Evidence map›Paper›PMID 38832202›Full record

ReviewCureus2024

E-cigarette Use and Severe Coronavirus Disease 2019 (COVID-19) Outcomes: A Meta-Analysis.

Karen Valadez-Cuen, Tulsi Bhatt, Ileana E Mendez, Dhanshree Solanki, Nawal Abdi, Vrushali Shelar, Jerry J Akplor, Sai Akhila Reddy Bhumanapalli, Suprada Vinyak, Digantkumar Patel and 4 more

Abstract readReview
In one paragraph

Review in Cureus, 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

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

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

14 authors.

Karen Valadez-CuenDepartment of Internal Medicine, Las Palmas Del Sol Healthcare, El Paso, USA.
Tulsi BhattDepartment of Internal Medicine, Pramukhswami Medical College, Karamsad, IND.
Ileana E MendezDepartment of Medical Sciences, Universidad Autónoma de Centro América (UACA), San José, CRI.
Dhanshree SolankiDepartment of Hospital Administration, Rutgers University, New Brunswick, USA.
Nawal AbdiDepartment of Internal Medicine, University Hospitals Cleveland Medical Center, Cleveland, USA.
Vrushali ShelarDepartment of Internal Medicine, Saratov State Medical University, Saratov, RUS.
Jerry J AkplorFaculty of Medicine, Hebei North University, Zhangjiakou, CHN.
Sai Akhila Reddy BhumanapalliDepartment of Internal Medicine, State University of New York (SUNY) Downstate Health Sciences University, School of Public Health (SPH), New York, USA.
Suprada VinyakDepartment of Internal Medicine, Wellmont/Norton Community Hospital (NCH), Norton, USA.
Digantkumar PatelDepartment of Medicine, Springfield Memorial Hospital, Springfield, USA.
Raghavendra TirupathiDepartment of Internal Medicine, Keystone Health, Chambersburg, USA.
Viray ShahDepartment of Hospital Medicine, MedStar Good Samaritan Hospital, Baltimore, USA.
Urvish K PatelDepartment of Public Health and Neurology, Icahn School of Medicine at Mount Sinai, New York, USA.
Rishabh K RanaDepartment of Preventive and Social Medicine/Community Medicine, Shaheed Nirmal Mahto Medical College and Hospital (Erstwhile Patliputra Medical College), Dhanbad, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

E-cigarettes have been known to cause varied poor health outcomes prior to coronavirus disease 2019 (COVID-19), but after the impact of COVID-19, evidence came out that was, in some instances, not as expected regarding the severity of COVID-19 among e-cigarette users (vapers). A meta-analysis was performed on the available evidence to comprehensively find the effect of COVID-19 on existing or past e-cigarette users (vapers). The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were used to perform this meta-analysis. PubMed was searched for observational studies that described outcomes after COVID-19 positivity from December 1, 2019, to December 2023. Medical Subject Headings (MeSH) keywords were used for searching the relevant studies highlighting the relationship between COVID-19 and e-cigarette users. Calculations for pooled prevalence, 95% confidence interval (95% CI), weights for current e-cigarette users and vapers, and outcomes (events) were made. To analyze the data, Review Manager V.5.4 was used. The I² statistic was used to assess statistical heterogeneity. The I² statistic of >50% was considered significant heterogeneity. The "leave-one-out" method was used for sensitivity analysis. Out of 3231 studies, four studies reported data on vaping and non-vaping status and composite outcomes, resulting in a sample size of 653 COVID-19-positive cases. The pooled prevalence of being COVID-19 positive, having symptoms, or visiting an emergency room was 7.78% (653/8392). COVID-19 patients with current vaping status had decreased odds of poor outcomes compared to non-smokers, with a pooled odds ratio (OR) of 0.09 (95% CI 0.00-2.42; p>0.05) with heterogeneity between studies (I²=99%, p=0.15). Because of difficulties related to data collection and other factors, this meta-analysis was unable to conclusively establish the correlation between e-cigarette usage and severe COVID-19 outcomes such as hospitalization, admission to the intensive care unit, and fatality. Additional research using more detailed data is necessary to fully understand this correlation.

Indexed as

covid-19e-cigarette smokingeffects of vapingmeta-analysispublic health and safetysars-covsars-cov-2 and covid-19

Identifiers

PMID38832202
PMCPMC11144579

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.