ABSTRACT
PURPOSE: To evaluate the transancestry portability of current myopia polygenic risk scores (PRSs) to predict high myopia (HM) and myopic macular degeneration (MMD) in an Asian population. DESIGN: Population-based study. PARTICIPANTS: A total of 5894 adults (2141 Chinese, 1913 Indian, and 1840 Malay) from the Singapore Epidemiology of Eye Diseases study were included in the analysis. The mean ± standard deviation age was 57.05 ± 9.31 years. A total of 361 adults had a diagnosis of HM (spherical equivalent [SE] < -5.00 diopters [D]) from refraction measurements, 240 individuals had a diagnosis of MMD graded by the International Photographic Classification and Grading System for Myopic Maculopathy criteria from fundus photographs, and 3774 individuals were control participants without myopia (SE > -0.5 D). METHODS: The PRS, derived from 687 289 HapMap3 single nucleotide polymorphisms (SNPs) from the largest genome-wide association study of myopia in Europeans to date (n = 260 974), was assessed on its ability to predict patients with HM and MMD versus control participants. MAIN OUTCOME MEASURES: The primary outcomes were the area under the receiver operating characteristic curve (AUC) to predict HM and MMD. RESULTS: The PRS had an AUC of 0.73 (95% confidence interval [CI], 0.70-0.75) for HM and 0.66 (95% CI, 0.63-0.70) for MMD versus no myopia. The inclusion of the PRS with other predictors (age, sex, educational attainment [EA], and ancestry; age-by-ancestry, sex-by-ancestry, and EA-by-ancestry interactions; and 20 genotypic principal components) increased the AUC to 0.84 (95% CI, 0.82-0.86) for HM and 0.79 (95% CI, 0.76-0.82) for MMD. Individuals with a PRS in the top 5% showed up to a 4.66 (95% CI, 3.34-6.42) times higher risk of HM developing and up to a 3.43 (95% CI, 2.27-5.05) times higher risk of MMD developing compared with the remaining 95% of individuals. CONCLUSIONS: The PRS is a good predictor for HM and facilitates the identification of high-risk children to prevent myopia progression to HM. In addition, the PRS also predicts MMD and helps to identify high-risk adults with myopia who require closer monitoring for myopia-related complications.
Subject(s)
Eye Diseases , Macular Degeneration , Myopia, Degenerative , Aged , Eye Diseases/complications , Genome-Wide Association Study , Humans , Macular Degeneration/diagnosis , Macular Degeneration/epidemiology , Macular Degeneration/genetics , Middle Aged , Myopia, Degenerative/complications , Myopia, Degenerative/diagnosis , Myopia, Degenerative/genetics , Risk Factors , Singapore/epidemiologyABSTRACT
PURPOSE OF REVIEW: The application of artificial intelligence (AI) in medicine and ophthalmology has experienced exponential breakthroughs in recent years in diagnosis, prognosis, and aiding clinical decision-making. The use of digital data has also heralded the need for privacy-preserving technology to protect patient confidentiality and to guard against threats such as adversarial attacks. Hence, this review aims to outline novel AI-based systems for ophthalmology use, privacy-preserving measures, potential challenges, and future directions of each. RECENT FINDINGS: Several key AI algorithms used to improve disease detection and outcomes include: Data-driven, imagedriven, natural language processing (NLP)-driven, genomics-driven, and multimodality algorithms. However, deep learning systems are susceptible to adversarial attacks, and use of data for training models is associated with privacy concerns. Several data protection methods address these concerns in the form of blockchain technology, federated learning, and generative adversarial networks. SUMMARY: AI-applications have vast potential to meet many eyecare needs, consequently reducing burden on scarce healthcare resources. A pertinent challenge would be to maintain data privacy and confidentiality while supporting AI endeavors, where data protection methods would need to rapidly evolve with AI technology needs. Ultimately, for AI to succeed in medicine and ophthalmology, a balance would need to be found between innovation and privacy.
