Differentiating stages of functional vision loss from glaucoma using the Disc Damage Likelihood Scale and cup:disc ratio.

BACKGROUND: Glaucoma staging is critical for treatment planning but has rarely been tested in severe/end-stage disease. We compared the performance of the Disc Damage Likelihood Scale (DDLS) and cup:disc ratio (CDR) using a functional glaucoma staging system (GSS) as the reference standard. METHODS: Post hoc analysis of a randomised controlled trial at the Eye Department of Kilimanjaro Christian Medical Centre, Tanzania. Eligible participants (aged ≥18 years) with open-angle glaucoma, intraocular pressure (IOP) of >21 mm Hg, were randomised to timolol 0.5% eye drops or selective laser trabeculoplasty. Fundoscopy established vertical and horizontal CDRs and DDLS. Visual acuity and static visual fields were graded (GSS). The study used area under the receiver operating characteristic (AROC) curves and Spearman's rank correlation coefficients to compare staging systems. Logistic regression with generalised estimating equations determined risk factors of functional severe/end-stage glaucoma. RESULTS: 382 eyes (201 participants) were evaluated; 195 (51%) had severe or end-stage glaucoma; mean IOP was 26.7 (SD 6.9) mm Hg. DDLS yielded an AROC of 0.90 (95% CI 0.87 to 0.93), vertical cup:disc ratio (vCDR) of 0.88 (95% CI 0.85 to 0.91, p=0.048) for identifying severe/end-stage disease. Correlation coefficients comparing GSS to DDLS and vCDRs were 0.73 and 0.71, respectively. Advanced structural stages, vision impairment, higher IOP and less financial resources were risk factors of functional severe/end-stage glaucoma. CONCLUSION: This study indicates that both structural staging systems can differentiate severe/end-stage glaucoma from less severe disease, with a moderate advantage of DDLS over CDR. Clinical examination of the optic disc plays an important role in addition to functional assessment when managing severe/end-stage glaucoma.

Automatic retinal image analysis methods using colour fundus images for screening glaucomatous optic neuropathy.

OBJECTIVES: Train an automatic retinal image analysis (ARIA) method to screen glaucomatous optic neuropathy (GON) on non-mydriatic retinal images labelled with the additional results of optical coherence tomography (OCT) and assess different models for the GON classification. METHODS: All the images were obtained from the hospital for training and 10-fold cross-validation. Two methods were used to improve the classification performance: (1) using images labelled with the additional results of OCT as the reference standard and (2) generating models using retinal features from the entire images, the region of interest (ROI) of the optic disc, and the ROI of the macula, and the combination of all the features. RESULTS: Overall, we collected 1338 images with paired OCT scans. In 10-fold validation, ARIA achieved sensitivities of 92.2 %, 92.7% and 85.7%, specificities of 88.8%, 86.7% and 80.2% and accuracies of 90.6%, 89.9% and 83.1% using the retinal features from the entire images, the ROI of the optic disc and the ROI of the macula, respectively. We found the model combining all the features has the best classification performance and obtained a sensitivity of 92.5%, a specificity of 92.1% and an accuracy of 92.4%, which is significantly different from other models (p<0.001). CONCLUSION: We used two methods to improve the classification performance and found the best model to detect glaucoma on colour fundus retinal images. It can become a cost-effective and relatively more accurate glaucoma screening tool than conventional methods.

Application of artificial intelligence system for screening multiple fundus diseases in Chinese primary healthcare settings: a real-world, multicentre and cross-sectional study of 4795 cases.

