ReviewJournal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society2019
Big Data Research in Neuro-Ophthalmology: Promises and Pitfalls.
Review in Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Big data in ophthalmology: a systematic review of public databases for ophthalmic research.Eye (London, England) · 2023Pooled it
- Validity of International Classification of Diseases Codes for Identifying Neuro-Ophthalmic Disease in Large Data Sets: A Systematic Review.Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society · 2020Pooled it
- Postoperative vision loss and visual disturbances in a Canadian provincial administrative data repository.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2025Article
- Longitudinal visual outcomes in idiopathic intracranial hypertension: the role of early prognostic indicators and risk stratification in disease management.Journal of neurology · 2025Article
- From real world data to real world evidence to improve outcomes in neuro-ophthalmology.Eye (London, England) · 2024Review
- Characterization of technologies in digital health applied in vision care.Journal of optometry · 2022Review
- Nationwide population-based incidence and etiologies of pediatric and adult Horner syndrome.Journal of neurology · 2021Article
- Predicting Risk of Perioperative Ischemic Optic Neuropathy in Spine Fusion Surgery: A Cohort Study Using the National Inpatient Sample.Anesthesia and analgesia · 2020Article
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
Abstract
backgroundBig data clinical research involves application of large data sets to the study of disease. It is of interest to neuro-ophthalmologists but also may be a challenge because of the relative rarity of many of the diseases treated. EVIDENCE ACQUISITION: Evidence for this review was gathered from the authors' experiences performing analysis of large data sets and review of the literature.
resultsBig data sets are heterogeneous, and include prospective surveys, medical administrative and claims data and registries compiled from medical records. High-quality studies must pay careful attention to aspects of data set selection, including potential bias, and data management issues, such as missing data, variable definition, and statistical modeling to generate appropriate conclusions. There are many studies of neuro-ophthalmic diseases that use big data approaches.
conclusionsBig data clinical research studies complement other research methodologies to advance our understanding of human disease. A rigorous and careful approach to data set selection, data management, data analysis, and data interpretation characterizes high-quality studies.
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.