Explore the vast range of titles available.

This study aimed to investigate the correlation between myopia severity and the stress–strain index (SSI), measured with the Corneal Visualization Scheimpflug Technology (Corvis ST) device. The subjects were divided into two groups, based on both the axial length (AL) and spherical equivalent refraction (SER): 22–26.00 AL group (22 mm < AL < 26.00 mm) associated with SER of less than − 6.00D, and ≥ 26.00 AL group (AL ≥ 26.00 mm) associated with SER over − 6.00D. The differences in the Corvis ST-derived dynamic corneal response parameters and stiffness parameters between the two groups were investigated. The correlation between SSI and AL, SER, age, ratio of AL to radius of corneal curvature (CR) (AL/CR), and axial length minus anterior chamber depth (ACD) (AL-ACD) were analyzed. The SSI (0.95 ± 0.13 in the 22–26.00 AL group and 0.86 ± 0.15 in the ≥ 26.00 AL group) were significantly different between the two groups ( P  < 0.01). In the ≥ 26.00 AL group, there was evidence of a weak negative correlation between SSI and AL (r = − 0.265, P  < 0.01), AL/CR (r = − 0.376, P  < 0.01), and AL-ACD (r = − 0.224, P  < 0.01); and a weak positive correlation between SSI and SER (r = 0.251, P  < 0.01). However, in the 22–26.00 AL group, there was no correlation between SSI and AL, AL-ACD, AL/CR or SER ( P  > 0.05). SSI was significantly correlated with AL, which is the major determinant of SER, in the ≥ 26.00 AL group. This correlation was not affected with CR and ACD, as both AL/CR and AL-ACD also correlated with SSI at the same degree.

PurposeHigh myopia and pathologic myopia are common causes of visual morbidity. Myopic pathology can affect all regions of the retina, though there is currently no classification system to distinguish anterior (peripheral) and posterior (macular) pathology. We hypothesize that these classifications are characterized by distinct demographic and refractive features, highlighting the disparity in types of pathologic myopia.MethodsInstitutional retrospective cohort study. The Stanford University Medical Center Clinical Data Warehouse was used to identify patients with high myopia by ICD-9 and ICD-10 codes. Predetermined ICD diagnoses were then used to classify patients with high myopia into isolated high myopia (IHM), anterior pathologic myopia (APM), posterior pathologic myopia (PPM), and combined pathologic myopia (CPM). A cohort of this population was then manually reviewed to gather refractive data and confirm accuracy of ICD coding.ResultsPatients (3274) were identified with high myopia. Overall, 22.1% individuals met criteria for APM, 10.7% for PPM, 17.0% for CPM, and 50.2% for IHM. We identified a significantly higher frequency of females with PPM compared to APM (62.3 vs. 48.3%; OR, 1.73; 95% CI, 1.34 to 2.25), Asian patients with PPM as compared to APM (42.9 vs. 33.3%; OR, 1.50; 95% CI, 1.16 to 1.95), and younger patients with APM compared to PPM (median 45.3 vs. 63.4 years). The refractive error was significantly more myopic in the CPM (median − 9.8D; interquartile range, IQR 6.7) and PPM (median − 10.5D; IQR 9.8) subgroups as compared to the APM (median − 8.1D; IQR 3.5), and IHM (median − 8.2D; IQR 4.1) subgroups (p = 0.003).ConclusionsHigh myopia may be divided into four distinct subgroups based on presence and location of pathology, which is associated with differences in age, gender, race, and refractive error.

High myopia can lead to pathologic myopia and visual impairment, whereas its causes are unclear. We retrospectively researched high myopia cases from patient records to investigate the association between axial elongation and myopic maculopathy. Sixty-four eyes were examined in patients who visited the department between July 2017 and June 2018, had an axial length of 26 mm or more, underwent fundus photography, and had their axial length measured twice or more. The average axial length was 28.29 ± 1.69 mm (mean ± standard deviation). The average age was 58.3 ± 14.4 years old. Myopic maculopathy was categorized as mild (grades 0 and 1) and severe (grades 2, 3, and 4). The severe group had longer axial lengths than the mild group ( P  < 0.05). Moreover, the severe group exhibited thinner choroidal thickness than the mild group ( P  < 0.05). When subjects were grouped by axial elongation over median value within a year, the elongation group showed thinner central choroidal thickness than the non-elongation group (142.1 ± 91.9 vs. 82.9 ± 69.8, P  < 0.05). In conclusion, in patients with high myopia, the severity of maculopathy correlated with choroidal thickness and axial length. Thinner choroidal thickness was associated with axial elongation based on the baseline axial length.

