Prevalence and Risk Factors of Dry Eye Disease in the South of Palestine.

Background: The prevalence of dry eye disease (DED) is rising globally and needs to be urgently addressed by medical professionals because it lowers patients' quality of life. There are as yet no available data in the literature about the prevalence of and risk factors for DED in the Gaza Strip, a gap that the present study seeks to address. Methods: A cross-sectional study was carried out between March and August 2022 in Gaza governorates using a proportional stratified sampling technique. Only Gazan individuals ≥ 18 years old and able to follow the instructions were included. The Ocular Surface Disease Index (OSDI) questionnaire, which has previously been translated into Arabic and validated, was applied to evaluate DED symptoms. Subjective clinical tests for DED conducted were tear meniscus height (TMH), meibomian gland dysfunctions (MGDs), Marx line (ML), conjunctival Lissamine green staining (LGS), tear film break-up time test (TBUT), corneal fluorescein staining (CFS) and Schirmer II tear test (STT). DED was defined based on an Arab-OSDI score ≥ 13 and at least one positive clinical sign. Results: A total of 426 participants were assessed from four areas (North Gaza Strip, 82; Gaza City, 147; Mid-Zone Gaza Strip, 62; South Gaza Strip, 135). The prevalence of DED in the present study was 31.5% (95% CI: 27.1, 36.1). Age > 50 years old (odds ratio [OR] = 10.45; 95% CI: 2.95, 37.05; P < 0.001), female gender (OR = 3.24; 95% CI: 1.40, 7.52, P = 0.006), menopause or pregnancy (OR = 2.59; 95% CI: 1.25, 5.35; P = 0.03) and pharmacotherapy (artificial tears; OR = 9.91; 95% CI: 2.77, 35.46; P < 0.001) were each associated with DED symptoms. South Gaza Strip (OR = 0.04; 95% CI: 0.01, 0.12; P < 0.001), unemployed (OR = 11.67; 95% CI: 1.43, 95.44; P = 0.02), non-consumption of caffeine (OR = 0.40; 95% CI: 0.19, 0.88; P = 0.02) and TMH < 0.2 (OR = 1.80; 95% CI: 1.02, 3.19; P = 0.04) were associated with TBUT < 5 s. LGS was associated with those > 50 years old (OR = 2.70; 95% CI: 1.38, 5.28; P = 0.004), previous refractive or ocular surface surgeries (OR = 2.97; 95% CI: 1.34, 6.59; P = 0.008) and CFS ≥ 1 (OR = 1.91; 95% CI: 1.07, 3.44; P = 0.03). Conclusion: Various aspects of DED were linked with different risk factors, suggesting that DED subtypes have different underlying pathophysiologies.

The validity and reliability of the Arabic version of the ocular surface disease index (OSDI) questionnaire in a sample of the Gazan population: a study from Palestine.

PURPOSE: To develop an Arabic version of OSDI for the Gazan population. METHODS: A cross-sectional observational study was conducted using a convenience sample technique. The translation procedure included five stages: forward translation, revision of translation, backward translation, refinement of translation, and a final test of the pre-final version. The final sets of questionnaires were constructed using an online JotForm platform. The online platform was chosen to automatically calculate the questionnaire's final overall score. Overall, 260 participants were instructed to fill out the English and the Arab-OSDI version twice to conduct the reliability of the translated version and repeatability evaluation. RESULTS: The mean age of the participants was 33.45 ± 11.74 years old. Cronbach's alpha for all items was greater than 0.80, except for the "blurred vision" and "deteriorating vision" items (0.77 and 0.74, respectively). The mean overall score difference between the English-OSDI and Arab-OSDI was 0.86 based on the Bland-Altman chart. For repeatability, no significant difference in the overall scores between the two repeats of the Arab-OSDI (p = 0.632). The Arab-OSDI overall score (sessions 1 and 2) has a clinical difference (bias) of 0.21. Using the varimax rotation method, only three factors (ocular symptoms, vision-related function, and environmental triggers) had eigenvalues greater than one in the structure of the Arab-OSDI. CONCLUSION: The Arab-OSDI is an appropriate, reliable, and repeatable tool for the determination of dry eye symptoms, ocular discomfort, and quality of life in the Gazan population. This version could remove the language barrier in answering OSDI items more easily.

