Introduction: Increased left atrial (LA) size is a risk factor for cardiovascular events and all-cause mortality. It is closely related to left ventricular hypertrophy and chronic volume overload, both of which are common in hemodialysis. Calcimimetic treatment with etelcalcetide (ETL) previously showed an inhibitory effect on left ventricular mass index (LVMI) progression in this population. Methods: This is a post hoc analysis of the EtECAR-HD trial, where 62 patients were randomized to ETL or alfacalcidol (ALFA) for 1 year. LA volume index (LAVI) was measured using cardiac magnetic resonance imaging. The aim of the study was to investigate whether ETL was associated with a change of LAVI. Results: Median baseline levels of LAVI were 40 mL/m2 (31, 54 IQR) in the ETL group and 36 mL/m2 (26, 46 IQR) in the ALFA group. In the ITT population, the change of LAVI was 5.0 mL/m2 [95% CI: −0.04, 10] lower under ETL, compared to ALFA (p = 0.052, R2adj = 0.259). In the PP population, the difference in LAVI changes widened to 5.8 [95% CI: 0.36, 11], p = 0.037, R2adj = 0.302). Secondary analysis showed that the study delta of LVMI was correlated with the LAVI delta (r = 0.387) and that an inclusion of LVMI delta in the ANCOVA model mediated the effect on LAVI delta to β = 3.3 [95% CI: −0.04, 10] (p = 0.2, R2adj = 0.323). The same could not be observed for parameters assessing the volume status. Conclusions: The analysis indicates that ETL could inhibit LAVI progression compared with ALFA. This effect was mediated by the change of LVMI.

The enlargement of the left atrium (LA) is an important potential indicator of cardiovascular (CV) complications because it performs three crucial physiological functions that impact the filling and performance of the left ventricle (LV) [1‒4]. These functions include acting as a contractile chamber, collecting pulmonary venous return during LV systole, and as a conduit for the passage of blood from the LA to the LV during early diastole [5, 6]. LA dilation occurs as a result of increased pressure and volume overload and can happen in the setting of both systolic and diastolic dysfunction [7‒9].

Fluid overload and changes in left ventricular mass (LVM) are frequent observed in the dialysis population. These factors significantly contribute to the enlargement of left atrial volume (LAV) [10]. A study conducted by Tripepi et al. [1] revealed that a progressive increase in LAV predicts CV events in dialysis patients, independent of the baseline measurement of LAV and LVM. Similarly, Patel et al. [11, 12] conducted a cardiac magnetic resonance (CMR) imaging study, which demonstrated a link between pretransplant LAV and mortality after transplantation. Furthermore, Kainz et al. [13] showed that LAV independently contributes to the risk of CV death in patients with end-stage kidney disease (ESKD) who undergo kidney transplantation. Moreover, a decrease in LAV following transplantation was associated with a reduced risk of both CV-related mortality and overall mortality [14]. Studies have indicated that the relationship between CV diseases and LA size is more robust when considering LA volume rather than the LA linear dimension [15]. The American Society of Echocardiography recommends utilizing LAV indexed by body surface area (LAVI) to assess the LA size [10, 16].

In our randomized-controlled clinical trial, named “Effect of etelcalcetide on cardiac hypertrophy in hemodialysis patients” (EtECAR-HD), we successfully demonstrated that the calcimimetic etelcalcetide (ETL) has the ability to impede the progression of LVM index (LVMI) when compared to treatment with active vitamin D using alfacalcidol (ALFA) in hemodialysis patients [17, 18]. Although there was a positive correlation observed between LAVI and LVMI, it was found that LAVI exhibited a stronger predictive value for both all-cause and CV mortality in patients undergoing peritoneal dialysis [19]. The objective of this trial was to investigate whether the use of ETL compared to ALFA in patients on maintenance hemodialysis has an effect on LAVI progression within 1 year of treatment.

