BackgroundPrior work has demonstrated the near-perfect accuracy of a deep learning retinal image analysis system for diagnosing plus disease in retinopathy of prematurity (ROP). Here we assess the screening potential of this scoring system by determining its ability to detect all components of ROP diagnosis.MethodsClinical examination and fundus photography were performed at seven participating centres. A deep learning system was trained to detect plus disease, generating a quantitative assessment of retinal vascular abnormality (the i-ROP plus score) on a 1–9 scale. Overall ROP disease category was established using a consensus reference standard diagnosis combining clinical and image-based diagnosis. Experts then ranked ordered a second data set of 100 posterior images according to overall ROP severity.Results4861 examinations from 870 infants were analysed. 155 examinations (3%) had a reference standard diagnosis of type 1 ROP. The i-ROP deep learning (DL) vascular severity score had an area under the receiver operating curve of 0.960 for detecting type 1 ROP. Establishing a threshold i-ROP DL score of 3 conferred 94% sensitivity, 79% specificity, 13% positive predictive value and 99.7% negative predictive value for type 1 ROP. There was strong correlation between expert rank ordering of overall ROP severity and the i-ROP DL vascular severity score (Spearman correlation coefficient=0.93; p<0.0001).ConclusionThe i-ROP DL system accurately identifies diagnostic categories and overall disease severity in an automated fashion, after being trained only on posterior pole vascular morphology. These data provide proof of concept that a deep learning screening platform could improve objectivity of ROP diagnosis and accessibility of screening.

IMPORTANCE Azithromycin has been hypothesized to have activity against SARS-CoV-2.OBJECTIVE To determine whether oral azithromycin in outpatients with SARS-CoV-2 infection leads to absence of self-reported COVID-19 symptoms at day 14. DESIGN, SETTING, AND PARTICIPANTS Randomized clinical trial of azithromycin vs matching placebo conducted from May 2020 through March 2021. Outpatients from the US were enrolled remotely via internet-based surveys and followed up for 21 days. Eligible participants had a positive SARS-CoV-2 diagnostic test result (nucleic acid amplification or antigen) within 7 days prior to enrollment, were aged 18 years or older, and were not hospitalized at the time of enrollment. Among 604 individuals screened, 297 were ineligible, 44 refused participation, and 263 were enrolled. Participants, investigators, and study staff were masked to treatment randomization.INTERVENTIONS Participants were randomized in a 2:1 fashion to a single oral 1.2-g dose of azithromycin (n = 171) or matching placebo (n = 92). MAIN OUTCOMES AND MEASURESThe primary outcome was absence of self-reported COVID-19 symptoms at day 14. There were 23 secondary clinical end points, including all-cause hospitalization at day 21. RESULTS Among 263 participants who were randomized (median age, 43 years; 174 [66%] women; 57% non-Hispanic White and 29% Latinx/Hispanic), 76% completed the trial. The trial was terminated by the data and safety monitoring committee for futility after the interim analysis. At day 14, there was no significant difference in proportion of participants who were symptom free (azithromycin: 50%; placebo: 50%; prevalence difference, 0%; 95% CI, −14% to 15%; P > .99). Of 23 prespecified secondary clinical end points, 18 showed no significant difference. By day 21, 5 participants in the azithromycin group had been hospitalized compared with 0 in the placebo group (prevalence difference, 4%; 95% CI, −1% to 9%; P = .16).CONCLUSIONS AND RELEVANCE Among outpatients with SARS-CoV-2 infection, treatment with a single dose of azithromycin compared with placebo did not result in greater likelihood of being symptom free at day 14. These findings do not support the routine use of azithromycin for outpatient SARS-CoV-2 infection.