Subject(s)
Artificial Intelligence , Ophthalmology , Humans , Natural Language Processing , Privacy , TechnologyABSTRACT
PURPOSE: To evaluate associations of dietary factors with myopia, spherical equivalent refractive error (SE) and axial length (AL) in children at age 9 from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort. METHODS: We included 467 multi-ethnic children (933 eyes) who participated in the GUSTO prospective birth cohort and were delivered in two major hospitals in Singapore (2009-2010). At the 9-year visit, we assessed the 6-year incidence of myopia (between ages 3 to 9), cycloplegic SE and AL in children without myopia (SE ≤ -0.5 D in either eye) at the 3-year visit. Using a validated 112-item food frequency questionnaire, parents reported each child's average daily intake of dietary factors (nutrients and food groups) in the past month. Paired eyes were analysed using Generalised Estimating Equations with multivariable logistic or linear regression. Bonferroni corrections were applied, correcting for multiple comparisons between the 13 nutrients (p < 0.004) or 8 food groups (p < 0.006) and each outcome. RESULTS: In children aged 9 years (51.0% boys; 56.3% Chinese), the 6-year incidence of myopia was 35.5%. Overall, the mean (SD) SE and AL were -0.3 (1.7) D and 23.4 (1.0) mm, respectively. In multivariable regression, macronutrients or micronutrients were not associated with incident myopia (p ≥ 0.004 for all), adjusting for total energy, gender, ethnicity, time outdoors, near-work and the number of myopic parents (additionally child's height for outcome AL). Similarly, all food groups (including refined grains, sugar-sweetened beverages, protein foods, fruits and vegetables) were not associated with incident myopia (p ≥ 0.006 for all). Additionally, none of the nutrients (p ≥ 0.004 for all) or food groups (p ≥ 0.006 for all) were associated with SE or AL. CONCLUSIONS: Our study findings of no significant association between specific nutrients or food groups and incident myopia or SE or AL suggest that diet may not be associated with myopia in children aged 9 years. Well-conducted prospective studies in other populations may clarify the association.
Subject(s)
Myopia , Refraction, Ocular , Child , Child, Preschool , Eating , Female , Humans , Male , Myopia/epidemiology , Myopia/etiology , Prospective Studies , Risk Factors , Singapore/epidemiologyABSTRACT
PURPOSE OF REVIEW: Artificial intelligence (AI) is the fourth industrial revolution in mankind's history. Natural language processing (NLP) is a type of AI that transforms human language, to one that computers can interpret and process. NLP is still in the formative stages of development in healthcare, with promising applications and potential challenges in its applications. This review provides an overview of AI-based NLP, its applications in healthcare and ophthalmology, next-generation use case, as well as potential challenges in deployment. RECENT FINDINGS: The integration of AI-based NLP systems into existing clinical care shows considerable promise in disease screening, risk stratification, and treatment monitoring, amongst others. Stakeholder collaboration, greater public acceptance, and advancing technologies will continue to shape the NLP landscape in healthcare and ophthalmology. SUMMARY: Healthcare has always endeavored to be patient centric and personalized. For AI-based NLP systems to become an eventual reality in larger-scale applications, it is pertinent for key stakeholders to collaborate and address potential challenges in application. Ultimately, these would enable more equitable and generalizable use of NLP systems for the betterment of healthcare and society.
Subject(s)
Deep Learning , Natural Language Processing , Ophthalmology , Artificial Intelligence/trends , Deep Learning/trends , Delivery of Health Care/trends , Forecasting , Humans , Ophthalmology/trendsABSTRACT
PURPOSE OF REVIEW: Myopia is one of the leading causes of visual impairment, with a projected increase in prevalence globally. One potential approach to address myopia and its complications is early detection and treatment. However, current healthcare systems may not be able to cope with the growing burden. Digital technological solutions such as artificial intelligence (AI) have emerged as a potential adjunct for myopia management. RECENT FINDINGS: There are currently four significant domains of AI in myopia, including machine learning (ML), deep learning (DL), genetics and natural language processing (NLP). ML has been demonstrated to be a useful adjunctive for myopia prediction and biometry for cataract surgery in highly myopic individuals. DL techniques, particularly convoluted neural networks, have been applied to various image-related diagnostic and predictive solutions. Applications of AI in genomics and NLP appear to be at a nascent stage. SUMMARY: Current AI research is mainly focused on disease classification and prediction in myopia. Through greater collaborative research, we envision AI will play an increasingly critical role in big data analysis by aggregating a greater variety of parameters including genomics and environmental factors. This may enable the development of generalizable adjunctive DL systems that could help realize predictive and individualized precision medicine for myopic patients.
