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Kaimen Rigor review

Electronic Cigarette Use and Myocardial Infarction Among Adults in the US Population Assessment of Tobacco and Health

Bhatta DN, Glantz SA.

DOI: 10.1161/jaha.119.012317
Record issued: 2026-08-05
Engine: 7.15.0
Exported: 2026-09-19

Prepared by Alpha1. This document is confidential: it is intended for the recipient it was shared with and must not be redistributed. The live record at alpha1science.com/verify/bc840dcd-1b60-4c4a-91b0-74c411b3fdd9 is authoritative.

Kaimen Rigor review

Kaimen Rigor reviewed

3 / 5

Adequate — real issues to address

Observational Study

Critical

High-priority

How this rating was calculated

Started at 5★ — deductions

ClaimsOverstated claim−0.5★
ReportingStudy design not met−0.5★
CitationsUnresolved reference ×2−0.5★
ReportingEthical approvals partially met−0.25★
ReportingStatistical analysis partially met−0.25★

Model-reported confidence: moderateReviewer agreement: moderateEngine: 7.15.0Source: full text

Not verified in this report

Declared data/code links were not checked for liveness or content.

Biggest issues

01Study design lacks key rigor safeguards
highDisclosurereviewer-assessedFull detail
The study design element is inadequately reported; no a priori power analysis, no pre-specified inclusion/exclusion criteria, and no outlier handling are described.
“Current experimental e‐cigarette users (current e‐cigarette users but never used e‐cigarettes fairly regularly) were not included in the main analysis but were considered some‐day users in a sensitivity analysis.”
Methods
02Conclusion reaches beyond the evidence
mediumOverreachreviewer-assessedFull detail
E-cigarettes should not be promoted or prescribed as a less risky alternative to combustible cigarettes.
“E‐cigarettes should not be promoted or prescribed as a less risky alternative to combustible cigarettes and should not be recommended for smoking cessation among people with or at risk of myocardial infarction.”
Conclusion

Findings by category

01ArithmeticNone found 202OverreachOverstated conclusions 03AuthenticityNone found 304DisclosureReporting gaps 105AvailabilityBroken references and links · partly checked 06Copyedit14 minor suggestions

This Kaimen Rigor review uses Kaimen Rigor reviewers trained on a curated corpus of high-fidelity and retracted papers, with expert supervision and curation. It can still make mistakes; verify each finding against the source before relying on it.

The paper is a well-motivated observational re-analysis of PATH data with clearly reported demographic/clinical variables, named statistical tests, and 11 recomputed statistics consistent with the text. Its main weaknesses are reporting gaps rather than demonstrable errors: no a priori power analysis for the primary analysis, no outlier/missing-data handling, threshold-only dose-response p-values, no STROBE reference, no sharing of analysis code, and a conclusion that over-extends the evidence on e-cigarette prescription/promotion.

Synthesis integrates three independent reviewer runs (same model), a copyedit pass, a citation check (37 references), and a statistics verification covering 11 recomputable tests; key resources was treated as not applicable. The statistics verification covers only tests with test statistics and degrees of freedom or effect estimates with CIs, so the broader analysis is unverified rather than confirmed.

Numerical inconsistencies

None found

Values that contradict each other or are impossible for the stated sample: recomputed p-values and test statistics, GRIM/GRIMMER checks on summary numbers, percentages against their own counts, totals against their parts, and estimates against their own confidence intervals.

Checked — nothing surfaced.

Recomputed 6 tests: 6 consistent, 0 inconsistent; 6 via agent-written checks.

Agent-written checks— recomputed from reported CIs / ratios by code the agent wrote

CONSISTENTreported p = .010 · recomputed p = .008Reviewers 1, 2, 3
p-value for every-day e-cigarette use AOR=2.25, 95% CI 1.23-4.11
How we recomputed it: pCI(2.25, 1.23, 4.11, 1)
CONSISTENTreported p = .024 · recomputed p = .021Reviewers 1, 2, 3
p-value for some-day e-cigarette use AOR=1.99, 95% CI 1.11-3.58
How we recomputed it: pCI(1.99, 1.11, 3.58, 1)
CONSISTENTreported p = .001 · recomputed p = <.001Reviewers 1, 3
p-value for every-day cigarette smoking AOR=2.95, 95% CI 1.91-4.56
How we recomputed it: pCI(2.95, 1.91, 4.56, 1)
CONSISTENTreported p = .687 · recomputed p = .692Reviewer 1
p-value for reverse causality: MI at Wave 1 predicting every-day e-cig use at Wave 2 (overall sample)
How we recomputed it: pCI(0.85, 0.38, 1.90, 1)
CONSISTENTreported p < .001 · recomputed p = <.001Reviewer 2
p-value for every-day cigarette smoking from AOR and 95% CI
How we recomputed it: pCI(2.95, 1.91, 4.56, 1)
CONSISTENTreported p = .002 · recomputed p = .001Reviewer 3
p-value for some-day cigarette smoking AOR 2.38, 95% CI 1.40-4.06 (log scale)
How we recomputed it: pCI(2.38, 1.40, 4.06, 1)

Overstated conclusions

2 findings · worst medium

Conclusions that reach past what the paper's own results support — including a significance claim that no longer holds when the statistic is recomputed, and efficacy resting on an unvalidated surrogate endpoint.

