Left ventricular geometry and the risk of heavy coronary artery calcification in patients with pre-dialysis chronic kidney disease: the KoreaN Cohort Study for Outcome in Patients With Chronic Kidney Disease (KNOW-CKD)

LVG and CACS in CKD

Article information

Korean J Nephrol. 2025;.j.krcp.25.070

Publication date (electronic) : 2025 August 11

doi : https://doi.org/10.23876/j.krcp.25.070

Sang Heon Suh ¹

, Hong Sang Choi ¹

, Chang Seong Kim ¹

, Eun Hui Bae ¹

, Seong Kwon Ma ¹

, Kook-Hwan Oh ²^,³

, Young Youl Hyun ⁴

, Jong Cheol Jeong ⁵

, Seung Hyeok Han ⁶

, Sue K. Park ⁷^,⁸^,⁹

, Soo Wan Kim^,¹

, on behalf of the KoreaN Cohort Study for Outcomes in Patients With Chronic Kidney Disease (KNOW-CKD) Investigators

¹Department of Internal Medicine, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea

²Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea

³Kidney Research Institute, Seoul National University Medical Research Center, Seoul, Republic of Korea

⁴Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

⁵Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea

⁶Division of Nephrology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea

⁷Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea

⁸Cancer Research Institute, Seoul National University, Seoul, Republic of Korea

⁹Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, Republic of Korea

Correspondence: Soo Wan Kim Department of Internal Medicine, Chonnam National University Medical School, 42 Jebong-ro, Dong-gu, Gwangju 61469, Republic of Korea. E-mail: skimw@chonnam.ac.kr

Received 2025 March 16; Revised 2025 April 24; Accepted 2025 May 16.

Abstract

Background

The association between abnormal left ventricular geometry (LVG) patterns and the presence of coronary artery calcification is unclear in patients with CKD.

Methods

A total of 2,038 patients with pre-dialysis CKD at stages 1 to 5 were categorized by LVG patterns, which were echocardiographically determined by the presence or absence of left ventricular hypertrophy (LVH) and relative wall thickness (RWT): normal, concentric remodeling, eccentric LVH, and concentric LVH. The study outcome was the presence of heavy coronary artery calcification, which is defined as coronary artery calcium score >1,000 Agatston units.

Results

Logistic regression analyses demonstrated that concentric remodeling (adjusted odds ratio [OR], 2.53; 95% confidence interval [95% CI], 1.32–4.85) and concentric LVH (adjusted OR, 2.89; 95% CI, 1.49–5.62), but not eccentric LVH (adjusted OR, 1.58; 95% CI, 0.71–3.51), were significantly associated with the risk of heavy coronary artery calcification. The presence of LVH alone was not significantly associated with the risk of heavy coronary artery calcification (adjusted OR, 1.65; 95% CI, 0.97–2.81), while the increase in RWT independently increased the risk of heavy coronary artery calcification (adjusted OR, 2.423; 95% CI, 1.48–4.00).

Conclusion

Abnormal LVG patterns, such as concentric remodeling and concentric LVH, but not eccentric LVH, are significantly associated with the risk of heavy coronary artery calcification in patients with CKD. It is expected that the determination of LVG patterns may facilitate risk stratification in relation to the coronary evaluation strategy.

Keywords: Chronic renal insufficiency; Left ventricular hypertrophy; Vascular calcification; Ventricular remodeling

Introduction

Cardiovascular events account for the leading cause of mortality in patients with chronic kidney disease (CKD) [1–3]. Coronary artery disease (CAD) and heart failure (HF) are the major two cardiovascular disease entities in this population [1], and their high prevalence implies the overlapping pathogenesis between CKD progression and those diseases [4–6].

Vascular calcification is, for instance, frequently detected among patients with CKD, and is distinguished from atherosclerotic vascular lesions that is the most common cause of CAD in the general population [7–9]. The principal mechanism of vascular calcification is now attributed to the transdifferentiation of vascular smooth muscle cells (VSMCs) to osteoblast-like phenotype resulting in calcium deposition [10,11]. As calcium deposition occurs in VSMCs stimulated with uremic toxins or high concentrations of phosphate in vitro and in vivo [12–14], this process could be promoted or accelerated in patients with CKD.

The phenotypical picture of HF in patients with CKD is also different from that of the general population [15]. The prevalence of HF with preserved ejection fraction (HFpEF) is relatively higher among patients with CKD [16–18], although the overall mortality of HFpEF is similar to that of HF with reduced ejection fraction (HFrEF) [19]. Whereas ischemic heart diseases are the leading cause of HFrEF [20], the pathogenesis of HFpEF is more complex and multifactorial [21]. It has been reported that various conditions, such as volume overload, uncontrolled hypertension, and anemia, lead to the structural remodeling of the left ventricle, ultimately contributing to the development of HFpEF, all of which are common in patients with CKD [18,21,22]. It is not surprising that, therefore, regardless of the reduction in left ventricular ejection fraction (LVEF), left ventricular geometry (LVG) is frequently altered in this population [23,24], which is defined by the concentricity (i.e., relative wall thickness [RWT]) and the presence or absence of left ventricular hypertrophy (LVH).