BACKGROUND/AIMS: This study evaluates the performance of the Airdoc retinal artificial intelligence system (ARAS) for detecting multiple fundus diseases in real-world scenarios in primary healthcare settings and investigates the fundus disease spectrum based on ARAS. METHODS: This real-world, multicentre, cross-sectional study was conducted in Shanghai and Xinjiang, China. Six primary healthcare settings were included in this study. Colour fundus photographs were taken and graded by ARAS and retinal specialists. The performance of ARAS is described by its accuracy, sensitivity, specificity and positive and negative predictive values. The spectrum of fundus diseases in primary healthcare settings has also been investigated. RESULTS: A total of 4795 participants were included. The median age was 57.0 (IQR 39.0-66.0) years, and 3175 (66.2%) participants were female. The accuracy, specificity and negative predictive value of ARAS for detecting normal fundus and 14 retinal abnormalities were high, whereas the sensitivity and positive predictive value varied in detecting different abnormalities. The proportion of retinal drusen, pathological myopia and glaucomatous optic neuropathy was significantly higher in Shanghai than in Xinjiang. Moreover, the percentages of referable diabetic retinopathy, retinal vein occlusion and macular oedema in middle-aged and elderly people in Xinjiang were significantly higher than in Shanghai. CONCLUSION: This study demonstrated the dependability of ARAS for detecting multiple retinal diseases in primary healthcare settings. Implementing the AI-assisted fundus disease screening system in primary healthcare settings might be beneficial in reducing regional disparities in medical resources. However, the ARAS algorithm must be improved to achieve better performance. TRIAL REGISTRATION NUMBER: NCT04592068.

Validation of a deep learning system for the detection of diabetic retinopathy in Indigenous Australians.

BACKGROUND/AIMS: Deep learning systems (DLSs) for diabetic retinopathy (DR) detection show promising results but can underperform in racial and ethnic minority groups, therefore external validation within these populations is critical for health equity. This study evaluates the performance of a DLS for DR detection among Indigenous Australians, an understudied ethnic group who suffer disproportionately from DR-related blindness. METHODS: We performed a retrospective external validation study comparing the performance of a DLS against a retinal specialist for the detection of more-than-mild DR (mtmDR), vision-threatening DR (vtDR) and all-cause referable DR. The validation set consisted of 1682 consecutive, single-field, macula-centred retinal photographs from 864 patients with diabetes (mean age 54.9 years, 52.4% women) at an Indigenous primary care service in Perth, Australia. Three-person adjudication by a panel of specialists served as the reference standard. RESULTS: For mtmDR detection, sensitivity of the DLS was superior to the retina specialist (98.0% (95% CI, 96.5 to 99.4) vs 87.1% (95% CI, 83.6 to 90.6), McNemar's test p<0.001) with a small reduction in specificity (95.1% (95% CI, 93.6 to 96.4) vs 97.0% (95% CI, 95.9 to 98.0), p=0.006). For vtDR, the DLS's sensitivity was again superior to the human grader (96.2% (95% CI, 93.4 to 98.6) vs 84.4% (95% CI, 79.7 to 89.2), p<0.001) with a slight drop in specificity (95.8% (95% CI, 94.6 to 96.9) vs 97.8% (95% CI, 96.9 to 98.6), p=0.002). For all-cause referable DR, there was a substantial increase in sensitivity (93.7% (95% CI, 91.8 to 95.5) vs 74.4% (95% CI, 71.1 to 77.5), p<0.001) and a smaller reduction in specificity (91.7% (95% CI, 90.0 to 93.3) vs 96.3% (95% CI, 95.2 to 97.4), p<0.001). CONCLUSION: The DLS showed improved sensitivity and similar specificity compared with a retina specialist for DR detection. This demonstrates its potential to support DR screening among Indigenous Australians, an underserved population with a high burden of diabetic eye disease.

Ensemble of deep convolutional neural networks is more accurate and reliable than board-certified ophthalmologists at detecting multiple diseases in retinal fundus photographs.

