Evidence map›Paper›PMID 34989951›Full record

ArticleInternational ophthalmology2022

The detection of keratoconus using novel metrics derived by anterior segment optical coherence tomography.

Isa S K Mohammed, Sang Tran, Luis A Toledo-Espiett, Wuqaas M Munir

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Article in International ophthalmology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

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4 · The record

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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

4 authors.

Isa S K MohammedDepartment of Ophthalmology and Visual Sciences, University of Maryland School of Medicine, 419 W Redwood Street, Suite 470, Baltimore, MD, 21201, USA.
Sang TranDepartment of Ophthalmology and Visual Sciences, University of Maryland School of Medicine, 419 W Redwood Street, Suite 470, Baltimore, MD, 21201, USA.
Luis A Toledo-EspiettDepartment of Ophthalmology and Visual Sciences, University of Maryland School of Medicine, 419 W Redwood Street, Suite 470, Baltimore, MD, 21201, USA.
Wuqaas M MunirDepartment of Ophthalmology and Visual Sciences, University of Maryland School of Medicine, 419 W Redwood Street, Suite 470, Baltimore, MD, 21201, USA. wmunir@som.umaryland.edu.ORCID http://orcid.org/0000-0001-8070-6668

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo determine through a feasibility study whether anterior and posterior corneal arc length and cross-sectional area measured using anterior segment ocular coherence tomography (AS-OCT) can distinguish between healthy and keratoconic corneas.

methodsPatients diagnosed with keratoconus along with healthy controls underwent AS-OCT. ImageJ was used to determine the central 6 mm anterior and posterior corneal arc lengths and cross-sectional areas. Each length and area was then divided into 1-mm segment and relative differences compared.

resultsTwenty-five eyes from 15 patients with keratoconus, along with 25 eyes from 14 healthy controls were enrolled. There was a statistically significant difference in anterior and posterior corneal arc lengths as well as corneal cross-sectional area (p = 0.006, p = 0.005, p = 0.01, respectively). When selecting for the less advanced keratoconus eye, it was noted that posterior corneal arc length was longer in the paracentral temporal segment (1003 vs. 1010 µm, p = 0.04) and that greater change in corneal cross-sectional areas occurred between adjacent segments in less advanced keratoconus eyes.

conclusionAS-OCT is capable of reliably measuring corneal arc lengths in patients with keratoconus and healthy patients. Both anterior and posterior corneal arc lengths along with central cross-sectional areas are statistically different between healthy and keratoconus eyes.

Indexed as

KeratoconusBiometryCorneaCorneal TopographyHumansTomography, Optical CoherenceAnterior segment optical coherence tomographyCorneal imagingKeratoconusRefractive surgery

Identifiers

PMID34989951

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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.