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Varenicline for Tobacco-Dependent Adults Who Are Not Ready to Discontinue Use: A Systematic Review and Meta-Analysis

2022· review· en· W4296714196 on OpenAlexaff
Luciane Cruz Lopes, Yuan Zhang, Stephanie Ross, Izabela Fulone, Meng Zhu, Kelly K. O’Brien, Sureka Pavalagantharajah, Frank T. Leone, David P.L. Sachs, Hasmeena Kathuria, Rachael L Murray, Yuqing Zhang

Bibliographic record

VenueAnnals of the American Thoracic Society · 2022
Typereview
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsMcMaster UniversityImpact
FundersChina Academy of Chinese Medical Sciences
KeywordsMedicineVareniclineMeta-analysisMEDLINESmoking cessationSystematic reviewTobacco useIntensive care medicineEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Abstract Rationale Not all individuals with tobacco dependence are ready to give up smoking. Research reveals behavioral differences between adults ready to discontinue tobacco use and those who are not. Thus, the interventions applied to these populations might differ. However, the evidence of using varenicline in individuals who are not ready to discontinue tobacco use is uncertain. Objectives To determine if, in tobacco-dependent adults who report not being ready to discontinue tobacco use, clinicians should begin treatment with varenicline or wait until subjects are ready to discontinue tobacco use. Methods We conducted a systematic review to assess the effectiveness and safety of treatment with varenicline in tobacco-dependent adults who are not ready to discontinue tobacco use. We systematically searched the Cumulative Index to Nursing and Allied Health Literature, Embase, MEDLINE, and the Cochrane Central Register of Controlled Trials to identify randomized controlled trials comparing varenicline versus placebo for individuals who were not ready to discontinue tobacco use. Outcomes of interest include point prevalence abstinence during treatment or at six months or longer, smoking reduction, motivation to quit, adverse events, and withdrawal symptoms. Two authors independently extracted data and assessed eligibility and risk of bias using a standardized data collection form. We followed the Grading of Recommendations, Assessment, Development and Evaluations approach to assess the certainty of evidence. Results Five trials met our inclusion criteria. All 2,616 participants were adults who were not ready to discontinue tobacco use at study entry. For 7-day point prevalence abstinence at six months or longer, high-certainty evidence suggested that varenicline increased abstinence compared with placebo (relative risk, 2.00 [95% confidence interval (CI), 1.70–2.35]; absolute risk reduction, 173 more per 1,000 [95% CI, 121 more to 234 more]). We identified moderate-certainty evidence suggesting that varenicline increased serious adverse events (relative risk, 1.75 [95% CI, 0.98–3.13]; absolute risk reduction, 12 more per 1,000 [95% CI, 0 fewer to 35 more]). For withdrawal, low-certainty evidence suggested that varenicline treatment was associated with a lower symptom score (mean difference, 1.54 points lower; 95% CI, 2.15–0.93 points lower; low certainty) assessed using the Brief Questionnaire of Smoking Urges. Conclusions In tobacco-dependent adults who are not ready to discontinue tobacco use, initiating varenicline treatment results in a large increase in abstinence and likely results in a slight increase in serious adverse events.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.027
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0190.026
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.373
GPT teacher head0.495
Teacher spread0.122 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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