specific symptoms, using the Ocular Surface Disease Index (100-point scale; scores 0-12 indicate normal, healthy eyes; 13-22, mild dry eye; 23-32, moderate dry eye; 33-100, severe dry eye symptoms), and the Zung Self-Rating Depression Scale (total of 20 items, total score ranging from 20-80, with ≥40 highly suggestive of depression). Main Outcomes and Measures: Multivariate-adjusted logistic regression analysis was used to identify risk factors for symptomatic dry eye and to identify risk factors for undiagnosed symptomatic dry eye. Results: A total of 21394 records were identified in our database; 4454 users, included 899 participants (27.3%) with diagnosed and 2395 participants (72.7%) with undiagnosed symptomatic dry eye, completed all questionnaires and their data were analyzed. A total of 2972 participants (66.7%) were women; mean (SD) age was 27.9 (12.6) years. The identified risk factors for symptomatic vs no symptomatic dry eye included younger age (odds ratio [OR], 0.99; 95% CI, 0.987-0.999, P =.02), female sex (OR, 1.99; 95% CI, 1.61-2.46; P <.001), pollinosis (termed hay fever on the questionnaire) (OR, 1.35; 95% CI, 1.18-1.55; P <.001), depression (OR, 1.78; 95% CI, 1.18-2.69; P =.006), mental illnesses other than depression or schizophrenia (OR, 1.87; 95% CI, 1.24-2.82; P =.003), current contact lens use (OR, 1.27; 95% CI, 1.09-1.48; P =.002), extended screen exposure (OR, 1.55; 95% CI, 1.25-1.91; P <.001), and smoking (OR, 1.65; 95% CI, 1.37-1.98; P <.001). The risk factors for undiagnosed vs diagnosed symptomatic dry eye included younger age (OR, 0.96; 95% CI, 0.95-0.97; P <.001), male sex (OR, 0.55; 95% CI, 0.42-0.72; P <.001), as well as absence of collagen disease (OR, 95% CI, 0.23; 0.09-0.60; P =.003), mental illnesses other than depression or schizophrenia (OR, 0.50; 95% CI, 0.36-0.69; P <.001), ophthalmic surgery other than cataract surgery and laser-assisted in situ keratomileusis (OR, 0.41; 95% CI, 0.27-0.64; P <.001), and current (OR, 0.64; 95% CI, 0.54-0.77; P <.001) or past (OR, 0.45; 95% CI, 0.34-0.58; P <.001) contact lens use. Conclusions and Relevance: This study's findings suggest that crowdsourced research identified individuals with diagnosed and undiagnosed symptomatic dry eye and the associated risk factors. These findings could play a role in earlier prevention or more effective interventions for dry eye disease.

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