Postsurgery Classification of Best-Corrected Visual Acuity Changes Based on Pterygium Characteristics Using the Machine Learning Technique.

INTRODUCTION: Early detection of visual symptoms in pterygium patients is crucial as the progression of the disease can cause visual disruption and contribute to visual impairment. Best-corrected visual acuity (BCVA) and corneal astigmatism influence the degree of visual impairment due to direct invasion of fibrovascular tissue into the cornea. However, there were different characteristics of pterygium used to evaluate the severity of visual impairment, including fleshiness, size, length, and redness. The innovation of machine learning technology in visual science may contribute to developing a highly accurate predictive analytics model of BCVA outcomes in postsurgery pterygium patients. AIM: To produce an accurate model of BCVA changes of postpterygium surgery according to its morphological characteristics by using the machine learning technique. Methodology. A retrospective of the secondary dataset of 93 samples of pterygium patients with different pterygium attributes was used and imported into four different machine learning algorithms in RapidMiner software to predict the improvement of BCVA after pterygium surgery. RESULTS: The performance of four machine learning techniques were evaluated, and it showed the support vector machine (SVM) model had the highest average accuracy (94.44% ± 5.86%), specificity (100%), and sensitivity (92.14% ± 8.33%). CONCLUSION: Machine learning algorithms can produce a highly accurate postsurgery classification model of BCVA changes using pterygium characteristics.

Comparison of Dry Eye Parameters between Diabetics and Non-Diabetics in District of Kuantan, Pahang.

INTRODUCTION: Diabetes may affect the human body's systems and organs, including the eye. Diabetic retinopathy is the 5th leading cause of blindness globally. Diabetic subjects demonstrated dry eye symptoms that were also supported by the low values of the clinical tests. PURPOSE: This study aimed to compare the dry eye symptoms and signs between diabetics and non-diabetics and tear functions between diabetic subjects with and without dry eye. METHODS: This retrospective study was based on the observation of 643 medical files. Using a convenience sampling method, 88 subjects were found to report diabetes mellitus. The information extracted from the files included: date of first examination, age at first visit, gender, past ocular history, systemic disease, symptoms of dry eye disease and details of clinical diagnostic signs. Non-contact lens wearers were excluded. A group of 88, age and gender matched, control subjects were included for this comparison study. RESULTS: The percentage of dry eye symptoms was higher in diabetic subjects (15.9%) compared with non-diabetic subjects (13.6%; p<0.001). The percentage of dry eye symptoms was also higher in diabetics with dry eye (63%) than in diabetics without dry eye (36.9%; p<0.001). Tear break up time was significantly different between diabetics and non-diabetics (p<0.001) and between diabetics with and without dry eye (p=0.046). The corneal staining was significantly different between diabetic subjects with and without dry eye (p=0.028). CONCLUSION: Dry eye symptoms were significantly associated with diabetics. Tear break up time was significantly shorter in diabetics with dry eye compared to diabetics without dry eye.

Zone specific fractal dimension of retinal images as predictor of stroke incidence.

Fractal dimensions (FDs) are frequently used for summarizing the complexity of retinal vascular. However, previous techniques on this topic were not zone specific. A new methodology to measure FD of a specific zone in retinal images has been developed and tested as a marker for stroke prediction. Higuchi's fractal dimension was measured in circumferential direction (FDC) with respect to optic disk (OD), in three concentric regions between OD boundary and 1.5 OD diameter from its margin. The significance of its association with future episode of stroke event was tested using the Blue Mountain Eye Study (BMES) database and compared against spectrum fractal dimension (SFD) and box-counting (BC) dimension. Kruskal-Wallis analysis revealed FDC as a better predictor of stroke (H = 5.80, P = 0.016, α = 0.05) compared with SFD (H = 0.51, P = 0.475, α = 0.05) and BC (H = 0.41, P = 0.520, α = 0.05) with overall lower median value for the cases compared to the control group. This work has shown that there is a significant association between zone specific FDC of eye fundus images with future episode of stroke while this difference is not significant when other FD methods are employed.

