Evidence map›Paper›PMID 34484520›Full record

ArticleRadiology case reports2021

Crazy vaping and crazy-paving, a case of E-Cigarette/Vaping-Associated Lung Injury (EVALI) with chest CT showing crazy-paving pattern.

Sherif Roman, Christopher Millet, Shady Geris, Rajapriya Manickam, Ashesha Mechineni

Erratum issuedAbstract readCase Reports
In one paragraph

Article in Radiology case reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Sherif RomanDepartment of Medicine, St. Joseph's University Medical Center, NJ, USA.
Christopher MilletDepartment of Medicine, St. Joseph's University Medical Center, NJ, USA.
Shady GerisDepartment of Medicine, St. Joseph's University Medical Center, NJ, USA.
Rajapriya ManickamDepartment of Pulmonary/Critical Care, St. Joseph's University Medical Center, NJ, USA.
Ashesha MechineniDepartment of Medicine, St. Joseph's University Medical Center, NJ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

E-cigarettes are devices that generate an aerosol by heating a fluid containing multiple chemicals, such as nicotine, additives, and flavorings. They were developed to aid in smoking cessation and were promoted as socially acceptable, healthier, cheaper than conventional cigarettes. Multiple lung disorders related to e-cigarette use are reported, and they range from mild cases of pneumonitis to life-threatening lung disorders that may require intubation and mechanical ventilation. Most of the complications are due to the generation of various unknown and potentially harmful chemicals within the aerosol generated in the e-cigarette. These disorders are known collectively as e-cigarette/Vaping-associated lung injury (EVALI). E-cigarettes are marketed as safer alternatives to traditional cigarettes, with the highest rates of use are noted in young smokers. Given the significant prevalence of e-cigarettes use and their pulmonary complications, EVALI should be considered a potential etiology in the broad differential diagnosis of patients with pulmonary disease and a history of vaping. Herein, we present a case of cryptogenic organizing pneumonia with a chest C.T. showing a crazy-paving pattern in a patient with a history of vaping.

Indexed as

CannabisCDC, Centers for Disease Control and Prevention(COP, formerly BOOP), Cryptogenic organizing pneumoniaCrazy-Paving PatternCT, Computed TomographyE-CigaretteE-cigarette, Electronic CigaretteEVALIEVALI, E-cigarettes or Vaping Associated Lung IllnessGround-Glass OpacityNicotineOrganizing PneumoniaVAPIVaping

Identifiers

PMID34484520
PMCPMC8405923

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.