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IMPORTANCE Examinations for retinopathy of prematurity (ROP) are typically performed using binocular indirect ophthalmoscopy. Telemedicine studies have traditionally assessed the accuracy of telemedicine compared with ophthalmoscopy as a criterion standard. However, it is not known whether ophthalmoscopy is truly more accurate than telemedicine. OBJECTIVE To directly compare the accuracy and sensitivity of ophthalmoscopy vs telemedicine in diagnosing ROP using a consensus reference standard. DESIGN, SETTING, AND PARTICIPANTS This multicenter prospective study conducted between July 1, 2011, and November 30, 2014, at 7 neonatal intensive care units and academic ophthalmology departments in the United States and Mexico included 281 premature infants who met the screening criteria for ROP. EXPOSURES Each examination consisted of 1 eye undergoing binocular indirect ophthalmoscopy by an experienced clinician followed by remote image review of wide-angle fundus photographs by 3 independent telemedicine graders. MAIN OUTCOMES AND MEASURES Results of both examination methods were combined into a consensus reference standard diagnosis. The agreement of both ophthalmoscopy and telemedicine was compared with this standard, using percentage agreement and weighted κ statistics. RESULTS Among the 281 infants in the study (127 girls and 154 boys; mean [SD] gestational age, 27.1 [2.4] weeks), a total of 1553 eye examinations were classified using both ophthalmoscopy and telemedicine. Ophthalmoscopy and telemedicine each had similar sensitivity for zone I disease (78% [95% CI, 71%–84%] vs 78% [95% CI, 73%–83%]; P > .99 [n = 165]), plus disease (74% [95% CI, 61%–87%] vs 79% [95% CI, 72%–86%]; P = .41 [n = 50]), and type 2 ROP (stage 3, zone I, or plus disease: 86% [95% CI, 80%–92%] vs 79% [95% CI, 75%–83%]; P = .10 [n = 251]), but ophthalmoscopy was slightly more sensitive in identifying stage 3 disease (85% [95% CI, 79%–91%] vs 73% [95% CI, 67%–78%]; P = .004 [n = 136]). CONCLUSIONS AND RELEVANCE No difference was found in overall accuracy between ophthalmoscopy and telemedicine for the detection of clinically significant ROP, although, on average, ophthalmoscopy had slightly higher accuracy for the diagnosis of zone III and stage 3 ROP. With the caveat that there was variable accuracy between examiners using both modalities, these results support the use of telemedicine for the diagnosis of clinically significant ROP.

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Purpose of review To revisit ocular rosacea as an underappreciated condition which can cause permanent blindness if inadequately treated, and to review data supporting improved diagnostic and treatment strategies. Recent findings Ocular rosacea has an underrecognized prevalence in children and individuals with darker skin tone. Rosacea has several associations with other significant systemic diseases. Variations in local and systemic microbiome, including demodex infestation, may play a role in pathogenesis, severity, and in explaining the different phenotypes of rosacea. The National Rosacea Society Expert Committee established an updated classification system of rosacea in 2017. New treatment algorithms based on these clinical subtypes are suggested. Summary With continued advancements in the understanding of the epidemiology and pathogenesis of rosacea, randomized controlled trials specific for ocular rosacea remain lacking. There is overall consensus that rosacea and ocular rosacea require chronic maintenance treatment strategies involving combination topical and systemic therapies.

Purpose To measure the effect of electronic health record (EHR) implementation on productivity and efficiency in the pediatric ophthalmology division at an academic medical center. Methods Four established providers were selected from the pediatric ophthalmology division at the Oregon Health & Science University Casey Eye Institute. Clinical volume was compared before and after EHR implementation for each provider. Time elapsed from chart open to completion (OTC time) and the proportion of charts completed during business hours were monitored for 3 years following implementation. Results Overall there was an 11% decrease in clinical volume following EHR implementation, which was not statistically significant (P = 0.18). The mean OTC time ranged from 5.5 to 28.3 hours among providers in this study, and trends over time were variable among the four providers. Forty-four percent of all charts were closed outside normal business hours (30% on weekdays, 14% on weekends). Conclusions EHR implementation was associated with a negative impact on productivity and efficiency in our pediatric ophthalmology division.

A new remote wet lab allowing residents to maintain social distancing during the COVID-19 pandemic and perform a corneal suturing task on porcine eyes with remote attending feedback is described.