Preprint
Article

Progression of Coronary Artery Calcification According to Changes in Risk Factors in Asymptomatic Individuals

Altmetrics

Downloads

113

Views

31

Comments

0

A peer-reviewed article of this preprint also exists.

This version is not peer-reviewed

Submitted:

27 June 2024

Posted:

27 June 2024

You are already at the latest version

Alerts
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 (△CAC/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 △CAC/year>20. Age, male sex, body mass index, and all risk factors were significantly associated with △CAC/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 patients with higher initial CAC scores may benefit from more frequent follow-up scans and checks regarding risk factor changes.
Keywords: 
Subject: Medicine and Pharmacology  -   Cardiac and Cardiovascular Systems

1. Introduction

Coronary artery calcium (CAC) scoring assessed by computed tomography (CT) is a widely used and reproducible tool to guide risk stratification, as well as a powerful surrogate marker for cardiovascular disease (CVD) [1,2]. The CAC score has been extensively validated as a strong predictor of coronary events, and its superiority to risk factor-based paradigms such as the Framingham Risk Score, and individual risk factors has been demonstrated [3,4,5]. Therefore, the CAC score is recommended for the assessment of asymptomatic middle-aged populations, particularly of intermediate-risk cohorts, by various cardiovascular society guidelines across the world [6,7].
In addition to using a single CAC score for assessments, several studies have suggested the clinical significance of CAC progression determined using serial CT scans, as CAC progression is significantly more associated with a worse prognosis than CAC non-progression [8,9]. Moreover, CAC progression has been associated with several traditional risk factors [10,11]. Some of these risk factors, such as smoking or hyperlipidemia, are modifiable, so changes in these risk factors may affect CAC changes. Currently, little evidence exists for CAC progression related to changes in risk factors; thus, current guidelines do not specify the optimal timing for follow-up CAC scanning. Therefore, we aimed to assess CAC progression according to changes in risk factors through serial CT measurements in asymptomatic individuals.

2. Materials and Methods

2.1. Study Design and Participants

Based on the health screening data registry of the Seoul National University Bundang Hospital (SNUBH) between January 2006 and December 2012, patients who underwent serial CAC scoring at least two times with more than one-year intervals were assessed. All individuals were asked whether they had chest pain or equivalent symptoms according to the WHO Rose angina questionnaire [12]. Physicians subsequently determined asymptomatic individuals who were free of coronary artery disease based on the patients’ history including the answers from the questionnaire. We excluded participants who had a history of myocardial infarction, stroke, percutaneous coronary intervention, or coronary artery bypass graft. Finally, we enrolled 448 self-referred asymptomatic individuals who had undergone serial CAC scoring at least two times with more than one-year intervals.

2.2. Risk Factor Assessment

Basic demographic data were acquired from a database maintained by the SNUBH Health Promotion Center. Medical history of myocardial infarction, angina, hypertension, stroke, diabetes mellitus (DM), family history of CVD (myocardial infarction or stroke history in first-degree relatives), current medication profile, and smoking status were systematically determined by personal interviews during the patients’ hospital visits for initial and follow-up CAC scans.
Body weight and height were also recorded during their visits, and blood samples were collected and analyzed. We recorded the mean blood pressure (BP) after the measurement of the resting BP three times with the participant in a seated position. Hypertension was defined as a systolic/diastolic BP≥140/90 mmHg, respectively, or the current use of antihypertensive medication. Lipid profiles, including total cholesterol and triglycerides, and fasting plasma glucose were measured with blood sampling obtained after a 12-h fast. DM was defined as a fasting blood glucose level ≥126 mg/dL or current antidiabetic treatment. Hyperlipidemia was defined as a total cholesterol concentration of ≥240 mg/dL or current treatment with lipid-lowering drugs. Current smoking was considered if the participant had smoked regularly during the previous 3 months.

2.3. Data Acquisition

CT data were acquired using 64-multidetector cardiac CT (Brilliance 64; Philips Medical Systems, Best, The Netherlands) with collimation of 64 × 0.625 mm and rotation time of 420 ms. CT scans used 120 kVp with variable mA according to the patient’s body weight and non-overlapping sections with 2.5 mm slice thickness [13].
Calcium scoring was calculated using the Agatson score with a threshold of 130 Hounsfield Units (HU), with only contiguous voxels totaling ≥1 mm2 in the area on pre-contrast CT images [14]. The score for an individual lesion was obtained by multiplying the lesion area with the density weighting factor determined by the maximum CT attenuation in the specified lesion. The density weighting factor was determined as follows: lesions with a peak attenuation of 130–199 HU were assigned a value of 1, those with a peak attenuation of 200–299 HU were assigned a value of 2, those with a peak attenuation of 300–399 HU were assigned a value of 3, and those with a peak attenuation value >400 HU were assigned a value of 4 [15]. The total Agatston score was the summed score of all coronary lesions. According to the initial CAC score, patients were categorized into three groups as follows: zero-CAC (CAC=0), low-CAC (0.1≤CAC score≤100), and high-CAC (CAC score>100) groups.

