Four-year change in ocular biometric components and refraction in schoolchildren: A cohort study

Distribution and correlation of refractive parameters in children with different corneal curvatures in southeast China

AIM

To analyze the distribution of refractive status in school-age children with different corneal curvatures (CC) and the correlation between CC and refractive status.

METHODS

A total of 2214 school-aged children of grade 4 in Hangzhou who were screened for school myopia were included. Uncorrected distance visual acuity (UCDVA), non-cycloplegic refraction, axial length (AL), horizontal and vertical corneal curvature (K1, K2) were measured and spherical equivalent (SE), corneal curvature radius (CCR) and axial length/corneal radius of curvature ratio (AL/CR) were calculated. UCDVA<5.0 and SE≤-0.50 D were classified as school-screening myopia. According to the different CCRs, the patients were divided into the lower corneal curvature (LCC) group (CCR≥7.92) and the higher corneal curvature (HCC) group (CCR<7.92). Each group was further divided into the normal AL subgroup and the long AL subgroup. The refractive parameters were compared to identify any differences between the two groups.

RESULTS

Both SE and AL were greater in the LCC group (P=0.013, P<0.001). The prevalence of myopia was 38% in the LCC group and 44% in the HCC group (P<0.001). The proportion of children without screening myopia was higher in the LCC group (62%) than in the HCC group (56%). Among these children without screening myopia, the proportion of long AL in the LCC group (24%) was significantly higher than that in the HCC group (0.012%; P<0.001). The change of SE in the LCC group was less affected by the increase of AL than that in the HCC group.

CONCLUSION

School-aged children in the LCC group have a lower incidence of screening myopia and longer AL. Low CC can mask SE reduction and AL growth to some extent, and the change of AL growth change more in children with low CC than high CC. Before the onset of myopia, its growth rate is even faster than that after the onset of myopia.

The Guiding Significance of Ocular Biometry in Evaluating the Refractive Status of Preschool Children

INTRODUCTIONS

This study aimed to analyze the correlation between refractive status and ocular biological parameters in preschool-age children (3-6 years old), establish a regression curve, guide the clinical judgment of children's refractive status, and improve the accuracy of refractive screening for this age group.

METHODS

A total of 508 children, aged 3-6 years, were admitted to the hospital, exhibiting symptoms of ametropia and a need for dilation optometry. Among these, 326 children were included in the statistics group, having been examined between August 2021 and October 2022, and 182 children were included in the validation group, having been examined between November 2022 and March 2023. Using IOL Master700, ocular biometry parameters were measured for all participants, including axial length (AL), keratometry readings (K1 and K2), anterior chamber depth (ACD), lens thickness (LT), and central corneal thickness (CCT). One percent atropine sulfate eye gel was administered, and then the spherical equivalent (SE) was calculated by Bennett's formula. The correlation between SE and other ocular biometrics was analyzed, followed by the establishment of an SE prediction equation. The SE prediction equation was used to calculate the spherical equivalent (SE#) using ocular biometry data from the validation group, and the consistency between SE and SE# was evaluated.

RESULTS

SE showed a negative correlation with AL/CR (r = -0.936), AL (r = -0.811), ACD (r = -0.500), age (r = -0.396), and Km (r = -0.213) (p < 0.001), and positive correlation with LT (r = 0.301), LP (r = 0.176) (p < 0.001). A multiple linear regression equation was established for SE using the stepwise selection method, SE = 49.232 - 23.583 × AL/CR + 1.703 × ACD + 0.589 × Km - 0.609 × LP + 1.103 × LT (R2 = 0.997). Based on the regression equation, the predicted SE# highly correlated with SE after cycloplegia in the validation group (r = 0.998, p < 0.001).

CONCLUSION

The main ocular biological factors of ocular diopter in children aged 3-6 years are AL/CR, ACD, Km, LP, and LT, which are jointly influenced by multiple factors. Ocular biometry is a reliable predictor of real refraction among children aged 3-6.

Clouclip combined with a questionnaire on the influence factors of myopia in children

Purpose

To evaluate eye use behavior in myopic and non-myopic children objectively using Clouclip M2 device and subjectively using questionnaire and compare the results. The study also aimed to assess the relationships between ocular biometric parameters and refractive status.

Methods

Clouclip M2 was used in monitoring eye use behavior and visual environment in children aged 9-11 years. The participants were monitored for 7 days. On the eighth day, data stored in the device were collected, relevant eye examination were conducted and survey questionnaire was administered. The paired sample t-test was used to compare the eye use behavior obtained objectively and subjectively. The relationships between ocular biometric parameters and refractive status were assessed using the Pearson's Correlation analysis.

Results

Spherical equivalent refraction was significantly correlated with axial length, axial length to corneal radius, anterior chamber depth, lens thickness, and corneal radius (P < 0.05). The average time per day spent on near work, the maximum time for single near work, and the average near working distance were significantly lower, and the average total time spent on outdoor activities was significantly longer as determined by questionnaire method than that found using Clouclip M2. Logistic regression analysis revealed that prolonged near work, shorter working distance, presence of parental myopia, and lesser outdoor activities were significant risk factors for myopia.