Study Design and Participants

In this post hoc analysis, we examined data from the ETECAR-HD trial, which was a prospective, randomized, controlled, single-blinded trial. It included 62 subjects diagnosed with secondary hyperparathyroidism (sHPT) who were randomly assigned to receive either intravenous ETL or ALFA treatment for a duration of 1 year. The study design specific have been previously published [17, 18]. All participants provided written informed consent, and the trial received approval from the Ethics Committee of the Medical University of Vienna (MUV; EK # 1127/2017) as well as the national regulatory authorities (AGES # 10087746). The study was conducted in accordance with the principles outlined in the Declaration of Helsinki.

Study Definitions and Outcomes

The primary aim of the study was to evaluate whether ETL medication prevented the progression of LAVI when compared with ALFA in addition to its previously reported inhibitory effect on LVMI in hemodialysis patients [17]. Additionally, as the circulatory overload has a direct association with LAV, a secondary analysis was performed to examine whether different methods of assessing the volume status of hemodialysis patients, such as body composition monitoring (BCM), lung comet tail score (LCTS) through lung ultrasound, and NT-pro-brain-natriuretic peptide (NT-proBNP) measurements, were linked to the progression of LAVI.

LAVI

CMR was conducted at the initiation of the study and after 1 year of treatment, specifically on a nondialysis day during the middle of the week. The calculation of body surface area, which was utilized for determining LAVI, involved using the patients’ body weight on the day the imaging took place.

Body Composition Monitoring

Bioimpedance spectroscopy-based BCM was carried out during the screening phase, and subsequent measurements were taken at 2-month intervals throughout the study prior to the initiation of hemodialysis treatment [20]. Patients who were unable to achieve their target dry weight were excluded from participating in the trial [21].

Lung Ultrasound

During the screening and end phase of the study, lung ultrasound was employed to visualize lung edema. This ultrasonographic visualization, known as the LCTS, is a straightforward and noninvasive method for measuring extravascular lung water. The examination can be conveniently conducted at the patient’s bedside and provides a semiquantitative assessment of lung edema [22‒24]. The LCTS is derived by summing the comet tails observed in four lung segments (mid-clavicular and mid-axillary regions of the left and right hemithorax).

NT-pro-Brain-Natriuretic Peptide

The serum level of NT-proBNP serves as an indicator of myocardial cell distension in response to circulating volume overload [25]. It is primarily stimulated by the stretch of the LA and pressure overload in the LV, leading to the secretion of cardiac peptides [10]. NT-proBNP levels were measured at nine different timepoints throughout the duration of the trial.

Statistical Analysis

We summarized demographic variables and laboratory measurements at study begin in the two study groups ETL and ALFA, using median (IQR) for continuous variables and count (frequency) for categorical variables. To assess if the medication was associated with the change in LAVI throughout the study period, we fitted an ANCOVA model for the delta of LAVI per subject (i.e., LAVI at study end minus LAVI at baseline) with medication as the covariate of interest, adjusted for LAVI at baseline. We conducted this primary analysis for the intention-to-treat (ITT) and the per-protocol (PP) study cohorts. For sensitivity analyses of the primary results, we fitted an ANCOVA model (using ITT data) with additional adjustments for the randomization factors of the original trail (dialysis center and residual kidney function). To check the effect of highly influential data points, we refitted the ITT model with winsorized data, i.e., the clipping of data points below and above predefined quantiles to the quantile values, which we set to the 0.5%/99.5% and 2.5% and 97.5% quantiles in two distinct models.

For the secondary analysis, we included additional covariates for the study deltas (i.e., study end minus study baseline) of LVMI, lung ultrasound, BCM, and NT-proBNP to the main ITT model in four distinct ANCOVA models and compared the regression coefficients and adjusted R2 values of the new models to the primary model. We further depicted scatter plots and reported Pearson correlations between the study delta of LAVI and the four potential mediators. Due to skew distributions, BCM and NT-proBNP entered the models on the log2 scale. Furthermore, for these two markers repeated measurements throughout the study were available. In addition to the adjustments for BCM and NT-proBNP delta – which only used the first and last measurements – we derived estimates for the change of these markers over time per study participants. This was achieved via linear mixed-effects regression models with a fixed effect for time since baseline and a random intercept and slope per subject. We defined the change of BCM and NT-proBNP as the sum of the fixed and random slope effect. These estimates of parameter change over time were then used as an adjustment in two ANCOVA models, which were again compared to the primary model.