Conclusions overstated beyond the evidenceAssessed
Conclusions only partially backed by the presented evidenceAssessed

11 major claims checked against the paper's own evidence: 1 not fully backed by the presented evidence (unsupported or overstated).

overstatedReviewers 1, 2, 3
E-cigarettes should not be promoted or prescribed as a less risky alternative to combustible cigarettes.
The paper's data show that e-cigarettes are associated with increased MI risk, but the claim that they should not be prescribed for smoking cessation extends beyond the direct evidence, which does not test efficacy of e-cigarettes for cessation.
Evidence: The paper provides no data on cessation outcomes; it only shows that e-cigarette use is associated with MI risk independent of smoking.
“E‐cigarettes should not be promoted or prescribed as a less risky alternative to combustible cigarettes and should not be recommended for smoking cessation among people with or at risk of myocardial infarction.”
Conclusion
partialReviewer 2
Switching from combustible cigarettes to e-cigarettes does not reduce the risk of myocardial infarction.
The paper calculates that switching yields a risk factor of 1.13 compared to continuing smoking, which is 'virtually no benefit.' However, this calculation is based on cross-sectional odds ratios and may not reflect causal effects of switching.
Evidence: Discussion: (OR former smoker × OR every-day e-cigarette user)/OR every-day smoker = 3.33/2.95 = 1.13.
Odds of having had a myocardial infarction for individuals who switched from every‐day combustible cigarette smoking to every‐day e‐cigarette use would change by a factor of … 1.13, which is virtually no benefit in terms of myocardial infarction risk.
Discussion ¶4reviewer’s wording
supportedReviewer 1
E-cigarette use is independently associated with increased odds of having had a myocardial infarction, with a dose-response.
The cross-sectional analysis provides adjusted odds ratios (some-day: 1.99, 95% CI 1.11-3.58; every-day: 2.25, 95% CI 1.23-4.11) and a significant dose-response test (P<0.0005).
Evidence: Table 3 and Results: 'There was a significant dose‐response for both e‐cigarette use (P<0.0005) and smoking (P=0.019) and myocardial infarction.'
There was a significant dose‐response for both e‐cigarette use (P<0.0005) and smoking (P=0.019) and myocardial infarction controlling for demographic and clinical variables.
Results ¶3reviewer’s wording
supportedReviewer 1
The association between e-cigarette use and MI is not due to reverse causality.
Longitudinal analysis shows that having had an MI at Wave 1 does not predict e-cigarette use at Wave 2 (P>0.62 for all outcomes), directly addressing reverse causality.
Evidence: Table 4 and Results: 'Having had a myocardial infarction at Wave 1 did not predict every‐day e‐cigarette use at Wave 2 among overall follow‐up sample (P=0.687).'
Having had a myocardial infarction at Wave 1 did not predict every‐day e‐cigarette use at Wave 2 among overall follow‐up sample (P=0.687), every‐day cigarette smokers at Wave 1 (P=0.675), or current cigarette smokers at Wave 1 (P=0.634), adjusting for demographic and clinical variables.
Resultsreviewer’s wording
supportedReviewers 1, 2, 3
Dual use of e-cigarettes and combustible cigarettes is riskier than using either product alone.
The paper calculates that the odds for dual users (every-day e-cigarette and every-day cigarette) is 6.64 compared to never users of both, and provides a direct regression estimate (AOR 5.06, 95% CI 1.99-12.83).
Evidence: Discussion: 'the total odds of having had a myocardial infarction among every‐day cigarette smokers who also use e‐cigarettes every day … is 2.95×2.25=6.64' and Table S5.
the total odds of having had a myocardial infarction among every‐day cigarette smokers who also use e‐cigarettes every day … is 2.95×2.25=6.64 compared with a never cigarette smoker who has never used e‐cigarettes
Discussion ¶2reviewer’s wording
supportedReviewer 1
Switching from combustible cigarettes to e-cigarettes is not associated with lower risk of MI compared to continuing smoking.
The paper calculates that the odds for a switcher would be 1.13 times that of continuing smoking, indicating virtually no benefit, and compares to quitting (odds 2.25).
Evidence: Discussion: 'Odds of having had a myocardial infarction for individuals who switched from every‐day combustible cigarette smoking to every‐day e‐cigarette use would change by a factor of … 1.13, which is virtually no benefit.'
“Odds of having had a myocardial infarction for individuals who switched from every‐day combustible cigarette smoking to every‐day e‐cigarette use would change by a factor of ([odds of myocardial infarction among former combustible cigarette smokers]×[odds of myocardial infarction among every‐day e‐cigarette user])/(odds of myocardial infarction among every‐day combustible cigarette smoker)=3.33/2.95=1.13, which is virtually no benefit in terms of myocardial infarction risk.”
Discussion ¶2
supportedReviewer 2
E-cigarette use is independently associated with increased odds of having had a myocardial infarction.
The cross-sectional analysis shows significant adjusted odds ratios for some-day and every-day e-cigarette use, with a dose-response trend.
Evidence: Table 3: AOR for some-day = 1.99 (95% CI 1.11-3.58, p=0.024); every-day = 2.25 (95% CI 1.23-4.11, p=0.010).
Every‐day (adjusted odds ratio, 2.25, 95% CI: 1.23–4.11) and some‐day (1.99, 95% CI: 1.11–3.58) e‐cigarette use were independently associated with increased odds of having had an MI with a significant dose‐response (P <0.0005).
Table 3reviewer’s wording
supportedReviewer 2
Reverse causality does not explain the observed cross-sectional association.
The longitudinal analysis shows that having had an MI at Wave 1 does not predict e-cigarette use at Wave 2 (p>0.62), consistent with the conclusion.
Evidence: Table 4: AOR for MI predicting every-day e-cigarette use = 0.85 (95% CI 0.38-1.90, p=0.687) in overall sample; similar results in subgroups.
Having had a myocardial infarction at Wave 1 did not predict every‐day e‐cigarette use at Wave 2 among overall follow‐up sample (P =0.687)
Table 4reviewer’s wording
supportedReviewer 3
Every-day and some-day e-cigarette use are independently associated with increased odds of having had a myocardial infarction.
The adjusted odds ratios are statistically significant (AOR 2.25, p=0.010; AOR 1.99, p=0.024) and the evidence is presented in Table 3.
Evidence: Table 3 shows AOR 2.25 (95% CI 1.23-4.11) for everyday e-cigarette use and AOR 1.99 (95% CI 1.11-3.58) for someday use, with p-values.
Every day e-cigarette use (adjusted odds ratio, 2.25, 95% CI: 1.23–4.11) and some‐day e‐cigarette users (adjusted odds ratio, 1.99, 95% CI: 1.11–3.58)
Table 3reviewer’s wording
supportedReviewer 3
Reverse causality cannot explain the cross-sectional association between e-cigarette use and MI.
The longitudinal analysis shows that having had an MI at Wave 1 did not predict e-cigarette use at Wave 2 (p>0.62 for all outcomes), as presented in Table 4.
Evidence: Table 4 shows AORs for MI predicting everyday e-cigarette use: 0.85 (0.38-1.90), p=0.687 in overall sample, and similar non-significant results in subgroups.
“Having had a myocardial infarction at Wave 1 did not predict every‐day e‐cigarette use at Wave 2 among overall follow‐up sample ( P =0.687), every‐day cigarette smokers at Wave 1 ( P =0.675), or current cigarette smokers at Wave 1 ( P =0.634)”
Table 4
supportedReviewer 3
Switching from combustible cigarettes to e-cigarettes is not associated with lower risk of myocardial infarction.
The paper calculates that switching would change the odds by a factor of 1.13, indicating virtually no benefit, and the odds relative to quitting are 2.25.
Evidence: Results section: 'Odds of having had a myocardial infarction for individuals who switched from every‐day combustible cigarette smoking to every‐day e‐cigarette use would change by a factor of … 1.13, which is virtually no benefit' and 'the total odds of having had a myocardial infarction for an individual who switched … compared with quitting smoking would be … 2.25.'
“Odds of having had a myocardial infarction for individuals who switched from every‐day combustible cigarette smoking to every‐day e‐cigarette use would change by a factor of ([odds of myocardial infarction among former combustible cigarette smokers]×[odds of myocardial infarction among every‐day e‐cigarette user])/(odds of myocardial infarction among every‐day combustible cigarette smoker)=3.33/2.95=1.13”
Discussion ¶2