Conclusions

The childhood myopia is influenced by eye use behavior, eye use environment, and parental myopia. Results from this study further support that biometric and optical parameters of the eye determine refractive status. Being an objective method, Clouclip M2 provides an independent eye use behavior data which potentially are more reliable than obtained from subjective method. Our study provided a theoretical basis for myopia prevention and control in clinical practice.

Distribution and Characteristics of Ocular Biometric Parameters among a Chinese Population: A Hospital-Based Study

INTRODUCTION

This study aimed to describe the distribution and characteristics of ocular biometric parameters among a large Chinese population.

METHODS

This retrospective cross-sectional study included 146,748 subjects whose ocular biometric parameters were measured at the ophthalmology clinic of West China Hospital, Sichuan University, and recorded in the hospital database. Ocular biometric parameters, including axial length, anterior chamber depth, corneal keratometry, and keratometric astigmatism, were recorded. Only monocular data for each subject were analyzed to avoid bias.

RESULTS

Valid data from 85,770 subjects (43,552 females and 42,218 males) aged 3-114 years were included in this study. The mean axial length, mean anterior chamber depth, average corneal keratometry, and mean keratometric astigmatism were 24.61 mm, 3.30 mm, 43.76 D, and 1.19 D, respectively. The stratification of the ocular parameters by age and gender showed significant inter-gender and inter-age differences.

CONCLUSIONS

Analysis of a large population of subjects in western China aged 3-114 years showed that the distribution and characteristics of ocular biometric parameters, including axial length, anterior chamber depth, corneal keratometry, and keratometric astigmatism, differed by age and gender. This study is the first to describe ocular biometric parameters in subjects aged > 100 years.

Baseline metrics that may predict future myopia in young children

PURPOSE

We used baseline data from the PICNIC longitudinal study to investigate structural, functional, behavioural and heritable metrics that may predict future myopia in young children.

METHODS

Cycloplegic refractive error (M) and optical biometry were obtained in 97 young children with functional emmetropia. Children were classified as high risk (HR) or low risk (LR) for myopia based on parental myopia and M. Other metrics included axial length (AXL), axial length/corneal radius (AXL/CR) and refractive centile curves.

RESULTS

Based on the PICNIC criteria, 46 children (26 female) were classified as HR (M = +0.62 ± 0.44 D, AXL = 22.80 ± 0.64 mm) and 51 (27 female) as LR (M = +1.26 ± 0.44 D, AXL = 22.77 ± 0.77 mm). Based on centiles, 49 children were HR, with moderate agreement compared with the PICNIC classification (k = 0.65, p < 0.01). ANCOVA with age as a covariate showed a significant effect for AXL (p < 0.01), with longer AXL and deeper anterior chamber depth (ACD) (p = 0.01) in those at HR (differences AXL = 0.16 mm, ACD = 0.13 mm). Linear regression models showed that central corneal thickness (CCT), ACD, posterior vitreous depth (PVD) (=AXL - CCT - ACD-lens thickness (LT)), corneal radius (CR) and age significantly predicted M (R = 0.64, p < 0.01). Each 1.00 D decrease in hyperopia was associated with a 0.97 mm elongation in PVD and 0.43 mm increase in CR. The ratio AXL/CR significantly predicted M (R = -0.45, p < 0.01), as did AXL (R = -0.25, p = 0.01), although to a lesser extent.

CONCLUSIONS

Although M and AXL were highly correlated, the classification of pre-myopic children into HR or LR was significantly different when using each parameter, with AXL/CR being the most predictive metric. At the end of the longitudinal study, we will be able to assess the predictability of each metric.

Emmetropization and nonmyopic eye growth

Most eyes start with a hypermetropic refractive error at birth, but the growth rates of the ocular components, guided by visual cues, will slow in such a way that this refractive error decreases during the first 2 years of life. Once reaching its target, the eye enters a period of stable refractive error as it continues to grow by balancing the loss in corneal and lens power with the axial elongation. Although these basic ideas were first proposed over a century ago by Straub, the exact details on the controlling mechanism and the growth process remained elusive. Thanks to the observations collected in the last 40 years in both animals and humans, we are now beginning to get an understanding how environmental and behavioral factors stabilize or disrupt ocular growth. We survey these efforts to present what is currently known regarding the regulation of ocular growth rates.

Refractive development I: Biometric changes during emmetropisation

PURPOSE

Although there are many reports on ocular growth, these data are often fragmented into separate parameters or for limited age ranges. This work intends to create an overview of normal eye growth (i.e., in absence of myopisation) for the period before birth until 18 years of age.

METHODS

The data for this analysis were taken from a search of six literature databases using keywords such as "[Parameter] & [age group]", with [Parameter] the ocular parameter under study and [age group] an indication of age. This yielded 34,409 references that, after screening of title, abstract and text, left 294 references with usable data. Where possible, additional parameters were calculated, such as the Bennett crystalline lens power, whole eye power and axial power.