2.4. Statistical Analysis

Continuous parameters are presented as mean±SD, and nominal or ordinal parameters are given as n (%). Continuous parameters among the three groups classified according to the initial CAC score were compared using one-way analysis of variance (ANOVA) with Scheffe’s post hoc test, whereas nominal data were evaluated using the chi-square or Fisher’s exact test.
Annualized progression of the CAC score (ΔCAC/year) was calculated as the last CAC score minus the initial CAC score divided by the time between the initial and last CAC scan. The group with an initial CAC score of zero was divided into two groups by examining the changes in the follow-up CAC scan: a group with continuous zero CAC scores (zero-CAClast) and a group with new calcium (new-CAClast). Those with calcium present on the initial CT scan were divided into two groups based on an annual CAC increase of more than 20 (ΔCAC/year>20). Differences between two groups were analyzed using Student’s t-test for continuous data and the chi-square test for nominal or ordinal data.
Finally, univariate and multivariate logistic regression analyses were assessed for independent predictors of ΔCAC/year>20. SPSS 17.0 package (SPSS Inc., Chicago, Illinois) was used for all statistical analyses, and a p-value <0.05 was regarded as statistical significance.

3. Results

3.1. Basic Demographics of Enrolled Asymptomatic Individuals

A total of 448 asymptomatic individuals underwent serial CAC scans two times with an interval of more than one year. The initial CAC scores ranged from 0 to 758.3. Among them, the initial CAC score was zero in 336 patients (75.0%). The low-CAC group comprised 70 individuals (15.6%) with a CAC score of 31.6±26.7, whereas 42 individuals (9.4%) with a mean CAC score of 250.6±190.3 belonged to the high-CAC group. Table 1 summarizes the baseline demographic characteristics and risk factors of the study population in the three groups classified according to the initial CAC score. The mean age was higher and male sex more prevalent in the low-CAC and high-CAC groups compared to the zero-CAC group (all p<0.05). Hypertension prevalence significantly increased according to the initial CAC score: the high-CAC group had the highest percentage, followed by the low-CAC and then zero-CAC groups (all p<0.05). Other demographic parameters, including the presence of DM and hyperlipidemia, as well as statin and aspirin medication use, were significantly higher in the low- and high-CAC groups than in the zero-CAC group (all p<0.05). However, these parameters were not significantly different between the low-CAC and high-CAC groups. Overall, the number of risk factors was higher in groups with CAC presence (low-CAC and high-CAC group) than in that with CAC absence (zero-CAC group).

3.2. CAC Progression and Changes in Risk Factors during Follow-up

During the mean 3.5±1.3 years of follow-up (range 1.0–7.5 years), the mean annual progression in CAC score was 10.0±29.6. The △CAC/year was >10 in 87 patients (19.4%), whereas △CAC/year was >20 in 61 patients (13.6%). The degree of annual CAC progression was significantly higher in the group with a higher initial CAC score (p<0.001).
During the follow-up period, hypertension, DM, and hyperlipidemia were newly diagnosed in 14 individuals (3.1%), 7 individuals (1.6%), and 31 individuals (6.9%), respectively. In the smoking status survey, 22 individuals (4.9%) quit smoking, whereas 6 individuals (1.3%) started smoking. These new risk factors were more frequently recorded in the group with CAC presence than in that with CAC absence in the initial CAC scan. Table 2 presents CAC progression and changes in risk factors during the follow-up period among the three groups classified according to the initial CAC score.

3.3. Comparison of Changes in CAC Scores and Risk Factors in the Initial Zero-CAC Group: Zero-CAClast vs. New-CAClast

Of the 336 individuals with an initial CAC score of zero, 43 individuals (12.8%) developed coronary artery calcifications during follow-up (new-CAClast group), whereas the remaining 293 individuals (87.2%) did not develop coronary artery calcifications (zero-CAClast group).
Table 3 compares the changes in CAC scores and risk factors between these two groups. Age, body mass index (BMI), and hyperlipidemia prevalence were significantly higher in the new-CAClast group than in the zero-CAClast group (all p<0.05). During follow-up, hypertension developed significantly more frequently in the new-CAClast group; therefore, the prevalence rates of hypertension and hyperlipidemia at the time of the final CAC scan were higher in the new-CAClast group than in the zero-CAClast group (all p<0.05).