Data authenticity concerns

None found

An adversarial read for patterns associated with data that may not be genuine: results that look too clean, implausibly large effects, duplicated data or images, and methods that do not match the results reported.

Checked — nothing surfaced.

Reporting gaps

3 findings · worst high

Required detail the manuscript never states — study design, biological variables, ethics approval and consent, key resources, statistical reporting, data and code availability, and overall transparency.

Statistical reporting gaps (tests, assumptions, effect sizes)Assessed
Study design lacks key rigor safeguardsAssessed
Ethics/consent reporting incompleteAssessed

Eight Dimensions4 pass · 2 warn · 1 fail

Prior work is cited (e.g., Alzahrani & Glantz, Vindhyal et al., Stokes et al.) with strengths and weaknesses acknowledged. The rationale linking e-cigarette use to MI through biological mechanisms (endothelial dysfunction, oxidative stress) is logically presented. Limitations of prior cross-sectional studies (reverse causality) are explicitly addressed and tested using longitudinal data.

Sub-criteria

prior work citedADEQUATE

premise rationaleADEQUATE

limitations addressedADEQUATE

Per reviewer (3) — the votes behind the verdict

PASSReviewer 1· 95% conf

The paper clearly establishes the scientific premise by citing prior research on e-cigarettes and cardiovascular effects, including the National Academies report, and discusses the controversy around reverse causality.

Evidence

paraphrase[Introduction, paragraph 2]

“Nevertheless, the 2018 National Academies of Science, Engineering, and Medicine report Public Health Consequences of E‐Cigarettes observed that 'there are no epidemiological studies evaluating clinical outcomes such as coronary heart disease ….' Since then, 2 studies … found cross‐sectional associations between e‐cigarette use and having had a myocardial infarction.”

“We use the Population Assessment of Tobacco and Health (PATH) data set to test for the relationship between e‐cigarette use and myocardial infarction, controlling for cigarette use, demographic and clinical variables and use the longitudinal data from PATH to test the reverse causality hypothesis.”

Introduction ¶4

paraphrase[Introduction, paragraph 2]

“E‐cigarettes and combustible cigarettes have similar effects on endothelial function which increases the risk of cardiovascular disease. … E‐cigarettes increase oxidative stress and the release of inflammatory mediators.”

