ArticleJournal of personalized medicine2024
Progression of Coronary Artery Calcification According to Changes in Risk Factors in Asymptomatic Individuals.
Article in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Serial Coronary Artery Calcium Progression and Risk of Major Adverse Cardiovascular Events in an Asian Cohort.Journal of clinical medicine · 2026Article
- Associations of Central Adiposity With Subclinical Coronary Calcification and Disease Progression: Meta-Analysis of 68,629 Participants.JACC. Advances · 2026Article
- New kidneys, old risks: cardiovascular challenges after transplantation.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2026Review
- Development and validation of a LASSO-selected machine learning prediction pipeline for predicting coronary artery calcification in a health check-up population.Frontiers in medicine · 2026Article
- Evaluation of the impact of cardiopulmonary rehabilitation exercise training on cardiopulmonary function in patients with chronic obstructive pulmonary disease complicated by unstable angina pectoris using a hierarchical deep learning CT image model.Frontiers in physiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This retrospective study aimed to assess coronary artery calcium (CAC) progression in serial computed tomography measurements according to risk factor changes. In 448 asymptomatic adults who underwent CAC measurements with more than one-year intervals, CAC progression was assessed according to age, sex, variable traditional risk factors (diabetes mellitus, hypertension, hyperlipidemia, and smoking), and initial CAC score (0, 0.1-100, and >100). Univariate and multivariate logistic regression analyses were assessed for independent predictors of rapid CAC progression (ΔCAC/year > 20). During the 3.5-year follow-up, coronary artery calcifications occurred in 43 (12.8%) of 336 individuals with an initial CAC score of zero. Of 112 individuals with initial CAC presence, 60 (53.6%) had ΔCAC/year > 20. Age, male sex, body mass index, and all risk factors were significantly associated with ΔCAC/year > 20, but recently diagnosed hypertension (odds ratio [OR], 11.3) and initial CAC score (OR, 1.05) were significant independent predictors in multivariate regression analyses. CAC progression was affected by demographic and traditional risk factors; but, adjusting for these factors, recently diagnosed hypertension and initial CAC score were the most influential factors for rapid CAC progression. These findings suggest that individuals with higher initial CAC scores may benefit from more frequent follow-up scans and checks regarding risk factor changes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.