3.4. Comparison of Changes in CAC Scores and Risk Factors in the Group with Initial CAC Presence: Rapidly vs. Slowly Progressing-CAC Groups

Among the 112 patients with CAC presence in the initial scan, 60 patients had rapid progression in CAC changes with △CAC/year>20, and 52 patients had slow progression with △CAC/year≤20. Table 4 compares the changes in CAC scores and risk factors between these two groups. BMI and prevalence of statin medication were higher in the rapidly progressing-CAC group than in the slowly progressing-CAC group (both p<0.05). Likewise, the prevalence rates of newly developed hypertension and current smoking were higher in the rapidly progressing-CAC group than in the slowly progressing-CAC group (both p<0.05). The initial CAC score was also higher in the rapidly progressing-CAC group than in the slowly progressing-CAC group (178.9±190.5 vs. 38.5±44.2, respectively; p<0.001).

3.5. Predictors of Rapid CAC Progression

Table 5 shows the results of univariate and multivariate logistic regression analyses for the predictors of rapid CAC progression in asymptomatic adults. Based on univariate analysis, the parameters age, male sex, BMI, and all risk factors including hypertension, DM, hyperlipidemia, current smoking, and family history of CVD were significantly associated with rapid CAC progression defined as △CAC/year>20 (all p<0.05). Using multivariate analysis, strong predictors for rapid CAC progression were the presence of hypertension at the time of the last CAC scan (odds ratio [OR] 11.3; 95% confidence interval [CI] 1.33, 95.42) and the initial CAC score (OR 1.05; 95% CI 1.04, 1.07).

4. Discussion

This study evaluated CAC progression according to changes in risk factors based on serial CTs to calculate the Agatston score in asymptomatic individuals. The main findings of the study were as follows: 1) At the time of the initial CAC scan, the parameters age, prevalence of male sex, and all risk factors were significantly higher in the group with CAC presence than in the no-CAC group; 2) During the mean 3.5±1.3 years of follow-up, 43 (12.8%) of 336 individuals with an initial CAC score of zero developed coronary artery calcifications, and 60 (53.6%) of the 112 individuals with initial CAC presence showed rapid annual CAC progression of more than 20; 3) Age, male sex, BMI, and all risk factors were significantly associated with △CAC/year>20, but recently diagnosed hypertension (OR, 11.3) and initial CAC score (OR, 1.05) were significant independent predictors in multivariate regression analyses. This suggests that patients with higher initial CAC scores may benefit from more frequent follow-up scans compared to patients with lower initial scores. This also suggests that continuously checking the changes in risk factors is important because most risk factors are modifiable and dynamic in response to treatment.
Our study was motivated by the lack of guideline-supported recommendations for repeat CAC scans, although an increase in CAC score on serial scans is a well-known and strong predictor of CVD and worse survival rates [16]. Regarding the natural progression of CAC in asymptomatic populations with an initial CAC score of zero, limited prior studies have suggested not to repeat scans for at least 4–5 years because asymptomatic populations have a low incidence of CAC progression within 5 years [16,17,18,19]. Similarly, we observed a minimal increase (0.6±2.7) in CAC score in the initial zero-CAC group during a mean follow-up of 3.5 years.
However, few studies have examined the natural progression of CAC in populations with an initial CAC score above zero, and no information exists on the optimal timing for follow-up scans in this population [20,21,22]. Based on several studies [23,24], it is evident that individuals with higher initial CAC scores tend to exhibit more rapid CAC progression over time. This finding is supported by the fact that persons with higher initial CAC scores have a higher risk of developing atherosclerosis and, hence, experience more pronounced CAC progression over time. Our study also demonstrated that the initial CAC score is one of the independent predictors for CAC progression, even after adjusting for traditional risk factors. Accordingly, the optimal timing and frequency of follow-up scans for this population should be decided based on their initial CAC score.
Previous studies have demonstrated that traditional risk factors, such as age, male sex, BMI, hypertension, DM, hyperlipidemia, current smoking, and family history of CVD, are associated with the presence and degree of CAC progression [10,11], which is consistent with our results. Furthermore, Lehmann et al. [25] reported that recent risk factors assessed at the last follow-up, rather than initial risk factors, are the more influential predictors for coronary and cardiovascular event rates. Our study also demonstrates that recently diagnosed hypertension was one of the most powerful predictors of CAC progression. This means that recent health conditions have the greatest impact on CAC progression because most clinical risk factors improve or worsen depending on lifestyle changes or medical treatment. Therefore, regular health checkups and risk factor control may be helpful for slowing down CAC progression.
Regarding medications, the effectiveness of lipid-lowering drugs, such as statins, in slowing the CAC progression rate has been a topic of considerable interest. While initial studies showed CAC regression with statin therapy, more recent data showed the opposite [26]. That is, recent studies have reported persistent CAC progression despite intensive lipid-lowering therapy [27,28]. Our study also identified statin medication as one of the independent predictors for CAC progression. This can be explained by the ‘calcium paradox’ concept of improved clinical outcome despite plaque progression when plaque progression is characterized by a predominant increase in dense calcium and plaque stabilization [29].
Our study has several limitations. First, our study has no information on cardiovascular events as we aimed to assess CAC progression in relation to changes in risk factors. Second, we assessed major traditional risk factors such as hypertension and DM but did not include novel risk factors such as C-reactive protein or lipid profiles. Although there are no conclusive findings regarding their specific value for CAC progression, a prospective study would be needed to analyze more risk factors. Finally, as this is a single-center retrospective study using a single type of scanner, the generalizability of our findings to other populations and imaging settings may be limited. Hence, large-scale, multicenter, multivendor studies are needed to validate our results.
In conclusion, our study showed that CAC progression was affected by demographic and traditional risk factors, but adjusting for these factors, recently diagnosed risk factors and the initial CAC score were the most influential factors for rapid CAC progression. This suggests that patients with higher initial CAC scores may benefit from more frequent follow-up scans and need continuous checks regarding changes in risk factors. Based on this study, we recommend that the appropriate follow-up time for CAC measurements should be individually determined based on each patient’s initial CAC score and changes in risk factors. This personalized approach to follow-up could help optimize the timing of repeat scans and facilitate early detection and management of CVD.