PASSReviewer 2· 95% conf

The paper establishes a strong scientific foundation by citing prior research, providing a logical rationale, and addressing limitations of previous work.

Evidence

paraphrase[Introduction, paragraph 2]

“the 2018 National Academies of Science, Engineering, and Medicine report Public Health Consequences of E‐Cigarettes observed that “there are no epidemiological studies evaluating clinical outcomes such as coronary heart disease ….” Since then, 2 studies … found cross‐sectional associations between e‐cigarette use and having had a myocardial infarction”

Introduction ¶3

“Both the present and earlier, results are based on cross‐sectional analysis, which raises the possibility of reverse causality”

Discussion ¶2

PASSReviewer 3· 95% conf

The paper establishes a clear scientific premise by citing prior research on e-cigarette biological effects and epidemiological gaps, and provides a logical rationale for the study.

Evidence

“Nevertheless, the 2018 National Academies of Science, Engineering, and Medicine report Public Health Consequences of E‐Cigarettes observed that “there are no epidemiological studies evaluating clinical outcomes such as coronary heart disease ….”

Introduction ¶1

paraphrase[Introduction, paragraph 1]

“E‐cigarettes increase oxidative stress and the release of inflammatory mediators, induce platelet activation, aggregation, and adhesion and alters cardiovascular function in mice.”

Introduction ¶2

For an observational study, the applicable sub-criteria are power_analysis, inclusion_exclusion, and outlier_handling. The paper does not mention an a priori power or sample size calculation for the main analysis. Inclusion/exclusion criteria are described post-hoc (e.g., excluding experimental users) but not pre-specified. Outlier handling is not addressed. None of these three applicable criteria are adequately reported, resulting in a fail.

Sub-criteria

controlsN/A

power analysisNOT REPORTED

blinding levelsN/A

outlier handlingNOT REPORTED

randomization unitN/A

inclusion exclusionINADEQUATE

randomization methodN/A

replicate distinctionN/A

independent replicationN/A

Per reviewer (3) — the votes behind the verdict

WARNReviewer 1· 70% conf

The study design is appropriate for an observational analysis, but power analysis for the primary cross-sectional analysis is not reported, and outlier handling is not addressed.

Evidence

“To achieve 0.80 power with α=0.005 (2‐tail) with observed sample size calculated using GPower 3.1.92.”

Table 4

paraphrase[Methods, Independent Variables]

“Respondents who reported that they have ever used e‐cigarettes, have used fairly regularly, and currently use every day were classified as 'Every‐day users.' … Respondents who were current smokers but who had not smoked 100 cigarettes (experimental smokers) were excluded from the main analysis, but included in a sensitivity analysis as some‐day smokers.”

absence[Methods, Analysis]

Outlier handling is not mentioned.

FAILReviewer 2· 90% conf

The study design element is inadequately reported; no a priori power analysis, no pre-specified inclusion/exclusion criteria, and no outlier handling are described.

Evidence

absence[Methods, Analysis section and Table 4 footnote]

No a priori power analysis is reported.

“Current experimental e‐cigarette users (current e‐cigarette users but never used e‐cigarettes fairly regularly) were not included in the main analysis but were considered some‐day users in a sensitivity analysis.”

Methods

absence[Methods]

Outlier handling is not mentioned.

FAILReviewer 3· 85% conf

The study design lacks an a priori power analysis, formal inclusion/exclusion criteria, and outlier handling, all of which are applicable for an observational study.

Evidence

absence[Methods, Analysis section, and entire paper]

No a priori power analysis is reported.

Methods

absence[Methods, entire paper]

Outlier handling is not mentioned.

The paper reports sex (men/women), age (mean±SD), BMI, race/ethnicity, poverty level, and education. Clinical variables (high blood pressure, high cholesterol, diabetes) are also reported. Sex is reported with both men and women included, so justification is not applicable. Species/strain and housing conditions are not applicable for a human study.

Sub-criteria

demographicsADEQUATE

sex reportedADEQUATE

sex justifiedN/A

age weight healthADEQUATE

housing conditionsN/A

species strain sourceN/A

Per reviewer (3) — the votes behind the verdict

PASSReviewer 1· 95% conf

Relevant biological variables (sex, age, BMI, health status) are reported for the human study population.

Evidence

paraphrase[Table 1]

“Age in y, mean (±SD) 46.7 (17.9±SD); Body mass index (±SD) kg/m2 28.0 (7.5±SD); Sex: Men 48.1, Women 51.9”

paraphrase[Table 1]

“White alone 77.8; Black alone 12.4; Asian alone 5.5; Other, including multiracial 4.3; Education: Less than high school 4.5; High school or equivalent 36.6; Some college and associate 31.0; Bachelor and advanced degree 27.9”

PASSReviewer 2· 95% conf

Biological and demographic variables are well-reported, including sex, age, BMI, health conditions, and demographics.

Evidence

paraphrase[Results, Table 1]

“Age in y, mean (±SD) 46.7 (17.9±SD) | Body mass index (±SD) kg/m2 28.0 (7.5±SD) | Sex Men 48.1 Women 51.9”

paraphrase[Results, Table 1]

“Race/ethnicity | White alone 77.8 | Black alone 12.4 | Asian alone 5.5 | Other, including multiracial 4.3”

PASSReviewer 3· 95% conf

Sex, age, BMI, and demographics are fully reported in Table 1, meeting the applicable criteria for a human observational study.

