Efficacy of anti-suppression therapy in improving binocular vision in children with small-angle Esotropia

Purpose: To evaluate the efficacy of anti-suppression exercises in children with small-angle esotropia in achieving binocular vision. Methods: A retrospective review of patients aged 3–8 years who underwent anti-suppression exercises for either monocular or alternate suppression between January 2016 and December 2021 was conducted. Patients with esotropia less than 15 prism diopters (PD) and visual acuity ≥ 6/12 were included. Patients with previous intra-ocular surgery or less than three-month follow-up were excluded. Success was defined as the development of binocular single vision (BSV) for distance, near, or both (measured clinically with either the 4 prism base out test or Worth four dot test) and maintained at two consecutive visits. Qualified success was defined as the presence of diplopia response for both distance and near. Additionally, improvement in near stereo acuity was measured using the Stereo Fly test. Results: Eighteen patients with a mean age of 5.4 ± 1.38 years (range 3–8 years) at the time of initiation of exercises were included in the study. The male female ratio was 10:8. The mean best corrected visual acuity was 0.18 LogMAR unit(s) and the mean spherical equivalent was +3.8 ± 0.14 diopters (D). The etiology of the esotropia was fully accommodative refractive esotropia (8), microtropia (1), post–operative infantile esotropia (4), partially accommodative esotropia (1), and post-operative partially accommodative esotropia (4). Patients received either office-based, home-based, or both modes of treatment for an average duration of 4.8 months (range 3–8). After therapy, BSV was achieved for either distance or near in 66.6 % of patients (95 % CI = 40.03–93.31 %). Binocular single vision for both distance and near was seen in 50 % of children. Qualified success was observed in 38.46% of patients. Persistence of suppression was observed in one patient (5.5 %)... (AU)

Visual function correlates of self-reported vision-related nighttime driving difficulties / La función visual se correlaciona con las dificultades de conducción nocturna relacionadas con la visión autoinformadas

Purpose: To investigate the visual function correlates of self-reported vision-related night driving difficulties among drivers. Methods: One hundred and seven drivers (age: 46.06 ± 8.24, visual acuity [VA] of 0.2logMAR or better) were included in the study. A standard vision and night driving questionnaire (VND-Q) was administered. VA and contrast sensitivity were measured under photopic and mesopic conditions. Mesopic VA was remeasured after introducing a peripheral glare source into the participants' field of view to enable computation of disability glare index. Regression analyses were used to assess the associations between VND-Q scores, and visual function measures. Results: The mean VND-Q score was -3.96±1.95 logit (interval scale score: 2.46±1.28). Simple linear regression models for photopic contrast sensitivity, mesopic VA, mesopic contrast sensitivity, and disability index significantly predicted VND-Q score (P<0.05), with mesopic VA and disability glare index accounting for the greatest variation (21 %) in VND-Q scores followed by photopic contrast sensitivity (19 %), and mesopic contrast sensitivity (15 %). A multiple regression model to determine the association between the predictors (photopic contrast sensitivity, mesopic VA, mesopic contrast sensitivity, and disability index) and VND-Q score yielded significant results, F (4, 102) = 8.58, P < 0.001, adj. R2 = 0.2224. Seeing dark-colored cars was the most challenging vision task. Conclusion: Changes in mesopic visual acuity, photopic and mesopic contrast sensitivity, as well as disability glare index are associated with and explain night driving-related visual difficulties. It is recommended to incorporate measurement of these visual functions into assessments related to driving performance.(AU)

Assessing the role of visual dysfunctions in the association between visual symptomatology and the use of digital devices / Evaluación del papel de las disfunciones visuales en la asociación entre la sintomatología visual y el uso de dispositivos digitales