AIMS: To develop an algorithm to classify multiple retinal pathologies accurately and reliably from fundus photographs and to validate its performance against human experts. METHODS: We trained a deep convolutional ensemble (DCE), an ensemble of five convolutional neural networks (CNNs), to classify retinal fundus photographs into diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and normal eyes. The CNN architecture was based on the InceptionV3 model, and initial weights were pretrained on the ImageNet dataset. We used 43 055 fundus images from 12 public datasets. Five trained ensembles were then tested on an 'unseen' set of 100 images. Seven board-certified ophthalmologists were asked to classify these test images. RESULTS: Board-certified ophthalmologists achieved a mean accuracy of 72.7% over all classes, while the DCE achieved a mean accuracy of 79.2% (p=0.03). The DCE had a statistically significant higher mean F1-score for DR classification compared with the ophthalmologists (76.8% vs 57.5%; p=0.01) and greater but statistically non-significant mean F1-scores for glaucoma (83.9% vs 75.7%; p=0.10), AMD (85.9% vs 85.2%; p=0.69) and normal eyes (73.0% vs 70.5%; p=0.39). The DCE had a greater mean agreement between accuracy and confident of 81.6% vs 70.3% (p<0.001). DISCUSSION: We developed a deep learning model and found that it could more accurately and reliably classify four categories of fundus images compared with board-certified ophthalmologists. This work provides proof-of-principle that an algorithm is capable of accurate and reliable recognition of multiple retinal diseases using only fundus photographs.

Red filter meibography by smartphones in patients with meibomian gland dysfunction: a validity and reliability study.

OBJECTIVE: The objective of this study is to determine the validity and reliability of the red filter meibography by smartphone compared with infrared in assessing meibomian gland drop-out. METHODS AND ANALYSIS: An analytical cross-sectional study was done with a total of 35 subjects (68 eyes) with suspected MGD based on symptoms and lid morphological abnormalities. Meibomian glands were photographed using two smartphones (Samsung S9 and iPhone XR) on a slit-lamp with added red filter. Images were assessed subjectively using meiboscore by the two raters and drop-out percentages were assessed by ImageJ. RESULTS: There was no agreement in meiboscore and a minimal level of agreement in drop-out percentages between red filter meibography and infrared. Inter-rater reliability showed no agreement between two raters. Intra-rater reliability demonstrated weak agreement in rater 1 and no agreement in rater 2. CONCLUSION: Validity of the red filter meibography technique by smartphones is not yet satisfactory in evaluating drop-out. Further improvement on qualities of images must be done and research on subjective assessment was deemed necessary due to poor results of intrarater and inter-rater reliability.

Oscillatory potential findings in patients with acute ischaemic central retinal vein occlusion.

AIMS: To explore the sensitive components of full-field electroretinography (ERG) as indicators of retina function at the onset of acute ischaemic central retinal vein occlusion (CRVO). METHODS: 11 patients (11 eyes) with ischaemic CRVO and 32 patients (32 eyes) with non-ischaemic CRVO who presented with first-episode unilateral CRVO within 1 month of symptom onset and with no previous intervention were examined by the International Society for Clinical Electrophysiology of Vision standard ERG. RESULTS: A significant amplitude decline and peak time delay in light-adapted (LA) 3 ERG and LA 30 Hz flicker ERG (p<0.05 for all) was found in the ischaemic CRVO eyes, compared with the non-ischaemic CRVO eyes. The b/a amplitude ratio of dark-adapted (DA) 3 ERG, DA 10 ERG and LA 3 ERG was significantly different between the ischaemic and non-ischaemic groups (p<0.05 for all). Regarding oscillatory potentials (OPs), the amplitudes of OP1, OP2 and OP3 as well as the sum of DA 3 OP1-4 amplitudes (∑OPs) showed significant changes (p<0.01 for all) between two groups. No peak time delay of OPs was found between the ischaemic and non-ischaemic CRVO eyes. CONCLUSION: The amplitude of DA 0.01 ERG, components of LA 3 ERG and LA 30 Hz flicker ERG, and the b/a amplitude ratio could be among the most sensitive indicators in patients with acute ischaemic CRVO. The amplitudes of OP1, OP2, OP3 and ∑OPs in the CRVO eyes were reduced to 40% of the control values, showing that this quantitative method is reliable for detecting ischaemic retinal diseases, even in early stage.