Evidence

paraphrase[Table 1]

“Sex: Men 48.1, Women 51.9”

paraphrase[Table 1]

“Age in y, mean (±SD): 46.7 (17.9±SD); Body mass index (±SD) kg/m²: 28.0 (7.5±SD)”

paraphrase[Table 1]

“White alone 77.8, Black alone 12.4, Asian alone 5.5, Other, including multiracial 4.3; Below poverty (<100% of poverty guideline) 25.2; Less than high school 4.5, High school or equivalent 36.6, Some college and associate 31.0, Bachelor and advanced degree 27.9”

The paper states that the UCSF Committee on Human Research approved the study and that informed consent was obtained by PATH. However, it does not mention adherence to a specific regulatory framework such as the Declaration of Helsinki. According to the scoring guide, this makes regulatory_compliance not_reported, and since not all applicable criteria are adequate, the dimension receives a warning.

Sub-criteria

iacuc statementN/A

informed consentADEQUATE

irb ethics statementADEQUATE

regulatory complianceNOT REPORTED

Per reviewer (3) — the votes behind the verdict

WARNReviewer 1· 85% conf

Ethics approval and informed consent are reported, but compliance with a recognized regulatory framework is not explicitly stated.

Evidence

“The University of California San Francisco (UCSF) Committee on Human Research approved this study.”

Methods

“Informed consent was obtained by PATH.”

Methods

absence[Methods, Ethical Approvals]

Regulatory compliance with a named framework is not mentioned.

WARNReviewer 2· 90% conf

Ethical approval and informed consent are reported, but regulatory compliance with a named framework is not stated.

Evidence

“Informed consent was obtained by PATH. The University of California San Francisco (UCSF) Committee on Human Research approved this study.”

Methods

absence[Methods]

No statement of adherence to a regulatory framework (e.g., Declaration of Helsinki) is provided.

WARNReviewer 3· 90% conf

The IRB approval and informed consent are named and adequate, but regulatory compliance with a recognized framework (e.g., Declaration of Helsinki) is not explicitly stated.

Evidence

“The University of California San Francisco (UCSF) Committee on Human Research approved this study.”

Methods

“Informed consent was obtained by PATH.”

Methods

absence[Methods, entire paper]

No statement of compliance with the Declaration of Helsinki or other regulatory framework is provided.

No antibodies, cell lines, organisms, or reagents are used. The software used (R with survey package) is mentioned but not a key resource requiring version details for reproducibility of the statistical analysis, and the study is not computational in nature. The PATH data is the primary resource and is covered under data availability.

Sub-criteria

mycoplasma testingN/A

reagents identifiedN/A

organisms identifiedN/A

antibodies identifiedN/A

cell line authenticationN/A

software tools identifiedN/A

Per reviewer (3) — the votes behind the verdict

N/AReviewer 1· 90% conf

The study is a secondary analysis of survey data and does not use biological or chemical resources, investigational products, or bespoke software requiring detailed identification.

Evidence

absence[Methods]

No biological or chemical resources are used.

N/AReviewer 2· 80% conf

The study is an observational survey analysis that does not use any biological/chemical resources, investigational products, or custom software, making this dimension not applicable.

Evidence

absence[Methods]

No biological or chemical resources are used.

FAILReviewer 3· 85% conf

The only applicable resource (statistical software) is incompletely identified (name only, no version), and no other resources are used, leading to a fail due to inadequate reporting.

Evidence

“We used “survey package” in R software for statistical analyses.”

Methods

The paper names the statistical model (logistic regression) and reports odds ratios with 95% CIs and exact p-values for most comparisons. However, assumptions such as linearity of logit or goodness-of-fit are not discussed. Some p-values are reported as '<0.001' or '<0.0005' rather than exact values. The software (R survey package) is named but version is omitted. Data presentation is adequate with tables and CIs. No demonstrable arithmetic errors are present. With 4 of 7 applicable sub-criteria adequate (tests_named, effect_sizes_ci, data_presentation, mathematical_plausibility), the dimension falls in the warning range.

Sub-criteria

tests namedADEQUATE

exact p valuesINADEQUATE

effect sizes ciADEQUATE

data presentationADEQUATE

software identifiedINADEQUATE

assumptions verifiedNOT REPORTED

mathematical plausibilityPASS

Per reviewer (3) — the votes behind the verdict

PASSReviewer 1· 95% conf

The statistical analysis is well-reported with exact p-values, confidence intervals, effect sizes, and appropriate tests; arithmetic plausibility checks confirm consistency.

Evidence

paraphrase[Table 3]

“Every day e-cigarette: AOR 2.25 (1.23–4.11) P=0.010; Some day: 1.99 (1.11–3.58) P=0.024”

“All variance inflation factors were <1.1, indicating that the effects of e‐cigarette and conventional cigarette use were independent risk factors for myocardial infarction.”

Results ¶3

paraphrase[Table 1]

“E‐cigarette user: Never 85.0, Former 12.6, Some day 1.4, Every day 1.0”

WARNReviewer 2· 85% conf

Statistical analysis is generally adequate, but assumption verification is missing, some p-values are reported as thresholds, and software version is not given.