Subject(s)
Artificial Intelligence , Myopia , Artificial Intelligence/trends , Deep Learning , Forecasting , Genomics , Humans , Machine Learning/trends , Myopia/diagnosis , Myopia/genetics , Myopia/therapy , Natural Language Processing , Neural Networks, ComputerABSTRACT
PURPOSE: Comparison of hemodynamic profiles and pain scores in diabetic patients undergoing diabetic foot surgery receiving peripheral nerve block (PNB) or spinal anesthesia [subarachnoid block (SAB)]. METHODS: This was a prospective, randomised controlled trial. We recruited diabetic patients aged > 18 years, American Society of Anesthesiologists class II-III, who were scheduled for unilateral diabetic foot surgery below the knee. All patients were assessed for autonomic dysfunction using the Survey of Autonomic Symptoms score. Participants were randomly assigned to receive either PNB or SAB for the surgery. Hemodynamic data, including usage of vasopressors, were recorded at 5-min intervals for up to 1 h after the induction of anesthesia. Pain scores were recorded postoperatively, and follow-up was done via telephone 6 months later. RESULTS: Compared to the PNB group, the SAB group had a larger number of patients with significant hypotension (14 vs. 1; p = 0.001) and more patients who required vasopressor boluses (6 vs. 0 patients). Compared to SAB group, the patients in the PNB group had a longer postoperative pain-free duration (9 vs. 4.54 h; p = 0.002) and lower pain scores 1 day after surgery (3.63 vs. 4.69; p = 0.01). CONCLUSION: Peripheral nerve block should be considered, whenever possible, as the first option of anesthesia for lower limb surgery in diabetic patients as it provides hemodynamic stability and superior postoperative pain control compared to SAB. TRIAL REGISTRATION: Clinical trial registry: ClinicalTrials.gov. ID NCT02727348.
Subject(s)
Anesthesia, Spinal/methods , Autonomic Nerve Block/methods , Diabetic Foot/surgery , Hemodynamics/physiology , Pain Measurement/methods , Pain, Postoperative/prevention & control , Aged , Diabetic Foot/diagnosis , Diabetic Foot/physiopathology , Female , Follow-Up Studies , Humans , Male , Middle Aged , Pain, Postoperative/diagnosis , Pain, Postoperative/physiopathology , Prospective Studies , Single-Blind MethodABSTRACT
BACKGROUND: To determine the effectiveness of atropine 1% administered once, twice and thrice per week. METHODS: Retrospective review of 166 cases in a tertiary eye hospital. RESULTS: In total, 166 patients started atropine 1% at different frequencies (once, twice and thrice per week) between January 2003 and August 2013 were identified. All patients had at least 15 months of follow-up. There was no significant difference in mean spherical equivalent (SE) (p = 0.341), age (p = 0.699), gender (p = 0.815) and ethnicity (p = 0.922) among the three groups at baseline. Patients were reviewed at 3, 9 and 15 months. Over a 15-month period, the mean change in SE was 0.26 ± 0.70 D, 0.51 ± 0.70 D and 0.46 ± 0.76 D in the patients started on once, twice and thrice per week, respectively (p = 0.342). Further analysis was performed by dividing patients into three groups of different changes in SE at the 15-month mark-≤ 0.5 D, between 0.5 D and 1.0 D and > 1.0 D. Groups with less myopic progression at the 15-month mark (< 0.5 and 0.5 to 1.0 D groups) were more myopic, - 5.32 D ± 1.88 and - 5.21 D ± 1.76, respectively, compared to - 4.13 D ± 2.05 in the > 1.0 D group. Multivariate linear regression analysis confirmed this relationship (p = 0.005), after adjusting for age, gender, ethnicity and frequency of dose. CONCLUSIONS: Part-time use of atropine 1% provides an alternative regimen of treating patients with myopia and can have a lower side effect profile compared to daily doses of atropine.
Subject(s)
Atropine , Myopia , Atropine/therapeutic use , Child , Disease Progression , Humans , Mydriatics , Myopia/drug therapy , Myopia/prevention & control , Ophthalmic Solutions , Refraction, Ocular , Retrospective StudiesABSTRACT
To date, most of the studies on safety and efficacy of supraglottic airway devices were done in Caucasian patients, and the results may not be extrapolated to Asian patients due to the different airway anatomy. We conducted this study to compare Supreme™ LMA (SLMA) and Proseal™ LMA (PLMA) size 1.5 in anaesthetized children among an Asian population. This prospective randomized clinical trial was conducted in a tertiary teaching hospital from September 2013 until May 2016. Sixty children, weighing 5-10 kg, who were scheduled for elective surgery under general anaesthesia were recruited and completed the study. Patients were randomly assigned to have either SLMA or PLMA as the airway device for general anaesthesia, and standard anaesthesia protocol was followed. The primary outcome measured was the oropharyngeal leak pressure (OLP). The rate of successful insertion, insertion time, fibreoptic view of larynx and airway complications for each device were also assessed. There were no statistically significant differences between SLMA and PLMA size 1.5 in oropharyngeal leak pressure [19.1 (± 5.5) cmH2O vs. 19.8 (± 4.5) cmH2O, p = 0.68]. Secondary outcomes including time to insertion [20.8 (± 8.3) vs. 22.1 (± 8.3) s, p = 0.57], first attempt success rate for device insertion, fibreoptic view of larynx, and airway complications were also comparable between the two devices. We found that all the patients who had a failed device insertion (either PLMA or SLMA) were of a smaller size (5-6.2 kg). The oropharyngeal leak pressure of the SLMA 1.5 was comparable with the PLMA 1.5, and both devices were able to maintain an airway effectively without significant clinical complications in anaesthetized children from an Asian population.
