TY - JOUR
T1 - Stratification of individual symptoms of contact lens-associated dry eye using the iphone app dryeyerhythm
T2 - Crowdsourced cross-sectional study
AU - Inomata, Takenori
AU - Nakamura, Masahiro
AU - Iwagami, Masao
AU - Midorikawa-Inomata, Akie
AU - Sung, Jaemyoung
AU - Fujimoto, Keiichi
AU - Okumura, Yuichi
AU - Eguchi, Atsuko
AU - Iwata, Nanami
AU - Miura, Maria
AU - Fujio, Kenta
AU - Nagino, Ken
AU - Hori, Satoshi
AU - Tsubota, Kazuo
AU - Dana, Reza
AU - Murakami, Akira
N1 - Funding Information:
Special thanks to Ohako Inc for developing the DryEyeRhythm app, and Tina Shiang, Yosuke Yoshimura, Yoshimune Hiratsuka, and Miki Uchino for the initial development of the app. This study was supported by Seed Co, Ltd; Alcon Japan, Ltd; Rohto Pharmaceutical Co, Ltd; Hoya Corporation; and Wakamoto Co, Ltd. The sponsors had no role in the design or conduct of this research.
Publisher Copyright:
© Takenori Inomata, Masahiro Nakamura, Masao Iwagami, Akie Midorikawa-Inomata, Jaemyoung Sung, Keiichi Fujimoto, Yuichi Okumura, Atsuko Eguchi, Nanami Iwata, Maria Miura, Kenta Fujio, Ken Nagino, Satoshi Hori, Kazuo Tsubota, Reza Dana, Akira Murakami. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 26.06.2020. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
PY - 2020/6
Y1 - 2020/6
N2 - Background: Discontinuation of contact lens use is mainly caused by contact lens-associated dry eye. It is crucial to delineate contact lens-associated dry eye's multifaceted nature to tailor treatment to each patient's individual needs for future personalized medicine. Objective: This paper aims to quantify and stratify individual subjective symptoms of contact lens-associated dry eye and clarify its risk factors for future personalized medicine using the smartphone app DryEyeRhythm (Juntendo University). Methods: This cross-sectional study included iPhone (Apple Inc) users in Japan who downloaded DryEyeRhythm. DryEyeRhythm was used to collect medical big data related to contact lens-associated dry eye between November 2016 and January 2018. The main outcome measure was the incidence of contact lens-associated dry eye. Univariate and multivariate adjusted odds ratios of risk factors for contact lens-associated dry eye were determined by logistic regression analyses. The t-distributed Stochastic Neighbor Embedding algorithm was used to depict the stratification of subjective symptoms of contact lens-associated dry eye. Results: The records of 4454 individuals (median age 27.9 years, SD 12.6), including 2972 female participants (66.73%), who completed all surveys were included in this study. Among the included participants, 1844 (41.40%) were using contact lenses, and among those who used contact lenses, 1447 (78.47%) had contact lens-associated dry eye. Multivariate adjusted odds ratios of risk factors for contact lens-associated dry eye were as follows: younger age, 0.98 (95% CI 0.96-0.99); female sex, 1.53 (95% CI 1.05-2.24); hay fever, 1.38 (95% CI 1.10-1.74); mental illness other than depression or schizophrenia, 2.51 (95% CI 1.13-5.57); past diagnosis of dry eye, 2.21 (95% CI 1.63-2.99); extended screen exposure time >8 hours, 1.61 (95% CI 1.13-2.28); and smoking, 2.07 (95% CI 1.49-2.88). The t-distributed Stochastic Neighbor Embedding analysis visualized and stratified 14 groups based on the subjective symptoms of contact lens-associated dry eye. Conclusions: This study identified and stratified individuals with contact lens-associated dry eye and its risk factors. Data on subjective symptoms of contact lens-associated dry eye could be used for prospective prevention of contact lens-associated dry eye progression.
AB - Background: Discontinuation of contact lens use is mainly caused by contact lens-associated dry eye. It is crucial to delineate contact lens-associated dry eye's multifaceted nature to tailor treatment to each patient's individual needs for future personalized medicine. Objective: This paper aims to quantify and stratify individual subjective symptoms of contact lens-associated dry eye and clarify its risk factors for future personalized medicine using the smartphone app DryEyeRhythm (Juntendo University). Methods: This cross-sectional study included iPhone (Apple Inc) users in Japan who downloaded DryEyeRhythm. DryEyeRhythm was used to collect medical big data related to contact lens-associated dry eye between November 2016 and January 2018. The main outcome measure was the incidence of contact lens-associated dry eye. Univariate and multivariate adjusted odds ratios of risk factors for contact lens-associated dry eye were determined by logistic regression analyses. The t-distributed Stochastic Neighbor Embedding algorithm was used to depict the stratification of subjective symptoms of contact lens-associated dry eye. Results: The records of 4454 individuals (median age 27.9 years, SD 12.6), including 2972 female participants (66.73%), who completed all surveys were included in this study. Among the included participants, 1844 (41.40%) were using contact lenses, and among those who used contact lenses, 1447 (78.47%) had contact lens-associated dry eye. Multivariate adjusted odds ratios of risk factors for contact lens-associated dry eye were as follows: younger age, 0.98 (95% CI 0.96-0.99); female sex, 1.53 (95% CI 1.05-2.24); hay fever, 1.38 (95% CI 1.10-1.74); mental illness other than depression or schizophrenia, 2.51 (95% CI 1.13-5.57); past diagnosis of dry eye, 2.21 (95% CI 1.63-2.99); extended screen exposure time >8 hours, 1.61 (95% CI 1.13-2.28); and smoking, 2.07 (95% CI 1.49-2.88). The t-distributed Stochastic Neighbor Embedding analysis visualized and stratified 14 groups based on the subjective symptoms of contact lens-associated dry eye. Conclusions: This study identified and stratified individuals with contact lens-associated dry eye and its risk factors. Data on subjective symptoms of contact lens-associated dry eye could be used for prospective prevention of contact lens-associated dry eye progression.
KW - Contact lens-associated dry eye
KW - Dry eye
KW - DryEyeRhythm
KW - Mobile health
KW - Mobile phone
KW - ResearchKit
KW - Risk factors
KW - Smartphone app
KW - Stratification
KW - Subjective symptoms
UR - http://www.scopus.com/inward/record.url?scp=85087182578&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087182578&partnerID=8YFLogxK
U2 - 10.2196/18996
DO - 10.2196/18996
M3 - Article
C2 - 32589162
AN - SCOPUS:85087182578
SN - 1439-4456
VL - 22
JO - Journal of medical Internet research
JF - Journal of medical Internet research
IS - 6
M1 - e18996
ER -