For all regression models, we checked the model assumptions via visual assessments of outcome distributions and residual analyses (histograms, qq-plots). We reported regression coefficients with 95% confidence intervals and respective p values at a significance level of 95%. For the ANCOVA models, we further calculated adjusted R2 in order to compare models. All p values are of exploratory nature; hence, we did not correct them for multiple testing. Since this is a post hoc subanalysis, the sample size was determined by the sample size of the original trial.

This post hoc analysis comprised 62 ITT patients included in the original study, of which 32 were treated with ETL and 30 with ALFA. When reduced to participants where the study protocol was followed (PP), 10 patients had to be excluded, five in each treatment group (6 patients received a kidney transplant, 3 patients died, and 1 patient discontinued hemodialysis due to renal recovery).

Table 1 shows the baseline characteristics of patients in the two medication groups, ETL and ALFA, using the ITT cohort. The study cohort was well balanced regarding all considered parameters, which included demographics, randomization factors, comorbidities, CMR parameters, and volume status assessments.

Table 1.

Patient characteristics at baseline by study medication

CharacteristicETL, N = 32ALFA, N = 30
Sex, n (%) 
 Female 10 (31) 6 (20) 
 Male 22 (69) 24 (80) 
Age, years 66 (53, 71) 62 (54, 66) 
Dialysis vintage, months 11 (4, 19) 12 (5, 23) 
Randomization factors, n (%) 
Site identifier   
 MUW 10 (31) 10 (33) 
 WDZ 22 (69) 20 (67) 
Residual kidney function, n (%) 
 ≤500 mL/d 6 (19) 6 (20) 
 >500 mL/d 26 (81) 24 (80) 
Comorbidities, n (%) 
 Diabetes 14 (44) 12 (40) 
 Hypertension 32 (100) 29 (97) 
 Hyperlipidemia 15 (47) 14 (47) 
 Peripheral vascular disease 7 (22) 6 (20) 
 Coronary artery disease 18 (56) 20 (67) 
Baseline CMR parameters 
 LAVI 40 (31, 54) 36 (26, 46) 
 LVMI 69 (59, 84) 70 (64, 85) 
Baseline assessment of volume status 
 LCTS 0.25 (0.00, 0.50) 0.25 (0.00, 0.69) 
 BCM 2.35 (1.73, 4.52) 2.30 (1.00, 4.53) 
 NT-proBNP 413 (192, 1,896) 702 (190, 2,426) 
CharacteristicETL, N = 32ALFA, N = 30
Sex, n (%) 
 Female 10 (31) 6 (20) 
 Male 22 (69) 24 (80) 
Age, years 66 (53, 71) 62 (54, 66) 
Dialysis vintage, months 11 (4, 19) 12 (5, 23) 
Randomization factors, n (%) 
Site identifier   
 MUW 10 (31) 10 (33) 
 WDZ 22 (69) 20 (67) 
Residual kidney function, n (%) 
 ≤500 mL/d 6 (19) 6 (20) 
 >500 mL/d 26 (81) 24 (80) 
Comorbidities, n (%) 
 Diabetes 14 (44) 12 (40) 
 Hypertension 32 (100) 29 (97) 
 Hyperlipidemia 15 (47) 14 (47) 
 Peripheral vascular disease 7 (22) 6 (20) 
 Coronary artery disease 18 (56) 20 (67) 
Baseline CMR parameters 
 LAVI 40 (31, 54) 36 (26, 46) 
 LVMI 69 (59, 84) 70 (64, 85) 
Baseline assessment of volume status 
 LCTS 0.25 (0.00, 0.50) 0.25 (0.00, 0.69) 
 BCM 2.35 (1.73, 4.52) 2.30 (1.00, 4.53) 
 NT-proBNP 413 (192, 1,896) 702 (190, 2,426) 

Median (IQR) for continuous and count (percentage) for categorical variables. ALFA, alfacalcidol; BCM, body composition monitoring; ETL, etelcalcetide; LAVI, left atrial volume index; LCTS, lung comet tail score; LVMI, left ventricular mass index; MUW, Medical University of Vienna; WDZ, Vienna Dialysis Center.

