Chronic health effects associated with electronic cigarette use: A systematic review
Bibliographic record
Abstract
Introduction: Over the last decade, e-cigarette use has been on the rise but with growing health concerns. The objective of this systematic review was to update findings for chronic health outcomes associated with e-cigarette use from the 2018 National Academies of Sciences, Engineering, and Medicine (NASEM) report. Methods: Three bibliographic databases were searched to identify studies comparing the chronic health effects of e-cigarette users (ECU) to non-smokers (NS), smokers, and/or dual users indexed between 31 August 2017 and 29 January 2021. Two independent reviewers screened abstracts and full texts. Data were extracted by one reviewer and verified by a second one. Outcomes were synthesized in a narrative manner using counts and based on statistical significance and direction of the association stratified by study design and exposure type. Risk of bias and certainty of evidence was assessed. The protocol was prospectively registered on Open Science Framework https://osf.io/u9btp. Results: A total of 180 articles were eligible. This review focused on 93 studies for the 11 most frequently reported outcomes and from which 59 reported on daily e-cigarette use. The certainty of evidence for all outcomes was very low because of study design (84% cross-sectional) and exposure type (27% reported on exclusive ECU, i.e., never smoked traditional cigarettes). Overall, the summary of results for nearly all outcomes, including inflammation, immune response, periodontal and peri-implant clinical parameters, lung function, respiratory symptoms, and cardiovascular disease, suggested either non-significant or mixed results when daily ECU was compared to NS. This was also observed when comparing exclusive ECU to NS. The only notable exception was related to oral health where most (11/14) studies reported significantly higher inflammation among daily ECU vs. NS. Compared to the smokers, the exclusive-ECUs had no statistically significant differences in inflammation orperiodontal clinical parameters but had mixed findings for peri-implant clinical parameters. Conclusions: This review provides an update to the 2018 NASEM report on chronic health effects of e-cigarette use. While the number of studies has grown, the certainty of evidence remains very low largely because of cross-sectional designs and lack of reporting on exclusive e-cigarette exposure. There remains a need for higher quality intervention and prospective studies to assess causality, with a focus on exclusive e-cigarette use.
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 | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".