Evidence map›Paper›PMID 31582921›Full record

ArticleTobacco induced diseases2019

A meta-analysis of the effectiveness of gradual versus abrupt smoking cessation.

Jixiang Tan, Lin Zhao, Hong Chen

Open access · goldAbstract read
In one paragraph

Article in Tobacco induced diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

11 citing papers in PubMed, 24 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
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  8. A call to ban the sale of tobacco products.Frontiers in public health · 2022
    Article
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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

3 authors at 2 institutions in 1 country.

Jixiang TanDepartment of Emergency & Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Lin ZhaoDepartment of Emergency & Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Hong ChenDepartment of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Chongqing Medical University · CNFirst Affiliated Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe aim of this review is to test whether a gradual reduction in smoking results in a superior quit rate compared to abrupt cessation.

methodsThis review was based on Cochrane methodology for conducting meta-analysis. Only randomized controlled trials were eligible for this review. The participants were adult smokers who were addicted to tobacco, defined as those who smoked at least 15 cigarettes or 12.5 grams of loose-leaf tobacco daily or who had an end-expiratory carbon monoxide concentration of at least 15 ppm. Both groups used an equal amount of nicotine replacement therapy (NRT) before and after quitting smoking. The Review Manager Database (RevMan version 5.3) was used to analyze selected studies.

resultsThree randomized controlled trials involving 1607 patients were included. The prolonged abstinence rate of the gradual cessation group was significantly lower than that of the abrupt group (relative risk, RR=0.77). The result of 7-day smoking cessation rate was also lower in the gradual group (RR=0.76).

conclusionsComparing the combination of NRT and abrupt cessation, the smoking cessation rate of the combination of NRT and gradual cessation is significantly lower. No significant adverse events were found in either group.

Indexed as

abruptgradualmeta-analysissmoking cessation

Identifiers

PMID31582921
PMCPMC6752113
OpenAlexW2913135182

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.