Purpose: To evaluate the association between visual symptoms and use of digital devices considering the presence of visual dysfunctions. Methods: An optometric examination was conducted in a clinical sample of 346 patients to diagnose any type of visual anomaly. Visual symptoms were collected using the validated SQVD questionnaire. A threshold of 6 hours per day was used to quantify the effects of digital device usage and patients were divided into two groups: under and above of 35 years old. A multivariate logistic regression was employed to investigate the association between digital device use and symptoms, with visual dysfunctions considered as a confounding variable. Crude and the adjusted odds ratio (OR) were calculated for each variable. Results: 57.02 % of the subjects reported visual symptoms, and 65.02% exhibited some form of visual dysfunction. For patients under 35 years old, an association was found between having visual symptoms and digital device use (OR = 2.10, p = 0.01). However, after adjusting for visual dysfunctions, this association disappeared (OR = 1.44, p = 0.27) and the association was instead between symptoms and refractive dysfunction (OR = 6.52, p < 0.001), accommodative (OR = 10.47, p < 0.001), binocular (OR = 6.68, p < 0.001) and accommodative plus binocular dysfunctions (OR = 46.84, p < 0.001). Among patients over 35 years old, no association was found between symptoms and the use of digital devices (OR = 1.27, p = 0.49) but there was an association between symptoms and refractive dysfunction (OR = 3.54, p = 0.001). Conclusions: Visual symptoms are not dependent on the duration of digital device use but rather on the presence of any type of visual dysfunction: refractive, accommodative and/or binocular one, which should be diagnosed.(AU)

Study of stereopsis using a depth sensation detection platform equipped with computer vision technology (DALE3D) / Estudio de estereopsis mediante una plataforma de detección de sensaciones de profundidad equipada con tecnología de visión por ordenador (DALE3D)

Background and objectives: The invention described herein is a prototype based on computer vision technology that measures depth perception and is intended for the early examination of stereopsis. Materials and methods: The prototype (software and hardware) is a depth perception measurement system that consists on: (a) a screen showing stereoscopic models with a guide point that the subject must point to; (b) a camera capturing the distance between the screen and the subject's finger; and (c) a unit for recording, processing and storing the captured measurements. For test validation, the reproducibility and reliability of the platform were calculated by comparing results with standard stereoscopic tests. A demographic study of depth perception by subgroup analysis is shown. Subjective comparison of the different tests was carried out by means of a satisfaction survey. Results: We included 94 subjects, 25 children and 69 adults, with a mean age of 34.2 ± 18.9 years; 36.2 % were men and 63.8 % were women. The DALE3D platform obtained good repeatability with an interclass correlation coefficient (ICC) between 0.94 and 0.87, and coefficient of variation (CV) between 0.1 and 0.26. Threshold determining optimal and suboptimal results was calculated for Randot and DALE3D test. Spearman's correlation coefficient, between thresholds was not statistically significant (p value > 0.05). The test was considered more visually appealing and easier to use by the participants (90 % maximum score). Conclusions: The DALE3D platform is a potentially useful tool for measuring depth perception with optimal reproducibility rates. Its innovative design makes it a more intuitive tool for children than current stereoscopic tests. Nevertheless, further studies will be needed to assess whether the depth perception measured by the DALE3D platform is a sufficiently reliable parameter to assess stereopsis.(AU)

Binocular vision parameters and visual performance in bilateral keratoconus corrected with spectacles versus rigid gas-permeable contact lenses / Parámetros de visión binocular y rendimiento visual en queratocono bilateral corregido con gafas versus lentes de contacto rígidos permeables al gas

Purpose: To analyze binocular vision of individuals aged 18 to 35 years diagnosed with keratoconus, utilizing spectacles and rigid gas-permeable (RGP) contact lenses. Research was led by the Universidad Autónoma de Aguascalientes, México and Fundación Universitaria del Área Andina Pereira, Colombia. Methods: A single center, prospective non-randomized, comparative, interventional, open-label study, in which the differences in binocular vision performance with both spectacles and RGP contact lenses was carried out from December 2018 to December 2019. Sampling was performed according to consecutive cases with keratoconus that met the inclusion criteria until the proposed sample size was reached. Results: Rigid gas-permeable (RGP) contact lenses notably enhanced distance and near visual acuity in keratoconus patients compared to spectacles. Visual alignment analysis shows exophoria at both distances and is slightly higher with RGP contact lenses. The difference was statistically significant (p<0.05), with 82.5 % presenting compensated phoria with spectacles and pnly 42.50% with RGP contact lenses. Stereoscopic vision improved while wearing RGP contact lenses (42.59 %), although accommodation and accommodative flexibility remained within normal ranges. Conclusions: Patients with keratoconus fitted with RGP contact lenses have improved binocular vision skills such as visual acuity, stereopsis, and accommodative flexibility. However, even when the vergence and motor system is decompensated with respect to normal ranges, the range between break and recovery points for both fusional reserves and the near point of convergence (NPC) improves with the use of RGP contact lenses, giving indications of an adaptive condition of the motor system from the medium to the long term.(AU)

The severity of dry eye symptoms and risk factors among university students in Saudi Arabia: a cross-sectional study.

