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Supplemental Digital Content is Available in the Text. Background: Optic disc drusen (ODD) represent an important differential diagnosis of papilledema caused by intracranial hypertension, but their distinction may be difficult in clinical practice. The aim of this study was to train, validate, and test a dedicated deep learning system (DLS) for binary classification of ODD vs papilledema (including various subgroups within each category), on conventional mydriatic digital ocular fundus photographs collected in a large international multiethnic population. Methods: This retrospective study included 4,508 color fundus images in 2,180 patients from 30 neuro-ophthalmology centers (19 countries) participating in the Brain and Optic Nerve Study with Artificial Intelligence (BONSAI) Group. For training and internal validation, we used 857 ODD images and 3,230 papilledema images, in 1,959 patients. External testing was performed on an independent data set (221 patients), including 207 images with ODD (96 visible and 111 buried), provided by 3 centers of the Optic Disc Drusen Studies Consortium, and 214 images of papilledema (92 mild-to-moderate and 122 severe) from a previously validated study. Results: The DLS could accurately distinguish between all ODD and papilledema (all severities included): area under the receiver operating characteristic curve (AUC) 0.97 (95% confidence interval [CI], 0.96–0.98), accuracy 90.5% (95% CI, 88.0%–92.9%), sensitivity 86.0% (95% CI, 82.1%–90.1%), and specificity 94.9% (95% CI, 92.3%–97.6%). The performance of the DLS remained high for discrimination of buried ODD from mild-to-moderate papilledema: AUC 0.93 (95% CI, 0.90–0.96), accuracy 84.2% (95% CI, 80.2%–88.6%), sensitivity 78.4% (95% CI, 72.2%–84.7%), and specificity 91.3% (95% CI, 87.0%–96.4%). Conclusions: A dedicated DLS can accurately distinguish between ODD and papilledema caused by intracranial hypertension, even when considering buried ODD vs mild-to-moderate papilledema. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore corneal curvature changes following strabismus surgery using a quadric surface fitting model to address ocular misalignment. Material and Methods: In this prospective cross-sectional study, 54 completed cases (84 eyes) of patients aged 6-60 years old (mean 10 years old) undergoing horizontal rectus muscle surgery were examined using placidobased keratometry with the Oculus Keratograph 5M system. Data on corneal curvature were collected one week preoperatively, and again one week, one month, and three months post-operation. Asphericity in the vertical meridian (Qy) and horizontal meridian (Qx), and surgically induced astigmatism (SIA) were calculated. Results: The 84 eyes included were categorized into three groups: horizontal muscle surgeries, oblique muscle surgery, and combined horizontal and oblique muscle surgeries. Significant corneal prolation (steep central, flat peripheral) was revealed in the vertical meridian (Qy) at 3 months postoperatively for lateral rectus (LR) recession in the first group (p < 0.001), and the mean SIA was 0.45 D (95% CI: 0.35-0.56 D). A similar effect was seen in the vertical meridian of the third group (p < 0.01), with a mean SIA at 3 months of 0.27 D (95% CI: 0.23-0.32 D). Conclusion: Lateral rectus muscle recession induces corneal vertical prolation for up to 3 months post-operation. Surgeons are thus advised to re-evaluate refraction and defer contact lens refitting, refractive surgery, and intraocular lens calculations for at least 3 months after the procedure. [ABSTRACT FROM AUTHOR]