It is unclear, on the other hand, whether the alteration in LVG is significantly associated with the presence of underlying coronary artery lesions in patients with CKD, because it has been believed that ischemic heart diseases mainly contribute to the reduction of LVEF, rather than to the alteration of LVG in relation to the development of HFpEF [16]. Yet, we assumed that, while the reduction in LVEF is still a typical consequence of long-standing ischemic heart disease, the earlier structural remodeling of the heart accompanied by coronary artery calcifications may also include the alterations in LVG with or without the reduction in LVEF. In this context, we here investigated the association of LVG and coronary artery calcification in patients with pre-dialysis CKD. Taking advantage of the data on echocardiographic measures and coronary artery calcium score (CACS) from more than 2,000 patients with CKD, we conducted a cross-sectional analysis to determine the association between LVG and the burden of coronary artery calcification.

Methods

Study design

The KNOW-CKD (KoreaN Cohort Study for Outcome in Patients With Chronic Kidney Disease) [25] is a prospective cohort study of patients with CKD at stages 1 to pre-dialysis 5 recruited from nine tertiary hospitals in South Korea from 2011 to 2016 (NCT01630486; https://www.clinicaltrials.gov). The study was conducted in accordance with the Declaration of Helsinki. The study design and protocol were approved by the Institutional Review Board at each participating center (see Additional information) [25]. The informed consent was voluntarily submitted by all the participants. Those lacking of the baseline measurement of CACS (n = 175), and those lacking the determination of LVG (n = 25) were excluded from a total of 2,238 participants who were initially enrolled. Finally, a total of 2,038 participants were included in the analysis (Fig. 1).

Figure 1.

Flow diagram of the study participants.

CACS, coronary artery calcification; LVG, left ventricular geometry; LVH, left ventricular hypertrophy.

Data collection from participants

The data on the demographics, anthropometrics, and medical history of the participants were recorded at the baseline, according to the study protocol [25]. Blood and urine specimens were acquired after an overnight fasting and were transferred to the central laboratory for analysis (Lab Genomics, Seongnam, Republic of Korea). The estimated glomerular filtration rate (eGFR) was calculated by the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation using serum creatinine level, as previously described [25,26]. CKD stages were defined by eGFR according to the KDIGO (Kidney Disease: Improving Global Outcomes) guideline [25,27].

Echocardiographic measurements

Complete two-dimensional M-mode and Doppler studies were conducted by the cardiologists blinded to the clinical data in each participating center according to the standard approach [28,29]. The recorded echocardiographic data were the ratio of the early transmitral blood flow velocity to early diastolic velocity of the mitral annulus (E/e′), LVEF, left atrial diameter (LAD), regional wall motion abnormality, valve calcification, left ventricular posterior wall thickness (PWT), interventricular septum thickness, left ventricular end-diastolic diameter (LVEDD), and left ventricular end-systolic diameter. Left ventricular mass was determined by the Devereux formula [28,29]. Left ventricular mass index (LVMI) was calculated by normalizing left ventricular mass to height² (g/m²). LVH was defined as LVMI >115 g/m² in male and >95 g/m² in female, respectively [28–30]. RWT was calculated as (2 × PWT) / LVEDD. RWT >0.42 was defined as increased [28,29]. LVG patterns were determined by the presence or absence of LVH and RWT: normal (no LVH and normal RWT), concentric remodeling (no LVH and increased RWT), eccentric LVH (LVH and normal RWT), and concentric LVH (LVH and increased RWT) [31].

Determination of the coronary artery calcium score

The baseline CACS was determined in the Agatston unit (AU) [32] on a digital radiologic workstation following electrocardiography-gated coronary multi-detector computed tomography according to the standard protocol at each participating center.

Exposure and study outcome

The participants were categorized by LVG patterns: normal, concentric remodeling, eccentric LVH, and concentric LVH. The study outcome was the presence of heavy coronary artery calcification, which is defined as CACS >1,000 AU [33], as a CACS ≥1,000 AU increased the hazard ratio for CVD 6.8-fold and all-cause mortality 2.9-fold compared to those with no coronary artery calcification in a study of the Coronary Artery Calcium Consortium [34].

