Evidence map›Paper›PMID 39494281›Full record

ArticlePeerJ2024

A comparative study on the lipid layer thickness analysis of medical staff before and after work.

Qian Li, Xiufen Liu, Yu Ren, Tianlong He, Fei Shao, Nuerailimu Yimingtuohuti, Dan Li, Chengwei Lu

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Qian LiDepartment of Ophthalmology, The First Hospital of Jilin University, Changchun, Jilin, China.
Xiufen LiuDepartment of Ophthalmology, The First Hospital of Jilin University, Changchun, Jilin, China.
Yu RenDepartment of Ophthalmology, The First Hospital of Jilin University, Changchun, Jilin, China.
Tianlong HeDepartment of Ophthalmology, The First Hospital of Jilin University, Changchun, Jilin, China.
Fei ShaoDepartment of Ophthalmology, The First Hospital of Jilin University, Changchun, Jilin, China.
Nuerailimu YimingtuohutiDepartment of Ophthalmology, The First Hospital of Jilin University, Changchun, Jilin, China.
Dan LiDepartment of Ophthalmology, The First Hospital of Jilin University, Changchun, Jilin, China.
Chengwei LuDepartment of Ophthalmology, The First Hospital of Jilin University, Changchun, Jilin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background & Aims: To study the change of the lipid layer thickness analysis in medical staff (MS) before and after work, and to explore the significance of measuring lipid layer thickness (LLT) respectively in four quadrants. Methods: Ocular Surface Disease Index (OSDI) questionnaire and video display terminal using time for 55 MS were collected (the informed consent was obtained from all patients). Noninvasive tear break-up time, LLT, tear meniscus height (TMH), meibomian glands (MG) dropout, and blink pattern before and after work (worked for more than 4 h) of 110 eyes were measured by Gaush iDea Ocular surface analyzer. Lid margin abnormalities were evaluated by the slit-lamp microscopy. Results: The average OSDI score of 55 MS was 25.68 ± 14.91. The average LLT of 110 eyes after work (65.12 ± 3.63 nm) was significantly reduced compared to before work (66.54 ± 4.16 nm), Conclusion: The LLT significantly decreases after work in MS. The distribution of the lipid layer on the ocular surface is uneven. It is unreasonable for current detection instruments to measure the inferior quadrant LLT alone to represent average LLT.

Indexed as

TearsAdultBlinkingDry Eye SyndromesFemaleHumansLipidsMaleMedical StaffMeibomian GlandsMiddle AgedSurveys and QuestionnairesLipidsDry eye diseaseGaush iDea Ocular surface analyzerLipid layer thicknessMedical staffVideo display terminal

Identifiers

PMID39494281
PMCPMC11531743

What OpenQuestion holds

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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.