Author Contributions

Conceptualization and design of the work, E.J.C.; methodology, E.J.C.; formal analysis, J.Y.Y. and E.J.C.; data curation, J.Y.Y. and S.R.K.; manuscript drafting, J.Y.Y., S.R.K., and E.J.C.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and the institutional review board of Seoul National University Bundang Hospital approved the study protocol (SNUBH IRB No. 1507-308-105).

Informed Consent Statement

All participants of this study waived informed consent due to retrospective study.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, Eun Ju Chun, upon reasonable request.

Acknowledgments

None.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Hecht, H. S. Coronary artery calcium scanning: past, present, and future. JACC Cardiovasc. Imaging 2015, 8, 579–596. [Google Scholar] [CrossRef]
  2. Gupta, A.; Bera, K.; Kikano, E.; Pierce, J. D.; Gan, J.; Rajdev, M.; Ciancibello, L. M.; Gupta, A.; Rajagopalan, S.; Gilkeson, R. C. Coronary artery calcium scoring: current status and future directions. Radiographics 2022, 42, 947–967. [Google Scholar] [CrossRef]
  3. Detrano, R.; Guerci, A. D.; Carr, J. J.; Bild, D. E.; Burke, G.; Folsom, A. R.; Liu, K.; Shea, S.; Szklo, M.; Bluemke, D. A. , et al. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N. Engl. J. Med. 2008, 358, 1336–1345. [Google Scholar] [CrossRef]
  4. Erbel, R.; Möhlenkamp, S.; Moebus, S.; Schmermund, A.; Lehmann, N.; Stang, A.; Dragano, N.; Grönemeyer, D.; Seibel, R.; Kälsch, H. , et al. Coronary risk stratification, discrimination, and reclassification improvement based on quantification of subclinical coronary atherosclerosis: the Heinz Nixdorf Recall study. J. Am. Coll. Cardiol. 2010, 56, 1397–1406. [Google Scholar] [CrossRef]
  5. Becker, A.; Leber, A.; Becker, C.; Knez, A. Predictive value of coronary calcifications for future cardiac events in asymptomatic individuals. Am. Heart J. 2008, 155, 154–160. [Google Scholar] [CrossRef]
  6. Arnett, D. K.; Blumenthal, R. S.; Albert, M. A.; Buroker, A. B.; Goldberger, Z. D.; Hahn, E. J.; Himmelfarb, C. D.; Khera, A.; Lloyd-Jones, D.; McEvoy, J. W. , et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J. Am. Coll. Cardiol. 2019, 74, 1376–1414. [Google Scholar] [CrossRef]
  7. Mach, F.; Baigent, C.; Catapano, A. L.; Koskinas, K. C.; Casula, M.; Badimon, L.; Chapman, M. J.; De Backer, G. G.; Delgado, V.; Ference, B. A. , et al. 2019 ESC/EAS guidelines for the management of dyslipidaemias: Lipid modification to reduce cardiovascular risk. Atherosclerosis 2019, 290, 140–205. [Google Scholar] [CrossRef]
  8. Budoff, M. J.; Hokanson, J. E.; Nasir, K.; Shaw, L. J.; Kinney, G. L.; Chow, D.; Demoss, D.; Nuguri, V.; Nabavi, V.; Ratakonda, R. , et al. Progression of coronary artery calcium predicts all-cause mortality. JACC Cardiovasc. Imaging 2010, 3, 1229–1236. [Google Scholar] [CrossRef]
  9. McEvoy, J. W.; Blaha, M. J.; Defilippis, A. P.; Budoff, M. J.; Nasir, K.; Blumenthal, R. S.; Jones, S. R. Coronary artery calcium progression: an important clinical measurement? A review of published reports. J. Am. Coll. Cardiol. 2010, 56, 1613–1622. [Google Scholar] [CrossRef]
  10. Arad, Y.; Goodman, K. J.; Roth, M.; Newstein, D.; Guerci, A. D. Coronary calcification, coronary disease risk factors, C-reactive protein, and atherosclerotic cardiovascular disease events: the St. Francis Heart Study. J. Am. Coll. Cardiol. 2005, 46, 158–165. [Google Scholar] [CrossRef]
  11. Kronmal, R. A.; McClelland, R. L.; Detrano, R.; Shea, S.; Lima, J. A.; Cushman, M.; Bild, D. E.; Burke, G. L. Risk factors for the progression of coronary artery calcification in asymptomatic subjects: results from the Multi-Ethnic Study of Atherosclerosis (MESA). Circulation 2007, 115, 2722–2730. [Google Scholar] [CrossRef]
  12. Lawlor, D. A.; Adamson, J.; Ebrahim, S. Performance of the WHO Rose angina questionnaire in post-menopausal women: are all of the questions necessary. J. Epidemiol. Community Health 2003, 57, 538–541. [Google Scholar] [CrossRef]
  13. Detrano, R. C.; Anderson, M.; Nelson, J.; Wong, N. D.; Carr, J. J.; McNitt-Gray, M.; Bild, D. E. Coronary calcium measurements: effect of CT scanner type and calcium measure on rescan reproducibility—MESA study. Radiology 2005, 236, 477–484. [Google Scholar] [CrossRef]
  14. Agatston, A. S.; Janowitz, W. R.; Hildner, F. J.; Zusmer, N. R.; Viamonte, M.; Detrano, R. Quantification of coronary artery calcium using ultrafast computed tomography. J. Am. Coll. Cardiol. 1990, 15, 827–832. [Google Scholar] [CrossRef]