Subject(s)
Anesthesia, General/instrumentation , Laryngeal Masks , Asian People , Equipment Design , Equipment Failure , Female , Humans , Infant , Laryngeal Masks/statistics & numerical data , Malaysia , Male , Outcome Assessment, Health Care , Prospective StudiesABSTRACT
We report a case of drug-induced myoclonus possibly related to palonosetron, a second-generation 5-hydroxytryptamine-3 receptor antagonist which was administered as a prophylaxis for postoperative nausea and vomiting in a 28-year-old female. The recurrent episodes of myoclonus jerk involving the head, neck and shoulder persisted for a period of 4 days. The patient also exhibited an episode of severe bradycardia leading to hypotension 7 h after surgery. To our knowledge, this is the first report presenting these adverse events potentially associated with the use of palonosetron.
Subject(s)
Antiemetics/adverse effects , Isoquinolines/adverse effects , Myoclonus/chemically induced , Quinuclidines/adverse effects , Adult , Antiemetics/therapeutic use , Female , Humans , Isoquinolines/therapeutic use , Palonosetron , Postoperative Nausea and Vomiting/prevention & control , Quinuclidines/therapeutic useABSTRACT
Purpose: The purpose of this study was to assess the choroidal thickness and the Bruch's membrane opening size and their relationship to visual acuity in eyes with myopic macular degeneration (MMD). Methods: This was a population-based, cross-sectional study. Patients over the age of 30 years with high myopia (spherical equivalent ≤-5 diopters [D]) were recruited. The eyes were grouped according to the International Meta-Analysis for Pathologic Myopia (META-PM) classification based on fundus photographs and diffuse atrophy was subdivided into peripapillary diffuse choroidal atrophy (PDCA) or macular diffuse choroidal atrophy (MDCA). Swept-source optical coherence tomography imaging was performed and then the subfoveal choroidal thickness (SFCT) and Bruch's membrane opening diameter (BMOD) were measured. Results: Of the 470 study participants recruited, 373 patients (691 eyes), with a mean age of 42.8 ± 7.2 years, were eligible for the study and included in the analysis. There was no significant difference in SFCT between MDCA and patchy atrophy (M3) groups (P = 1.000), and the BMOD enlarged significantly from no myopic macular lesions to M3 (the P values of multiple comparison tests were all <0.005). Simple linear regression analysis showed that BMOD correlated positively with age (P < 0.001) and axial length (P < 0.001). Multiple linear regression analysis showed that best corrected visual acuity (BCVA) was significantly correlated with age (P = 0.041), axial length (P = 0.001), and BMOD (P = 0.017), but not with SFCT (P = 0.231). Conclusions: The significant variation of BMOD among MMD groups and the correlation between BMOD and BCVA in MMD eyes suggest that BMOD may be an imaging biomarker for monitoring MMD.
Subject(s)
Bruch Membrane , Macular Degeneration , Myopia, Degenerative , Tomography, Optical Coherence , Visual Acuity , Humans , Bruch Membrane/pathology , Bruch Membrane/diagnostic imaging , Male , Tomography, Optical Coherence/methods , Cross-Sectional Studies , Female , Visual Acuity/physiology , Myopia, Degenerative/physiopathology , Myopia, Degenerative/complications , Myopia, Degenerative/diagnosis , Middle Aged , Adult , Macular Degeneration/physiopathology , Macular Degeneration/diagnosis , Choroid/pathology , Choroid/diagnostic imaging , AgedABSTRACT
PURPOSE: To identify subgroups of primary angle-closure suspects (PACS) based on anterior segment optical coherence tomography (AS-OCT) and biometric parameters. DESIGN: Cross-sectional study. PARTICIPANTS: We evaluated 243 PACS subjects in the primary group and 165 subjects in the validation group. METHODS: Participants underwent gonioscopy and AS-OCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure AS-OCT parameters. An agglomerative hierarchical clustering method was first used to determine the optimum number of parameters to be included in the determination of subgroups. The best number of subgroups was then determined using Akaike Information Criterion (AIC) and Gaussian Mixture Model (GMM) methods. MAIN OUTCOME MEASURES: Subgroups of PACS. RESULTS: The mean age of the subjects was 64.8 years, and 65.02% were female. After hierarchical clustering, 1 or 2 parameters from each cluster were chosen to ensure representativeness of the parameters and yet keep a minimum of redundancy. The parameters included were iris area, anterior chamber depth (ACD), anterior chamber width (ACW), and lens vault (LV). With the use of GMM, the optimal number of subgroups as given by AIC was 3. Subgroup 1 was characterized by a large iris area, subgroup 2 was characterized by a large LV and a shallow ACD, and subgroup 3 was characterized by elements of both subgroups 1 and 2. The results were replicated in a second independent group of 165 PACS subjects. CONCLUSIONS: Clustering analysis identified 3 distinct subgroups of PACS subjects based on AS-OCT and biometric parameters. These findings may be relevant for understanding angle-closure pathogenesis and management.