Dry eye syndrome (DES) is a tear film disorder caused by increased tear evaporation or decreased production. The heavy workload on the eye and the increased usage of digital screens may decrease blink frequency, leading to an increased evaporation rate and an upsurge in the incidence and severity of DES. This study aims to assess the severity of DES symptoms and the risk factors among university students. A cross-sectional study was conducted at Umm AlQura University to evaluate the severity of DES among students and explore its potential association with digital screen use. Validated questionnaires were used to assess the severity of DES and digital screen usage. The study included 457 participants, of which 13% had symptoms suggestive of severe DES. Furthermore, multiple risk factors had a significant association with the severity of DES, including gender, use of monitor filters, monitor and room brightness, and smoking habits. DES symptoms were prevalent among university students, particularly female students. Although there was no significant association with the duration of screen usage and collage distribution. Other factors however, such as the usage of screen monitors and the brightness of both the monitor and the room, were significantly associated with the severity of DES symptoms.

Brittle cornea syndrome: A novel mutation.

Purpose: To report the clinical, tomographic, histopathological and genetic findings of a patient with brittle cornea syndrome and a novel mutation in the ZNF469 gene likely implicated in the development of this disorder. Methods: A 64-year-old man presented with a two-year history of worsening vision in both eyes. The patient and his son were examined by imaging and genetic analysis. Results: The patient exhibited persistent ocular irritation, decreased vision, corneal epithelial defects and corneal stromal opacity. Confocal microscopy revealed that the anterior corneal stroma had a large amount of highly reflective and striated tissue. However, his son had no symptoms. Genetic analysis identified a heterozygous c.1781C > T:p.P594L variation in the ZNF469 gene. Conclusions: We reported a novel mutation in the ZNF469 gene (c.1781C > T:p.P594L) in a patient with brittle cornea syndrome from China, which enriched the spectrum of ZNF469 variants implicated in brittle cornea syndrome.

The mechanism of human color vision and potential implanted devices for artificial color vision.

Vision plays a major role in perceiving external stimuli and information in our daily lives. The neural mechanism of color vision is complicated, involving the co-ordinated functions of a variety of cells, such as retinal cells and lateral geniculate nucleus cells, as well as multiple levels of the visual cortex. In this work, we reviewed the history of experimental and theoretical studies on this issue, from the fundamental functions of the individual cells of the visual system to the coding in the transmission of neural signals and sophisticated brain processes at different levels. We discuss various hypotheses, models, and theories related to the color vision mechanism and present some suggestions for developing novel implanted devices that may help restore color vision in visually impaired people or introduce artificial color vision to those who need it.

LUMINA: Linguistic unified multimodal Indonesian natural audio-visual dataset.

The LUMINA (Linguistic Unified Multimodal Indonesian Natural Audio-Visual) Dataset is a carefully curated constrained audio-visual dataset designed to support research in the field of speech perception. Spoken exclusively in Indonesian, LUMINA contains high-quality audio-visual recordings featuring 14 native speakers, including 9 males and 5 females. Each speaker contributes approximately 1,000 sentences, producing a rich and diverse data collection. The recorded videos focus on facial recordings, capturing essential visual cues and expressions that accompany speech. This extensive dataset provides a valuable resource for understanding how humans perceive and process spoken language, paving the way for speech recognition and synthesis technology advancements.

Accessibility of and barriers to the use of eye health services in Kumasi Metropolis, Ghana.