  15. Blaha, M. J.; Mortensen, M. B.; Kianoush, S.; Tota-Maharaj, R.; Cainzos-Achirica, M. Coronary artery calcium scoring: is it time for a change in methodology? JACC Cardiovasc. Imaging 2017, 10, 923–937. [Google Scholar] [CrossRef]
  16. Min, J. K.; Lin, F. Y.; Gidseg, D. S.; Weinsaft, J. W.; Berman, D. S.; Shaw, L. J.; Rozanski, A.; Callister, T. Q. Determinants of coronary calcium conversion among patients with a normal coronary calcium scan: what is the “warranty period” for remaining normal. J. Am. Coll. Cardiol. 2010, 55, 1110–1117. [Google Scholar] [CrossRef]
  17. Shen, Y. W.; Wu, Y. J.; Hung, Y. C.; Hsiao, C. C.; Chan, S. H.; Mar, G. Y.; Wu, M. T.; Wu, F. Z. Natural course of coronary artery calcium progression in Asian population with an initial score of zero. BMC Cardiovasc. Disord. 2020, 20, 212. [Google Scholar] [CrossRef]
  18. Gopal, A.; Nasir, K.; Liu, S. T.; Flores, F. R.; Chen, L.; Budoff, M. J. Coronary calcium progression rates with a zero initial score by electron beam tomography. Int. J. Cardiol. 2007, 117, 227–231. [Google Scholar] [CrossRef]
  19. Koulaouzidis, G.; Charisopoulou, D.; Maffrett, S.; Tighe, M.; Jenkins, P. J.; McArthur, T. Coronary artery calcification progression in asymptomatic individuals with initial score of zero. Angiology 2013, 64, 494–497. [Google Scholar] [CrossRef]
  20. Budoff, M. J.; Young, R.; Lopez, V. A.; Kronmal, R. A.; Nasir, K.; Blumenthal, R. S.; Detrano, R. C.; Bild, D. E.; Guerci, A. D.; Liu, K. , et al. Progression of coronary calcium and incident coronary heart disease events: MESA (Multi-Ethnic Study of Atherosclerosis). J. Am. Coll. Cardiol. 2013, 61, 1231–1239. [Google Scholar] [CrossRef]
  21. Hisamatsu, T.; Liu, K.; Chan, C.; Krefman, A. E.; Fujiyoshi, A.; Budoff, M. J.; Miura, K.; Lloyd-Jones, D. M.; Ueshima, H. Coronary artery calcium progression among the US and Japanese men. Circ. Cardiovasc. Imaging 2019, 12, e008104. [Google Scholar] [CrossRef] [PubMed]
  22. Schmermund, A.; Baumgart, D.; Möhlenkamp, S.; Kriener, P.; Pump, H.; Grönemeyer, D.; Seibel, R.; Erbel, R. Natural history and topographic pattern of progression of coronary calcification in symptomatic patients: An electron-beam CT study. Arterioscler. Thromb. Vasc. Biol. 2001, 21, 421–426. [Google Scholar] [CrossRef] [PubMed]
  23. Lee, K. K.; Fortmann, S. P.; Fair, J. M.; Iribarren, C.; Rubin, G. D.; Varady, A.; Go, A. S.; Quertermous, T.; Hlatky, M. A. Insulin resistance independently predicts the progression of coronary artery calcification. Am. Heart J. 2009, 157, 939–945. [Google Scholar] [CrossRef]
  24. Wong, N. D.; Kawakubo, M.; LaBree, L.; Azen, S. P.; Xiang, M.; Detrano, R. Relation of coronary calcium progression and control of lipids according to National Cholesterol Education Program guidelines. Am. J. Cardiol. 2004, 94, 431–436. [Google Scholar] [CrossRef]
  25. Lehmann, N.; Erbel, R.; Mahabadi, A. A.; Rauwolf, M.; Möhlenkamp, S.; Moebus, S.; Kälsch, H.; Budde, T.; Schmermund, A.; Stang, A. , et al. Value of progression of coronary artery calcification for risk prediction of coronary and cardiovascular events: result of the HNR Study (Heinz Nixdorf Recall). Circulation 2018, 137, 665–679. [Google Scholar] [CrossRef] [PubMed]
  26. McCullough, P. A.; Chinnaiyan, K. M. Annual progression of coronary calcification in trials of preventive therapies: a systematic review. Arch. Intern. Med. 2009, 169, 2064–2070. [Google Scholar] [CrossRef] [PubMed]
  27. Valenti, V.; Ó Hartaigh, B.; Heo, R.; Cho, I.; Schulman-Marcus, J.; Gransar, H.; Truong, Q. A.; Shaw, L. J.; Knapper, J.; Kelkar, A. A. , et al. A 15-year warranty period for asymptomatic individuals without coronary artery calcium: a prospective follow-up of 9,715 individuals. JACC Cardiovasc. Imaging 2015, 8, 900–909. [Google Scholar] [CrossRef] [PubMed]
  28. Terry, J. G.; Carr, J. J.; Kouba, E. O.; Davis, D. H.; Menon, L.; Bender, K.; Chandler, E. T.; Morgan, T.; Crouse, J. R. Effect of simvastatin (80 mg) on coronary and abdominal aortic arterial calcium (from the coronary artery calcification treatment with zocor [CATZ] study). Am. J. Cardiol. 2007, 99, 1714–1717. [Google Scholar] [CrossRef] [PubMed]
  29. Rodriguez-Granillo, G. A.; Carrascosa, P.; Bruining, N. Progression of coronary artery calcification at the crossroads: sign of progression or stabilization of coronary atherosclerosis. Cardiovasc. Diagn. Ther. 2016, 6, 250–258. [Google Scholar] [CrossRef]
Table 1. Patient characteristics.
Table 1. Patient characteristics.
Parameter Total