Subject(s)
Anterior Eye Segment/pathology , Glaucoma, Angle-Closure/diagnosis , Tomography, Optical Coherence , Biometry , Cross-Sectional Studies , Female , Gonioscopy , Humans , Male , Middle Aged , PupilABSTRACT
OBJECTIVE: A recent study found that a combination of 6 anterior segment optical coherence tomography (ASOCT) parameters (anterior chamber area, volume, and width [ACA, ACV, ACW], lens vault [LV], iris thickness at 750 µm from the scleral spur, and iris cross-sectional area) explain >80% of the variability in angle width. The aim of this study was to evaluate classification algorithms based on ASOCT measurements for the detection of gonioscopic angle closure. DESIGN: Cross-sectional study. PARTICIPANTS: We included 2047 subjects aged ≥50 years. METHODS: Participants underwent gonioscopy and ASOCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters in horizontal ASOCT scans. Six classification algorithms were considered (stepwise logistic regression with Akaike information criterion, Random Forest, multivariate adaptive regression splines, support vector machine, naïve Bayes' classification, and recursive partitioning). The ASOCT-derived parameters were incorporated to generate point and interval estimates of the area under the receiver operating characteristic (AUC) curves for these algorithms using 10-fold cross-validation as well as 50:50 training and validation. MAIN OUTCOME MEASURES: We assessed ASOCT measurements and angle closure. RESULTS: Data on 1368 subjects, including 295 (21.6%) subjects with gonioscopic angle closure were available for analysis. The mean (±standard deviation) age was 62.4±7.5 years and 54.8% were females. Angle closure subjects were older and had smaller ACW, ACA, and ACV; greater LV; and thicker irides (P<0.001 for all). For both, the 10-fold cross-validation and the 50:50 training and validation methods, stepwise logistic regression was the best algorithm for detecting eyes with gonioscopic angle closure with testing set AUC of 0.954 (95% confidence interval [CI], 0.942-0.966) and 0.962 (95% CI, 0.948-0.975) respectively, whereas recursive partitioning had relatively the poorest performance with testing set AUC 0.860 (95% CI, 0.790-0.930) and 0.905 (95% CI, 0.876-0.933), respectively. This algorithm performed similarly well (AUC, 0.957) in a second independent sample of 200 angle closure subjects and 302 normal controls. CONCLUSIONS: A classification algorithm based on stepwise logistic regression that used a combination of 6 parameters obtained from a single horizontal ASOCT scan identified subjects with gonioscopic angle closure>95% of the time. FINANCIAL DISCLOSURE(S): The authors have no proprietary or commercial interest in any of the materials discussed in this article.
Subject(s)
Algorithms , Anterior Eye Segment/pathology , Glaucoma, Angle-Closure/diagnosis , Tomography, Optical Coherence/classification , Area Under Curve , Cross-Sectional Studies , Female , Gonioscopy , Humans , Intraocular Pressure/physiology , Male , Middle Aged , Prospective Studies , ROC Curve , Tonometry, OcularABSTRACT
BACKGROUND/AIMS: To evaluate the association of reported time outdoors and light exposure patterns with myopia among children aged 9 years from the Growing Up in Singapore Towards Healthy Outcomes birth cohort. METHODS: We assessed reported time outdoors (min/day), light exposure patterns and outdoor activities of children aged 9 years (n=483) with a questionnaire, the FitSight watch and a 7-day activity diary. Light levels, the duration, timing and frequency of light exposure were assessed. Cycloplegic spherical equivalent (SE), myopia (SE≤-0.5 D) and axial length (AL) of paired eyes were analysed using generalised estimating equations. RESULTS: In this study, 483 (966 eyes) multiethnic children (50.0% boys, 59.8% Chinese, 42.2% myopic) were included. Reported time outdoors (mean±SD) was 100±93 min/day, and average light levels were 458±228 lux. Of the total duration children spent at light levels of ≥1000 lux (37±19 min/day), 76% were spent below 5000 lux. Peak light exposure occurred at mid-day. Children had 1.7±1.0 light exposure episodes/day. Common outdoor activities were walks, neighbourhood play and swimming. Greater reported time outdoors was associated with lower odds of myopia (OR=0.82, 95% CI 0.70 to 0.95/hour increase daily; p=0.009). Light levels, timing and frequency of light exposures were not associated with myopia, SE or AL (p>0.05). CONCLUSION: Reported time outdoors, light levels and number of light exposure episodes were low among Singaporean children aged 9 years. Reported time outdoors was protective against myopia but not light levels or specific light measures. A multipronged approach to increase time outdoors is recommended in the combat against the myopia epidemic.
