Design and Pilot data of the high myopia registration study: Shanghai Child and Adolescent Large‐scale Eye Study (SCALE‐HM)

Background/aimsTo apply deep learning technology to develop an artificial intelligence (AI) system that can identify vision-threatening conditions in high myopia patients based on optical coherence tomography (OCT) macular images.MethodsIn this cross-sectional, prospective study, a total of 5505 qualified OCT macular images obtained from 1048 high myopia patients admitted to Zhongshan Ophthalmic Centre (ZOC) from 2012 to 2017 were selected for the development of the AI system. The independent test dataset included 412 images obtained from 91 high myopia patients recruited at ZOC from January 2019 to May 2019. We adopted the InceptionResnetV2 architecture to train four independent convolutional neural network (CNN) models to identify the following four vision-threatening conditions in high myopia: retinoschisis, macular hole, retinal detachment and pathological myopic choroidal neovascularisation. Focal Loss was used to address class imbalance, and optimal operating thresholds were determined according to the Youden Index.ResultsIn the independent test dataset, the areas under the receiver operating characteristic curves were high for all conditions (0.961 to 0.999). Our AI system achieved sensitivities equal to or even better than those of retina specialists as well as high specificities (greater than 90%). Moreover, our AI system provided a transparent and interpretable diagnosis with heatmaps.ConclusionsWe used OCT macular images for the development of CNN models to identify vision-threatening conditions in high myopia patients. Our models achieved reliable sensitivities and high specificities, comparable to those of retina specialists and may be applied for large-scale high myopia screening and patient follow-up.

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Levy, F., Hay, D.A., McStephen, M., Wood, C. & Waldman, I. (1997). ADHD: A category or a continuum ? Genetic analysis of a large scale twin study. Journal of the American Academy of Child and Adolescent Psychiatry, 36, 737-744.

Journal of Attention Disorders ◽

10.1177/108705479700200206 ◽

1997 ◽

Vol 2 (2) ◽

pp. 129-129

Author(s):

Sam Goldstein

Keyword(s):

Genetic Analysis ◽

American Academy ◽

Adolescent Psychiatry ◽

Twin Study ◽

Large Scale ◽

Child And Adolescent ◽

Child And Adolescent Psychiatry

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The National Survey of Mental Health and Wellbeing: The Child and Adolescent Component

Australian & New Zealand Journal of Psychiatry ◽

10.1080/j.1440-1614.2000.00729.x ◽

2000 ◽

Vol 34 (2) ◽

pp. 214-220 ◽

Cited By ~ 63

Author(s):

Michael G. Sawyer ◽

Robert J. Kosky ◽

Brian W. Graetz ◽

Fiona Arney ◽

Stephen R. Zubrick ◽

...

Keyword(s):

Mental Health ◽

National Survey ◽

Large Scale ◽

Adolescent Mental Health ◽

Child And Adolescent ◽

Epidemiological Studies ◽

Quality Data ◽

High Quality Data ◽

Health And Wellbeing ◽

Key Issues

Objective: This paper describes the Child and Adolescent Component of the National Survey of Mental Health and Wellbeing. Method: The aims of the study, critical decisions in planning for the study, progress to date and key issues which influenced the course of the study are described. Results: The Child and Adolescent Component of the National Survey of Mental Health and Wellbeing is the largest study of child and adolescent mental health conducted in Australia and one of the few national studies to be conducted in the world. Results from the study will provide the first national picture of child and adolescent mental health in Australia. Conclusions: Large-scale epidemiological studies have the potential to provide considerable information about the mental health of children and adolescents. However, having a clear set of aims, ensuring that the scope of the study remains within manageable proportions and paying careful attention to the details of fieldwork are essential to ensure that high-quality data is obtained in such studies.

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EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics

International Journal of Epidemiology ◽

10.1093/ije/dyz244 ◽

2020 ◽

Vol 49 (4) ◽

pp. 1075-1081

Author(s):

Jussi Ekholm ◽

Pauli Ohukainen ◽

Antti J Kangas ◽

Johannes Kettunen ◽

Qin Wang ◽

...

Keyword(s):

Web Application ◽

Large Scale ◽

Source Code ◽

Statistical Analyses ◽

Data Driven ◽

Graphical Interface ◽

Self Organizing Maps ◽

Web Browser ◽

Pilot Data ◽

Molecular Measures

Abstract Motivation An intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming. Implementation EpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser. General features Standard epidemiological analyses and self-organizing maps for data-driven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N >10 000). Availability The software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal].

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Yokoyama procedure for esotropia associated with high myopia: real‐world data from a large‐scale multicentre analysis

Acta Ophthalmologica ◽

10.1111/aos.14808 ◽

2021 ◽

Author(s):

Bettina Wabbels ◽

Julia Fricke ◽

Michael Schittkowski ◽

Michael Gräf ◽

Birgit Lorenz ◽

...