Validation of a deep learning model for automatic detection and quantification of five OCT critical retinal features associated with neovascular age-related macular degeneration.

PURPOSE: To develop and validate a deep learning model for the segmentation of five retinal biomarkers associated with neovascular age-related macular degeneration (nAMD). METHODS: 300 optical coherence tomography volumes from subject eyes with nAMD were collected. Images were manually segmented for the presence of five crucial nAMD features: intraretinal fluid, subretinal fluid, subretinal hyperreflective material, drusen/drusenoid pigment epithelium detachment (PED) and neovascular PED. A deep learning architecture based on a U-Net was trained to perform automatic segmentation of these retinal biomarkers and evaluated on the sequestered data. The main outcome measures were receiver operating characteristic curves for detection, summarised using the area under the curves (AUCs) both on a per slice and per volume basis, correlation score, enface topography overlap (reported as two-dimensional (2D) correlation score) and Dice coefficients. RESULTS: The model obtained a mean (±SD) AUC of 0.93 (±0.04) per slice and 0.88 (±0.07) per volume for fluid detection. The correlation score (R2) between automatic and manual segmentation obtained by the model resulted in a mean (±SD) of 0.89 (±0.05). The mean (±SD) 2D correlation score was 0.69 (±0.04). The mean (±SD) Dice score resulted in 0.61 (±0.10). CONCLUSIONS: We present a fully automated segmentation model for five features related to nAMD that performs at the level of experienced graders. The application of this model will open opportunities for the study of morphological changes and treatment efficacy in real-world settings. Furthermore, it can facilitate structured reporting in the clinic and reduce subjectivity in clinicians' assessments.

Comparison of the accommodative amplitude measured with and without the use of a specialised accommodative rule in children.

OBJECTIVE: To determine the agreement between measurements of accommodative amplitude (AoA) in children using a specialised accommodative rule and measurments without it. METHODS: A total of 502 children underwent optometric examinations, including the measurement of visual acuity, objective and subjective refraction. AoA measurements were done with and without the Berens accommodative rule. The measurements of AoA were conducted monocularly using a -4 D lens. A fixation stick containing English letters equivalent to 20/30 visual acuity and a long millimetre ruler was used to measure AoA without the accommodative rule. This measurement was performed by the two trained examiners. The agreement between these methods was reported by 95% limits of agreement (LoA) and interclass correlation coefficient (ICC). RESULTS: The mean age of the participants was 11.7±1.3 years (range: 9-15 years) and 52.4% were male. The mean AoA with and without the accommodative rule was 20.02±6.02 D and 22.46±6.32 D, respectively. The 95% LoA between the two methods was -12.5 to 7.5 D, and the ICC was 0.67 (95% CI 0.63 to 0.70). The 95% LoA was narrower in higher age groups and males compared with females (18.92 vs 20.87). The 95% LoA was narrower in hyperopes (16.83 D) compared with emmetropes (18.37 D) and myopes (18.27 D). The agreement was not constant and decreased in higher values of AoA. CONCLUSION: There is a poor and non-constant agreement between the measurements of the AoA with and without the accommodative rule. The mean AoA was 2.5 D lower with using the accommodative rule.

Effect of intravenous methylprednisolone on serum antibody levels in thyroid eye disease.