Evidence

paraphrase[Methods, Analysis section]

“Multivariable logistic regressions were performed to examine the associations between e‐cigarette use … and myocardial infarction”

absence[Methods, Analysis section]

Assumptions are not verified; no mention of model diagnostics.

paraphrase[Results, Table 3 and text]

“P <0.0005”

WARNReviewer 3· 80% conf

Statistical tests are named, effect sizes with CIs are reported, and no arithmetic errors are detected, but model assumptions are not verified, some p-values are reported as thresholds, and software version is missing.

Evidence

paraphrase[Methods, Analysis]

“The paper states 'Multivariable logistic regressions were performed' but does not mention testing for goodness-of-fit, linearity, or multicollinearity beyond VIF <1.1.”

“There was a significant dose‐response for both e‐cigarette use ( P <0.0005) and smoking ( P =0.019) and myocardial infarction controlling for demographic and clinical variables (detailed results not shown).”

Results ¶2

“We used “survey package” in R software for statistical analyses.”

Methods

The paper states that the restricted-use PATH data is available at the University of Michigan National Addiction & HIV Data Archive Program, which is a concrete access route. No custom code is shared, but the analysis uses standard logistic regression in R, which is reproducible from the methods description. The data access procedure is adequate for controlled-access data.

Sub-criteria

code sharingNOT REPORTED

accession numbersADEQUATE

repository depositADEQUATE

data availability statementADEQUATE

Per reviewer (3) — the votes behind the verdict

PASSReviewer 1· 85% conf

The data availability statement is concrete, naming a repository, and code sharing is not required as the analysis is standard; however, code is not provided.

Evidence

“The restricted use PATH data set is available at the University of Michigan National Addiction & HIV Data Archive Program.”

Methods

absence[Methods, Analysis]

Code sharing is not reported.

PASSReviewer 2· 80% conf

The data availability statement is adequate, naming a specific repository (NAHDAP), and no custom code was developed, making code sharing not applicable.

Evidence

“The restricted use PATH data set is available at the University of Michigan National Addiction & HIV Data Archive Program.”

Methods

“We used “survey package” in R software for statistical analyses.”

Methods

WARNReviewer 3· 85% conf

The data availability statement names a concrete repository (NAHDAP), and the PATH dataset is deposited there, but no custom analysis code is shared, which is a reporting gap.

Evidence

“The restricted use PATH data set is available at the University of Michigan National Addiction & HIV Data Archive Program.”

Methods

absence[Methods, entire paper and supplements]

No custom code is shared.

Methods are detailed enough for replication. All outcomes are reported, including null results (e.g., longitudinal analysis). Limitations such as reverse causality, small numbers, and self-report bias are discussed. Conclusions are proportional to the evidence. Funding sources and a conflict of interest statement are provided. The only missing element is a reference to a reporting guideline (e.g., STROBE), which is not mentioned.

Sub-criteria

funding coiADEQUATE

trial registrationN/A

reporting guidelineNOT REPORTED

methods completenessADEQUATE

all outcomes reportedADEQUATE

limitations discussedADEQUATE

conclusions proportionalADEQUATE

Per reviewer (3) — the votes behind the verdict

PASSReviewer 1· 90% conf

The manuscript is well-structured with detailed methods, transparent reporting of outcomes, limitations discussion, and funding/COI disclosure.

Evidence

paraphrase[Sources of Funding and Disclosures]

“This work was supported by grants R01DA043950 from the National Institute on Drug Abuse … Disclosures: None.”

“While PATH is a longitudinal study, there were only 8 people who used e‐cigarettes and had first myocardial infarctions during this follow‐up, so there was not enough power to detect an effect.”

Limitations

absence[Methods]

Reporting guideline is not mentioned.

PASSReviewer 2· 90% conf

Reporting is transparent with detailed methods, all outcomes reported, limitations discussed, proportional conclusions, and funding/COI stated. Only the reporting guideline is not referenced.

Evidence

paraphrase[Methods, entire section]

“The Methods section describes study design, outcome variables, independent variables, demographic and clinical variables, and analysis plan.”

Limitations

paraphrase[End of paper, Sources of Funding and Disclosures]

“This work was supported by grants R01DA043950 … Disclosures None.”

PASSReviewer 3· 90% conf

Methods are detailed, limitations are discussed, conclusions are proportional, and funding/COI are disclosed, meeting the 60% threshold even though no reporting guideline is referenced and not all outcomes are pre-specified.

Evidence

paraphrase[Methods, Study Population and Design, Variables, Analysis]

“The paper provides detailed definitions of e-cigarette and cigarette use categories, demographic and clinical variables, and the logistic regression models.”

Limitations

paraphrase[Sources of Funding and Disclosures]

“This work was supported by grants R01DA043950 from the National Institute on Drug Abuse… Disclosures: None.”

Broken references and links

1 finding · worst low

References checked against Crossref, OpenAlex and Retraction Watch for retractions and resolvability, plus declared data and code links probed for whether they resolve to content matching the paper.

References not resolvable to a published paperRecomputed

Checked 37 references by DOI: 26 verified — 2 DOI unresolved, 9 no DOI (shown, not verified).