Subject(s)
Myopia , Male , Child , Humans , Female , Myopia/epidemiology , Refraction, Ocular , Eye , Surveys and Questionnaires , Time FactorsABSTRACT
Pathologic myopia is a severe form of myopia that can lead to permanent visual impairment. The recent global increase in the prevalence of myopia has been projected to lead to a higher incidence of pathologic myopia in the future. Thus, imaging myopic eyes to detect early pathological changes, or predict myopia progression to allow for early intervention, has become a key priority. Recent advances in optical coherence tomography (OCT) have contributed to the new grading system for myopic maculopathy and myopic traction maculopathy, which may improve phenotyping and thus, clinical management. Widefield fundus and OCT imaging has improved the detection of posterior staphyloma. Non-invasive OCT angiography has enabled depth-resolved imaging for myopic choroidal neovascularisation. Artificial intelligence (AI) has shown great performance in detecting pathologic myopia and the identification of myopia-associated complications. These advances in imaging with adjunctive AI analysis may lead to improvements in monitoring disease progression or guiding treatments. In this review, we provide an update on the classification of pathologic myopia, how imaging has improved clinical evaluation and management of myopia-associated complications, and the recent development of AI algorithms to aid the detection and classification of pathologic myopia.
Subject(s)
Macular Degeneration , Myopia, Degenerative , Humans , Myopia, Degenerative/diagnostic imaging , Artificial Intelligence , Tomography, Optical Coherence/methods , Vision Disorders/etiology , Fundus Oculi , Macular Degeneration/complications , Retrospective StudiesABSTRACT
PURPOSE: To develop and validate models to predict who will develop myopia in the following year based on cycloplegic refraction or ocular biometry and to identify thresholds of premyopia. METHODS: Prospective longitudinal data of nonmyopic children at baseline from the Guangzhou Twins Eye Study and the Guangzhou Outdoor Activity Longitudinal Study were used as the training set, and the Singapore Cohort Study of the Risk factors for Myopia study formed the external validation set. Age, sex, cycloplegic refraction, ocular biometry, uncorrected visual acuity, and parental myopia were integrated into 3 logistic regression models to predict the onset of myopia in the following year. Premyopia cutoffs and an integer risk score system were derived based on the identified risk. RESULTS: In total, 2896 subjects with at least 2 visits were included. Cycloplegic refraction at baseline is a better predictor to identify the children with myopia onset [C-statistic=0.91, 95% confidence interval (CI), 0.87-0.94; C-statistic=0.92, 95% CI, 0.92-0.92 for internal and external validation, respectively], comparing to axial length, corneal curvature radius (CR) and anterior chamber depth (C-statistic=0.81, 95% CI, 0.73-0.88; C-statistic=0.80, 95% CI, 0.79-0.80, respectively), and axial length/CR (C-statistic=0.78, 95% CI, 0.71-0.85; C-statistic=0.76, 95% CI, 0.75-0.76). With a risk of >70%, the definitions of premyopia indicating approaching myopia onset were 0.00 D for 6-8 years and -0.25 D for ≥9 years in children with 2 myopic parents. CONCLUSIONS: Either cycloplegic refraction or ocular biometry can predict 1-year risk of myopia. Premyopia can be successfully defined through risk assessments based on children's age and predict who would require more aggressive myopia prophylaxis.
