Machine learning‐based nomogram to predict poor response to overnight orthokeratology in Chinese myopic children: A multicentre, retrospective study

Acta Ophthalmologica, Год журнала: 2024, Номер unknown

Опубликована: Март 22, 2024

Abstract Purpose To develop and validate an effective nomogram for predicting poor response to orthokeratology. Methods Myopic children (aged 8–15 years) treated with orthokeratology between February 2018 January 2022 were screened in four hospitals of different tiers (i.e. municipal provincial) China. Potential predictors included 32 baseline clinical variables. Nomogram the outcome (1‐year axial elongation ≥0.20 mm: response; <0.20 good response) was computed from a logistic regression model least absolute shrinkage selection operator. The data First Affiliated Hospital Chengdu Medical College randomly assigned (7:3) training validation cohorts. An external cohort three independent multicentre used test. Model performance assessed by discrimination (the area under curve, AUC), calibration (calibration plots) utility (decision curve analysis). Results Between March 2023, 1183 eligible subjects College, then divided into ( n = 831) 352) A total 405 cohort. Predictors age, spherical equivalent, length, pupil diameter, surface asymmetry index parental myopia p < 0.05). This demonstrated excellent calibration, net benefit discrimination, AUC 0.871 (95% CI 0.847–0.894), 0.863 (0.826–0.901) 0.817 (0.777–0.857) training, cohorts, respectively. online calculator generated free access http://39.96.75.172:8182/#/nomogram ). Conclusion provides accurate individual prediction overnight Chinese myopic children.

Язык: Английский

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Development and evaluation of a deep neural network model for orthokeratology lens fitting

Ophthalmic and Physiological Optics, Год журнала: 2024, Номер 44(6), С. 1224 - 1236

Опубликована: Июль 9, 2024

Abstract Purpose To optimise the precision and efficacy of orthokeratology, this investigation evaluated a deep neural network (DNN) model for lens fitting. The objective was to refine standardisation fitting procedures curtail subjective evaluations, thereby augmenting patient safety in context increasing global myopia. Methods A retrospective study successful orthokeratology treatment conducted on 266 patients, with 449 eyes being analysed. DNN an 80%–20% training‐validation split predicted parameters (curvature, power diameter) using corneal topography refractive indices. featured two hidden layers precision. Results achieved mean absolute errors 0.21 D alignment curvature (AC), 0.19 target (TP) 0.02 mm diameter (LD), R 2 values 0.97, 0.95 0.91, respectively. Accuracy decreased myopia less than 1.00 D, astigmatism exceeding 2.00 curvatures >45.00 D. Approximately, 2% cases unique physiological characteristics showed notable prediction variances. Conclusion While exhibiting high accuracy, model's limitations specifying myopia, cylinder highlight need algorithmic refinement clinical validation practice.

Язык: Английский

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Artificial intelligence in myopia in children: current trends and future directions

Current Opinion in Ophthalmology, Год журнала: 2024, Номер 35(6), С. 463 - 471

Опубликована: Авг. 26, 2024

Myopia is one of the major causes visual impairment globally, with myopia and its complications thus placing a heavy healthcare economic burden. With most cases developing during childhood, interventions to slow progression are effective when implemented early. To address this public health challenge, artificial intelligence has emerged as potential solution in childhood management.

Язык: Английский

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Sleep Quality is Associated with Axial Length Elongation in Myopic Children Receiving Orthokeratology: A Retrospective Study

Nature and Science of Sleep, Год журнала: 2023, Номер Volume 15, С. 993 - 1001

Опубликована: Ноя. 1, 2023

To identify potential demographic and lifestyle factors associated with progression of myopia orthokeratology (ortho-k) treatment via follow-up axial length (AL).In this retrospective observational study, demographics, ocular parameters, near-work distance, outdoor activities, sleep quality were analyzed in 134 children aged 8~15 years using ortho-k a for one year.Compared the slow group, participants fast group younger age (10.55 ±1.70 vs 9.90 ±1.18 years, P = 0.009), demonstrated higher spherical equivalent (SE) value (-2.52 ±0.63 diopters (D) -3.05 ±0.89 D, < 0.001), shorter distance (P 0.010), poorer (Pittsburgh index [PSQI], 4.79 ±1.29 3.81 ±1.38, 0.001) one-year follow-up. Furthermore, multivariate linear regression analyses showed that baseline (B =-0.020, 0.020), SE 0.0517, total PSQI (B=0.026, elongation. Advanced logistic average 0.034), 0.023), 0.003) elongation.Sleep is key elongation after year. Further studies are required to confirm observation expand its practical applications.

Язык: Английский

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Artificial intelligence in paediatrics: Current events and challenges

Anales de Pediatría (English Edition), Год журнала: 2024, Номер 100(3), С. 195 - 201

Опубликована: Март 1, 2024

This article examines the use of artificial intelligence (AI) in field paediatric care within framework 7P medicine model (Predictive, Preventive, Personalized, Precise, Participatory, Peripheral and Polyprofessional). It highlights various applications AI diagnosis, treatment management diseases as well role prevention efficient health resources resulting impact on sustainability public systems. Successful cases application setting are presented, placing emphasis need to move towards a model. Artificial is revolutionizing society at large has great potential for significantly improving care. Se examina el uso de la inteligencia (IA) en campo atención salud pediátrica dentro del marco "Medicina las 7P" (Predictiva, Preventiva, Personalizada, Precisa, Participativa, Periférica y Poliprofesional). destacan diversas aplicaciones IA diagnóstico, tratamiento control enfermedades pediátricas, así como su papel prevención gestión eficiente los recursos médicos con repercusión sostenibilidad sistemas públicos salud. presentan casos éxito aplicación ámbito pediátrico se hace un gran énfasis necesidad caminar hacia Medicina 7P. La está revolucionando sociedad general ofreciendo potencial para mejorar significativamente cuidado pediatría.

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