Purpose: To identify and assess the quality of questionnaires used to measure quality of life in keratoconus and guide selection of the most appropriate questionnaire for evaluating the impact of keratoconus. Methods: A literature search was carried out in Scopus, Web of Science, PubMed, MEDLINE, Cochrane, and PsycINFO databases. Articles that described a questionnaire to measure quality of life in keratoconus were included. Information on psychometric properties and validity was extracted and analyzed based on a set of quality criteria. Finally, the impact of keratoconus and its management methods on quality of life was reviewed. Results: The search yielded 331 publications, of which 45 articles describing 18 (12 ophthalmic including 2 keratoconus-specific and 6 generic) questionnaires were reviewed. Most of the articles (40, 88.9%) described ophthalmic questionnaires not specific to keratoconus. The National Eye Institute Visual Function Questionnaire was the most frequently used questionnaire (n = 26). Only 4 articles provided information on psychometric properties. The Keratoconus Outcomes Research Questionnaire, the only validated keratoconus-specific questionnaire, had the most superior psychometric properties. However, it consists of items on only 2 domains of quality of life (activity limitation and symptoms). Overall, keratoconus management methods (spectacles, contact lenses, and cross-linking in early stages, corneal transplantation in late stages) improved quality of life. The quality of life scores were associated with clinical measures including visual acuity, corneal topography, pachymetry, and keratoconus severity. Conclusions: There is a need for a comprehensive and high-quality patient-reported outcome measure in keratoconus. A questionnaire should be chosen based on the purpose and the quality of the questionnaire. This review guides selection of an appropriate questionnaire.

Background: The objectives of this study were to evaluate the quality‐of‐life (QoL) impact of eye diseases (keratoconus; neovascular age‐related macular degeneration, AMD; retinal vein occlusion, RVO; and diabetic macular edema, DME) using the Impact of Vision Impairment (IVI) questionnaire, and to determine the relationship between the IVI scores and visual acuity.Methods: This cross‐sectional, multicentre, real‐world study utilised the prospective, web‐based Save Sight Registries. The IVI was completed by 1557 patients: 307 with keratoconus, 1049 with AMD, 148 with RVO and 53 with DME. Statistical analysis included Rasch analysis, Welcht‐test, one‐way ANOVA, Tukey's test, Pearson correlation, and multiple regression.Results: The IVI scales (Overall; Visual Function, VF; Emotional, EM) had robust psychometric properties. The keratoconus patients had the worst Overall (adjusted mean: 48.2 vs. DME 58.8, RVO 64.6, AMD 67.6 units), VF (47.7 vs. DME 59.4, RVO 65.9, AMD 68.9 units) and EM (50.8 vs. DME 63.1, RVO 69.2, AMD 71.8 units) scores (allp < 0.05).The IVI scales scores weakly correlated with better and worse eye visual acuity (Pearson'sr0.24–0.39, allp < 0.05). The correlations were similar in the better eye (Overall 0.35, VF 0.39, EM 0.24) and the worse eye (Overall 0.31, VF 0.33, EM 0.25) visual acuity. Correlations with visual acuity were stronger for VF than for the EM scores.Conclusions: The IVI was a psychometrically robust QoL questionnaire. Keratoconus patients had worse IVI scores than patients with retinal diseases. The low strength of correlations between visual acuity and QoL scores, although statistically significant, suggested that a complex relationship exists.

Antimicrobial resistance (AMR) is a global public health threat with significant impact on treatment outcomes. The World Health Organization's Global Action Plan on AMR recommended strengthening the evidence base through surveillance programs and research. Comprehensive, timely data on AMR for organisms isolated from ocular infections are needed to guide treatment decisions and inform researchers and microbiologists of emerging trends. This article aims to provide an update on the development of AMR in ocular organisms, AMR in bacterial ocular infections and on AMR stewardship programs globally. The most common ocular pathogens are Pseudomonas aeruginosa, Staphylococcus spp., Streptococcus pneumoniae, and Haemophilus influenzae in ocular infections. A variety of studies and a few surveillance programs worldwide have reported on AMR in these infections over time. Fluoroquinolone resistance has increased particularly in Asia and North America. For conjunctivitis, the ARMOR cumulative study in the USA reported a slight decrease in resistance to ciprofloxacin. For keratitis, resistance to methicillin has remained stable for S. aureus and CoNS, while resistance to ciprofloxacin has decreased for MRSA globally. Methicillin‐resistance and multidrug resistance are also emerging, requiring ongoing monitoring. Antimicrobial stewardship (AMS) programmes have a critical role in reducing the threat of AMR and improving treatment outcomes. To be successful AMS must be informed by up‐to‐date AMR surveillance data. As a profession it is timely for ophthalmology to act to prevent AMR leading to greater visual loss through supporting surveillance programmes and establishing AMS.

Aims We set out to identify risk factors for progression in untreated keratoconus patients from 34 centres across Australia, New Zealand, Spain and Italy. Methods Patients were divided into ‘progressors’ and ‘stable’ patients for each clinical parameter: visual acuity (VA), steepest keratometry (maximum keratometry (Max-K)) and thinnest corneal thickness (TCT). Primary outcomes were the proportion of eyes with sustained progression in VA, Max-K or TCT within 3 years. Secondary outcomes included predictors of progression. Results There were 3994 untreated eyes from 2283 patients. The proportion of eyes with VA, Max-K and TCT progression at 1 year were 3.2%, 6.6% and 3.1% respectively. Factors associated with VA loss were higher baseline VA (HR 1.15 per logMAR line increase in VA; p<0.001) and steeper baseline Max-K (HR 1.07 per 1D increase; p<0.001). Younger baseline age was associated with Max-K steepening (HR 0.96 per year older; p=0.001). Thicker baseline TCT, steeper baseline Max-K and younger baseline age were associated with TCT thinning: (HR 1.08 per 10 µm increase in TCT; p<0.001), (HR 1.03 per 1D increase; p=0.02) and (HR 0.98 per year younger; p=0.01), respectively. Conclusions Steeper Max-K and younger age were the most clinically useful baseline predictors of progression as they were associated with worsening of two clinical parameters. Every 1D steeper Max-K was associated with a 7% and 3% greater risk of worsening VA and thinning TCT, respectively. Each 1 year younger was associated with a 4% and 2% greater risk of steepening Max-K and thinning TCT, respectively.