Statistical analyses

The baseline characteristics were analyzed by one-way analysis of variance and chi-square test for continuous and categorical variables, respectively. The correlation between LVMI or RWT and CACS was visually demonstrated in scatter plots with Spearman coefficient analysis. Binary logistic regression analyses were conducted to address the independent association of LVG, LVH, or concentricity with the risk of heavy coronary artery calcification. Model 1 was unadjusted. Model 2 was adjusted for age and sex. Model 3 was further adjusted for Charlson comorbidity index, primary cause of CKD, smoking status, medication history (antiplatelets and/or anticoagulants, angiotensin-converting enzyme inhibitors and/or angiotensin II receptor blockers, diuretics, and lipid-lowering agents), body mass index (BMI), and systolic blood pressure (SBP). Model 4 was additionally adjusted for hemoglobin, albumin, low-density lipoprotein cholesterol (LDL-C), fasting glucose, high-sensitivity C-reactive protein (hs-CRP), 25-hydroxyvitamin D, eGFR, and spot urine albumin-to-creatinine ratio (ACR). The results of logistic regression analyses were reported as the odds ratios (ORs) with 95% confidence intervals (CIs). Penalized spline curve analysis [35] was used to visualize the linear correlation of LVMI or RWT as a continuous variable with the risk of heavy coronary artery calcification. We performed a series of sensitivity analyses to validate the result from the primary analysis by excluding a variety of minor subpopulations, including the participant with eGFR ≥90 mL/min/1.73 m² or with eGFR <15 mL/min/1.73 m², the participant without coronary artery calcification (i.e., CACS of 0 AU), and the participants with LVEF <50% (i.e., those with both reduced and mildly reduced LVEF). We also conducted prespecified subgroup analyses to evaluate whether the association between LVG and the risk of heavy coronary artery calcification is modified by certain clinical settings, such as age (<60 years vs. ≥60 years), sex (male vs. female), BMI (<25 kg/m² vs. ≥25 kg/m²), eGFR (<45 mL/min/1.73 m² vs. ≥45 mL/min/1.73 m²), and spot urine ACR (<300 mg/g vs. ≥300 mg/g). Two-sided p-values <0.05 were considered statistically significant. Statistical analysis was performed using IBM SPSS for Windows version 22.0 (IBM Corp.) and R (version 4.1.1; R project for Statistical Computing).

Results

Baseline characteristics

To describe the baseline characteristics of the participants, the study participants were categorized by LVG patterns (Table 1). Most of the features, such as age, sex, comorbid conditions, smoking history, and the primary cause of CKD were significantly differed by LVG patterns. Especially, the burden of coronary artery calcification was relatively higher in patients with concentric remodeling and concentric LVH. SBP and BMI were highest in patients with concentric LVH. Hemoglobin, albumin, LDL-C, hs-CRP, and creatinine levels were relatively higher in patients with eccentric and concentric LVH. Importantly, lower eGFR and higher spot urine ACR levels were related to eccentric and concentric LVH patterns. In addition, all the recorded echocardiographic parameters significantly differed by LVG patterns (Supplementary Table 1, available online). Especially, the indices related to diastolic dysfunction, such as E/e′ and LAD, gradually increased from normal LVG to concentric LVH. Collectively, abnormal LVG patterns were related to unfavorable clinical features at the baseline, including a heavier burden of coronary artery calcification.

Table 1.

Baseline characteristics of study participants by LVG patterns

Association between abnormal left ventricular geometry patterns and the risk of heavy coronary artery calcification

Weak, positive correlations of CACS with both LVMI (r = 0.267, p < 0.001) and RWT (r = 0.222, p < 0.001) were depicted in the scatter plots to address the correlation of LVMI or RWT with the extent of coronary artery calcification (Fig. 2). To address the independent association between abnormal LVG patterns and the risk of heavy coronary artery calcification, confounding factors were adjusted in the logistic regression analysis (Table 2). Concentric remodeling (adjusted OR, 2.53; 95% CI, 1.32–4.85) and concentric LVH (adjusted OR, 2.89; 95% CI, 1.49–5.62) were significantly associated with the risk of heavy coronary artery calcification. The presence of LVH alone was not significantly associated with the risk of heavy coronary artery calcification, while the increase in RWT independently increased the risk of heavy coronary artery calcification (adjusted OR, 2.43; 95% CI, 1.48–4.00). Penalized spline curve analyses demonstrated the linear associations of LVMI or RWT with the risk of coronary artery calcification are both significant (Fig. 3), though the positive association between LVMI and the risk of coronary artery calcification was only marginally significant.

Figure 2.

Scatter plot of LVMI or RWT with CACS.

The correlation of LVMI (A) or RWT (B) with the CACS was assessed by the Spearman correlation coefficient (r).

AU, Agatston unit, CACS, coronary artery calcium score; LVMI, left ventricular mass index; RWT, relative wall thickness.

Table 2.

ORs for heavy coronary artery calcification (CACS >1,000 AU) by LVG patterns

Figure 3.

Penalized spline curve of LVMI or RWT on the risk of heavy coronary artery calcification.

Adjusted odds ratio (OR) of LVMI (A) or RWT (B) as a continuous variable for the risk of heavy coronary artery calcification is depicted. The model was adjusted for age, sex, Charlson comorbidity index, primary causes of chronic kidney disease, smoking status, medication (antiplatelets/anticoagulants, angiotensin-converting enzyme inhibitors and/or angiotensin II receptor blockers, diuretics, lipid-lowering agents), body mass index, systolic blood pressure, hemoglobin, albumin, low-density lipoprotein cholesterol, fasting glucose, 25-hydroxyvitamin D, high-sensitivity C-reactive protein, estimated glomerular filtration rate, and spot urine albumin-to-creatinine ratio.

