Evidence map›Paper›PMID 35957745›Full record

ArticleJournal of ophthalmology2022

A Novel, Low-Cost Glaucoma Calculator to Identify Glaucoma Patients and Stratify Management.

Daniel Laroche, Kara Rickford, Elise V Mike, Liane Hunter, Ezekiel Ede, Chester Ng, John Douglas

Open access · goldAbstract read
In one paragraph

Article in Journal of ophthalmology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 13% of its field
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

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
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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

7 authors at 6 institutions in 1 country.

Daniel LarocheNew York Eye and Ear Infirmary, Icahn School of Medicine of Mount Sinai, New York, NY, USA.ORCID https://orcid.org/0000-0002-4864-0918
Kara RickfordNew York Medical College, Valhalla, NY, USA.ORCID https://orcid.org/0000-0003-4160-7020
Elise V MikeWilmer Eye Institute, Johns Hopkins Hospital, Baltimore, MD, USA.
Liane HunterMontefiore Medical Center, Bronx, NY, USA.
Ezekiel EdeAdvanced Eye Care of New York, New York, NY, USA.
Chester NgAdvanced Eye Care of New York, New York, NY, USA.
John DouglasMercer University School of Medicine, Savannah, GA, USA.
Eye Care Associates · USJohns Hopkins Hospital · USMercer University · USMontefiore Medical Center · USNew York Eye and Ear Infirmary · USNew York Medical College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glaucoma is a leading cause of preventable blindness globally. Nearly, half of the patients who have glaucoma in the United States are unaware of their diagnosis, and this number is far greater in resource poor areas. The risk of progressive and irreversible loss of vision is decreased with an early diagnosis, and better access to treatment is vital to improve the visual outcome for patients. We therefore postulated that a minimally invasive, low-cost calculator used to predict the risk of glaucoma and inform the course of follow-up care will improve patient prognosis. We retrospectively examined data from 104 eyes of patients who underwent a complete ocular examination, visual field, and corneal pachymetry at Advanced Eye Care of New York (54 with glaucoma and 50 controls). Receiver operating curves (ROC) were utilized to determine the correct glaucoma classification rates of the Laroche glaucoma calculator (Range -3 to 18), a novel tool that combines age, intraocular pressure (IOP), and central corneal thickness (CCT) into a composite metric. Additionally, we compared the discriminatory power of this calculator to age, intraocular pressure (IOP), and central corneal thickness (CCT) separately. A score of greater than or equal to 6 on the Laroche glaucoma calculator (sensitivity 90.74%, specificity 64.00%, correct classification 77.88%) optimizes the accuracy of this tool. Compared to IOP (Area Under the Curve (AUC) = 0.72, chi

Identifiers

PMID35957745
PMCPMC9357680
OpenAlexW4289133689

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.