(n=448)
Zero-CAC
(CAC=0)
(n=336)
Low-CAC
(0.1≤CAC≤100)
(n=70)
High-CAC
(CAC>100)
(n=42)
Initial CAC score 28.4±93.2 0 31.6±26.7* 250.6±190.3*†
Age (years) 53.4±8.1 51.9±7.2 56.9±9.4* 57.4±8.6*
Male sex 329 (73.4%) 228 (67.9%) 62 (88.6%)* 39 (92.9%)*
BMI (kg/m2) 24.6±2.9 24.4±2.9 25.6±2.6 24.7±2.9
Risk factors
 Hypertension 90 (20.1%) 40 (11.9%) 21 (30.0%)* 22 (52.4%)*†
 DM 29 (6.5%) 7 (2.1%) 11 (15.7%)* 11 (26.2%)*
 Current smoker 159 (35.5%) 111 (33.0%) 30 (42.9%) 18 (42.9%)
 Hyperlipidemia 77 (17.2%) 48 (14.3%) 19 (27.1%)* 12 (28.6%)*
 Family history of CVD 111 (24.8%) 77 (22.9%) 24 (34.3%) 10 (23.8%)
Medication
 Statin 32 (7.1%) 12 (3.6%) 10 (14.3%)* 10 (23.8%)*
 Aspirin 38 (8.5%) 14 (4.2%) 13 (18.6%)* 11 (26.2%)*
Number of risk factors
 None 154 (34.4%) 137 (40.8%) 11 (15.7%)* 6 (14.3%)*
 1 174 (38.8%) 135 (42.0%) 23 (32.9%) 16 (38.1%)
 ≥2 120 (26.8%) 64 (19.0%) 35 (50.0%)* 21 (50.0%)*
Note – BMI, body mass index; CAC, coronary artery calcium; CVD, cardiovascular disease; DM, diabetes mellitus. *p-value<0.05 between the zero-CAC group vs. low-CAC group, or zero-CAC group vs. high-CAC group, from a pairwise comparison that used the zero-CAC group as a control. †p-value<0.05 between low-CAC group vs. high-CAC group.
Table 2. Comparison of CAC progression and changes in risk factors according to the initial CAC score.
Table 2. Comparison of CAC progression and changes in risk factors according to the initial CAC score.
Parameter Total