Subject(s)
Myopia , Refraction, Ocular , Child , Humans , Cohort Studies , Longitudinal Studies , Mydriatics , Prospective Studies , Myopia/diagnosisABSTRACT
PURPOSE: To evaluate factors influencing stabilisation of myopia in the Singapore Cohort of Risk factors for Myopia. METHODS: We evaluated the longitudinal natural history of 424 myopic participants from 1999 to 2022. The outcome was the change in myopia from the adolescence follow-up visit (aged 12-19 years) to the adulthood follow-up visit (aged 26-33 years). Association of predictive factors, including baseline spherical error, gender, ethnicity, parental myopia, time outdoor, near work and age at adolescence, was examined with the dichotomous outcome of adult myopia progression (≤ -1.00 dioptres (D) over 10 years) using multiple logistic regression and progression in linear regression models. RESULTS: For the primary outcome, the mean rate of progression of the outcome was found to be -0.04±0.09 D per year from the adolescent to the adulthood follow-up visits. 82.3% (95% CI 78.3% to 85.8%) had myopia stabilisation, with progression of less than 1.00 D over 10 years while 61.3% (95% CI 56.5% to 66.0%) of the subjects had progression of less than 0.50 D. In logistic regression models, both male gender (p=0.035) and non-Chinese ethnicity (p=0.032) were more likely to achieve myopia stabilisation while in linear multivariate regression models, males had a significantly slower degree of myopia progression (p=0.021). CONCLUSION: 5 in 6 Singaporean young adults had myopia stabilisation. Male gender is 2 times and non-Chinese ethnicities are 2.5 times more likely to achieve myopia stabilisation. However, a proportion of myopes continue to exhibit a clinically significant degree of progression in adulthood.
ABSTRACT
PURPOSE: To investigate the predictive factors for myopic macular degeneration (MMD) and progression in adults with myopia. METHODS: We examined 828 Malay and Indian adults (1579 myopic eyes) with myopia (spherical equivalent (SE) ≤-0.5 dioptres) at baseline who participated in both baseline and 12-year follow-up visits of the Singapore Malay Eye Study and the Singapore Indian Eye Study. Eye examinations, including subjective refraction and axial length (AL) measurements, were performed. MMD was graded from fundus photographs following the Meta-Analysis for Pathologic Myopia classification. The predictive factors for MMD development and progression were assessed in adults without and with MMD at baseline, respectively as risk ratios (RR) using multivariable modified Poisson regression models. The receiver operating characteristic curve was used to visualise the performance of the predictive models for the development of MMD, with performance quantified by the area under the curve (AUC). RESULTS: The 12-year cumulative MMD incidence was 10.3% (95% CI 8.9% to 12.0%) among 1504 myopic eyes without MMD at baseline. Tessellated fundus was a major predictor of MMD (RR=2.50, p<0.001), among other factors including age, worse SE and longer AL (all p<0.001). The AUC for prediction of MMD development was found to be 0.78 (95% CI 0.76 to 0.80) for tessellated fundus and increased significantly to an AUC of 0.86 (95% CI 0.84 to 0.88) with the combination of tessellated fundus with age, race, gender and SE (p<0.001). Older age (p=0.02), worse SE (p<0.001) and longer AL (p<0.001) were found to be predictors of MMD progression. CONCLUSIONS: In adults with myopia without MMD, tessellated fundus, age, SE and AL had good predictive value for incident MMD. In adults with MMD, 1 in 10 eyes experienced progression over the same period. Older age, more severe myopia and longer AL were independent risk factors for progression.
Subject(s)
Macular Degeneration , Myopia, Degenerative , Humans , Adult , Longitudinal Studies , Visual Acuity , Singapore/epidemiology , Myopia, Degenerative/diagnosis , Myopia, Degenerative/epidemiology , Myopia, Degenerative/complications , Macular Degeneration/diagnosis , Macular Degeneration/epidemiology , Macular Degeneration/etiology , Refraction, Ocular , Vision DisordersABSTRACT
Our study aims to identify children at risk of developing high myopia for timely assessment and intervention, preventing myopia progression and complications in adulthood through the development of a deep learning system (DLS). Using a school-based cohort in Singapore comprising of 998 children (aged 6-12 years old), we train and perform primary validation of the DLS using 7456 baseline fundus images of 1878 eyes; with external validation using an independent test dataset of 821 baseline fundus images of 189 eyes together with clinical data (age, gender, race, parental myopia, and baseline spherical equivalent (SE)). We derive three distinct algorithms - image, clinical and mix (image + clinical) models to predict high myopia development (SE ≤ -6.00 diopter) during teenage years (5 years later, age 11-17). Model performance is evaluated using area under the receiver operating curve (AUC). Our image models (Primary dataset AUC 0.93-0.95; Test dataset 0.91-0.93), clinical models (Primary dataset AUC 0.90-0.97; Test dataset 0.93-0.94) and mixed (image + clinical) models (Primary dataset AUC 0.97; Test dataset 0.97-0.98) achieve clinically acceptable performance. The addition of 1 year SE progression variable has minimal impact on the DLS performance (clinical model AUC 0.98 versus 0.97 in primary dataset, 0.97 versus 0.94 in test dataset; mixed model AUC 0.99 versus 0.97 in primary dataset, 0.95 versus 0.98 in test dataset). Thus, our DLS allows prediction of the development of high myopia by teenage years amongst school-going children. This has potential utility as a clinical-decision support tool to identify "at-risk" children for early intervention.
