Evidence map›Paper›PMID 38409465›Full record

ArticleScientific reports2024

Optimal cutoff value of the dry eye-related quality-of-life score for diagnosing dry eye disease.

Xinrong Zou, Ken Nagino, Yuichi Okumura, Akie Midorikawa-Inomata, Atsuko Eguchi, Alan Yee, Keiichi Fujimoto, Maria Miura, Jaemyoung Sung, Tianxiang Huang and 5 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

9 citing papers in PubMed, 5 citations in OpenAlex.

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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

15 authors at 2 institutions in 1 country.

Xinrong Zou *Department of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Ken Nagino *Department of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Yuichi OkumuraDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Akie Midorikawa-InomataDepartment of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Atsuko EguchiDepartment of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Alan YeeDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Keiichi FujimotoDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Maria MiuraDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Jaemyoung SungDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Tianxiang HuangDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Kenta FujioDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Yasutsugu AkasakiDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Shintaro NakaoDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Hiroyuki KobayashiDepartment of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Takenori InomataDepartment of Ophthalmology, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. tinoma@juntendo.ac.jp.
Juntendo University · JPJuntendo University Hospital · JP

Funding

Japan Society for the Promotion of Science 20KK0207Japan Society for the Promotion of Science 21K17311Japan Society for the Promotion of Science 22K16983
6 · The paper itself

Abstract

This retrospective study aimed to determine the optimal cutoff values of the Dry Eye-Related Quality-of-Life Score (DEQS) questionnaire for diagnosing dry eye disease (DED) and classifying DED severities. Participants completed the DEQS questionnaire, the Japanese version of the Ocular Surface Disease Index (J-OSDI) questionnaire, and DED examinations. DED was diagnosed according to the 2016 Asia Dry Eye Society diagnostic criteria based on DED symptoms (J-OSDI ≥ 13 points) and tear film breakup time ≤ 5 s. Receiver operating characteristic (ROC) analysis was used to calculate the optimal cutoff values of the DEQS summary score for detecting DED and grading its severity. Among 427 patients, 296 (69.3%) and 131 (30.7%) were diagnosed with DED and non-DED, respectively. ROC analysis determined an optimal cutoff value of 15.0 points for DED diagnosis, with 83.5% sensitivity, 87.0% specificity, and an area under the curve of 0.915. The positive and negative predictive values for DEQS ≥ 15.0 points were 93.6% and 69.9%, respectively. DEQS cutoff values of 15.0, 20.0, and 26.8 points could be accepted for severity classification of DED subjective symptoms in clinical use and represent mild, moderate, and severe DED, respectively. Conclusively, the optimal cutoff values of DEQS enable DED detection and subjective symptom severity classification.

Indexed as

Dry Eye SyndromesHumansPredictive Value of TestsQuality of LifeRetrospective StudiesROC CurveTears

Identifiers

PMID38409465
PMCPMC10897401
OpenAlexW4392167995

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.