Evidence map›Paper›PMID 38091282›Full record

SynthesisPloS one2023

Prevalence of dry eye during the COVID-19 pandemic: A systematic review and meta-analysis.

Haiyang Ji, Yun Yang, Yunqiong Lu, Xiehe Kong, Guang Yang, Jie Liu, Yanting Yang, Xuejun Wang, Xiaopeng Ma

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
4.1field-weighted citation impact, top 6% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Pregnancy and Dry Eye Syndrome: A Review for Clinical Practice.International journal of molecular sciences · 2025
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. 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

9 authors at 3 institutions in 1 country.

Haiyang JiYueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.ORCID 0000-0002-2895-9606
Yun YangYueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.ORCID 0000-0001-9429-8204
Yunqiong LuYueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Xiehe KongShanghai Research Institute of Acupuncture and Meridian, Shanghai, China.
Guang YangShanghai Research Institute of Acupuncture and Meridian, Shanghai, China.
Jie LiuShanghai Research Institute of Acupuncture and Meridian, Shanghai, China.
Yanting YangShanghai Research Institute of Acupuncture and Meridian, Shanghai, China.
Xuejun WangEye & ENT Hospital, Fudan University, Shanghai, China.
Xiaopeng MaYueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Shanghai University of Traditional Chinese Medicine · CNShanghai Research Center for Acupuncture and Meridians · CNEye & ENT Hospital of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDuring the COVID-19 pandemic, many people devoted longer time to screen viewing due to the need for study, work, and online social activities, instead of outdoor activities, which may have led to an increase in dry eye symptoms. This study aimed to evaluate the prevalence of dry eye during the COVID-19 pandemic.

methodsPubMed, Cochrane Library, Embase, and Web of Science were searched from January 1, 2020 to October 20, 2022. Cross-sectional surveys on dry eye prevalence conducted after January 1, 2020 were included. Two review authors independently performed data extraction and assessed study quality. The random-effects model was used to analyze the prevalence of dry eye, and the odds ratio was used to assess the strength of the association between variables. Subgroup analysis was performed to detect heterogeneity, the leave-one-out method for sensitivity analysis, and the Egger test for publication bias.

resultsA total of eleven studies with 15692 individuals met the eligibility criteria. The prevalence of dry eye during the COVID-19 pandemic was 61.0% (95%CI: 51.8%-70.2%) globally and 56.7% (95%CI: 45.3%-68.1%) in Asia. The prevalence of dry eye had significant differences in sex and visual display time, with higher prevalence among females and visual display time of more than 4 hours per day. Subgroup analysis was performed based on diagnostic tools, study population, and average age. A significant difference was found in diagnostic tools, but no significant change in heterogeneity (P<0.05). The leave-one-out method showed stable results, and the Egger test identified no significant publication bias.

conclusionThe prevalence of dry eye during the COVID-19 pandemic is significantly higher than before, and a higher prevalence is found among females and those having a visual display time of more than 4 hours per day.

Indexed as

COVID-19Dry Eye SyndromesCross-Sectional StudiesFemaleHumansPandemicsPrevalence

Identifiers

PMID38091282
PMCPMC10718424
OpenAlexW4389669200

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.