LVMI, left ventricular mass index; RWT, relative wall thickness.

Sensitivity and subgroup analyses

After excluding the participant with eGFR ≥90 mL/min/1.73 m² (Supplementary Table 2, available online) or with eGFR <15 mL/min/1.73 m² (Supplementary Table 3, available online), concentric remodeling, concentric LVH, and increased RWT, but not eccentric LVH, were associated with the risk of heavy coronary artery calcification. After excluding the participants without coronary artery calcification, concentric remodeling (adjusted OR, 2.49; 95% CI, 1.29–4.80), concentric LVH (adjusted OR, 2.89; 95% CI, 1.48–5.66), and increased RWT (adjusted OR, 2.37; 95% CI, 1.43–3.93) were still significantly associated with the risk of heavy coronary artery calcification (Supplementary Table 4, available online). Finally, even after excluding the participants with LVEF <50%, concentric remodeling (adjusted OR, 2.31; 95% CI, 1.19–4.491, concentric LVH (adjusted OR, 2.73; 95% CI, 1.39–5.38), and increased RWT (adjusted OR, 2.33; 95% CI, 1.40–3.88) were still robustly associated with the risk of heavy coronary artery calcification (Table 3). Subgroup analyses by age, sex, BMI, eGFR, and spot urine ACR (Table 4) demonstrated that the association between LVG patterns and the risk of heavy coronary artery calcification is not modified by those clinical contexts (All p for interaction > 0.05).

Table 3.

ORs for heavy coronary artery calcification (CACS >1,000 AU) by LVG patterns in the participants with LVEF ≥50%

Table 4.

ORs for heavy coronary artery calcification (CACS >1,000 AU) by LVG patterns in various subgroups

Discussion

In the present study, we found that abnormal LVG patterns are significantly associated with the risk of heavy coronary artery calcification in patients with CKD. Especially, the risk of heavy coronary artery calcification was significantly increased in patients with concentric remodeling and concentric LVH, but not in patients with eccentric LVH, indicating that concentric remodeling rather than LVH is independently associated with the risk of heavy coronary artery calcification in this population.

One of the sensitivity analyses in the present study validated that the association is still statistically significant even after the exclusion of the patients with reduced LVEF. Ischemic cardiomyopathy as a consequence of advanced coronary artery lesions usually presents with the reduction of LVEF [20,36,37]. As the prevalence of HFpEF is high in patients with CKD [6,18,21], while the mortality and morbidity rates due to CAD are also high [1,3], a decision for the invasive coronary evaluation becomes frequently dilemmatic in the absence of evidence for the reduction in LVEF among the patients with CKD. In this regard, we proved that certain types of abnormal LVG patterns, even without the reduction in LVEF, are significantly associated with the risk of heavy coronary artery calcification in patients with CKD, suggesting that more thorough coronary evaluation is required for patients with concentric remodeling of left ventricle.

One of the striking findings in the present study is that concentric remodeling, even in the absence of LVH, is associated with the risk of heavy coronary artery calcification, and that LVH without concentric remodeling was not significantly associated with the risk of heavy coronary artery calcification. Several studies reported that LVH, defined either by the echocardiographic evidence of the increase in LVMI or by the voltage evidence in electrocardiograms, is closely related to adverse cardiovascular outcomes both in the general population and in patients with CKD. Since the first report from the Framingham Heart Study [38], numerous subsequent studies confirmed the association between LVH and myocardial ischemia, HF, arrhythmias, thromboembolic disease, and stroke [39–44]. In contrast, the clinical implication of concentric remodeling without LVH remains less well-established. Ghali et al. [45], reported that, for example, among 988 patients who underwent both coronary arteriography for suspected CAD and echocardiography in a single center, an increase in LVMI, but not RWT, is independently associated with the risk of all-cause mortality. The probable association between coronary artery calcification and LVG patterns, nevertheless, has been suggested in previous studies including non-CKD populations. Gardin et al. [46] reported that, through the cross-sectional analysis of echocardiographic measures and CACS from 2,724 young adults, the extent of coronary artery calcification was significantly associated with left ventricular mass as well as PWT and septal wall thickness in diastole. Altunkan et al. [47] reported that, although LVH is a risk factor of subclinical atherosclerosis determined by the presence of coronary artery calcification, concentric, rather than eccentric, LVH is more evidently associated with the risk of the presence of coronary artery calcification, suggesting the potential link between concentric remodeling and concurrent coronary lesions. Paoletti et al. [44] reported that LVH regardless of LVG is associated with adverse outcomes in patients with CKD, including major adverse cardiovascular events (MACE) and CKD progression. It may seem contradictory to the major finding of the current study, but it should be also reminded that the outcome in each study was different. Though coronary artery calcification is a surrogate of MACE and CKD progression among this population, it seems reasonable that the specific correlation between the exposure and the outcomes should be delicately differed. The current study demonstrated that, therefore, concentric remodeling independent of the presence of LVH is significantly associated with the risk of heavy coronary artery calcification in patients with CKD, which is similar to, but distinguished from the previous studies, presenting a novel insight for the risk stratification in relation to the coronary evaluation strategy.