ABSTRACT
PURPOSE: Recent advances in anterior segment imaging have enabled the measurement of novel ocular biometric parameters, such as lens vault (LV), posterior corneal arc length (PCAL), and iris area. The aims of this study were to identify the determinants of anterior chamber depth (ACD) and to ascertain the relative importance of these determinants in Chinese persons in Singapore. DESIGN: Population-based, cross-sectional study. PARTICIPANTS: One thousand sixty Chinese participants recruited from the Singapore Chinese Eye Study. METHODS: All subjects underwent AS optical coherence tomography (OCT; Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure the AS-OCT parameters. Anterior chamber depth was determined using IOLMaster (Carl Zeiss Meditec). Univariate and multivariate regression analyses were performed to assess the association between ACD with ocular biometric and systemic parameters. A stepwise selection algorithm was used to identify sequentially the contribution of each independent variable. MAIN OUTCOME MEASURES: Anterior chamber depth and ocular biometric parameters. RESULTS: The mean age (±standard deviation) of participants was 56.9±8.57 years and 50.5% were men. The mean ACD was 3.24±0.35 mm. The strongest determinants of ACD were LV (R(2) = 0.582; P<0.001) and PCAL (partial R(2) = 0.186; P<0.001). For every 10-µm increase in LV and every 1-mm increase in PCAL, ACD changed by -0.008 mm (95% confidence interval [CI], -0.009 to -0.008 mm; P<0.001) and 0.525 mm (95% CI, 0.468-0.583 mm; P<0.001), respectively. The 8 most highly associated variables (including LV, PCAL, axial length, age, and iris area) explained 80.5% of the variability in ACD, but when excluding LV and PCAL, the other 6 variables explained only 3.7% of the variability in ACD. After controlling for LV and PCAL, axial length was a poor determinant of ACD (partial R(2) = 0.006), whereas lens thickness was not associated independently with ACD. CONCLUSIONS: Lens vault and PCAL explained 76.8% of the variability in ACD. When information about LV and PCAL were available, axial length was a poor determinant of ACD, whereas lens thickness was not associated independently with ACD. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.
Subject(s)
Anterior Chamber/pathology , Asian People/ethnology , Cornea/pathology , Glaucoma, Angle-Closure/ethnology , Adult , Aged , Aged, 80 and over , Biometry , Cross-Sectional Studies , Female , Humans , Intraocular Pressure , Male , Middle Aged , Risk Factors , Singapore/epidemiology , Tomography, Optical CoherenceABSTRACT
PURPOSE: To investigate determinants of angle width and derive mathematic models to best predict angle width. DESIGN: Population-based, cross-sectional study. PARTICIPANTS: A total of 1067 Chinese subjects aged ≥40 years. METHODS: Participants underwent gonioscopy, A-scan biometry, and imaging by anterior segment optical coherence tomography (ASOCT, Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters. Linear regression modeling was performed with trabecular-iris space area at 750 µm (TISA750) and angle opening distance at 750 µm (AOD750) from the scleral spur as the 2 dependent angle width variables. By using a combination of ASOCT and biometric parameters, an optimal model that was predictive of angle width was determined by a forward selection regression algorithm. Validation of the results was performed in a separate set of community-based clinic study of 1293 persons aged ≥50 years. MAIN OUTCOME MEASURES: Angle width and biometric parameters. RESULTS: The mean age (standard deviation) of the population-based subjects was 56.9 (8.5) years, and 50.2% were male. For TISA750, the strongest determinants among ASOCT and A-scan independent variables were anterior chamber volume (ACV, R(2)=0.51), followed by anterior chamber area (ACA, R(2)=0.49) and lens vault (LV, R(2)=0.47); for AOD750, these were LV (R(2)=0.56), ACA (R(2)=0.55), and ACV (R(2)=0.54). The R(2) values for anterior chamber depth and axial length were 0.39 and 0.27 for TISA750, respectively, and 0.46 and 0.30 for AOD750, respectively. An optimal model consisting of 6 variables (ACV, ACA, LV, anterior chamber width [ACW], iris thickness at 750 µm, and iris area) explained 81.4% of the variability in TISA750 and 85.5% of the variability in AOD750. The results of the population-based study were validated in the community-based clinic study, where the strongest determinants of angle width (ACA, ACV, and LV) and the optimal model with 6 variables were similar. CONCLUSIONS: Angle width is largely dependent on variations in ACA, ACV, and LV. A predictive model comprising 6 quantitative ASOCT parameters explained more than 80% of the variability of angle width and may have implications for screening for angle closure.