BACKGROUND/AIMS: We evaluated longitudinal autoantibody changes after intravenous methylprednisolone (IVMP), compared them with those in untreated patients and identified prognostic factors for treatment response. METHODS: In this single-centre, retrospective, observational study, a total of 163 individuals diagnosed with moderate-to-severe thyroid eye disease were enrolled and followed for 12 months. Depending on whether IVMP was administered, we divided the patients into treatment and control groups. Based on the effect of IVMP on TSH receptor (TSH Rc) antibody level, we divided the patients into Ab declined and Ab not declined groups.We evaluated the time, group and interaction associations with the longitudinal autoantibody titres over 12 months using generalised estimating equations. Using multivariable logistic regression, we investigated the prognostic factors for a poor response to IVMP. RESULTS: In the IVMP group, the TSH Rc antibody (Ab) titre decreased rapidly for 6 months and then decreased slowly until 12 months, becoming similar to the control group at 12 months. This suggests a difference in the decreasing pattern over time between the IVMP and control groups (group and time interaction p=0.029). Total cholesterol (OR 1.0217 (95% CI 1.0068 to 1.0370), p=0.0043) was a significant prognostic factor for the steroid response. The threshold total cholesterol value to distinguish between Ab declined and Ab not declined was 186 mg/dL. CONCLUSION: IVMP significantly decreased the TSH Rc Ab level for the 3 months after treatment, compared with the no-treatment group, but the groups did not differ significantly after 12 months. Patients with high total cholesterol levels generally showed a poor response to IVMP.

Expert CONsensus on Visual Evaluation in Retinal disease manaGEment: the CONVERGE study.

BACKGROUND/AIMS: Recent decades have seen significant advances in both structural and functional testing of retinal disease. However, the current clinical value of specific testing modalities, as well as future trends, need to be clearly identified in order to highlight areas for further development in routine care and clinical trials. METHODS: We designed a modified two-round Delphi study to obtain the opinion of a multidisciplinary group of 33 international experts involved in the field of retinal disease management/research to determine the level of agreement and consensus regarding the value and performance of specific structural and functional testing methods for retinal disease. On a Likert scale, a median of 1-2 indicated disagreement with the statement, and 5-6 indicated agreement with the statement. An IQR of ≤2 indicated consensus in the responses. Several questions also allowed comments on responses. RESULTS: There was overall agreement that structural testing currently predominates for detection and monitoring. There was moderate agreement that functional testing remains important and will continue to do so in the future because it provides complementary information. Certain respondents considered that properly designed and applied psychophysical tests are as reliable and repeatable as structural observations and that functional changes are the most important in the long run. Respondents considered future care and research to require a combination of structural and functional testing with strong consensus that the relative importance will depend on disease type and stage. CONCLUSION: The study obtained important insights from a group of international experts regarding current and future needs in the management of retinal disease using a mix of quantitative and qualitative approaches. Responses provide a rich range of opinions that will be of interest to researchers seeking to design tests for future patient care and clinical trials.

Multiple use of preservative-free single dose unit dexamethasone 0.1% eye drops is safe within 24 hours.

BACKGROUND: Unpreserved single-dose unit (SDU) eye drops are commonly used to avoid benzalkonium chloride-related toxicity. Although intended for single use, many patients report off-label repeated use of SDUs over a prolonged period. We investigated whether repeated use of dexamethasone 0.1% SDUs in the same patient increases the bacterial contamination rate. METHODS: We prospectively enrolled patients scheduled for inpatient corneal and glaucoma surgery receiving dexamethasone 0.1% SDU four times per day from the same vial. To assess contamination rates, one drop from the vial was cultured immediately after opening the SDU (t0), 10 hours later after four drop applications (t10) and 24 hours after opening without further drop applications (t24). Conjunctival swabs were taken before and after drop application. Contamination rate was assessed with a standard clinical culturing protocol without introducing a positive control. RESULTS: 110 eyes of 109 patients were evaluated. Drops collected immediately after opening the SDU (t0) were contaminated in 9/110 cultures (8.1%). At t10, 13/110 cultures were contaminated (11.8%; p=0.267) and 11/110 at t24 (10.0%; t24 vs t0; p=1.00). In 5 of 21 cases of contaminated drops at t10 and/or t24, the same isolates were cultured from the initial conjunctival swab and the SDU. In three cases, the same bacterial species was found in consecutive samples. CONCLUSION: The contamination rate of the SDU did not increase after multiple use within 24 hours. Contamination from fingertip flora was more likely than from ocular surface flora. Reuse of dexamethasone 0.1% SDU in the same patient within 24 hours appears to be safe.