PurposeTo evaluate the prevalence of dome-shaped macula (DSM) in highly myopic eyes among Chinese Han and to detect the correlation with myopic maculopathy and macular complications.MethodsA total of 736 Chinese Han patients (1384 eyes) with high myopia (refractive error≤6.0 diopters or axial length ≥26.5 mm) are reviewed based on information entered into a high-myopia database at Zhongshan Ophthalmic Centre. Subfoveal choroidal thickness (SFCT) and parafoveal choroidal thickness (PFCT) are measured. The prevalence of DSM in patients with myopic maculopathy is categorised from C0 to C4. Clinical features, including macular complications, SFCT and PFCT, are compared between myopic eyes with and without DSM.ResultsAmong the 1384 eyes, 149 (10.77%) show DSM. In highly myopic eyes without macular complications, the best corrected visual acuity is significantly worse in patients with DSM (p=0.002), and the ratio between subfoveal and parafoveal choroidal thickness (S/PCT) is significantly elevated in patients with DSM (p=0.021). The proportion of foveal schisis (17.24% vs 62.86%) is much lower in eyes with DSM compared with those without DSM. However, the proportions of extrafoveal schisis (39.66% vs 5.37%), foveal serous retinal detachment (SRD) (5.17% vs 0) and epiretinal membrane (ERM) (24.14% vs 10.74%) are much higher in eyes with DSM. The proportion of DSM was lower in C0 and C1, but higher proportion of DSM was found in C3 and C4.ConclusionsDSM is found in 10.77% of highly myopic eyes among Chinese Han. DSM might be a protective mechanism for foveal schisis and a risk factor for extrafoveal schisis, SRD and ERM.

To investigate annual myopia progression in individuals from South Indian states across different age groups, and its association with age of onset and severity of myopia. This retrospective study included the data of 6984 myopes (range: 1-30 years), who visited at least twice to LV Prasad Eye Institute and on whom a standard retinoscopy technique was performed to determine refractive error. Based on spherical equivalent (SE) refractive error, individuals were classified into mild, moderate, high and severe myopic groups. Myopia progression was calculated as difference between SE at 1-year follow-up visit and at baseline. To determine the age-specific myopia progression, individuals were further categorized as myopes who are at least 15 years or younger and those who are above 15. The mean annual progression of myopia was influenced by both the age group (p < 0.001) and severity type of myopia (p < 0.001). The overall mean myopia progression ranged from -0.07 ± 0.02 D (standard error) to -0.51 ± 0.02 D across different age groups with maximum change in refractive error noted in children aged 6-10 years and the least in adults aged 26-30 years. Myopia progression was greater in severe myopes, followed by high, moderate, mild myopes and in individuals aged ≤ 15 years compared to those aged >15 years (-0.45 ± 0.01 vs. 0.14 ± 0.01, p < 0.001). Severe myopes alone had similar annual myopia progression rate irrespective of age (i.e ≤15 and >15 years, p = 0.71). Early onset of myopia was associated with high myopia in adulthood. The magnitude of myopia progression in children from South Indian states is comparable to that of Caucasians and Chinese. The greater progression in 'severe myopes' across different age groups emphasize the need for regular follow-ups, monitoring axial lengths, and anti-myopia strategies to control myopia progression irrespective of the age and degree of myopia.

