Evidence map›Paper›PMID 23571234›Full record

Trial reportIndian journal of ophthalmology2013

Sensitivity and specificity of time-domain versus spectral-domain optical coherence tomography in diabetic macular edema.

Nishal Patel, Haziq Chowdhury, Richard Leung, Sobha Sivaprasad

Open access · diamondAbstract readComparative StudyMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Indian journal of ophthalmology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
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

4 authors at 1 institution in 1 country.

Nishal PatelDepartment of Retinal and Laser Research, Kings College Hospital and School of Medicine, Denmark Hill, United Kingdom, London, United Kingdom.
Haziq Chowdhury
Richard Leung
Sobha Sivaprasad
King's College Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe purpose was to evaluate the sensitivity and specificity of measurements of central macular thickness (CMT) in diabetic macular edema using stratus time-domain and cirrus spectral-domain optical coherence tomography (OCT; Carl Zeiss Meditec, Dublin, CA). MATERIALS AND

methodsA total of 36 eyes from 19 patients with clinically significant diabetic macular edema (DME) were included. All participants underwent automated scanning patterns using cirrus HD-OCT and stratus OCT examinations on the same day. The sensitivity/specificity of retinal thickness measurements was calculated from published normative data. Agreement was calculated using Bland--Altman method. The receiver operating characteristic curves (ROC) and areas under the ROC were plotted.

resultsThe mean difference between the cirrus HD-OCT and stratus OCT in the central foveal zone was 49.89 μm. Bland--Altman analysis confirmed that the retinal thickness measurements had poor agreement in patients with DME. The areas under the ROC for retinal thickness measurements were 0.88 using cirrus HD-OCT and 0.94 with stratus.

conclusionsIn patients with DME, the cirrus HD-OCT gives a higher reading than stratus OCT with poor agreement between the devices in most regions within the nine subfield zones. The sensitivity and specificity of the stratus OCT was comparable to the cirrus.

Indexed as

AlgorithmsDiabetic RetinopathyFemaleHumansMacular EdemaMaleMiddle AgedRetinal Ganglion CellsROC CurveTomography, Optical Coherence

Identifiers

PMID23571234
PMCPMC3730503
OpenAlexW2025748892

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.