Idiopathic Intracranial Hypertension: Management Challenges

IIH is a condition which can lead to chronic headaches and visual loss secondary to raised intracranial pressure (ICP) in the absence of a structural cause in the brain.1 World-wide the incidence and prevalence of idiopathic intracranial hypertension (IIH) has grown, with young obese women most commonly affected. 2-4 In the United Kingdom the incidence grew by 108% between 2002 to 2016 from 3.5 per 100,000 to 7.69 per 100,000 in the female population.3 Within this period there was over 440% rise in admissions to hospital (this included visits to accident and emergency and inpatient admissions),3 this makes IIH a top topic for consensus on how we approach the management of people with IIH

One Eye or Two: Statistical Considerations in Ophthalmology With a Focus on Interventional Clinical Trials

Research in ophthalmology is unusual in comparison with other many medical specialties by having 2 targets where frequent and accessible data can be collected and analyzed. The major factor is that 2 eyes are not independent as they belong to the same individual. As many statistical methods assume independence of observations, historically, many researchers have arbitrarily chosen one eye for analysis. Another approach to maintain independence of observations is to generate subject level index variables using information from both eyes. This was the approach taken by Anagnostou et al in this issue of Journal of Neuro-ophthalmology. Specifically, for measurements taken in both eyes of subjects with 3 possible grades (i.e., 0, 1, 2 in the right eye and 0, 1, 2 in the left eye), each combination was considered to yield 9 potential subject level outcomes for 2 analyses

A Datasheet for the INSIGHT University Hospitals Birmingham Retinal Vein Occlusion Data Set

Purpose: Retinal vein occlusion (RVO) is the second leading cause of visual loss due to retinal disease. Retinal vein occlusion increases the risk of cardiovascular mortality and the risk of stroke. This article describes the data contained within the INSIGHT eye health data set for RVO and cardiovascular disease. Design: Data set descriptor for routinely collected eye and systemic disease data. Participants: All people who had suffered an RVO aged ≥ 18 years old, attending the Ophthalmology Clinic at Queen Elizabeth Hospital, University Hospitals Birmingham (UHB) National Health Service (NHS) Trust were included. Methods: The INSIGHT Health Data Research Hub for Eye Health is an NHS-led ophthalmic bioresource. It provides researchers with safe access to anonymized routinely collected data from contributing NHS hospitals to advance research for patient benefit. This report describes the INSIGHT UHB RVO and major adverse cardiovascular events data set, a data set of ophthalmology and systemic data derived from the United Kingdom’s largest acute care trust. Main Outcome Measures: This data set consists of routinely collected data from the hospital’s electronic patient records. The data set primarily includes structured data (relating to their hospital eye care and any cardiovascular data held for the individual) and OCT ocular images. Further details regarding the available data points are available in the supplementary information. Results: At the time point of this analysis (September 30, 2022) the data set was composed of clinical data from 1521 patients, from Medisoft records inception. The data set includes 2196 occurrences of RVO affecting 2026 eyes, longitudinal eye follow-up clinical parameters, over 6217 eye-related procedures, and 982 encountered complications. The data set contains information on 2534 major adverse cardiovascular event occurrences, their subtype, number experienced per patient, and chronological relation to RVO event. Longitudinal follow-up data including laboratory results, regular medications, and all-cause mortality are also available within the data set. Conclusions: This data set descriptor article summarizes the data set contents, the process of its curation, and potential uses. The data set is available through the structured application process that ensures research studies are for patient benefit. Further information regarding the data repository and contact details can be found at https://www.insight.hdrhub.org/. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references

A Datasheet for the INSIGHT Birmingham, Solihull, and Black Country Diabetic Retinopathy Screening Dataset

Purpose: Diabetic retinopathy (DR) is the most common microvascular complication associated with diabetes mellitus (DM), affecting approximately 40% of this patient population. Early detection of DR is vital to ensure monitoring of disease progression and prompt sight saving treatments as required. This article describes the data contained within the INSIGHT Birmingham, Solihull, and Black Country Diabetic Retinopathy Dataset. Design: Dataset descriptor for routinely collected eye screening data. Participants: All diabetic patients aged 12 years and older, attending annual digital retinal photography-based screening within the Birmingham, Solihull, and Black Country Eye Screening Programme. Methods: The INSIGHT Health Data Research Hub for Eye Health is a National Health Service (NHS)–led ophthalmic bioresource that provides researchers with safe access to anonymized, routinely collected data from contributing NHS hospitals to advance research for patient benefit. This report describes the INSIGHT Birmingham, Solihull, and Black Country DR Screening Dataset, a dataset of anonymized images and linked screening data derived from the United Kingdom’s largest regional DR screening program. Main Outcome Measures: This dataset consists of routinely collected data from the eye screening program. The data primarily include retinal photographs with the associated DR grading data. Additional data such as corresponding demographic details, information regarding patients’ diabetic status, and visual acuity data are also available. Further details regarding available data points are available in the supplementary information, in addition to the INSIGHT webpage included below. Results: At the time point of this analysis (December 31, 2019), the dataset comprised 6 202 161 images from 246 180 patients, with a dataset inception date of January 1, 2007. The dataset includes 1 360 547 grading episodes between R0M0 and R3M1. Conclusions: This dataset descriptor article summarizes the content of the dataset, how it has been curated, and what its potential uses are. Data are available through a structured application process for research studies that support discovery, clinical evidence analyses, and innovation in artificial intelligence technologies for patient benefit. Further information regarding the data repository and contact details can be found at https://www.insight.hdrhub.org/. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article