BACKGROUND:  There is a high prevalence of vision impairment and blindness in Africa. The poor access to eye health services, among other barriers, has been found to have a considerable effect on the burden of avoidable vision loss and blindness, particularly in low- and middle-income countries. AIM:  To determine the accessibility of and barriers to the utilisation of eye health services in the Kumasi Metropolis of Ghana. SETTING:  A descriptive cross-sectional survey was conducted in the Kumasi Metropolis of the Ashanti Region in Ghana to identify barriers affecting the utilisation of eye health services. METHODS:  Convenience sampling was used to recruit participants visiting the eye clinics at five selected District Municipal Hospitals for the first time. Data were collected by means of questionnaires and analysed using Statistical Package for Social Sciences (SPSS). RESULTS:  Barriers faced by participants when accessing eye health services included distance to the clinic, cost of services, time spent away from work and/or school, self-medication and long waiting periods. CONCLUSION:  The study found that eye care services in the Kumasi Metropolis, Ghana are largely accessible, but underutilised. Improvement of public health education initiatives through engagement with community groups will also enhance uptake at health care facilities.Contribution: Underutilisation of health services in the Metropolis has been identified in the study and must be addressed by health managers in various sectors. Accessibility is relatively good but can further be improved especially for the elderly to be able to utilise health care services with ease.

Intelligent real-life key-pixel image detection system for early Arabic sign language learners.

Lack of an effective early sign language learning framework for a hard-of-hearing population can have traumatic consequences, causing social isolation and unfair treatment in workplaces. Alphabet and digit detection methods have been the basic framework for early sign language learning but are restricted by performance and accuracy, making it difficult to detect signs in real life. This article proposes an improved sign language detection method for early sign language learners based on the You Only Look Once version 8.0 (YOLOv8) algorithm, referred to as the intelligent sign language detection system (iSDS), which exploits the power of deep learning to detect sign language-distinct features. The iSDS method could overcome the false positive rates and improve the accuracy as well as the speed of sign language detection. The proposed iSDS framework for early sign language learners consists of three basic steps: (i) image pixel processing to extract features that are underrepresented in the frame, (ii) inter-dependence pixel-based feature extraction using YOLOv8, (iii) web-based signer independence validation. The proposed iSDS enables faster response times and reduces misinterpretation and inference delay time. The iSDS achieved state-of-the-art performance of over 97% for precision, recall, and F1-score with the best mAP of 87%. The proposed iSDS method has several potential applications, including continuous sign language detection systems and intelligent web-based sign recognition systems.

MCV-UNet: a modified convolution & transformer hybrid encoder-decoder network with multi-scale information fusion for ultrasound image semantic segmentation.

In recent years, the growing importance of accurate semantic segmentation in ultrasound images has led to numerous advances in deep learning-based techniques. In this article, we introduce a novel hybrid network that synergistically combines convolutional neural networks (CNN) and Vision Transformers (ViT) for ultrasound image semantic segmentation. Our primary contribution is the incorporation of multi-scale CNN in both the encoder and decoder stages, enhancing feature learning capabilities across multiple scales. Further, the bottleneck of the network leverages the ViT to capture long-range high-dimension spatial dependencies, a critical factor often overlooked in conventional CNN-based approaches. We conducted extensive experiments using a public benchmark ultrasound nerve segmentation dataset. Our proposed method was benchmarked against 17 existing baseline methods, and the results underscored its superiority, as it outperformed all competing methods including a 4.6% improvement of Dice compared against TransUNet, 13.0% improvement of Dice against Attention UNet, 10.5% improvement of precision compared against UNet. This research offers significant potential for real-world applications in medical imaging, demonstrating the power of blending CNN and ViT in a unified framework.

The real-time hand and object recognition for virtual interaction.

Recognizing hand-object interactions presents a significant challenge in computer vision. It arises due to the varying nature of hand-object interactions. Moreover, estimating the 3D position of a hand from a single frame can be problematic, especially when the hand obstructs the view of the object from the observer's perspective. In this article, we present a novel approach to recognizing objects and facilitating virtual interactions, using a steering wheel as an illustrative example. We propose a real-time solution for identifying hand-object interactions in eXtended reality (XR) environments. Our approach relies on data captured by a single RGB camera during a manipulation scenario involving a steering wheel. Our model pipeline consists of three key components: (a) a hand landmark detector based on the MediaPipe cross-platform hand tracking solution; (b) a three-spoke steering wheel model tracker implemented using the faster region-based convolutional neural network (Faster R-CNN) architecture; and (c) a gesture recognition module designed to analyze interactions between the hand and the steering wheel. This approach not only offers a realistic experience of interacting with steering-based mechanisms but also contributes to reducing emissions in the real-world environment. Our experimental results demonstrate the natural interaction between physical objects in virtual environments, showcasing precision and stability in our system.