(n=448)
Zero-CAC
(CAC=0)
(n=336)
Low-CAC
(0.1≤CAC≤100)
(n=70)
High-CAC
(CAC>100)
(n=42)
Follow-up CAC
△CAC/year 10.0±29.6 0.6±2.7 19.7±22.4* 69.5±64.3*†
△CAC/year>10 87 (19.4%) 6 (1.8%) 42 (60.0%)* 39 (92.9%)*†
△CAC/year>20 61 (13.6%) 1 (0.3%) 26 (37.1%)* 34 (81.0%)*†
Follow-up risk factors
Hypertension 103 (23.0%) 48 (14.3%) 29 (41.4%)* 25 (59.5%)*
 New hypertension 14 (3.1%) 8 (2.4%) 8 (11.4%)* 3 (7.1%)*
DM 36 (8.0%) 8 (2.4%) 18 (25.7%)* 13 (31.0%)*
 New DM 7 (1.6%) 1 (0.3%) 7 (10.0%)* 2 (4.8%)
Current smoker 137 (30.6%) 102 (30.4%) 23 (32.9%) 12 (28.6%)
 New smoking 6 (1.3%) 0 4 (5.7%)* 2 (4.8%)*
 Stop smoking 22 (4.9%) 9 (2.7%) 7 (10.0%)* 6 (14.3%)*
Hyperlipidemia 106 (23.7%) 65 (19.3%) 28 (40.0%)* 16 (38.1%)*
 New hyperlipidemia 31 (6.9%) 17 (5.1%) 9 (12.9%)* 6 (14.3%)*
*p-value<0.05 between the zero-CAC group vs. low-CAC group, or zero-CAC group vs. high-CAC group, from a pairwise comparison that used the zero-CAC group as a control. †p-value<0.05 between low-CAC group vs. high-CAC group.
Table 3. Changes in CAC score and risk factors in the initial zero-CAC group.
Table 3. Changes in CAC score and risk factors in the initial zero-CAC group.
Follow-up CAC zero-CAClast (n=293) new-CAClast (n=43) p-value
Age (years) 51.5±6.9 54.6±8.3 0.009*
Male 194 (66.2%) 34 (79.1%) 0.115
BMI (kg/m2) 24.2±2.9 25.3±2.8 0.024*
Initial risk factors
Hypertension 31 (10.6%) 9 (20.9%) 0.073
DM 5 (1.7%) 2 (4.7%) 0.222
Current smoker 92 (31.4%) 19 (44.2%) 0.118
Hyperlipidemia 37 (12.6%) 11 (25.6%) 0.034*
Family history of CVD 65 (22.2%) 12 (27.9%) 0.440
Medication statin 10 (3.4%) 2 (4.7%) 0.657
Medication aspirin 12 (4.1%) 2 (4.7%) 0.697
Follow-up risk factors
Hypertension 35 (11.9%) 13 (30.2%) 0.004*
New hypertension 4 (1.4%) 4 (9.3%) 0.011*
DM 5 (1.7%) 3 (7.0%) 0.069
New DM 0 1 (2.3%) 0.128
Hyperlipidemia 49 (16.7%) 16 (37.2%) 0.003*
New hyperlipidemia 12 (4.1%) 5 (11.6%) 0.052
Current smoker 86 (29.4%) 16 (37.2%) 0.292
New smoking 0 0 -
Stop smoking 6 (2.0%) 3 (7.0%) 0.095
Follow-up CAC score 0 16.7±27.9 <0.001*
*p-value<0.05.
Table 4. Changes in CAC scores and risk factors in the group with initial CAC presence.
Table 4. Changes in CAC scores and risk factors in the group with initial CAC presence.
Follow-up CAC score Slowly progressing-CAC:
△CAC/year≤20
(n=52)
Rapidly progressing-CAC:
△CAC/year>20
(n=60)
p-value
Age (years) 59.3±9.5 56.4±8.5 0.091
Male sex 46 (88.5%) 55 (91.7%) 0.752
BMI (kg/m2) 24.5±2.6 25.9±2.8 0.010*
Initial risk factors
Hypertension 15 (28.8%) 28 (46.7%) 0.079
DM 9 (17.3%) 13 (21.7%) 0.638