Pressure overload has long been the major mechanism of concentric remodeling [48], though a recent study reported that the remodeling of the left ventricle precedes that of large arterial vessels in patients with CKD [49]. This strongly suggests that certain pathogenic mechanism specific to CKD drives the structural remodeling of the left ventricle. It is now widely accepted that disturbance in phosphate homeostasis, uremic toxins, oxidative stress, and chronic inflammation all together contribute to cardiac remodeling in patients with CKD, while those are also well-known nontraditional cardiovascular risk factors [6,14,18,21]. It is best illustrated by the role of fibroblast growth factor 23 (FGF-23) both in cardiac remodeling and coronary artery calcification. Exogenously injected FGF-23 induced LVH in mice [50], while the subsequent clinical studies more sophisticatedly defined the association of elevated FGF-23 levels with concentric, but not eccentric, LVH [51,52]. High serum FGF-23 levels in patients with advanced CKD were, at the same time, associated with the risk of progression of coronary artery calcification [53,54]. The shared risk factors for left ventricular remodeling and vascular calcification in CKD, therefore, may explain the association of abnormal LVG patterns and the risk of heavy coronary artery calcification even in the absence of the reduction of LVEF which is a feature of ischemic cardiomyopathy. The “shared risk factor” theory, could also be supported by the correlation between the baseline characteristics and the abnormal LVG patterns. The high prevalence of clinically unfavorable features in patients with abnormal LVG patterns could also be attributed to the heavier burden of diverse clinical risk factors in those subpopulations, and those risk factors should represent the differences in the baseline characteristics by the LVG pattern.

The risk of adverse outcomes imposed by eccentric LVH is barely ignorable, though eccentric LVH did not increase the risk of heavy coronary artery calcification in the present study. In our previous study, eccentric LVH was independently associated with the risk of CKD progression [31]. A previous study on patients with end-stage renal disease also reported the risk of sudden death is increased with eccentric LVH [55]. The abnormal LVG patterns, regardless of their subtypes, thus, should trigger therapeutic interventions including strict blood pressure control.

Some limitations are to be noted. First, we cannot determine the temporal casualty between abnormal LVG patterns and coronary artery calcification, due to the nature of cross-sectional analyses. We assume that, however, the relation between abnormal LVG patterns and coronary artery calcification is more likely to be a true “association,”, rather than “cause-and-result,” considering the aforementioned shared risk factors [5,12–14]. Second, coronary artery calcification is a surrogate of commonly adopted hard outcomes. The correlation between the extent of coronary artery calcification and the risk of major adverse cardiac events, however, has been repeatedly confirmed both in the general population and in patients with CKD [56,57]. Moreover, the outcome in the present study is ‘heavy’ coronary artery calcification that is defined as CACS >1,000 AU to avoid the overestimation of the risk imposed by only mild-to-moderate extent of coronary artery calcification. Third, as the KNOW-CKD enrolled only ethnically Korean patients residing in South Korea, the extrapolation of the current results to other ethnic or geographical backgrounds requires caution, though previous studies with similar conclusions has been published based on the analyses from various ethnic and geographical backgrounds [45–47]. Fourth, provided the complex nature of CKD, unmeasured or residual confounders should be considered, though the findings in the present study result from the adjustments for numerous confounding factors and are also supported by a series of sensitivity analyses.

In conclusion, we report that abnormal LVG patterns, such as concentric remodeling and concentric LVH, but not eccentric LVH, are significantly associated with the risk of heavy coronary artery calcification in patients with CKD. It is expected that the determination of LVG patterns may facilitate risk stratification in relation to the coronary evaluation strategy.

Supplementary Materials

Supplementary data are available at Kidney Research and Clinical Practice online (https://doi.org/10.23876/j.krcp.25.070).

j-krcp-25-070-Supplementary-Table-1.pdf

j-krcp-25-070-Supplementary-Table-2.pdf

j-krcp-25-070-Supplementary-Table-3.pdf

j-krcp-25-070-Supplementary-Table-4.pdf

Notes

Additional information

The Institutional Review Board approval numbers of each institution are as follows: Seoul National University Hospital: No. 1104–089-359, May 25, 2011; Seoul National University Bundang Hospital: No. B-1106/129–008, August 24, 2011; Severance Hospital: No. 4–2011-0163, June 2, 2011; Kangbuk Samsung Medical Center: No. 2011–01-076, June 16, 2012; The Catholic University of Korea, Seoul St. Mary’s Hospital: No. KC11OIMI0441, June 30, 2011; Gachon University Gil Hospital: No. GIRBA2553, August 8, 2011; Eulji General Hospital: No. 201105–01, June 10, 2011; Chonnam National University Hospital: No. CNUH-2011-092, July 5, 2011; and Inje University Busan Paik Hospital: No. 11–091, July 26, 2011.