Figure 1 depicts the absolute LAVI levels at baseline and study end in the two treatment arms (Fig. 1a) and compares the LAVI deltas, i.e., the difference in LAVI between baseline and study end, by medication (Fig. 1b). The boxplots indicate that LAVI tended to increase throughout the study in patients treated with ALFA, but not when treated with ETL. Table 2 summarizes ITT and PP ANCOVA models for the LAVI delta by medication, with adjustment for baseline LAVI. In line with Figure 1, we observed a trend toward an effect of ETL versus ALFA treatment on LAVI delta (β = −5.0 [95% CI: −10, 0.04], p = 0.052) in the ITT population. This effect became numerically/statistically significant in the PP cohort (β = −5.8 [95% CI: −11, −0.36], p = 0.037). The adjusted R2 in the ITT model was Radj2 = 0.259, which is increased to Radj2 = 0.302 using PP data. These results were very similar in the conducted sensitivity analyses (additional adjustments for randomization factors, winsorized data). At baseline, the percentage of cases with LAVI values below the mean was similar between the two treatment groups. At the follow-up, the disparity increased, with the ETL group demonstrating an 11% higher proportion of patients presenting LAVI values below the mean compared to the ALFA group.

Fig. 1.

LAVI change from baseline to study end LAVI at baseline and study end in the two study groups (a) and delta of LAVI from study baseline to study end, by medication (b). ALFA, alfacalcidol; ETL, etelcalcetide; LAVI, left atrial volume index. The dashed line in (a) indicates the upper range of normal of LAVI according to the American Society of Echocardiography’s Guidelines for chamber quantification [26].

Fig. 1.

LAVI change from baseline to study end LAVI at baseline and study end in the two study groups (a) and delta of LAVI from study baseline to study end, by medication (b). ALFA, alfacalcidol; ETL, etelcalcetide; LAVI, left atrial volume index. The dashed line in (a) indicates the upper range of normal of LAVI according to the American Society of Echocardiography’s Guidelines for chamber quantification [26].

Close modal
Table 2.

ANCOVA models of study delta of LAVI

ITTPP
Beta95% CIp valueBeta95% CIp value
Medication   0.052   0.037 
 ALFA — —  — —  
 ETL −5.0 −10, 0.04  −5.8 −11, −0.36  
LAVI at baseline −0.29 −0.44, −0.15 <0.001 −0.33 −0.49, −0.17 <0.001 
Adjusted R2 0.259   0.302   
ITTPP
Beta95% CIp valueBeta95% CIp value
Medication   0.052   0.037 
 ALFA — —  — —  
 ETL −5.0 −10, 0.04  −5.8 −11, −0.36  
LAVI at baseline −0.29 −0.44, −0.15 <0.001 −0.33 −0.49, −0.17 <0.001 
Adjusted R2 0.259   0.302   

Models adjusted for LAVI at baseline; distinct models for ITT and PP study population; in the latter, n = 10 subjects were excluded. ALFA, alfacalcidol; ETL, etelcalcetide; LAVI, left atrial volume index; NT-proBNP, N-terminal prohormone brain natriuretic peptide.