Longitudinal assessment of female carriers of choroideremia using multimodal retinal imaging.

BACKGROUND/AIMS: Female choroideremia carriers present with a spectrum of disease severity. Unlike in men, the rate of disease progression has not been well characterised in carriers. This longitudinal study aimed to determine the rate of retinal degeneration in choroideremia carriers, using multimodal imaging and microperimetry. METHODS: Choroideremia carriers previously seen at Oxford Eye Hospital (United Kingdom) between 2012 and 2017 returned for testing between 2015 and 2023, providing up to 11 years' follow-up data. Participants had optical coherence tomography, fundus-tracked microperimetry and fundus autofluorescence (FAF) imaging performed. RESULTS: Thirty-four eyes of 17 choroideremia carriers were examined using multimodal imaging. Median age was 44 (range: 15-73) years at baseline and median follow-up duration was 7 (range: 1-11) years. At baseline, phenotype was classified as fine (n=5 eyes), coarse (n=13 eyes), geographic (n=12 eyes) or male pattern (n=4 eyes). Thirteen patients showed no change in phenotype classification, four showed slight changes associated with choroideremia-related retinal degeneration. Despite this, carriers with severe retinal phenotypes had a statistically significant decline in average retinal sensitivity (-0.7 dB and -0.8 dB per year, respectively, p<0.001), area of geographic loss defined by FAF (+2.5 mm2 and +3.7 mm2 per year, respectively, p<0.001) and thinning of the photoreceptor complex (up to -2.8 microns and -10.3 microns per year, p<0.001). CONCLUSION: Choroideremia carriers, particularly those with severe retinal phenotypes, exhibit progressive retinal degeneration, as evident by multimodal imaging biomarkers and functional testing. Clinicians should not rely on retinal severity classification alone to assess disease progression.

Deep sequencing as a diagnostic tool in patients with suspected primary vitreoretinal lymphoma.

PURPOSE: To compare the diagnostic utility of metagenomic deep sequencing (MDS) to cytology, flow cytometry and gene rearrangement by PCR in ocular samples of patients with suspected vitreoretinal lymphoma (VRL). METHODS: Patients with suspected VRL underwent ocular sampling of one or both eyes at the Emory Eye Center from September 2017 to June 2022. Ocular samples were evaluated with MDS and conventional diagnostics. MDS was performed at the Ralph and Sophie Heintz Laboratory at the F.I. Proctor Foundation. Relevant demographic and clinical data were retrospectively collected from medical records. Patients were diagnosed with VRL based on clinical assessment and conventional diagnostic testing. RESULTS: This study included 13 patients with suspected VRL who underwent diagnostic vitrectomy, including 1 patient who had an additional subretinal biopsy. Six patients (46.2%) were diagnosed with VRL. Among patients diagnosed with VRL, MDS detected pathogenic mutations in 5 out of 6 patients (83.3%) while cytology was positive for VRL in 4 out of 6 patients (66.7%), flow cytometry in 4 out of 4 patients (100.0%) and PCR in 4 out of 4 patients (100.0%). MDS detected mutations in MYD88 in 2 out of 6 patients diagnosed with VRL. In 7 patients (53.8%) not diagnosed with VRL, MDS detected pathogenic lymphoma mutations in 2 patients (28.6%). DISCUSSION: MDS detected pathogenic mutations in five out of six patients diagnosed with VRL, including in two patients with negative cytology, demonstrating its potential to improve diagnostic rates of VRL as an adjunctive test.

Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images.

