Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 264

The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.

Cholesterol variability and the risk of mortality, myocardial infarction, and stroke: a nationwide population-based study

Open access
Kim, Mee Kyoung, Han, Kyungdo, Kim, Hun-Sung, Park, Yong-Moon, Kwon, Hyuk-Sang, Yoon, Kun-Ho, Lee, Seung-Hwan·2017·European Heart Journal
DOI 10.1093/eurheartj/ehx585
Open this paper in CoChat — free account

Abstract

Aims: A high visit-to-visit variability in cholesterol levels has been suggested to be an independent predictor of major adverse cardiovascular events in patients with coronary artery disease (CAD). Because whether this notion applies to general population is not known, we aimed to investigate the associations between total cholesterol (TC) variability and the risk of all-cause mortality, myocardial infarction (MI), and stroke. Methods and results: We identified 3 656 648 subjects without a history of MI and stroke who underwent ≥3 health examinations from 2002 to 2007 in the Korean National Health Insurance System cohort. Total cholesterol variability was measured using the coefficient of variation (CV), standard deviation (SD), and variability independent of the mean (VIM). There were 84 625 deaths (2.3%), 40 991 cases of MI (1.1%), and 42 861 cases of stroke (1.2%) during the median follow-up of 8.3 years. There was a linear association between higher TC variability and outcome measures. In the multivariable adjusted model, the hazard ratios and 95% confidence intervals comparing the highest vs. lowest quartiles of CV of TC were 1.26 (1.24-1.28) for all-cause mortality, 1.08 (1.05-1.11) for MI, and 1.11 (1.08-1.14) for stroke, which was independent of mean TC levels and the use of lipid-lowering agents. The results were consistent when modelling variability of TC using SD and VIM, and in various sensitivity analyses. Conclusion: High variability in lipid levels is associated with adverse health-related outcomes. These findings suggest that lipid variability is an important risk factor in the general population.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/eurheartj/ehx585

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 29 references

Cited by

See all 264

Metadata

Authors
Kim, M. K., Han, K., Kim, H.-S., Park, Y.-M., Kwon, H.-S., Yoon, K.-H., & Lee, S.-H.
Venue
European Heart Journal
Publisher
Oxford University Press (OUP)
Published
2017-10-21
Volume
38
Issue
48
Pages
3560-3566
ISSN
  • 0195-668X (ISSN-L)
  • 1522-9645
DOI
10.1093/eurheartj/ehx585
OpenAlex
W2765887994
Cited by
264
References
29
FWCI
20.47
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Cholesterol variability and the risk of mortality, myocardial infarction, and stroke: a nationwide population-based study. https://app.cochat.ai/papers/10.1093/eurheartj/ehx585
The paper
Kim, M. K., Han, K., Kim, H.-S., Park, Y.-M., Kwon, H.-S., Yoon, K.-H., & Lee, S.-H. (2017). Cholesterol variability and the risk of mortality, myocardial infarction, and stroke: a nationwide population-based study. European Heart Journal. https://doi.org/10.1093/eurheartj/ehx585

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.