Scatterplots of the study delta of LAVI versus the deltas of LVMI, LCTS, BCM, and NT-proBNP and pairwise Pearson correlations (Fig. 2) showed that from the four variables, only the delta in LVMI indicated a positive correlation (r = 0.387) with LAVI delta. Table 3 summarizes ANCOVA models incorporating additional adjustments for the study deltas of LVMI, LCTS, BCM, and NT-proBNP, in order to compare these models to the main ITT ANCOVA model from Table 2. In a close relationship with the correlations, out of the four variables we considered, only the inclusion of LVMI delta substantially changed the medication effect, which decreased from β = −5.0 [95% CI: −10, 0.04] to β = −3.3 [95% CI: −8.3, 1.7]. The increase in adjusted R2 from 0.259 to 0.323 and the decreased significance (p = 0.052 vs. p = 0.2) when the LAVI delta is in included in the ANCOVA model, in addition to the positive correlation between LAVI delta and LVMI delta, suggest that the treatment effect on LAVI could be mediated by LVMI. For the other three variables, no such observation could be made, as correlations were close to zero and the effect estimates as well as adjusted R2 values did not change substantially. With BCM and NT-proBNP, we also calculated models adjusting for variable change over time, derived from a linear mixed-effects model in order to facilitate all data available. However, the differences between the models with adjustment for the study delta and adjustment for the derived change parameter were very small.

Fig. 2.

Association of LAVI delta with LVMI and parameters of volume assessment. Scatterplots of LAVI delta versus delta of LVMI, LCTS, BCM, and NT-proBNP, with linear regression line and Pearson correlation. BCM: body composition monitoring; LAVI, left atrial volume index; LCTS, lung comet tail score; LVMI, left ventricular mass index; NT-proBNP, N-terminal prohormone brain natriuretic peptide.

Fig. 2.

Association of LAVI delta with LVMI and parameters of volume assessment. Scatterplots of LAVI delta versus delta of LVMI, LCTS, BCM, and NT-proBNP, with linear regression line and Pearson correlation. BCM: body composition monitoring; LAVI, left atrial volume index; LCTS, lung comet tail score; LVMI, left ventricular mass index; NT-proBNP, N-terminal prohormone brain natriuretic peptide.

Close modal
Table 3.

ANCOVA models for LAVI delta

Beta95% CIp valueBeta95% CIp value
LVMIMain + LVMI delta
Medication   0.2    
 ALFA — —     
 ETL −3.3 −8.3, 1.7     
LAVI at baseline −0.27 −0.41, −0.13 <0.001    
LVMI delta 0.27 0.05, 0.48 0.016    
Adjusted R2 0.323      
Beta95% CIp valueBeta95% CIp value
LVMIMain + LVMI delta
Medication   0.2    
 ALFA — —     
 ETL −3.3 −8.3, 1.7     
LAVI at baseline −0.27 −0.41, −0.13 <0.001    
LVMI delta 0.27 0.05, 0.48 0.016    
Adjusted R2 0.323      
LCTSMain + LCTS delta
Medication   0.055    
 ALFA — —     
 ETL −5.0 −10, 0.11     
LAVI at baseline −0.30 −0.45, −0.15 <0.001    
LCTS delta 0.93 −4.1, 6.0 0.7    
Adjusted R2 0.248      
LCTSMain + LCTS delta
Medication   0.055    
 ALFA — —     
 ETL −5.0 −10, 0.11     
LAVI at baseline −0.30 −0.45, −0.15 <0.001    
LCTS delta 0.93 −4.1, 6.0 0.7    
Adjusted R2 0.248      
BCMMain + BCM deltaMain + BCM change
Medication   0.010   0.010 
 ALFA — —  — —  
 ETL −6.7 −12, −1.7  −6.6 −12, −1.7  
LAVI at baseline −0.19 −0.39, 0.00 0.049 −0.19 −0.39, 0.00 0.054 
BCM at baseline −0.03 −1.2, 1.1 >0.9    
BCM delta    0.04 −15, 15 >0.9 
Adjusted R2 0.226   0.226   
BCMMain + BCM deltaMain + BCM change
Medication   0.010   0.010 
 ALFA — —  — —  
 ETL −6.7 −12, −1.7  −6.6 −12, −1.7  
LAVI at baseline −0.19 −0.39, 0.00 0.049 −0.19 −0.39, 0.00 0.054 
BCM at baseline −0.03 −1.2, 1.1 >0.9    
BCM delta    0.04 −15, 15 >0.9 
Adjusted R2 0.226   0.226   
NT-proBNPMain + NT-proBNP deltaMain + NT-proBNP change
Medication   0.062   0.049 
 ALFA — —  — —  
 ETL −4.8 −9.8, 0.24  −5.1 −10, −0.03  
LAVI at baseline −0.32 −0.47, −0.17 <0.001 −0.29 −0.44, −0.15 <0.001 
NT-proBNP delta 0.00 0.00, 0.00 0.3    
NT-proBNP change    0.69 −0.59, 2.0 0.3 
Adjusted R2 0.264   0.262   
NT-proBNPMain + NT-proBNP deltaMain + NT-proBNP change
Medication   0.062   0.049 
 ALFA — —  — —  
 ETL −4.8 −9.8, 0.24  −5.1 −10, −0.03  
LAVI at baseline −0.32 −0.47, −0.17 <0.001 −0.29 −0.44, −0.15 <0.001 
NT-proBNP delta 0.00 0.00, 0.00 0.3    
NT-proBNP change    0.69 −0.59, 2.0 0.3 
Adjusted R2 0.264   0.262   