BACKGROUND: Artificial intelligence (AI) in medical imaging diagnostics has huge potential, but human judgement is still indispensable. We propose an AI-aided teaching method that leverages generative AI to train students on many images while preserving patient privacy. METHODS: A web-based course was designed using 600 synthetic ultra-widefield (UWF) retinal images to teach students to detect disease in these images. The images were generated by stable diffusion, a large generative foundation model, which we fine-tuned with 6285 real UWF images from six categories: five retinal diseases (age-related macular degeneration, glaucoma, diabetic retinopathy, retinal detachment and retinal vein occlusion) and normal. 161 trainee orthoptists took the course. They were evaluated with two tests: one consisting of UWF images and another of standard field (SF) images, which the students had not encountered in the course. Both tests contained 120 real patient images, 20 per category. The students took both tests once before and after training, with a cool-off period in between. RESULTS: On average, students completed the course in 53 min, significantly improving their diagnostic accuracy. For UWF images, student accuracy increased from 43.6% to 74.1% (p<0.0001 by paired t-test), nearly matching the previously published state-of-the-art AI model's accuracy of 73.3%. For SF images, student accuracy rose from 42.7% to 68.7% (p<0.0001), surpassing the state-of-the-art AI model's 40%. CONCLUSION: Synthetic images can be used effectively in medical education. We also found that humans are more robust to novel situations than AI models, thus showcasing human judgement's essential role in medical diagnosis.

Generative artificial intelligence in ophthalmology: current innovations, future applications and challenges.

The rapid advancements in generative artificial intelligence are set to significantly influence the medical sector, particularly ophthalmology. Generative adversarial networks and diffusion models enable the creation of synthetic images, aiding the development of deep learning models tailored for specific imaging tasks. Additionally, the advent of multimodal foundational models, capable of generating images, text and videos, presents a broad spectrum of applications within ophthalmology. These range from enhancing diagnostic accuracy to improving patient education and training healthcare professionals. Despite the promising potential, this area of technology is still in its infancy, and there are several challenges to be addressed, including data bias, safety concerns and the practical implementation of these technologies in clinical settings.

Measurement of visual function in infantile nystagmus: a systematic review.

BACKGROUND/AIMS: Recent work has called into question the ability of visual acuity (VA) to accurately represent changes in visual function in infantile nystagmus (IN). This systematic review investigated factors affecting visual performance in IN, to guide development of suitable alternatives to VA. METHODS: Included studies used an experimental manipulation to assess changes in visual function in people with IN. Interventional studies, case series and case studies were excluded. Six databases were searched in August 2023. Selection, detection, attrition and measurement bias were assessed. Due to heterogeneous methodologies, narrative synthesis was undertaken. RESULTS: Eighteen relevant papers were identified, 11 of which complied with the review criteria. Articles were grouped according to the factor manipulated to evoke within-participant changes in performance (motion blur, psychological state, gaze angle or visual crowding). Optotype, image, grating and moving stimuli have been employed under varying lighting conditions and exposure duration. CONCLUSION: Several factors affecting visual performance should be considered when assessing visual function in IN. While maximum VA is a useful metric, its measurement deliberately minimises nystagmus-specific factors such as changes in visual performance with gaze angle and the 'slow to see' phenomenon. Maximum VA can be measured using the null zone, providing unlimited viewing time, reducing stress/mental load and minimising visual crowding. Gaze-dependent functional vision space is a promising measure which quantifies the impact of the null zone but does not consider temporal vision. Although no complete measurement technique has yet been proven, this review provides insights to guide future work towards development of appropriate methods.

Systemic and ocular outcomes in TB-immunoreactive patients receiving immunomodulatory therapy for non-infectious uveitis: a case-control study.

