Evidence map›Paper›PMID 35165641›Full record

ArticleCureus2022

Marijuana and Myocardial Infarction in the UK Biobank Cohort.

Steven Lehrer, Peter H Rheinstein

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

2 authors at 1 institution in 1 country.

Steven LehrerRadiation Oncology, Icahn School of Medicine at Mount Sinai, New York City, USA.
Peter H RheinsteinFamily Medicine, Severn Health Solutions, Severna Park, USA.
Icahn School of Medicine at Mount Sinai · US

Funding

Big Omics Data Engine 2 SupercomputerS10OD026880 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2019 to 2019
$2.0M
Transforming Genomics with 5 PB Big Omics Data Engine Cray CS300-AC SupercomputerS10OD018522 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2014 to 2014
$1.9M
NIH HHS S10 OD018522NIH HHS S10 OD026880
6 · The paper itself

Abstract

backgroundAtrial fibrillation, ventricular tachycardia, acute coronary syndromes, and cardiac arrest have been attributed to marijuana. But the National Academy of Science's 2017 Report,

aimsWe sought to determine the association of marijuana smoking with MI in the UK Biobank cohort. Because red wine is a mood-altering substance, we compared the effect of marijuana with red wine on MI incidence.

methodsOur analysis included all subjects with MI. The diagnosis was ascertained using the 10

resultsWith marijuana use, MI incidence decreased (p < 0.001, two tail Fisher exact test). Red wine was associated with lower MI incidence, although the incidence begins to rise at 11 or more glasses per week (p < 0.001, two tail Fisher exact test). Multivariate analysis was done with logistic regression, MI dependent variable, cigarette pack-years, diabetes type 2, sex, BMI, hypertension, marijuana use, age, red wine consumption, independent variables. Odds ratio (O.R.) 0.844 associated with marijuana use indicates that MI was less likely in marijuana users and was comparable to the effect of red wine (O.R. 0.847).

conclusionMarijuana, which has not been shown to have the favorable physiologic effects of red wine on the heart, does reduce MI risk to an extent comparable to red wine. Perhaps both affect the heart by reducing stress.

Indexed as

heartmarijuanamyocardial infarctrisk factorssmoking

Identifiers

PMID35165641
PMCPMC8826760
OpenAlexW4210915559

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.