Models with additional adjustments for LVMI, LCTS, BCM, and NT-proBNP; the main model refers to the ITT model from Table 2, which had an adjusted R2 = 0.259; delta denotes the difference between the study end and the baseline value; change denotes the change of the variable over time, derived from a linear mixed model for the respective variables; BCM and NT-proBNP entered all models on a log2 scale. ALFA, alfacalcidol; BCM, body composition monitoring; ETL, etelcalcetide; LAVI, left atrial volume index; LCTS, lung comet tail score; LVMI, left ventricular mass index; MUW, Medical University of Vienna; NT-proBNP, N-terminal prohormone brain natriuretic peptide; WDZ, Vienna Dialysis Center.

The findings of this study indicate that the use of ETL in patients undergoing maintenance hemodialysis effectively halts the progression of LA enlargement when compared to the current standard therapy for sHPT, ALFA. This preventive effect on LA enlargement can be attributed to the impact of ETL on reducing left ventricular hypertrophy.

Elevated LAVI is recognized as an independent risk factor for all-cause mortality, both in the general population and among hemodialysis patients. There exists a notable inverse correlation between renal function and LAV, indicating that LAV tends to increase as the renal function declines [6]. Furthermore, LAV is considerably higher in dialysis patients compared to healthy individuals of similar age and gender [27]. LAVI exceeding 28 mL/m2 is classified as an increased level, mild being 29–33 mL/m2, moderate being 34–39 mL/m2, and severe being ≥40 mL/m2 [26]. In line with this classification, the hemodialysis population included in this trial exhibited significantly elevated LAVI levels at baseline, and these levels further increased under ALFA medication, but not with ETL.

In our previous findings, we demonstrated that ETL treatment effectively prevented the progression of LVMI in this specific study cohort. Furthermore, we suggested that fibroblast growth factor 23-mediated cardiac hypertrophy may be the underlying mechanism [17, 28]. In this subanalysis, we were able to establish a correlation between the impact of the study medication on LAVI and the changes observed in LVMI. These results align with the previous data, indicating a close relationship between LA size and LVM, with LV hypertrophy being a significant factor contributing to LAV, particularly among hemodialysis patients [29‒32]. Both LAVI and LVMI are critical parameters utilized in the diagnosis of heart failure, a highly prevalent CV condition across all stages of chronic kidney disease [33, 34].

