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Record W4309013167 · doi:10.3390/curroncol29110676

Nicotine-Free E-Cigarettes Might Promote Tobacco Smoking Reduction Better Than Nicotine Delivery Devices: Results of a Double-Blind Randomized Controlled Trial at 1 Year

2022· article· en· W4309013167 on OpenAlexvenueno aff
Claudio Lucchiari, Marianna Masiero, Ketti Mazzocco, Giulia Veronesi, Patrick Maisonneuve, Costantino Jemos, Emanuela Omodeo Salè, Stefania Spina, Raffaella Bertolotti, Derna Busacchio, Gabriella Pravettoni

Bibliographic record

VenueCurrent Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersFondazione Umberto VeronesiMinistero della Salute
KeywordsMedicineNicotineSmoking cessationRandomized controlled trialLung cancerClinical trialAlcohol consumptionNicotine replacement therapyCigarette smokingEnvironmental healthInternal medicineAlcoholPathology

Abstract

fetched live from OpenAlex

The purpose of the present study was to determine whether the use of e-cigarettes to aid in quitting contributed to the increase in the pulmonary health of chronic smokers. The efficacy of e-cigarettes to support a successful smoking cessation attempt was also investigated. A total of 210 smokers (78 women) were enrolled in a screening program for the early detection of lung cancer and distributed in three arms: nicotine e-cigarette plus support, nicotine-free e-cigarette plus support, and support. Results showed that participants in the nicotine e-cigarette arm had a significant and fast decrease in daily cigarettes, but that later they resume smoking more than the other two groups. Conversely, participants in the other two arms showed similar daily consumption at the two evaluation points. Among abstinent participants, only 12.5% reported cough, while 48% of current smokers had pulmonary symptoms. Our study suggests that, in the long run, the use of a nicotine-free liquid may favor reducing smoking and could be considered a good option in a clinical setting.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.084
GPT teacher head0.362
Teacher spread0.278 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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

Citations28
Published2022
Admission routes1
Has abstractyes

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