Conflicts of interest

All authors have no conflicts of interest to declare.

Funding

This work was supported by the Research Program funded by the Korea Disease Control and Prevention Agency (2011E3300300, 2012E3301100, 2013E3301600, 2013E3301601, 2013E3301602, 2016E3300200, 2016E3300201, 2016E3300202, 2019E320100, 2019E320101, 2019E320102, and 2022–11-007), by the National Institute of Health (NIH) research project (2025E110100), and by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2023–00217317 and RS-2023-00278258).

Data sharing statement

The data presented in this study are available from the corresponding author upon reasonable request.

Authors’ contributions

Conceptualization: SHS

Methodology: SHS, HSC, CSK, EHB, SKM

Data curation: KHO, YYH, JCJ, SHH

Formal analysis: SHS, SKP

Funding acquisition, Supervision: KHO, SWK

Writing–original draft: SHS

Writing–review & editing: All authors

All authors read and approved the final manuscript.

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Characteristic	LVG pattern				p-value
Characteristic	Normal	Concentric remodeling	Eccentric LVH	Concentric LVH	p-value
No. of participants	1,256	290	252	240
Age (yr)	50.897 ± 12.190	55.676 ± 11.941	56.486 ± 10.351	59.103 ± 10.597	<0.001
Male sex	783 (63.2)	197 (70.1)	91 (37.4)	130 (55.6)	<0.001
CACS (AU)					<0.001
0	694 (55.3)	113 (39.0)	114 (45.2)	69 (28.8)
>0 and ≤400	465 (37.0)	140 (48.3)	112 (44.4)	108 (45.0)
>400 and ≤1,000	64 (5.1)	16 (5.5)	15 (6.0)	35 (14.6)
>1,000	33 (2.6)	21 (7.2)	11 (4.4)	28 (11.7)
Charlson comorbidity index					<0.001
0–3	666 (53.8)	125 (44.5)	163 (67.1)	128 (54.7)
4–5	210 (17.0)	47 (16.7)	19 (7.8)	40 (17.1)
≥6	361 (29.2)	109 (38.8)	61 (25.1)	66 (28.2)
Primary cause of CKD					<0.001
Diabetes mellitus	232 (18.8)	78 (27.8)	79 (32.5)	91 (38.9)
Hypertension	210 (17.0)	60 (21.4)	50 (20.6)	59 (25.2)
TID	463 (37.4)	77 (27.4)	63 (25.9)	48 (20.5)
Glomerulonephritis	6 (0.5)	6 (2.1)	1 (0.4)	0 (0.0)
PKD	252 (20.4)	41 (14.6)	31 (12.8)	21 (9.0)
Others	74 (6.0)	19 (6.8)	19 (7.8)	15 (6.4)
Smoking status					<0.001
Non-smoker	666 (53.8)	125 (44.5)	163 (67.1)	128 (54.7)
Current smoker	210 (17.0)	47 (16.7)	19 (7.8)	40 (17.1)
Ex-smoker	361 (29.2)	109 (38.8)	61 (25.1)	66 (28.2)
Medication					<0.001
Antiplatelets/anticoagulants	319 (25.8)	86 (30.6)	76 (31.3)	88 (37.6)	0.001
ACEi/ARBs	1,057 (85.4)	241 (85.8)	199 (81.9)	210 (89.7)	0.11
Diuretics	303 (24.5)	99 (35.2)	103 (42.4)	108 (46.2)	<0.001
Lipid-lowering agents	608 (49.1)	166 (59.1)	131 (53.9)	144 (61.5)	<0.001
Body mass index (kg/m²)	24.251 ± 3.390	24.958 ± 3.539	24.813 ± 3.214	25.426 ± 3.574	<0.001
SBP (mmHg)	126.015 ± 15.429	127.317 ± 15.587	131.132 ± 16.614	134.432 ± 18.808	<0.001
DBP (mmHg)	76.950 ± 10.687	77.074 ± 10.743	76.886 ± 11.816	77.160 ± 12.737	0.99
Laboratory findings
Hemoglobin (g/dL)	13.087 ± 1.946	13.287 ± 2.083	11.950 ± 1.836	12.168 ± 2.053	<0.001
Albumin (g/dL)	4.208 ± 0.398	4.232 ± 0.440	4.081 ± 0.390	4.113 ± 0.456	<0.001
Total cholesterol (mg/dL)	174.916 ± 38.912	174.676 ± 43.061	174.419 ± 34.255	173.416 ± 38.217	0.96
LDL-C (mg/dL)	97.833 ± 32.086	98.036 ± 35.072	95.089 ± 27.051	94.917 ± 30.145	0.34
HDL-C (mg/dL)	50.584 ± 15.960	47.258 ± 13.216	48.790 ± 15.821	46.465 ± 14.415	<0.001
Triglycerides (mg/dL)	151.247 ± 90.862	165.332 ± 106.356	166.376 ± 107.596	169.921 ± 113.606	0.01
Fasting glucose (mg/dL)	107.318 ± 33.846	113.893 ± 39.829	111.088 ± 43.236	116.575 ± 49.953	0.005
25(OH)D (ng/mL)	17.991 ± 7.382	18.093 ± 8.130	17.613 ± 8.143	16.603 ± 9.862	0.21
hs-CRP (mg/dL)	0.540 (0.020–68.000)	0.705 (0.100–47.200)	0.755 (0.030–31.100)	0.800 (0.050–44.200)	<0.001
Creatinine (mg/dL)	1.674 ± 1.042	1.746 ± 0.932	1.985 ± 1.132	2.268 ± 1.472	<0.001
eGFR (mL/min./1.73 m²)	55.249 ± 31.168	49.702 ± 26.810	42.048 ± 27.709	39.900 ± 27.491	<0.001
Spot urine ACR (mg/g)	281.028 (0.698–11,204.430)	281.464 (1.199–7,385.296)	532.553 (1.432–12,586.840)	681.154 (3.280–10,099.950)	<0.001
CKD stages					<0.001
Stage 1	270 (20.8)	35 (11.3)	26 (9.5)	19 (7.2)
Stage 2	275 (21.2)	60 (19.4)	40 (14.7)	33 (12.5)
Stage 3a	219 (16.9)	60 (19.4)	34 (12.5)	35 (13.3)
Stage 3b	257 (19.8)	80 (25.9)	59 (21.6)	57 (21.7)
Stage 4	220 (16.9)	59 (19.1)	91 (33.3)	86 (32.7)
Stage 5	58 (4.5)	15 (4.9)	23 (8.4)	33 (12.5)