Studies have demonstrated that reductions in LAVI can be achieved through improved blood pressure control and as a result of heart valve surgery. Notably, both interventions also lead to a decrease in LVMI [35‒38]. The association between reductions in LV hypertrophy achieved through blood pressure therapy and decreases in LAV was demonstrated, highlighting the interconnection between these two parameters [39]. Previous reports indicated that in the population of ESKD, LAV exhibits a comparable prognostic significance to LVMI. Importantly, LAV maintains an independent association with the occurrence of CV events [29]. The predictive value of both parameters is significantly influenced by the presence of confounding risk factors, such as hypertension or obesity, which can contribute to their complexity [4]. In individuals with ESKD, it has been shown that kidney transplantation can lead to improvements in LAVI, primarily due to alterations in hemodynamic conditions [40, 41]. However, there is a scarcity of data regarding the effectiveness of medication used for treating sHPT on LAV in individuals undergoing maintenance hemodialysis.

A post hoc analysis from the PRIMO study demonstrated that treatment with paricalcitol was associated with a decrease in LAVI [42]. This finding appears to contrast with our study results, considering that both paricalcitol and ALFA are active vitamin D medications used for treating sHPT in hemodialysis patients. However, it is important to note that the PRIMO trial included patients with a glomerular filtration rate between 15 and 60 mL/min/1.73 m2, which differs from our study cohort consisting of ESKD patients [43].

Gaining insights into the mechanistic distinctions between vitamin D and calcimimetic therapy is crucial, as the latter drug may exhibit pleiotropic effects. The decline in kidney function leads to alterations in vitamin D metabolism, resulting in decreased levels of calcitriol, which subsequently leads to lowered serum calcium levels and impaired phosphate excretion [44]. SHPT emerges as an adaptive process in response to these dysregulations. Vitamin D and calcimimetics are commonly employed treatment options for sHPT [45]. Vitamin D treatment aims to address the deficiency of calcitriol by enhancing the intestinal reabsorption of calcium and phosphate, consequently suppressing PTH synthesis [46]. However, calcimimetics interact with the calcium-sensing receptor in the parathyroid gland, heightening its sensitivity to circulating calcium levels, thereby reducing PTH and fibroblast growth factor 23 concentrations [47].

Volume overload is a significant contributing factor to the enlargement of the LA cavity, particularly in the context of hemodialysis [48]. However, in this study, commonly utilized methods for assessing volume status, such as BCM, lung ultrasound, and measurements of NT-proBNP, did not show an association with changes in LAVI. The primary focus of this trial was to detect the treatment effect on LVMI. To minimize confounding factors, the study population underwent careful screening for overhydration, and only patients who achieved and maintained their individual optimal dry weight at the end of dialysis were included [18]. This approach aimed to mitigate the impact of fluid overload, which is a significant risk factor for increased LVM. Moreover, the volume status was continuously evaluated during the trial, and if hypervolemia was detected, adjustments to the dry weight were made based on clinical judgment and standard of care practices.

The trial has certain limitations that should be acknowledged. These include a relatively short duration of treatment and observation to detect changes in cardiac remodeling. Another limitation is the small sample size that was originally designed to assess a different outcome parameter. The analysis revealed a more pronounced impact of the medication on LAVI in the PP analysis compared to the ITT analysis, indicating that a longer duration of treatment may potentially enhance the observed effect. Furthermore, enhancing the informative value of the study could be achieved by crossing the two treatment groups after the initial year and conducting a reevaluation at the end.

The trial possessed several notable strengths. These included its prospective and randomized design, the administration of intravenous medication rather than oral treatment, and the utilization of CMR as the imaging modality. CMR holds significant importance, as the previous studies have demonstrated that echocardiography tends to underestimate atrial volumes when compared to CMR imaging [49]. CMR is a well-established technique for evaluating cardiac deformation, as it provides excellent delineation of endocardial and epicardial borders [50, 51].

In conclusion, our findings suggest that ETL treatment in hemodialysis patients effectively halted the progression of LAVI when compared to ALFA. This effect may be attributed to the associated changes in LVMI resulting from the treatment. Considering that both LA size and LVM are well-known CV risk factors, it is reasonable to speculate that preventing cardiac dilation could potentially alleviate the substantial burden of CV mortality in this population.