The quality of ocular fundus photographs can affect the accuracy of the morphologic assessment of the optic nerve head (ONH), either by humans or by deep learning systems (DLS). In order to automatically identify ONH photographs of optimal quality, we have developed, trained, and tested a DLS, using an international, multicentre, multi-ethnic dataset of 5015 ocular fundus photographs from 31 centres in 20 countries participating to the Brain and Optic Nerve Study with Artificial Intelligence (BONSAI). The reference standard in image quality was established by three experts who independently classified photographs as of "good", "borderline", or "poor" quality. The DLS was trained on 4208 fundus photographs and tested on an independent external dataset of 807 photographs, using a multi-class model, evaluated with a one-vs-rest classification strategy. In the external-testing dataset, the DLS could identify with excellent performance "good" quality photographs (AUC = 0.93 (95% CI, 0.91-0.95), accuracy = 91.4% (95% CI, 90.0-92.9%), sensitivity = 93.8% (95% CI, 92.5-95.2%), specificity = 75.9% (95% CI, 69.7-82.1%) and "poor" quality photographs (AUC = 1.00 (95% CI, 0.99-1.00), accuracy = 99.1% (95% CI, 98.6-99.6%), sensitivity = 81.5% (95% CI, 70.6-93.8%), specificity = 99.7% (95% CI, 99.6-100.0%). "Borderline" quality images were also accurately classified (AUC = 0.90 (95% CI, 0.88-0.93), accuracy = 90.6% (95% CI, 89.1-92.2%), sensitivity = 65.4% (95% CI, 56.6-72.9%), specificity = 93.4% (95% CI, 92.1-94.8%). The overall accuracy to distinguish among the three classes was 90.6% (95% CI, 89.1-92.1%), suggesting that this DLS could select optimal quality fundus photographs in patients with neuro-ophthalmic and neurological disorders affecting the ONH.

Aim: To investigate the relationship between the levels of prostaglandin E2 (PGE2) in tears and dry eye disease severity based on both clinical symptoms and signs., Methods: Tear samples were collected from 36 non-Sjögren syndrome dry eye patients (10 males and 26 females, mean age 50.11±11.17y). All participants completed the Ocular Surface Disease Index (OSDI) questionnaire and underwent a detailed ophthalmic examination including, tear film breakup time (TBUT), ocular surface fluorescein staining, Schirmer I test, and meibomian gland assessment. The level of PGE2 in tears was measured using enzyme-linked immunosorbent assay (ELISA). The independent associations between tear PGE2 levels and other variables including demographics, OSDI scores, TBUT, Schirmer scores, ocular surface staining scores, and stage of meibomian gland dysfunction (MGD) were evaluated using linear regression analysis., Results: The mean PGE2 level in tears of dry eye patients was 537.85±234.02 pg/mL. The tear PGE2 levels significantly positively correlated with OSDI scores ( R =0.608, P <0.001), however, they did not significantly associate with TBUT ( R =0.153, P =0.373), Schirmer scores ( R =-0.098, P =0.570), ocular surface staining scores ( R =0.282, P =0.095), and stage of MGD ( R =-0.107, P =0.535). Male sex was significantly negatively correlated with tear PGE2 levels., Conclusion: The levels of PGE2 in tears are positively correlated with dry eye symptoms. However, no significant association was found between tear PGE2 levels and the results of other common dry eye diagnostic tests.

Objective: To study the factors associated with dengue prevention and control in Moo 6 (the 6th village) and Moo 7 of Tambon Kaeng-phak-kut, Thaluang District, Lopburi Province., Material and Method: The authors reviewed the raw data collected by public health officers and village health volunteers (VHVs) as their routine tasks. The authors analyzed the data, 30 dwellings per each village, to compare the demographics, knowledge, attitude, and practice of subjects from Moo 6, a dengue-outbreak community, with that from Moo 7, a control group, as well as larval indices between these 2 studied groups. The present retrospective study is approved by Siriraj Institutional Review Board, Certificate of Approval No. Si393/2012., Results: Both groups of subjects had no statistically significant difference in basic dengue knowledge (p = 0.862), attitude towards dengue prevention and control, practical knowledge (p = 0.457), and actual practice to eliminate Aedes larvae and prevent it laying eggs, except for the practice of managing water container in bathroom or toilet (p = 0.015). On the other hand, dengue incidence and larval indices of both villages were apparently different., Conclusion: Although incorrect basic dengue and practical knowledge of subjects from both villages were similar dengue outbreak in Moo 6 of Tambon Kaeng-phak-kut was superior. It may be due to difference in actual practice on larval elimination in water container in bathroom or toilet as well as other factors other than personal factors such as public services, public places, and community surroundings.