LVG pattern	Events, n (%)	Model 1^a		Model 2^b		Model 3^c		Model 4^d
LVG pattern	Events, n (%)	OR (95% CI)	p-value	OR (95% CI)	p-value	OR (95% CI)	p-value	OR (95% CI)	p-value
Normal	33 (2.6)	Reference		Reference		Reference		Reference
Concentric remodeling	21 (7.2)	3.42 (1.90–6.15)	<0.001	2.59 (1.42–4.72)	0.002	2.53 (1.33–4.83)	0.005	2.53 (1.32–4.85)	0.005
Eccentric LVH	11 (4.4)	2.09 (1.02–4.27)	0.04	1.88 (0.89–3.94)	0.097	1.43 (0.65–3.13)	0.375	1.49 (0.67–3.29)	0.33
Concentric LVH	28 (11.7)	5.61 (3.21–9.83)	<0.001	3.94 (2.20–7.09)	<0.001	2.81 (1.47–5.37)	0.002	2.89 (1.49–5.62)	0.002
LVH (–)	54 (3.5)	Reference		Reference		Reference		Reference
LVH (+)	39 (7.9)	2.58 (1.66–4.02)	<0.001	2.15 (1.34–3.43)	0.001	1.58 (0.94–2.64)	0.085	1.63 (0.96–2.76)	0.07
RWT ≤0.42	45 (3.0)	Reference		Reference		Reference		Reference
RWT >0.42	49 (9.2)	3.71 (2.38–5.76)	<0.001	2.73 (1.73–4.30)	<0.001	2.42 (1.48–3.97)	<0.001	2.43 (1.48–4.00)	<0.001

LVG pattern	Events, n (%)	Model 1^a		Model 2^b		Model 3^c		Model 4^d
LVG pattern	Events, n (%)	OR (95% CI)	p-value	OR (95% CI)	p-value	OR (95% CI)	p-value	OR (95% CI)	p-value
Normal	33 (2.6)	Reference		Reference		Reference		Reference
Concentric remodeling	20 (6.9)	3.23 (1.78–5.86)	<0.001	2.43 (1.33–4.47)	0.004	2.36 (1.23–4.56)	0.01	2.31 (1.19–4.49)	0.01
Eccentric LVH	9 (3.7)	1.76 (0.82–3.80)	0.15	1.59 (0.72–3.52)	0.26	1.31 (0.57–3.04)	0.53	1.36 (0.58–3.20)	0.48
Concentric LVH	27 (11.4)	5.45 (3.09–9.59)	<0.001	3.78 (2.09–6.84)	<0.001	2.73 (1.42–5.26)	0.003	2.73 (1.39–5.38)	0.004
LVH (–)	53 (3.5)	Reference		Reference		Reference		Reference
LVH (+)	35 (7.5)	2.47 (1.57–3.90)	<0.001	2.06 (1.27–3.33)	0.003	1.58 (0.92–2.69)	0.096	1.61 (0.92–2.80)	0.09
RWT ≤0.42	42 (2.8)	Reference		Reference		Reference		Reference
RWT >0.42	47 (8.9)	3.72 (2.37–5.85)	<0.001	2.73 (1.71–4.34)	<0.001	2.38 (1.44–3.94)	0.001	2.33 (1.40–3.88)	0.001