Cross-cultural translation and validation of the Malay version of the Swanson, Nolan, and Pelham Parent Rating Scale of attention deficit hyperactivity disorders symptoms among Malaysian probands: A preliminary study.

The aim of this study is to evaluate the psychometric properties of the Malay version of the Swanson, Nolan, and Pelham Parent Rating Scale of attention deficit hyperactivity disorders (ADHD) symptoms (M-SNAP-IV). For this purpose, the SNAP-IV scale was translated into the Malay language and was pilot-tested on 91 parents of children aged 8 to 11 years (ADHD [n = 36] and non-ADHD children [n = 55]). The findings depicted that the M-SNAP-IV has excellent content validity, internal consistency, and test-retest reliability. The M-SNAP-IV is a valid and reliable screening tool to detect ADHD symptoms in children and has the advantages to assess the specific presentation of ADHD.

COVID-19 Deep Learning Prediction Model Using Publicly Available Radiologist-Adjudicated Chest X-Ray Images as Training Data: Preliminary Findings.

The key component in deep learning research is the availability of training data sets. With a limited number of publicly available COVID-19 chest X-ray images, the generalization and robustness of deep learning models to detect COVID-19 cases developed based on these images are questionable. We aimed to use thousands of readily available chest radiograph images with clinical findings associated with COVID-19 as a training data set, mutually exclusive from the images with confirmed COVID-19 cases, which will be used as the testing data set. We used a deep learning model based on the ResNet-101 convolutional neural network architecture, which was pretrained to recognize objects from a million of images and then retrained to detect abnormality in chest X-ray images. The performance of the model in terms of area under the receiver operating curve, sensitivity, specificity, and accuracy was 0.82, 77.3%, 71.8%, and 71.9%, respectively. The strength of this study lies in the use of labels that have a strong clinical association with COVID-19 cases and the use of mutually exclusive publicly available data for training, validation, and testing.

Prediction of Changes in Visual Acuity and Contrast Sensitivity Function by Tissue Redness after Pterygium Surgery.

PURPOSE: The goal of this study was to predict visual acuity (VA) and contrast sensitivity function (CSF) with tissue redness grading after pterygium surgery. MATERIALS AND METHODS: A total of 67 primary pterygium participants were selected from patients who visited an ophthalmology clinic. We developed a semi-automated computer program to measure the pterygium fibrovascular redness from digital pterygium images. The final outcome of this software is a continuous scale grading of 1 (minimum redness) to 3 (maximum redness). The region of interest (ROI) was selected manually using the software. Reliability was determined by repeat grading of all 67 images, and its association with CSF and VA was examined. RESULTS: The mean and standard deviation of redness of the pterygium fibrovascular images was 1.88 ± 0.55. Intra-grader and inter-grader reliability estimates were high with intraclass correlation ranging from 0.97 to 0.98. The new grading was positively associated with CSF (p < 0.01) and VA (p < 0.01). The redness grading was able to predict 25% and 23% of the variance in the CSF and the VA, respectively. CONCLUSIONS: The new grading of pterygium fibrovascular redness can be reliably measured from digital images and showed a good correlation with CSF and VA. The redness grading can be used in addition to the existing pterygium grading.

Retinal Vasculature Fractal Dimension Measures Vessel Density.