Research on 3D virtual vision matching based on interactive color segmentation.

Given the prevalent issues surrounding accuracy and efficiency in contemporary stereo-matching algorithms, this research introduces an innovative image segmentation-based approach. The proposed methodology integrates residual and Swim Transformer modules into the established 3D Unet framework, yielding the Res-Swim-UNet image segmentation model. The algorithm estimates the disparateness of segmented outputs by employing regression techniques, culminating in a comprehensive disparity map. Experimental findings underscore the superiority of the proposed algorithm across all evaluated metrics. Specifically, the proposed network demonstrates marked improvements, with IoU and mPA enhancements of 2.9% and 162%, respectively. Notably, the average matching error rate of the algorithm registers at 2.02%, underscoring its efficacy in achieving precise stereoscopic matching. Moreover, the model's enhanced generalization capability and robustness underscore its potential for widespread applicability.

Computational image analysis of distortion, sharpness, and depth of field in a next-generation hybrid exoscopic and microsurgical operative platform.

Objective: The development of surgical microscope-associated cameras has given rise to a new operating style embodied by hybrid microsurgical and exoscopic operative systems. These platforms utilize specialized camera systems to visualize cranial neuroanatomy at various depths. Our study aims to understand how different camera settings in a novel hybrid exoscope system influence image quality in the context of neurosurgical procedures. Methods: We built an image database using captured cadaveric dissection images obtained with a prototype version of a hybrid (microsurgical/exoscopic) operative platform. We performed comprehensive 4K-resolution image capture using 76 camera settings across three magnification levels and two working distances. Computer algorithms such as structural similarity (SSIM) and mean squared error (MSE) were used to measure image distortion across different camera settings. We utilized a Laplacian filter to compute the overall sharpness of the acquired images. Additionally, a monocular depth estimation deep learning model was used to examine the image's capability to visualize the depth of deeper structures accurately. Results: A total of 1,368 high-resolution pictures were captured. The SSIM index ranged from 0.63 to 0.85. The MSE was nearly zero for all image batches. It was determined that the exoscope could accurately detect both the sharpness and depth based on the Laplacian filter and depth maps, respectively. Our findings demonstrate that users can utilize the full range of camera settings available on the exoscope, including adjustments to aperture, color saturation, contrast, sharpness, and brilliance, without introducing significant image distortions relative to the standard mode. Conclusion: The evolution of the camera incorporated into a surgical microscope enables exoscopic visualization during cranial base surgery. Our result should encourage surgeons to take full advantage of the exoscope's extensive range of camera settings to match their personal preferences or specific clinical requirements of the surgical scenario. This places the exoscope as an invaluable asset in contemporary surgical practice, merging high-definition imaging with ergonomic design and adaptable operability.

Dynamic Expansions and Retinal Expression of Spectrally Distinct Short-Wavelength Opsin Genes in Sea Snakes.

The photopigment-encoding visual opsin genes that mediate colour perception show great variation in copy number and adaptive function across vertebrates. An open question is how this variation has been shaped by the interaction of lineage-specific structural genomic architecture and ecological selection pressures. We contribute to this issue by investigating the expansion dynamics and expression of the duplicated Short-Wavelength-Sensitive-1 opsin (SWS1) in sea snakes (Elapidae). We generated one new genome, 45 resequencing datasets, 10 retinal transcriptomes, and 81 SWS1 exon sequences for sea snakes, and analysed these alongside 16 existing genomes for sea snakes and their terrestrial relatives. Our analyses revealed multiple independent transitions in SWS1 copy number in the marine Hydrophis clade, with at least three lineages having multiple intact SWS1 genes: the previously studied Hydrophis cyanocinctus and at least two close relatives of this species; H. atriceps-H. fasciatus; and an individual H. curtus. In each lineage, gene copy divergence at a key spectral tuning site resulted in distinct UV and Violet/Blue-sensitive SWS1 subtypes. Both spectral variants were simultaneously expressed in the retinae of H. cyanocinctus and H. atriceps, providing the first evidence that these SWS1 expansions confer novel phenotypes. Finally, chromosome annotation for nine species revealed shared structural features in proximity to SWS1 regardless of copy number. If these features are associated with SWS1 duplication, expanded opsin complements could be more common in snakes than is currently recognised. Alternatively, selection pressures specific to aquatic environments could favour improved chromatic distinction in just some lineages.

