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Updated: Jul 19, 2026

A Semi-Automated and Reproducible Biological-Based Method to Quantify Calcium Deposition In Vitro
Published on: June 2, 2022
Development of a cardiovascular calcification index using simple imaging tools in haemodialysis patients
Paul Muntner1, Emiliana Ferramosca, Antonio Bellasi
1Department of Epidemiology, Tulane University, 1140 Canal Street, New Orleans, LA 70112, USA. pmuntner@tulane.edu
Insights
A new Cardiovascular Calcification Index (CCI) predicts coronary artery calcification (CAC) in hemodialysis patients using simple tests. This index offers an accessible alternative when advanced imaging like cardiac computed tomography (CCT) is unavailable.
Area of Science:
- Nephrology
- Cardiology
- Medical Imaging
Background:
- Coronary artery calcification (CAC) is common in hemodialysis patients, increasing cardiovascular risk.
- Cardiac computed tomography (CCT) accurately detects CAC but lacks widespread availability.
Purpose of the Study:
- To develop a Cardiovascular Calcification Index (CCI) for predicting CAC in hemodialysis patients.
- To utilize simple, in-office techniques for CAC prediction.
Main Methods:
- A cohort of 140 hemodialysis patients underwent CCT, abdominal aorta X-ray, echocardiogram, and pulse pressure measurement.
- A CCI was derived using prevalence rate ratios and validated with receiver operator characteristic curves and likelihood ratios.
Main Results:
- The CCI incorporates age, dialysis vintage, and calcification from aortic and mitral valves and the abdominal aorta.
- Higher CCI scores correlated with increased likelihood ratios for significant CAC (CAC > or =1000).
- For CCI scores of 2-4, 5, 6-8, and >=9, the probability of CAC > or =1000 was 26%, 38%, 43%, and 50%, respectively.
Conclusions:
- The developed CCI serves as a practical alternative for CAC prediction in hemodialysis patients.
- Further refinement of the CCI may enhance its clinical utility.
Background:
Coronary artery calcification (CAC) is highly prevalent in haemodialysis patients and is associated with cardiovascular outcomes. Though cardiac computed tomography (CCT) is accurate, it is not widely available.
Methods:
We developed a cardiovascular calcification index (CCI) to predict the presence of CAC for haemodialysis patients using simple in-office techniques. Prevalent haemodialysis patients (n = 140) underwent CCT imaging for CAC, a lateral abdominal X-ray for calcification of the abdominal aorta, an echocardiogram for valvular calcification, and pulse pressure measurement. A CCI was derived by weighting the prevalence rate ratios of CAC > or =1000. Using bootstrap techniques, validation was performed using receiver operator characteristic curves and likelihood ratios.
Results:
Points were assigned for patients' age (60-69 and > or =70 years, 1 and 2 points, respectively), dialysis vintage > or =2 years (1 point), aortic and mitral valve calcification (3 and 1 points, respectively), and abdominal aorta X-ray scores of 1-6 and > or =7 (2 and 4 points, respectively). Race, sex and pulse pressure did not contribute to the CCI. The CCI ranged from 0 to 11 points. The likelihood ratio of CAC > or =1000 associated with CCI scores of 2-4, 5, 6-8 and 9-11 were 1.28, 2.03, 2.94 and 3.83, respectively. Given the prevalence of CAC > or =1000 of 21% in the current study, the probability of having CAC > or =1000 was 26%, 38%, 43% and 50% for participants with CCI scores of 2-4, 5, 6-8, and > or =9, respectively.
Conclusions:
Although refinement is needed, the CCI developed in the current study provides an alternative for predicting CAC when CCT is not available.
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