UNRESOLVED10.1161/str.50.suppl
Electronic cigarette use is associated with a higher risk of stroke
Cited DOI does not resolve to any Crossref record.
UNRESOLVED10.3886/icpsr36231.v13
Population assessment of tobacco and health (PATH) study [United States] restricted-use files
Cited DOI does not resolve to any Crossref record.
NO DOI
Deaths: final data for 2015
No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
NO DOI
The health consequences of smoking: 50 years of progress: a report of the surgeon general
No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
NO DOI
Relative endothelial toxicity of tobacco smoke and e-cigarette aerosol: a functional and mechanistic assessment
No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
NO DOI
Assessing cardiovascular risks associated with e-cigarettes with human induced pluripotent stem cell-derived endothelial cells
No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
NO DOI
In utero exposure to e-cigarettes modulates platelet function and increases the risk of thrombogenesis, in mice
No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
NO DOI
Public Health Consequences of e-Cigarettes
No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
NO DOI
Population assessment of tobacco and health (PATH) study [United States] restricted-use files: user guide
No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
NO DOI
Fay's method for variance estimation
No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
NO DOI
Impact on cardiovascular outcomes among e-cigarette users: a review from National Health Interview Surveys
No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).

Copyediting

14 minor

Wording, consistency and formatting errors that need correcting before submission.

No major wording or formatting errors. 14 minor suggestions below.

14 copyedit issues flagged: mostly typo, consistency, punctuation.

MINORconsistencyTable 2, 'High school or equivalent' row for MI group
“461”
→ 46.1
The value '461' appears to be a typo; should be 46.1% to match the format.
MINORclarityTable 4 footnote 'BMI indicates bone mass index'
“BMI indicates bone mass index”
→ BMI indicates body mass index
Standard term is body mass index.
MINORpunctuationDiscussion, paragraph 2
“Thus, any differential misclassification is in the direction opposite to what would be required for reverse causality to explain our results, which strengthens our conclusion that e‐cigarette use is associated with the risk of having had an MI.”
→ Consider adding a comma after 'Thus' or rephrasing for clarity.
Minor punctuation consistency.
MINORtypoAbstract, Methods and Results
“and having had and MI”
→ and having had an MI
Typo: 'and' should be 'an'.
MINORtypoDiscussion, paragraph 1
“risker”
→ riskier
Typo: 'risker' should be 'riskier'.
MINORtypoDiscussion, paragraph 5
“becauseof”
→ because of
Missing space between 'because' and 'of'.
MINORtypoTable 4 footnote
“bone mass index”
→ body mass index
Typo: 'bone mass index' should be 'body mass index'.
MINORpunctuationThroughout
“Every‐day”
→ Every-day or 'every day' (consistent with usage in text)
Non-standard hyphenation; should be consistent with 'some-day' and 'every day'.
MINORconsistencyResults, Table 2
“461”
→ 46.1
In Table 2, under Education for MI Yes, 'High school or equivalent' shows 461, which appears to be a typo (should be 46.1% as in other cells).
MINORotherAuthor affiliations
“San Francisco CA”
→ San Francisco, CA
Missing comma between city and state.
MINORtypoTable 2, Education row for MI Yes
“461”
→ 46.1
Likely a missing decimal point; the weighted percentage should be 46.1%.
MINORclarityTable 4 footnote
“BMI indicates bone mass index;”
→ BMI indicates body mass index;
Typo: 'bone' should be 'body'.
MINORpunctuationTable 2, column header
“P Value”
→ P value
Standardize capitalization of 'P value' throughout.
MINORconsistencyTable 3, footnote
“VIF indicates variance inflation factor.”
→ Already defined but note that VIF is also mentioned in Table 4 footnote; ensure consistent definition.
Minor, but should be consistent.

Kaimen Rigor Action ItemsFinal pass before journal submission

In this post-publication audit, the published work is moderately robust: the core association estimates are arithmetically consistent, and limitations are candid, but an informed reader should weigh the missing primary power analysis, assumption checks, exact dose-response p-value, and code availability, and the journal should consider a correction for the Table 2 typo and the overstated prescription/promotion conclusion.

