ReviewEye (London, England)2024
From real world data to real world evidence to improve outcomes in neuro-ophthalmology.
Review in Eye (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Who Gets Referred for What? Large Scale Analysis of Clinical, Socioeconomic and Demographic Drivers Within Electronic Optometry Referrals.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026Article
- Defining a standards framework for ophthalmology real-world data methodologies through an expert-led Delphi consensus.Eye (London, England) · 2026Article
- Real-world data landscape for glaucoma in Europe: a questionnaire-based analysis of resources among European Glaucoma Society members.BMJ open ophthalmology · 2025Article
- Neuro-ophthalmology: recent advances and paradigm shifts.Eye (London, England) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Real-world data (RWD) can be defined as all data generated during routine clinical care. This includes electronic health records, disease-specific registries, imaging databanks, and data linkage to administrative databases. In the field of neuro-ophthalmology, the intersection of RWD and clinical practice offers unprecedented opportunities to understand and treat rare diseases. However, translating RWD into real-world evidence (RWE) poses several challenges, including data quality, legal and ethical considerations, and sustainability of data sources. This review explores existing RWD sources in neuro-ophthalmology, such as patient registries and electronic health records, and discusses the challenges of data collection and standardisation. We focus on research questions that need to be answered in neuro-ophthalmology and provide an update on RWE generated from various RWD sources. We review and propose solutions to some of the key barriers that can limit translation of a collection of data into impactful clinical evidence. Careful data selection, management, analysis, and interpretation are critical to generate meaningful conclusions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.