Keyword(s):

Real World ◽

High Myopia ◽

Large Scale ◽

Real World Data ◽

World Data

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Free flight is in the future: large-scale controller pilot data link communications emulation testbed

IEEE Aerospace and Electronic Systems Magazine ◽

10.1109/maes.2003.1232156 ◽

2003 ◽

Vol 18 (9) ◽

pp. 23-27 ◽

Cited By ~ 6

Author(s):

T. Mulkerin

Keyword(s):

Large Scale ◽

Free Flight ◽

Data Link ◽

Pilot Data ◽

The Future

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Prevalence of myopia and high myopia, and the association with education: Shanghai Child and Adolescent Large-scale Eye Study (SCALE): a cross-sectional study

BMJ Open ◽

10.1136/bmjopen-2020-048450 ◽

2021 ◽

Vol 11 (12) ◽

pp. e048450

Author(s):

Xiangui He ◽

Padmaja Sankaridurg ◽

Shuyu Xiong ◽

Wayne Li ◽

Thomas Naduvilath ◽

...

Keyword(s):

High Myopia ◽

Large Scale ◽

Public Awareness ◽

Cross Sectional Study ◽

Sectional Study ◽

Cross Sectional ◽

Factors Associated ◽

Education And Health ◽

School Based ◽

The Impact

ObjectivesTo report on: (a) overall myopia and high myopia prevalence, and (b) the impact of education on the spherical equivalent refractive error in children across Shanghai.DesignCross-sectional study.SettingAcross all 17 districts of Shanghai.Participants910 245 children aged 4–14 years from a school-based survey conducted between 2012 and 2013.Main outcome measuresData of children with non-cycloplegic autorefraction, visual acuity assessment and questionnaire were analysed (67%, n=6 06 476). Prevalence of myopia (≤−1.0 D) and high myopia (≤−5.0 D) was determined. We used a regression discontinuity design to determine the impact of school entry cut-off date (1 September) by comparing refractive errors at each age, for children born pre-September to post-1 September, and performed a multivariate analysis to explore risk factors associated with myopia. Data analysis was performed in 2017–2018.ResultsPrevalence rates of myopia and high myopia were 32.9% (95% CI: 32.8% to 33.1%) and 4.2% (95% CI: 4.1% to 4.2%), respectively. From 6 years of age onwards, children born pre-September were more myopic compared with those born post-1 September (ahead in school by 1 year, discontinuity at 6 years: −0.19 D (95% CI: −0.09 to −0.30 D); 14 years: −0.67 D (95% CI: −0.21 to −1.14 D)).ConclusionsOur findings suggest that myopia is associated with education, that is primarily focused on near-based activities. Efforts to reduce the burden should be directed to public awareness, reform of education and health systems.

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The role of mental health symptomology and quality of life in predicting referrals to special child and adolescent mental health services

BMC Psychiatry ◽

10.1186/s12888-021-03364-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yeosun Yoon ◽

Jessica Deighton ◽

Alice Wickersham ◽

Julian Edbrooke-Childs ◽

David Osborn ◽

...

Keyword(s):

Quality Of Life ◽

Mental Health ◽

Mental Health Services ◽

Health Services ◽

Confidence Interval ◽

Large Scale ◽

Mental Health Problems ◽

Adolescent Mental Health ◽

Child And Adolescent

Abstract Background Children and adolescents’ mental health problems have been largely assessed with conventional symptom scales, for example, Strengths and Difficulties Questionnaire (SDQ) given that it is one of the mostly widely used measures in specialist Child and Adolescent Mental Health Services (CAMHS). However, this emphasis on symptom scales might have missed some important features of the mental health challenges that children and young people experience including day to day functioning and life satisfaction aspect (i.e. qualify of life). Method The study examined longitudinal association between a young person’s self-perceptions of quality of life and mental health difficulties and referral to specialist CAMHS service using a population cohort study (Targeted Mental Health in Schools service data) nested within a large-scale linkage between school (National Pupil Data base) and child mental health service administrative data (South London and Maudsley NHS Foundation Trust children and adolescent mental health services health records). Cox proportional hazard regression to estimate crude and adjusted hazard ratios (HRs) for the association between participant psychopathology, and incidence of CAMHS referral. Results Pupils experiencing more behavioural difficulties, had an increased incidence of CAMHS referral (adjusted hazard ratio 1.1, 95% confidence interval 1.0–1.2). However, pupils who reported higher health related quality of life had a lower incidence of CAMHS referral over the follow-up period (adjusted hazard hario 0.94, 95% confidence interval 0.9–0.98). Conclusion Children and young people’s perception of their quality of life should be considered at the stages of a clinical needs assessment.

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