Evidence map›Paper›PMID 38260776›Full record

SynthesisFrontiers in psychiatry2023

Prevalence of poor sleep quality in COVID-19 patients: a systematic review and meta-analysis.

Zhen Gui, Yue-Ying Wang, Jia-Xin Li, Xiao-Hong Li, Zhaohui Su, Teris Cheung, Ka-In Lok, Gabor S Ungvari, Chee H Ng, Qinge Zhang and 1 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
7.7field-weighted citation impact, top 2% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Observational
  4. SARS-CoV-2 infection and sleep health in Military Health System beneficiaries.Sleep advances : a journal of the Sleep Research Society · 2026
    Article
  5. Article
  6. 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

11 authors at 8 institutions in 4 countries.

Zhen Gui *Unit of Psychiatry, Department of Public Health and Medicinal Administration, Faculty of Health Sciences, Institute of Translational Medicine, University of Macau, Macao SAR, China.
Yue-Ying Wang *Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China.
Jia-Xin Li *Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China.
Xiao-Hong Li *Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China.
Zhaohui SuSchool of Public Health, Southeast University, Nanjing, China.
Teris CheungSchool of Nursing, Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.
Ka-In LokFaculty of Health Sciences and Sports, Macao Polytechnic University, Macao SAR, China.
Gabor S UngvariSection of Psychiatry, University of Notre Dame Australia, Fremantle, WA, Australia.
Chee H NgDepartment of Psychiatry, The Melbourne Clinic and St Vincent's Hospital, University of Melbourne, Richmond, VIC, Australia.
Qinge ZhangBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Yu-Tao XiangUnit of Psychiatry, Department of Public Health and Medicinal Administration, Faculty of Health Sciences, Institute of Translational Medicine, University of Macau, Macao SAR, China.
University of Macau · MOCapital Medical University · CNHong Kong Polytechnic University · HKMacao Polytechnic University · MOPeking University · CNSoutheast University · CNSt Vincent's Hospital · AUThe University of Notre Dame Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The coronavirus disease (COVID-19) and the public health responses were associated with a huge health burden, which could influence sleep quality. This meta-analysis and systematic review examined the prevalence of poor sleep quality in COVID-19 patients. Methods: PubMed, Web of Science, Embase, and PsycINFO were systematically searched from their respective inception to October 27, 2022. Prevalence rates of poor sleep were analyzed using a random effects model. Results: Totally, 24 epidemiological and 12 comparative studies with 8,146 COVID-19 patients and 5,787 healthy controls were included. The pooled prevalence of poor sleep quality based on the included studies was 65.0% (95%CI: 59.56-70.44%, Conclusion: Poor sleep quality was found to be very common in COVID-19 patients. Considering the negative effects of poor sleep quality on daily life, sleep quality should be routinely assessed and appropriately addressed in COVID-19 patients.

Indexed as

COVID-19meta-analysisprevalencereviewsleep quality

Identifiers

PMID38260776
PMCPMC10800583
OpenAlexW4390665952

What OpenQuestion holds

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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.