Evidence map›Paper›PMID 36968284›Full record

ArticleClinical ophthalmology (Auckland, N.Z.)2023

Early Lifetime Substance Use and Development of Visual Impairment: Analysis of the National Survey on Drug Use and Health Data.

Zain S Hussain, Asher Khan, Asad Loya, Kaushal Shah, Fasika A Woreta, Kamran M Riaz

Abstract read
In one paragraph

Article in Clinical ophthalmology (Auckland, N.Z.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from 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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zain S HussainUniversity of Medicine and Health Sciences, Basseterre, Saint Kitts and Nevis.ORCID 0000-0003-3436-2651
Asher KhanDepartment of Ophthalmology, Dean McGee Eye Institute, Oklahoma City, OK, USA.
Asad LoyaDepartment of Ophthalmology, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0002-2136-4650
Kaushal ShahDepartment of Psychiatry and Behavioral Sciences, Oklahoma State University, Tulsa, OK, USA.ORCID 0000-0002-6444-5151
Fasika A WoretaDepartment of Ophthalmology, Johns Hopkins Wilmer Eye Institute, Baltimore, MD, USA.ORCID 0000-0001-9401-4283
Kamran M RiazDepartment of Ophthalmology, Dean McGee Eye Institute, Oklahoma City, OK, USA.ORCID 0000-0003-1090-5025

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To investigate the association between early lifetime substance use on the development of severe visual acuity impairment or blindness on a national level. Methods: National Survey of Drug Use and Health data was used to identify cases of substance use before 21* years of age, within the past year, and cases of self-reported blindness or visual impairment. Univariable and multivariable binary logistic regression with time-dependency was performed to evaluate odds of visual impairment influenced by 16 substances separated into three classes: prescription, non-prescription, and illicit drugs. Adjusted variables of interest included gender, marital status, race, level of education, total family income, poverty level, population density, and history of chronic disease. Results: 55,824 total responses were analyzed with 2577 (4.6%) cases of self-reported blindness or significant visual impairment. All early-use substance categories, including prescription, non-prescription, and illegal substances, were significantly associated with self-reported VI (OR 2.068, CI 1.451-2.949, Conclusion: Early lifetime use of all three classes of substances is associated with enhanced odds of subsequent visual impairment or blindness. Several readily available and commonly used substances have a greater risk. These findings may help clinicians and public health agencies in mitigation ventures including education, prevention, and rehabilitation efforts.

Indexed as

ophthalmologysubstance usevision loss

Identifiers

PMID36968284
PMCPMC10030542

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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.