Highly Efficient Back-End-of-Line Compatible Flexible Si-Based Optical Memristive Crossbar Array for Edge Neuromorphic Physiological Signal Processing and Bionic Machine Vision.

The emergence of the Internet-of-Things is anticipated to create a vast market for what are known as smart edge devices, opening numerous opportunities across countless domains, including personalized healthcare and advanced robotics. Leveraging 3D integration, edge devices can achieve unprecedented miniaturization while simultaneously boosting processing power and minimizing energy consumption. Here, we demonstrate a back-end-of-line compatible optoelectronic synapse with a transfer learning method on health care applications, including electroencephalogram (EEG)-based seizure prediction, electromyography (EMG)-based gesture recognition, and electrocardiogram (ECG)-based arrhythmia detection. With experiments on three biomedical datasets, we observe the classification accuracy improvement for the pretrained model with 2.93% on EEG, 4.90% on ECG, and 7.92% on EMG, respectively. The optical programming property of the device enables an ultra-low power (2.8 × 10-13 J) fine-tuning process and offers solutions for patient-specific issues in edge computing scenarios. Moreover, the device exhibits impressive light-sensitive characteristics that enable a range of light-triggered synaptic functions, making it promising for neuromorphic vision application. To display the benefits of these intricate synaptic properties, a 5 × 5 optoelectronic synapse array is developed, effectively simulating human visual perception and memory functions. The proposed flexible optoelectronic synapse holds immense potential for advancing the fields of neuromorphic physiological signal processing and artificial visual systems in wearable applications.

Optimization of vision transformer-based detection of lung diseases from chest X-ray images.

BACKGROUND: Recent advances in Vision Transformer (ViT)-based deep learning have significantly improved the accuracy of lung disease prediction from chest X-ray images. However, limited research exists on comparing the effectiveness of different optimizers for lung disease prediction within ViT models. This study aims to systematically evaluate and compare the performance of various optimization methods for ViT-based models in predicting lung diseases from chest X-ray images. METHODS: This study utilized a chest X-ray image dataset comprising 19,003 images containing both normal cases and six lung diseases: COVID-19, Viral Pneumonia, Bacterial Pneumonia, Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS), and Tuberculosis. Each ViT model (ViT, FastViT, and CrossViT) was individually trained with each optimization method (Adam, AdamW, NAdam, RAdam, SGDW, and Momentum) to assess their performance in lung disease prediction. RESULTS: When tested with ViT on the dataset with balanced-sample sized classes, RAdam demonstrated superior accuracy compared to other optimizers, achieving 95.87%. In the dataset with imbalanced sample size, FastViT with NAdam achieved the best performance with an accuracy of 97.63%. CONCLUSIONS: We provide comprehensive optimization strategies for developing ViT-based model architectures, which can enhance the performance of these models for lung disease prediction from chest X-ray images.

Visual, ocular surface, and extraocular diagnostic criteria for determining the prevalence of computer vision syndrome: a cross-sectional smart-survey-based study.

