Association of smoking reduction and mortality: protocol for a systematic review and meta-analysis of longitudinal observational studies
Bibliographic record
Abstract
INTRODUCTION: Strong evidence shows that smoking cessation decreases mortality. Much less is known regarding the association between reduction in cigarettes per day (CPD) and mortality. The primary aim of this systematic review is to compare the mortality risk between smokers achieving a sustained reduction of CPD and smokers maintaining their smoking rate. The secondary aims are to compare the mortality risk between smokers achieving complete, sustained smoking cessation and (1) smokers maintaining their smoking rate and (2) smokers who achieved a sustained reduction in smoking rate. METHODS AND ANALYSIS: MEDLINE, Web of Sciences and Embase will be searched using a prespecified search strategy, up to 23 November 2020, and will be limited to studies published in English and in French. Longitudinal observational studies using individual data including smokers with at least two distant CPD assessments and a follow-up period of systematic mortality data recording will be included. The main outcome will be the all-cause mortality. The secondary outcome will be specific mortality. The Newcastle-Ottawa Scale will be used to assess the risk of bias of individual studies. Outcomes will be analysed using HRs. All other outcomes' effect size reported in included studies will be converted in HRs using validated methods. ETHICS AND DISSEMINATION: We intend to publish the results of our review in a peer-reviewed journal and to present the findings at national and international meetings and conferences. PROSPERO REGISTRATION NUMBER: CRD42019138354.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.075 | 0.115 |
| Meta-epidemiology (narrow) | 0.008 | 0.006 |
| Meta-epidemiology (broad) | 0.027 | 0.030 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.054 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".