BACKGROUND: Tuberculosis (TB)-immunoreactivity, measured in vivo (tuberculin skin test (TST)) or in vitro (interferon gamma release assay (IGRA)), can be found in latent, active or even following clearance of TB infection. In this case-control study, we compared the systemic and ocular outcomes between patients with or without TB-immunoreactivity, who received immunomodulatory therapy (IMT) for non-infectious uveitis. METHODS: We retrospectively reviewed charts of patients with (cases) or without (controls) TB-immunoreactivity (TST±IGRA), who received conventional IMT for ≥6 months, for the treatment of non-infectious uveitis. Patients who received prior or concomitant anti-TB therapy were excluded. Systemic and ocular outcomes were compared between both groups. RESULTS: 36 cases and 70 controls (gender-matched and age-matched) were included. New-onset pulmonary or extrapulmonary TB developed in one case and none of the controls. Based on this outcome, the absolute risk increase for systemic TB reactivation was noted to be 0.028 (95% CI 0.005 to 0.051) and the number needed to harm was 36. The incidence of persistent or recurrent (worsening ≥2 grades) intraocular inflammation during IMT was comparable between both groups (cases 18/36, controls 35/70, p=1.0). A change in anatomical site of presentation at recurrence was not seen in any case, but in six controls (p=0.15). No new focal chorio-retinal lesions were noted in either group. CONCLUSIONS: Conventional IMT has a very low risk of systemic TB reactivation, and no additional detrimental effect on ocular outcomes, in TB-immunoreactive patients with non-infectious uveitis.

Improved accuracy of spectral-domain optical coherence tomography and optical coherence tomography angiography for monitoring myopic macular neovascularisation activity.

BACKGROUND/AIMS: To evaluate the diagnostic accuracy of spectral-domain optical coherence tomography (SD OCT) combined with OCT angiography (OCTA) for myopic myopic macular neovascularisation (MNV) activity. METHODS: Both eyes of patients with myopic MNV diagnosed with fluorescein angiography (FA), SD OCT and OCTA were assessed by unmasked investigators. The images were deidentified and randomised before graded by masked investigators, who determined the presence of active myopic MNV by using SD OCT together with OCTA without FA and by FA alone, respectively. The findings of masked investigators were compared with unmasked investigators. RESULTS: 213 eyes of 110 patients comprising 499 imaging episodes were eligible for grading. For diagnosing new-onset myopic MNV without FA, combined use of SD OCT and OCTA had a sensitivity of 0.94, specificity of 0.84 and area under the curve (AUC) of 0.92. FA had a sensitivity of 0.52 (p<0.01), specificity of 0.80 (p=0.38) and AUC of 0.66 (p<0.01). For recurrent myopic MNV, the combination of SD OCT and OCTA had a sensitivity of 0.98, specificity of 0.78 and AUC of 0.88. FA had a sensitivity of 0.50 (p=0.04), specificity of 0.76 (p=0.85) and AUC of 0.63 (p=0.01). Myopic traction maculopathy was more frequently associated with recurrent myopic MNV (p<0.01). CONCLUSION: SD OCT with dense volumetric scan was highly sensitive for diagnosing myopic MNV. The addition of OCTA improved the diagnostic specificity without FA. Monitoring of the longitudinal changes on SD OCT and judicious use of FA is a reliable surveillance strategy for myopic MNV.

European Glaucoma Society research priorities for glaucoma care.

BACKGROUND/AIMS: The goal of health research is to improve patients care and outcomes. Thus, it is essential that research addresses questions that are important to patients and clinicians. The aim of this study was to develop a list of priorities for glaucoma research involving stakeholders from different countries in Europe. METHODS: We used a three-phase method, including a two-round electronic Delphi survey and a workshop. The clinician and patient electronic surveys were conducted in parallel and independently. For phase I, the survey was distributed to patients from 27 European countries in 6 different languages, and to European Glaucoma Society members, ophthalmologists with expertise in glaucoma care, asking to name up to five research priorities. During phase II, participants were asked to rank the questions identified in phase I using a Likert scale. Phase III was a 1 day workshop with patients and clinicians. The purpose was to make decisions about the 10 most important research priorities using the top 20 priorities identified by patients and clinicians. RESULTS: In phase I, 308 patients and 150 clinicians were involved. In phase II, the highest-ranking priority for both patients and clinicians was 'treatments to restore vision'. In phase III, eight patients and four clinicians were involved. The top three priorities were 'treatments to stop sight loss', 'treatments to restore vision' and 'improved detection of worsening glaucoma'. CONCLUSION: We have developed a list of priorities for glaucoma research involving clinicians and patients from different European countries that will help guide research efforts and investment.