This study examined and compared outcomes of deep learning (DL) in identifying swept-source optical coherence tomography (OCT) images without myopic macular lesions [i.e., no high myopia (nHM) vs. high myopia (HM)], and OCT images with myopic macular lesions [e.g., myopic choroidal neovascularization (mCNV) and retinoschisis (RS)]. A total of 910 SS-OCT images were included in the study as follows and analyzed by k-fold cross-validation (k = 5) using DL's renowned model, Visual Geometry Group-16: nHM, 146 images; HM, 531 images; mCNV, 122 images; and RS, 111 images (n = 910). The binary classification of OCT images with or without myopic macular lesions; the binary classification of HM images and images with myopic macular lesions (i.e., mCNV and RS images); and the ternary classification of HM, mCNV, and RS images were examined. Additionally, sensitivity, specificity, and the area under the curve (AUC) for the binary classifications as well as the correct answer rate for ternary classification were examined. The classification results of OCT images with or without myopic macular lesions were as follows: AUC, 0.970; sensitivity, 90.6%; specificity, 94.2%. The classification results of HM images and images with myopic macular lesions were as follows: AUC, 1.000; sensitivity, 100.0%; specificity, 100.0%. The correct answer rate in the ternary classification of HM images, mCNV images, and RS images were as follows: HM images, 96.5%; mCNV images, 77.9%; and RS, 67.6% with mean, 88.9%.Using noninvasive, easy-to-obtain swept-source OCT images, the DL model was able to classify OCT images without myopic macular lesions and OCT images with myopic macular lesions such as mCNV and RS with high accuracy. The study results suggest the possibility of conducting highly accurate screening of ocular diseases using artificial intelligence, which may improve the prevention of blindness and reduce workloads for ophthalmologists.

Purpose: To compare the Visian Toric Implantable Collamer Lens (TICL), a toric phakic intraocular lens (IOL), and photorefractive keratectomy (PRK) in the correction of moderate to high myopic astigmatism. Methods: This prospective, randomized study consisted of 43 eyes implanted with the TICL (20 bilateral cases) and 45 eyes receiving PRK with mitomycin C (22 bilateral cases) with moderate to high myopia (−6.00 to −20.00 diopters [D] sphere) measured at the spectacle plane and 1.00 to 4.00 D of astigmatism. All patient treatment and follow-up occurred at the Naval Medical Center San Diego. Study follow-up was 1 day, 1 week, 1, 3, 6, and 12 months postoperative. Results: Mean best spectacle-corrected visual acuity (BSCVA), change in BSCVA, proportion of cases with improvement of 1 or more lines of BSCVA, proportion of cases with BSCVA and uncorrected visual acuity (UCVA) 20/12.5 or better, proportion of cases with BSCVA and UCVA 20/16 or better (6 months, 88% vs 54%, P=.002), and predictability ±1.00 D (6 months, 100% vs 67%, P<.001) were all significantly better in the TICL group than the PRK group at all time periods studied postoperatively. Similarly, contrast sensitivity, tested at both the 5% photopic level and the 25% mesopic level, was significantly better at all postoperative time points in the TICL group. Mean spherical equivalent refraction was closer to emmetropia (0.28±0.41 vs 0.76±0.86, P=.005), and predictability ±0.50 D and stability of manifest refraction (±0.50 D and ±1.00 D) were significantly better in the TICL group at all postoperative visits through 6 months. Mean astigmatism correction at 6 months was not significantly different between the two groups (0.52±0.33 vs 0.46±0.35, P=.450). Conclusions: The TICL performed better than PRK in all measures of safety (BSCVA), efficacy (UCVA), predictability, and stability in this comparison, supporting the TICL as a viable alternative to existing refractive surgical treatments. [J Refract Surg. 2007;23:853–867.]