Subgroup	LVG pattern	Events, n (%)	Unadjusted OR (95% CI)	p for interaction	Adjusted OR (95% CI)	p for interaction
Age <60 yr	Normal	10 (1.1)	Reference	0.06	Reference	0.12
	Concentric remodeling	7 (4.2)	4.09 (1.47–10.80)		3.12 (0.92–10.22)
	Eccentric LVH	6 (4.2)	4.02 (1.35–11.01)		4.60 (1.23–16.41)
	Concentric LVH	8 (7.1)	7.03 (2.63–18.22)		2.31 (0.66–7.79)
Age ≥60 yr	Normal	23 (7.0)	Reference		Reference
	Concentric remodeling	14 (11.4)	1.60 (0.76–3.23)		2.02 (0.86–4.07)
	Eccentric LVH	5 (4.6)	0.67 (0.22–1.68)		0.78 (0.23–2.26)
	Concentric LVH	20 (15.7)	2.38 (1.24–4.55)		2.72 (1.19–6.32)
Male sex	Normal	26 (3.3)	Reference	0.45	Reference	0.32
	Concentric remodeling	16 (7.8)	2.40 (1.22–4.57)		2.29 (1.05–4.91)
	Eccentric LVH	8 (8.3)	2.81 (1.16–6.14)		2.35 (0.86–5.95)
	Concentric LVH	22 (16.5)	5.61 (3.03–10.30)		4.03 (1.84–8.84)
Female sex	Normal	7 (1.5)	Reference		Reference
	Concentric remodeling	5 (5.9)	4.05 (1.17–13.01)		2.11 (0.45–9.31)
	Eccentric LVH	3 (1.9)	1.29 (0.28–4.70)		0.70 (0.12–3.33)
	Concentric LVH	6 (5.6)	3.92 (1.24–12.05)		1.25 (0.26–5.80)
BMI <25 kg/m²	Normal	16 (2.1)	Reference	0.12	Reference	0.096
	Concentric remodeling	16 (9.0)	4.82 (2.31–10.02)		4.44 (1.80–11.18)
	Eccentric LVH	6 (4.6)	2.32 (0.82–5.76)		3.13 (0.91–10.00)
	Concentric LVH	11 (9.5)	5.04 (2.22–11.08)		3.61 (1.27–10.14)
BMI ≥25 kg/m²	Normal	17 (3.5)	Reference		Reference
	Concentric remodeling	6 (4.8)	1.17 (0.38–3.02)		0.76 (0.21–2.36)
	Eccentric LVH	5 (4.1)	1.22 (0.39–3.16)		0.89 (0.25–2.81)
	Concentric LVH	17 (13.7)	4.12 (2.00–8.45)		1.89 (0.73–4.89)
eGFR ≥45 mL/min/1.73 m²	Normal	14 (2.0)	Reference	0.75	Reference	0.34
	Concentric remodeling	5 (3.7)	1.91 (0.61–5.10)		1.58 (0.40–5.45)
	Eccentric LVH	3 (3.4)	1.82 (0.41–5.73)		2.11 (0.35–10.39)
	Concentric LVH	7 (9.3)	5.00 (1.84–12.46)		6.31 (1.64–24.24)
eGFR <45 mL/min/1.73 m²	Normal	19 (3.5)	Reference		Reference
	Concentric remodeling	16 (10.4)	3.09 (1.51–6.23)		3.34 (1.43–7.84)
	Eccentric LVH	8 (4.9)	1.45 (0.59–3.28)		1.61 (0.58–4.20)
	Concentric LVH	21 (12.7)	3.98 (2.06–7.70)		2.76 (1.18–6.58)
Spot urine ACR <300 mg/g	Normal	13 (2.1)	Reference	0.83	Reference	0.33
	Concentric remodeling	7 (4.8)	2.42 (0.90–6.03)		3.30 (0.96–11.20)
	Eccentric LVH	3 (3.4)	1.74 (0.39–5.54)		2.05 (0.36–9.46)
	Concentric LVH	8 (11.0)	5.80 (2.22–14.30)		11.14 (2.95–44.46)
Spot urine ACR ≥300 mg/g	Normal	18 (3.1)	Reference		Reference
	Concentric remodeling	14 (10.2)	3.36 (1.57–7.00)		2.12 (0.88–5.01)
	Eccentric LVH	8 (5.1)	1.70 (0.69–3.86)		1.34 (0.49–3.43)
	Concentric LVH	20 (12.5)	4.33 (2.21–8.54)		1.96 (0.84–4.56)