Current smoker 19 (36.5%) 29 (48.3%) 0.252
Hyperlipidemia 12 (23.1%) 22 (36.7%) 0.398
Family history of CVD 65 (22.2%) 12 (27.9%) 0.150
Medication statin 5 (9.6%) 15 (25.0%) 0.047*
Medication aspirin 10 (19.2%) 14 (23.3%) 0.650
Follow-up risk factors
Hypertension 35 (30.8%) 38 (63.3%) 0.001*
New hypertension 1 (1.9%) 10 (16.7%) 0.010*
DM 11 (21.2%) 20 (33.3%) 0.204
New DM 2 (3.8%) 7 (11.7%) 0.172
Hyperlipidemia 18 (34.6%) 26 (43.3%) 0.438
New hyperlipidemia 6 (11.5%) 9 (15.0%) 0.782
Current smoker 13 (25.0%) 22 (36.7%) 0.222
New smoking 0 6 (10.0%) 0.029*
Stop smoking 6 (11.5%) 7 (11.7%) >0.99
CAC score
Initial CAC score 38.5±44.2 178.9±190.5 <0.001*
Follow-up CAC score 66.7±57.3 434.8±408.6 <0.001*
△CAC/year 7.7±7.0 64.9±54.6 <0.001*
*p-value<0.05.
Table 5. Predictors for an annual CAC progression of more than 20.
Table 5. Predictors for an annual CAC progression of more than 20.
Parameter Rapid CAC progression (△CAC/year>20)
Univariate
OR (95% CI)
p-value Multivariate
OR (95% CI)
p-value
Age 1.05 (1.02, 1.08) 0.003* 0.96 (0.89, 1.03) 0.206
Male sex 4.67 (1.83, 11.98) 0.001* 1.15 (0.19, 6.86) 0.876
BMI 1.18 (1.08, 1.30) <0.001* 1.30 (1.04, 1.63) 0.051
Initial risk factors
 Hypertension 5.12 (2.87, 9.14) <0.001* 0.22 (0.02, 1.97) 0.174
 DM 6.28 (2.85, 13.85) <0.001* 0.20 (0.02, 1.87) 0.157
 Hyperlipidemia 2.71 (1.49, 4.95) 0.001* 1.77 (0.28, 11.20) 0.545
 Current smoking 1.94 (1.12, 3.34) 0.017* 0.66 (0.14, 3.18) 0.606
 Family history of CVD 1.89 (1.06, 3.35) 0.03* 1.74 (0.55, 5.46) 0.344
Medication
 Statin 7.09 (3.32, 15.16) <0.001* 1.61 (0.34, 7.50) 0.546
 Aspirin 4.50 (2.18, 9.31) <0.001* 0.56 (0.16, 2.01) 0.376
Follow-up risk factors
 Hypertension 8.34 (4.65, 14.94) <0.001* 11.30 (1.33, 95.42) 0.026*
  New hypertension 8.24 (3.20, 21.23) <0.001*
 DM 9.45 (4.66, 19.14) <0.001* 5.95 (0.79, 44.93) 0.084
  New DM 16.59 (4.16, 66.10) <0.001* -
 Hyperlipidemia 2.95 (1.69, 5.18) <0.001* 0.99 (0.19, 5.13) 0.995
  New hyperlipidemia 2.74 (1.20, 6.24) 0.016*
 Smoking 1.45 (0.83, 2.54) 0.196 4.18 (0.78, 22.54) 0.096
  New smoking 0 -
Initial CAC score 1.04 (1.03, 1.05) <0.001* 1.05 (1.04, 1.07) <0.001*
 0 1 (ref) 1 (ref)
 0.1–100 0.001 (0, 0.01) <0.001* 0 (0, 0.01) <0.001*
 >100 0.14 (0.06, 0.35) <0.001* 0.06 (0.02, 0.19) <0.001*
Note – BMI, body mass index; CAC, coronary artery calcium; CI, confidence interval; CVD, cardiovascular disease; DM, diabetes mellitus; OR, odds ratio. *p-value<0.05.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

© 2024 MDPI (Basel, Switzerland) unless otherwise stated