Background: The American Optometric Association defines computer vision syndrome (CVS), also known as digital eye strain, as "a group of eye- and vision-related problems that result from prolonged computer, tablet, e-reader and cell phone use". We aimed to create a well-structured, valid, and reliable questionnaire to determine the prevalence of CVS, and to analyze the visual, ocular surface, and extraocular sequelae of CVS using a novel and smart self-assessment questionnaire. Methods: This multicenter, observational, cross-sectional, descriptive, survey-based, online study included 6853 complete online responses of medical students from 15 universities. All participants responded to the updated, online, fourth version of the CVS questionnaire (CVS-F4), which has high validity and reliability. CVS was diagnosed according to five basic diagnostic criteria (5DC) derived from the CVS-F4. Respondents who fulfilled the 5DC were considered CVS cases. The 5DC were then converted into a novel five-question self-assessment questionnaire designated as the CVS-Smart. Results: Of 10 000 invited medical students, 8006 responded to the CVS-F4 survey (80% response rate), while 6853 of the 8006 respondents provided complete online responses (85.6% completion rate). The overall CVS prevalence was 58.78% (n = 4028) among the study respondents; CVS prevalence was higher among women (65.87%) than among men (48.06%). Within the CVS group, the most common visual, ocular surface, and extraocular complaints were eye strain, dry eye, and neck/shoulder/back pain in 74.50% (n = 3001), 58.27% (n = 2347), and 80.52% (n = 3244) of CVS cases, respectively. Notably, 75.92% (3058/4028) of CVS cases were involved in the Mandated Computer System Use Program. Multivariate logistic regression analysis revealed that the two most statistically significant diagnostic criteria of the 5DC were ≥2 symptoms/attacks per month over the last 12 months (odds ratio [OR] = 204177.2; P <0.0001) and symptoms/attacks associated with screen use (OR = 16047.34; P <0.0001). The CVS-Smart demonstrated a Cronbach's alpha reliability coefficient of 0.860, Guttman split-half coefficient of 0.805, with perfect content and construct validity. A CVS-Smart score of 7-10 points indicated the presence of CVS. Conclusions: The visual, ocular surface, and extraocular diagnostic criteria for CVS constituted the basic components of CVS-Smart. CVS-Smart is a novel, valid, reliable, subjective instrument for determining CVS diagnosis and prevalence and may provide a tool for rapid periodic assessment and prognostication. Individuals with positive CVS-Smart results should consider modifying their lifestyles and screen styles and seeking the help of ophthalmologists and/or optometrists. Higher institutional authorities should consider revising the Mandated Computer System Use Program to avoid the long-term consequences of CVS among university students. Further research must compare CVS-Smart with other available metrics for CVS, such as the CVS questionnaire, to determine its test-retest reliability and to justify its widespread use.

Aflibercept or ranibizumab for diabetic macular edema.

Background: Vascular endothelial growth factor (VEGF) is the primary substance involved in retinal barrier breach. VEGF overexpression may cause diabetic macular edema (DME). Laser photocoagulation of the macula is the standard treatment for DME; however, recently, intravitreal anti-VEGF injections have surpassed laser treatment. Our aim was to evaluate the efficacy of intravitreal injections of aflibercept or ranibizumab for managing treatment-naive DME. Methods: This single-center, retrospective, interventional, comparative study included eyes with visual impairment due to treatment-naive DME that underwent intravitreal injection of either aflibercept 2 mg/0.05 mL or ranibizumab 0.5 mg/0.05 mL at Al-Azhar University Hospitals, Egypt between March 2023 and January 2024. Demographic data and full ophthalmological examination results at baseline and 1, 3, and 6 months post-injection were collected, including the best-corrected distance visual acuity (BCDVA) in logarithm of the minimum angle of resolution (logMAR) notation, slit-lamp biomicroscopy, dilated fundoscopy, and central subfield thickness (CST) measured using spectral-domain optical coherence tomography. Results: Overall, the 96 eyes of 96 patients with a median (interquartile range [IQR]) age of 57 (10) (range: 20-74) years and a male-to-female ratio of 1:2.7 were allocated to one of two groups with comparable age, sex, diabetes mellitus duration, and presence of other comorbidities (all P >0.05). There was no statistically significant difference in baseline diabetic retinopathy status or DME type between groups (both P >0.05). In both groups, the median (IQR) BCDVA significantly improved from 0.7 (0.8) logMAR at baseline to 0.4 (0.1) logMAR at 6 months post-injection (both P = 0.001), with no statistically significant difference between groups at all follow-up visits (all P >0.05). The median (IQR) CST significantly decreased in the aflibercept group from 347 (166) µm at baseline to 180 (233) µm at 6 months post-injection, and it decreased in the ranibizumab group from 360 (180) µm at baseline to 190 (224) µm at 6 months post-injection (both P = 0.001), with no statistically significant differences between groups at all follow-up visits (all P >0.05). No serious adverse effects were documented in either group. Conclusions: Ranibizumab and aflibercept were equally effective in achieving the desired anatomical and functional results in patients with treatment-naïve DME in short-term follow-up without significant differences in injection counts between both drugs. Larger prospective, randomized, double-blinded trials with longer follow-up periods are needed to confirm our preliminary results.