Validity of Administrative Claims and Electronic Health Registry Data From a Single Practice for Eye Health Surveillance.

Importance: Diagnostic information from administrative claims and electronic health record (EHR) data may serve as an important resource for surveillance of vision and eye health, but the accuracy and validity of these sources are unknown.

Objective: To estimate the accuracy of diagnosis codes in administrative claims and EHRs compared to retrospective medical record review.

Design, Setting, And Participants: This cross-sectional study compared the presence and prevalence of eye disorders based on diagnostic codes in EHR and claims records vs clinical medical record review at University of Washington-affiliated ophthalmology or optometry clinics from May 2018 to April 2020.

Comparing Telephone Survey Responses to Best-Corrected Visual Acuity to Estimate the Accuracy of Identifying Vision Loss: Validation Study.

Background: Self-reported questions on blindness and vision problems are collected in many national surveys. Recently released surveillance estimates on the prevalence of vision loss used self-reported data to predict variation in the prevalence of objectively measured acuity loss among population groups for whom examination data are not available. However, the validity of self-reported measures to predict prevalence and disparities in visual acuity has not been established.

Acute panuveitis after COVID-19 mRNA booster vaccination following cataract surgery.

Purpose: To report a case of presumed COVID-19 Pfizer third dose (booster) vaccination leading to severe panuveitis mimicking acute endophthalmitis in the early postoperative period following routine cataract extraction and intraocular lens implantation.

Observations: A 68-year-old female with mild refractive error who previously received 2 doses of the BNT162b2 vaccine underwent routine cataract extraction and intraocular lens implantation in the right eye. On postoperative day (POD) 2 the patient received her BNT162b2 booster vaccination.

Training Deep Learning Models to Work on Multiple Devices by Cross-Domain Learning with No Additional Annotations.

Purpose: To create an unsupervised cross-domain segmentation algorithm for segmenting intraretinal fluid and retinal layers on normal and pathologic macular OCT images from different manufacturers and camera devices.

Design: We sought to use generative adversarial networks (GANs) to generalize a segmentation model trained on one OCT device to segment B-scans obtained from a different OCT device manufacturer in a fully unsupervised approach without labeled data from the latter manufacturer.

Participants: A total of 732 OCT B-scans from 4 different OCT devices (Heidelberg Spectralis, Topcon 1000, Maestro2, and Zeiss Plex Elite 9000).

Endophthalmitis Rate in Immediately Sequential versus Delayed Sequential Bilateral Cataract Surgery within the Intelligent Research in Sight (IRIS®) Registry Data.

Purpose: To compare the rate of postoperative endophthalmitis after immediately sequential bilateral cataract surgery (ISBCS) versus delayed sequential bilateral cataract surgery (DSBCS) using the American Academy of Ophthalmology Intelligent Research in Sight (IRIS®) Registry database.

Design: Retrospective cohort study.

Participants: Patients in the IRIS Registry who underwent cataract surgery from 2013 through 2018.

"My husband says this: If you are alive, you can be someone…": Facilitators and barriers to cervical cancer screening among women living with HIV in India.

Purpose: Women living with human immunodeficiency virus (WLWH) have a higher risk of cervical cancer than women without HIV. In addition, women in India experience a high burden of death from cervical cancer. This qualitative study evaluated individual and interpersonal factors influencing cervical cancer screening among WLWH in Surat, India.