RESULTS

There were 3422 average values for 17 parameters, calculated over a combined total of 679,398 individually measured or calculated values. The age-related change in refractive error was best fitted by a sum of four exponentials (r²  = 0.58), while all other biometric parameters could be fitted well by a sum of two exponentials and a linear term ('bi-exponential function'; r² range: 0.64-0.99). The first exponential of the bi-exponential fits typically reached 95% of its end value before 18 months, suggesting that these reached genetically pre-programmed passive growth. The second exponentials reached this point between 4 years of age for the anterior curvature and well past adulthood for most lenticular dimensions, suggesting that this part represents the active control underlying emmetropisation. The ocular components each have different growth rates, but growth rate changes occur simultaneously at first and then act independently after birth.

CONCLUSIONS

Most biometric parameters grow according to a bi-exponential pattern associated with passive and actively modulated eye growth. This may form an interesting reference to understand myopisation.

Normative data and percentile curves for axial length and axial length/corneal curvature in Chinese children and adolescents aged 4-18 years

PURPOSE

To develop age-specific and gender-specific reference percentile charts for axial length (AL) and AL/corneal radius of curvature (AL/CR) and, to use percentiles to determine probability of myopia and estimate refractive error (RE).

METHODS

Analysis of AL, cycloplegic RE and CR of 14 127 Chinese participants aged 4-18 years from 3 studies. AL and AL/CR percentiles estimated using Lambda-Mu-Sigma method and compared for agreement using intraclass correlation (ICC). Logistic regression was used to model risk of myopia based on age, gender, AL and AL/CR percentiles. Accuracy of AL progression and RE estimated using percentiles was validated using an independent sample of 5742 eyes of children aged 7-10 years.

RESULTS

Age-specific and gender-specific AL and AL/CR (3rd, 5th, 10th, 25th, 50th, 75th, 90th and 95th) percentiles are presented. Concordance between AL and AL/CR percentiles improved with age (0.13 at 4 years to >0.75 from 13 years) and a year-to-year change was observed for all except <10th percentile from 15 years. Increasing age, AL and AL/CR was associated with a more myopic RE (r²=0.45,0.70 and 0.83, respectively). The sensitivity and specificity of the model to estimate probability of myopia was 86.0% and 84.5%, respectively. Estimation of 1-year change in AL using percentiles correlated highly with actual AL (ICC=0.98). Concordance of estimated to actual RE was high (ICC=0.80) and within ±0.50D and ±1.0D of actual RE for 47.4% and 78.9% of eyes, respectively.

CONCLUSION

Age-specific and gender-specific AL and AL/CR percentiles provide reference data, aid in identifying and monitoring individuals at risk of myopia and have utility in screening for myopia. AL/CR percentiles were more accurate in estimating probability of myopia in younger children.

Prediction of premyopia and myopia in Chinese preschool children: a longitudinal cohort

BACKGROUNDS

Myopia has become a global public health problem. Children with early onset of myopia are at particular risk of complications associated with myopia. Younger children and children with greater initial myopic refractive errors are at a greater risk of myopia progression. Therefore, it is essential to identify subjects at high risk of developing myopia to facilitate myopia prevention in the early stage, especially during the preschool period. The purpose of this study was to determine whether premyopia and myopia in preschool children can be predicted by easily obtainable parameters.

METHODS

Data was collected in a population-based cohort. Comprehensive examinations included height, weight, refraction, axial length (AL), and corneal radius of curvature (CR), with a follow-up of 2 years. Parental myopia history was obtained from a questionnaire. Myopia was defined as spherical equivalent (SE) ≤ - 0.50 D. Premyopia was defined as - 0.50 D < SE ≤ + 0.75 D. Multivariate linear regression models were fitted to determine the associations between these parameters at baseline and future SE. To predict premyopia and myopia, Cox proportional hazard regression analysis coupled with a nomogram was used.

RESULTS

A total of 830 children (433 boys and 397 girls) were included (40.83 ± 3.43 months old at baseline). A significantly negative relationship was observed in the multivariate analysis between baseline AL, AL/CR, two myopic parents, and the future SE after adjusting for age and gender (coefficient = - 0.291, coefficient = - 5.791, coefficient = - 0.273, respectively, both p <  0.001). Higher baseline AL, AL/CR (hazard ratio (HR) = 4.916, HR = 2.979, respectively, comparing the top quartile with the bottom quartile, both p <  0.001) and two myopic parents (HR = 1.756, compared to no myopic parents, p = 0.001) were associated with a higher risk of future onset of premyopia. From the nomogram, AL/CR was found to have the most enormous effect on survival. Different baseline AL and AL/CR values (both Log Rank p <  0.001) had different survival curves.

CONCLUSIONS

AL and AL/CR could be used as obtainable indicators for identifying subjects at high risk of developing premyopia and myopia in young preschool children.