Pharmacological Myopia Control Influence on Quality of Life and Psyche among Adolescents

Michalski, Andrzej; Rogaczewska, Małgorzata; Maleszka-Kurpiel, Magdalena; Stopa, Marcin

doi:10.3390/jcm9123920

Cited by 6 publications

(6 citation statements)

References 25 publications

(47 reference statements)

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“…Myopia is prevalent in the youth of many developed countries [ 1 , 2 , 3 , 4 ]. According to the Ministry of Health and Welfare of Taiwan, more than 80% of all school children develop myopia by the end of high school in Taiwan [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…According to the Ministry of Health and Welfare of Taiwan, more than 80% of all school children develop myopia by the end of high school in Taiwan [ 5 ]. Since the increase in myopia cases is a worldwide trend, there are many effective mechanisms to control myopia progression such as atropine [ 4 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ], orthokeratology [ 19 , 20 ], experimental bifocal/multifocal soft contact lenses (CLs) [ 21 , 22 ], commercial bifocal or multifocal soft CLs dedicated to presbyopia corrections but used for myopia control [ 23 , 24 ], and commercial multifocal CLs specially dedicated to myopia control [ 25 , 26 ]. Atropine, an anticholinergic blocking agent, can temporarily paralyze the smooth ciliary muscle causing cycloplegia.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the Effect of Topical Atropine Use for Myopia Control on Intraocular Pressure by Using Machine Learning

Chen

Jhou

et al. 2020

JCM

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Atropine is a common treatment used in children with myopia. However, it probably affects intraocular pressure (IOP) under some conditions. Our research aims to analyze clinical data by using machine learning models to evaluate the effect of 19 important factors on intraocular pressure (IOP) in children with myopia treated with topical atropine. The data is collected on 1545 eyes with spherical equivalent (SE) less than −10.0 diopters (D) treated with atropine for myopia control. Four machine learning models, namely multivariate adaptive regression splines (MARS), classification and regression tree (CART), random forest (RF), and eXtreme gradient boosting (XGBoost), were used. Linear regression (LR) was used for benchmarking. The 10-fold cross-validation method was used to estimate the performance of the five methods. The main outcome measure is that the 19 important factors associated with atropine use that may affect IOP are evaluated using machine learning models. Endpoint IOP at the last visit was set as the target variable. The results show that the top five significant variables, including baseline IOP, recruitment duration, age, total duration and previous cumulative dosage, were identified as most significant for evaluating the effect of atropine use for treating myopia on IOP. We can conclude that the use of machine learning methods to evaluate factors that affect IOP in children with myopia treated with topical atropine is promising. XGBoost is the best predictive model, and baseline IOP is the most accurate predictive factor for endpoint IOP among all machine learning approaches.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluating the Effect of Topical Atropine Use for Myopia Control on Intraocular Pressure by Using Machine Learning

Chen

Jhou

et al. 2020

JCM

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“…Among the revelations was the emergence of bespoke quality-of-life scales in four studies, a testament to the evolving landscape of pediatric refractive error research. 17 , 18 , 19 , 20 This pivot towards customization underscores an acute awareness of the nuanced impacts of refractive errors in young lives. Our synthesis, detailed in Table 1 , Table 2 , Table 3 , Table 4 , offers a panoramic view of these 16 assessments, tracing their utility in measuring children's refractive error-related quality of life.…”

Section: Resultsmentioning

confidence: 99%

“…Both of these tools can provide valuable insights into the patient's experience. 19 , 29 , 62 The LVP-FVQ is a specific questionnaire that measures functional vision, including color perception. In the intricate landscape of refractive error impacts, the judicious selection of a measurement tool, each with its distinct lens on the multifaceted aspects of quality of life, is crucial.…”

Section: Discussionmentioning

confidence: 99%

Health-related quality of life measurements in children and adolescents with refractive errors: A scoping review

Wu,

Yi,

Zhang

et al. 2024

Advances in Ophthalmology Practice and Research

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“…However, atropine may also cause side effects, such as blurred vision, increased sensitivity to light, and a dry mouth. Additionally, the contraindication of topical atropine, which possibly increases intraocular pressure (IOP), is also a concern for myopic control in children [9][10][11][12][13]. Regular monitoring of visual acuity, refraction, and IOP is essential for assessing treatment effectiveness and ensuring optimal outcomes.…”

Section: Introductionmentioning

confidence: 99%

Identifying and Exploring the Impact Factors for Intraocular Pressure Prediction in Myopic Children with Atropine Control Utilizing Multivariate Adaptive Regression Splines

Wu,

Chen,

Liu

et al. 2024

JPM

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Purpose: The treatment of childhood myopia often involves the use of topical atropine, which has been demonstrated to be effective in decelerating the progression of myopia. It is crucial to monitor intraocular pressure (IOP) to ensure the safety of topical atropine. This study aims to identify the optimal machine learning IOP-monitoring module and establish a precise baseline IOP as a clinical safety reference for atropine medication. Methods: Data from 1545 eyes of 1171 children receiving atropine for myopia were retrospectively analyzed. Nineteen variables including patient demographics, medical history, refractive error, and IOP measurements were considered. The data were analyzed using a multivariate adaptive regression spline (MARS) model to analyze the impact of different factors on the End IOP. Results: The MARS model identified age, baseline IOP, End Spherical, duration of previous atropine treatment, and duration of current atropine treatment as the five most significant factors influencing the End IOP. The outcomes revealed that the baseline IOP had the most significant effect on final IOP, exhibiting a notable knot at 14 mmHg. When the baseline IOP was equal to or exceeded 14 mmHg, there was a positive correlation between atropine use and End IOP, suggesting that atropine may increase the End IOP in children with a baseline IOP greater than 14 mmHg. Conclusions: MARS model demonstrates a better ability to capture nonlinearity than classic multiple linear regression for predicting End IOP. It is crucial to acknowledge that administrating atropine may elevate intraocular pressure when the baseline IOP exceeds 14 mmHg. These findings offer valuable insights into factors affecting IOP in children undergoing atropine treatment for myopia, enabling clinicians to make informed decisions regarding treatment options.

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Pharmacological Myopia Control Influence on Quality of Life and Psyche among Adolescents

Cited by 6 publications

References 25 publications

Evaluating the Effect of Topical Atropine Use for Myopia Control on Intraocular Pressure by Using Machine Learning

Evaluating the Effect of Topical Atropine Use for Myopia Control on Intraocular Pressure by Using Machine Learning

Health-related quality of life measurements in children and adolescents with refractive errors: A scoping review

Identifying and Exploring the Impact Factors for Intraocular Pressure Prediction in Myopic Children with Atropine Control Utilizing Multivariate Adaptive Regression Splines

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