1.
HIGHcopyedit
Correct the impossible percentage '461' to '46.1' in Table 2, Education row for the MI Yes group.
A percentage above 100 in a key baseline table is an obvious data-entry error that readers and editors will immediately catch.
2.
HIGHreporting
Temper the conclusion that e-cigarettes 'should not be promoted or prescribed as a less risky alternative' so it reflects only the MI-association evidence and does not imply conclusions about cessation efficacy, which this study did not test.
The claim audit rated this statement as overstated, and over-extension beyond the data is the most common and damaging reviewer objection.
3.
HIGHstatistics
Add an a priori power or sample-size justification for the primary cross-sectional analysis in Methods; the Table 4 footnote currently reports only a post-hoc power calculation for the reverse-causality analysis.
The primary analysis has no reported power/sample-size rationale, which is the main study-design gap flagged by two of three reviewers.
4.
HIGHstatistics
Report exact p-values instead of thresholds for the dose-response trend (currently 'P <0.0005') and either show the detailed dose-response results or state where they can be obtained.
Threshold-only p-values are imprecise reporting and 'detailed results not shown' leaves a reported analysis unverifiable.
5.
HIGHstatistics
Report logistic-regression assumption checks beyond VIF (e.g., goodness-of-fit, linearity of continuous predictors) and provide R and 'survey' package version numbers in the Methods.
Assumption verification and software versions are needed for reproducibility and were flagged as inadequate by two reviewers.
6.
HIGHethics
Add an explicit statement of regulatory compliance with a recognized framework, such as 'conducted in accordance with the Declaration of Helsinki', to the Ethics section.
IRB approval and consent are present, but the missing regulatory-compliance statement is a fixable reporting gap for medical journals.
7.
HIGHreporting
Reference the STROBE guideline for observational studies and either complete a checklist or explain why it was not used.
No reporting guideline is cited, and its absence is a transparency gap for an observational study.
8.
HIGHother
Verify or correct the reference 'Electronic cigarette use is associated with a higher risk of stroke' (DOI 10.1161/str.50.suppl), which has an incomplete DOI and was not found in any registry.
An unresolved citation may be fabricated or malformed and must be checked before the paper is relied upon.
9.
HIGHother
Verify the PATH restricted-use files citation (DOI 10.3886/icpsr36231.v13) and confirm it matches the exact dataset version analyzed.
The citation was not resolved by the registry check; datasets with incorrect version identifiers undermine reproducibility of the analysis.
10.
MEDIUMdata code
Deposit the analysis R scripts and data-processing workflow in a public repository and link them from the Data Availability statement.
The data statement is concrete, but without the code the exact variable recodes and model specifications cannot be independently reproduced.
11.
MEDIUMrigor
Describe in Methods how outliers/influential observations and missing data were handled, or state explicitly that none were excluded.
Outlier handling is completely absent and missing-data handling is not described; both are applicable reporting elements for an observational analysis.
12.
MEDIUMcopyedit
Fix the typos in the Abstract ('and MI' to 'an MI') and Discussion ('risker' to 'riskier'; 'becauseof' to 'because of').
These are simple typographical errors that undermine the manuscript's polish.
13.
MEDIUMcopyedit
Correct 'bone mass index' to 'body mass index' in the Table 4 footnote and harmonize 'Every-day' hyphenation, 'P value' capitalization, and 'San Francisco, CA' punctuation.
Inconsistent terminology and punctuation across tables/text are easily fixed and improve professionalism.
14.
MEDIUMreporting
Add a sentence to the Limitations stating that the analysis was not pre-registered and that some analytic decisions (e.g., exclusion of experimental users) were made post hoc.
Acknowledging the absence of preregistration contextualizes the post-hoc analytic decisions flagged by two reviewers.
15.
LOWrigor
Clarify the temporal relationship between e-cigarette initiation and MI by reporting age at first MI relative to age at first e-cigarette use, or explicitly note this unresolved temporal ordering as a limitation.
This would strengthen the reverse-causality discussion, which is central to the study's contribution.

Full text (37,957 chars)Analyzed: Aug 5, 2026

RigorReviewer 1

RigorReviewer 2

RigorReviewer 3

RigorPre-Submission Reviewer

CopyeditAgent Scribe

CitationsCitation Integrity

StatisticsStatistics Consistency

PreregistrationDeterministic check· no model (rule-based)

The star rating is the report’s one-glance summary. Every paper starts at 5★ and loses stars for the concrete problems the review finds — so a rating is never a vague average, it’s a running total you can read line by line under “How this rating was calculated.”

How stars are deducted

Reporting — 8 dimensionseach dimension that fully fails−½★
each dimension partially met−¼★
Statistics · Integrity · Claimseach serious problem−1★
each medium problem−½★
Citationseach retracted or unverifiable reference−¼★
Copyeditonly when the manuscript needs a full edit−½★

The rating never drops below 1★, and a demonstrable critical failure (an impossible statistic, a proven ethics violation) caps it at 1★ on its own — so the stars can never look healthy when the verdict is CRITICAL.

The rating draws on a panel of agents. Three independent Kaimen Rigor reviewers grade the eight dimensions below across several independent passes (the shown verdict is their majority vote — steadier than any single run), isolate the paper’s major claims and check its own evidence backs them, and flag integrity concerns. Alongside them, a citation agent resolves every reference against Crossref, OpenAlex, and Retraction Watch; a statistics agent recomputes reported tests; and rule-based checks verify that declared data/code links actually resolve. Full text is required — an abstract-only submission is not analyzed.

The eight reporting dimensions

Scientific PremisePrior work, rationale, and how it addresses gaps.

Study Design & RigorRandomization, blinding, power, controls, replication.

Biological VariablesSex, age, species/strain, housing, demographics.

Ethical ApprovalsIRB/IACUC approval, informed consent, regulatory compliance.

Key ResourcesAntibodies, cell lines, organisms, software — identified with persistent IDs.

Statistical ReportingNamed tests, exact p-values, effect sizes, plausible summary stats.

Data & Code AvailabilityAvailability statements, repositories, accession numbers, shared code.

Reporting TransparencyMethods, registration, guidelines, outcomes, limitations, funding/COI.

Graded against NIH, MDAR, ARRIVE 2.0, CONSORT, EQUATOR, and RRID guidelines. A dimension that doesn’t apply to the study type is skipped, never penalized.

This Kaimen Rigor review is model-assisted and is not a substitute for formal expert review. It complements human evaluation by surfacing potential methodological concerns — verify each finding against the source.

Electronic Cigarette Use and Myocardial Infarction Among Adults in the US Population Assessment of Tobacco and Health

Bhatta DN, Glantz SA.

DOI

10.1161/jaha.119.012317

Record issued

2026-08-05

Engine

7.15.0

Exported

2026-09-19