ArticleReviews in cardiovascular medicine2026
Development of Mathematical Models Evaluating Presence of Coronary Calcification Independent of Computed Tomography (DEPICT): Radiation-Free Evaluation of Coronary Atherosclerosis.
Article in Reviews in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
Background: The dependence of the acquisition of the coronary artery calcification score (CACS) on computed tomography (CT) has drawbacks, including the ethical concerns of radiation exposure in the care of patients with non-cardiovascular diseases, where CACS has been shown to correlate with its prognosis. Significant heterogeneities exist between patients with and without coronary artery calcification (CAC). Mathematical formulae using medical history and common, non-invasive test results enable cheap, ready assessment of CAC and subsequent research into how it can be used for clinical decision making. Methods: 694 patient records of visits to Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College from 2009 to 2023 were partitioned into a training (visited before 2023) and an independent validation set (visited in 2023). With age, gender, current smoking, diabetes, low-density lipoprotein cholesterol (LDL-C), reduced renal function, usage of statins and aspirin as candidate predictors, five logistic regression models were built under two paradigms. Bootstrap resampling was employed for internal validation, followed by external validation and calibration on the validation set. Models built under each paradigm were compared, followed by head-to-head comparison of the "best" models built under each paradigm with a comprehensive criteria involving both model performance and predictor parsimony. Results: 694 records were used for modeling, with 536 and 158 records in the training and validation set respectively. Model 1 ( Conclusion: With gender, current smoking, LDL-C, age, diabetes and reduced renal function as predictors, Model 5 outperformed other models and was hence recommended for further use. By assessing the presence of CAC with medical history and blood test results instead of CT, our model offers an approach to immediate, radiation-free assessment of CAC, which may further unleash the clinical utility of CAC in clinical practice that may have remained unraveled.
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.