PURPOSE: The goal of this study was to provide the empirical evidence of fractal dimension as an indirect measure of retinal vasculature density. MATERIALS AND METHODS: Two hundred retinal samples of right eye [57.0% females (n = 114) and 43.0% males (n = 86)] were selected from baseline visit. A custom-written software was used for vessel segmentation. Vessel segmentation is the process of transforming two-dimensional color images into binary images (i.e. black and white pixels). The circular area of approximately 2.6 optic disc radii surrounding the center of optic disc was cropped. The non-vessels fragments were removed. FracLac was used to measure the fractal dimension and vessel density of retinal vessels. RESULTS: This study suggested that 14.1% of the region of interest (i.e. approximately 2.6 optic disk radii) comprised retinal vessel structure. Using correlation analysis, vessel density measurement and fractal dimension estimation are linearly and strongly correlated (R = 0.942, R(2) = 0.89, p < 0.001). Polynomial regression model suggests quadratic regression as the best fit for our data (linear: R(2) = 0.1024, 198 d.f., p < 0.001, quadratic: R(2) = 0.1236, 197 d.f., p < 0.001, cubic: R(2) = 0.1236, 196 d.f., p < 0.001). CONCLUSIONS: This study demonstrated the ability of vessel density measurement to detect the changes in the morphology of retinal microvascular associated with increasing age. Thus, vessel density can be suggested to be another parameter in the quantification of retinal microvasculature.

A method for visualization of fine retinal vascular pulsation using nonmydriatic fundus camera synchronized with electrocardiogram.

Pulsatile changes in retinal vascular geometry over the cardiac cycle have clinical implication for diagnosis of ocular and systemic vascular diseases. In this study, we report a Vesselness Mapping of Retinal Image Sequence (VMRS) methodology to visualize the vessel pulsation and quantify the pulsatile motions in the cardiac cycle. Retinal images were recorded in an image sequence corresponding to 8 segments of the cardiac cycle using a nonmydriatic fundus camera (Canon CR45, Canon Inc., Japan) modified with ECG-synchronization. Individual cross-sectional vessel diameters were measured separately and the significance of the variations was tested statistically by repeated measures analysis of variance (ANOVA). The graders observed an improved quality of vessel pulsation on a wide region around the optic disk using the VMRS. Individual cross- sectional vessel diameter measurement after visualization of pulsatile motions resulted in the detection of more significant diameter change for both arterioles (3.3 µm, P = 0.001) and venules (6.6 µm, P < 0.001) compared to individual measurement without visualization of the pulsatile motions (all P values > 0.05), showing an increase of 2.1 µm and 4.7 µm for arterioles and venules, respectively.

Does retinal vascular geometry vary with cardiac cycle?

PURPOSE: Changes in retinal vascular parameters have been shown to be associated with systemic vascular diseases. In this study, we assessed the physiologic variations in retinal vascular measurements during the cardiac cycle. METHODS: Fundus images were taken using electrocardiogram-synchronized retinal camera at nine distinct cardiac points from 15 healthy volunteers (135 images). Analyses of retinal vessel geometric measures, including retinal vessel caliber (individual and summary), tortuosity, branching angle, length-diameter ratio (LDR), and optimality deviation, were performed using semiautomated computer software. Repeated-measures ANOVAs were used to obtain the means and to estimate the variation of each cardiac point compared with cardiac point 1. RESULTS: There was a significant variation of the caliber of the individual arteriolar and venular vessels. However, there was no significant variation found for vessel caliber summary, represented by the central retinal arteriolar equivalent (CRAE) and the central retinal venular equivalent (CRVE). There was also no significant variation found for tortuosity and branching angle, and LDR showed none or very little variations at different cardiac points: variations in caliber ranges between 0 and 4.1%, tortuosity 0 and 1.5%, branching angle 0 and 3.5%, and LDR 0 and 2%; all values for variations, P > 0.1; linear trend, P > 0.5; and nonlinear trend, P > 0.8. CONCLUSIONS: This study showed that there were minimal variations in the CRAE, CRVE, tortuosity, and branching angle that are clinically used for two-dimensional measures of retinal vascular geometry during cardiac cycles. However, there was significant variation in the caliber of the individual vessels over the cardiac cycle.