Background Myopia is a growing global health issue. This study aims to determine the current status and determinants of primary and secondary school students with myopia in the Shekou District, and to propose reforms in myopia prevention. Methods Four thousand seven hundred and sixty-three students were involved in this retrospective study, and categorized by spherical equivalent into normal, low myopia, moderate myopia, and high myopia. Multinomial logistic regression and multiple linear regression analyses were conducted to examine factors on the severity of myopia and axial length [AL], respectively. Results The multinomial logistic regression model indicated, compared to the normal group, each additional year of age significantly increased the odds for low myopia (odds ratio [OR] = 1.285, 95% confidence interval [CI]: 1.122–1.472), moderate myopia (OR = 1.271, 95% CI: 1.074–1.502), and high myopia (OR = 1.411, 95% CI: 1.090–1.826). Compared to the Grade 1, the OR for low myopia showed a gradual increase across grades: Grade 3 (OR = 2.065, 95% CI: 1.394–3.058), Grade 4(OR = 2.184, 95% CI: 1.338–3.562), Grade 5(OR = 2.640, 95% CI: 1.438–4.850) and Grade 6 (OR = 2.239, 95% CI: 1.077–4.657); The OR for moderate myopia rose significantly from Grade 2 (OR = 2.239, 95% CI: 1.077–4.657), peaked at Grade 9 (OR = 90.445, 95% CI: 14.325–571.040), and remained elevated at Grade 12 (OR = 72.069, 95% CI: 3.818–1360.260); The OR for high myopia was significantly elevated in Grade 6 (OR = 11.490, 95% CI: 1.082–122.077) and Grade 9 (OR = 26.259, 95% CI: 1.429–482.616). The multiple linear regression model indicated that longer AL was significantly associated with older age (β = 0.109, 95% CI: 0.065–0.141), males(β = 0.533, 95% CI: 0.482–0.583), and higher grade level (the largest effect observed at Grade 9, β = 1.124, 95% CI: 0.792–1.455). Conclusion Most myopic students in Shekou District exhibited low or moderate myopia. Alleviating educational stress and implementing AL monitoring are the essential measures for myopia prevention. A comprehensive myopia prevention necessitates a two-pronged strategy combining educational reforms and medical interventions.

Purpose To analyse the outcomes of phacoemulsification in extreme axial myopia Methods Consecutive cases of phacoemulsification in eyes with axial length ≥ 30.0 mm from January 1, 2010 to Dec 31, 2013 in a tertiary referral eye hospital were retrospectively reviewed. A single intraocular lens (IOL) type was used for all cases. Main outcome measures included perioperative complications and refractive outcome. Results Two hundred and twenty-one eyes were identified. Intraoperatively, two eyes (0.9 %) had unstable capsular bag and three (1.4 %) had posterior capsular rupture. At a mean follow-up duration was 27.4 ± 14.6 months, three eyes (1.5 % of 198 eyes with no history of retinal detachment or macular hole) developed retinal detachment. There was an overall hyperopic shift with a mean biometry error of 0.45 ± 1.21 D in all eyes. The mean absolute biometry prediction error was 0.98 ± 0.83 D in all eyes, 1.11 ± 0.86 D and 0.85 ± 0.82 D in eyes receiving negative- and positive-power IOL, respectively ( p  = 0.042). A total of 61.2 % of eyes had refractive outcome within ± 1.0 D of target spherical equivalent. Regression analysis showed low IOL power as an independent predictor for greater postoperative absolute biometry error ( p  = 0.014). Conclusions We showed no increase in perioperative complications in eyes with extreme high axial myopia. In eyes with long axial length, implantation of IOL with lower power was associated with more hyperopic shift, which was more pronounced with negative-power IOL.

Background Myopia is a major cause of vision impairment. To improve the efficiency of myopia screening, this paper proposes a deep learning model, X -ENet, which combines the advantages of depthwise separable convolution and dynamic convolution to classify different severities of myopia. The proposed model not only enables precise extraction of detailed features from fundus images but also achieves lightweight processing, thereby improving both computational efficiency and classification accuracy. Approach First, fundus images are enhanced and preprocessed to improve feature extraction effectiveness and enhance the model’s generalization capability. Then, the model is trained using fivefold cross-validation, leveraging dynamic convolution and depthwise separable convolution to extract features from each fundus image and classify the severity of myopia. Next, Grad-CAM is employed to visualize the model’s decision-making process, highlighting the regions contributing to classification. Finally, a user-friendly GUI interface is developed to intuitively present the classification results, thereby enhancing the system’s usability and practical applicability. Results The experimental results show that the proposed method achieves an accuracy of 0.9104, a precision of 0.8154, a recall of 0.8177, an F1-score of 0.8147, and a specificity of 0.9376 in the classification of myopia severity. Significance The model significantly outperforms existing conventional deep learning models in terms of accuracy, demonstrating strong effectiveness and reliability.