We thank the nursing staff of the General Hospital of Vienna and Vienna Dialysis Center for their assistance in the blood sample collections from subjects. We also thank the medical assistants of the Department of Cardiovascular and Interventional Radiology (Medical University of Vienna) and the lab technicians of the Department of Laboratory Medicine (Medical University of Vienna) for their assistance in study procedures.

Subjects have given their written informed consent and the trial was approved by the Ethics Committee of the Medical University of Vienna (MUV; EK # 1127/2017) and the national regulatory authorities (AGES # 10087746) and conducted in accordance with the principles of the Declaration of Helsinki.

Dr. Dörr and Dr. Reindl-Schwaighofer have a patent “Methods of treating left ventricle hypertrophy” pending. The other authors have nothing to disclose.

The study was sponsored by the Medical University of Vienna and by an unrestricted investigator-initiated research grant from Amgen (IIP #20167811).

Katharina Dörr and Roman Reindl-Schwaighofer were responsible for the conceptualization and methodology of the trial. Katharina Dörr was tasked with the investigation, including data collection, with the support by Matthias Lorenz. Sebastian Hödlmoser was assigned with the formal analysis and software. Dietrich Beitzke was the blinded radiologist, performing the analysis of CMR data. Rodrig Marculescu was responsible for laboratory analysis. Writing of the original draft was performed by Katharina Dörr and reviewed and edited by the coauthors.

Additional Information

The trial registration URL: https://clinicaltrials.gov/ct2/show/NCT03182699. Unique identifier: NCT03182699.

The data underlying this article will be shared on reasonable request to the corresponding author.

1.
Tripepi
G
,
Benedetto
FA
,
Mallamaci
F
,
Tripepi
R
,
Malatino
L
,
Zoccali
C
.
Left atrial volume monitoring and cardiovascular risk in patients with end-stage renal disease: a prospective cohort study
.
J Am Soc Nephrol
.
2007
;
18
:
1316
22
.
2.
Chen
SC
,
Chang
JM
,
Tsai
YC
,
Huang
JC
,
Su
HM
,
Hwang
SJ
.
Left atrial diameter and albumin with renal outcomes in chronic kidney disease
.
Int J Med Sci
.
2013
;
10
:
575
84
.
3.
Bouzas-Mosquera
A
,
Broullón
FJ
,
Álvarez-García
N
,
Méndez
E
,
Peteiro
J
,
Gándara-Sambade
T
.
Left atrial size and risk for all-cause mortality and ischemic stroke
.
Can Med Assoc J
.
2011
183
E657
64
.
4.
Patel
DA
,
Lavie
CJ
,
Milani
RV
,
Ventura
HO
.
Left atrial volume index predictive of mortality independent of left ventricular geometry in a large clinical cohort with preserved ejection fraction
.
Mayo Clin Proc
.
2011
;
86
:
730
7
.
5.
Leung
DY
,
Boyd
A
,
Ng
AA
,
Chi
C
,
Thomas
L
.
Echocardiographic evaluation of left atrial size and function: current understanding, pathophysiologic correlates, and prognostic implications
.
Am Heart J
.
2008
;
156
:
1056
64
.
6.
Shizuku
J
,
Yamashita
T
,
Ohba
T
,
Kabaya
T
,
Nitta
K
.
Left atrial volume is an independent predictor of all-cause mortality in chronic hemodialysis patients
.
Intern Med
.
2012
;
51
:
1479
85
.
7.
Pritchett
AM
,
Mahoney
DW
,
Jacobsen
SJ
,
Rodeheffer
RJ
,
Karon
BL
,
Redfield
MM
.
Diastolic dysfunction and left atrial volume: a population-based study
.
J Am Coll Cardiol
.
2005
;
45
(
1
):
87
92
.
8.
Appleton
CP
,
Galloway
JM
,
Gonzalez
MS
,
Gaballa
M
,
Basnight
MA
.
Estimation of left ventricular filling pressures using two-dimensional and doppler echocardiography in adult patients with cardiac disease. Additional value of analyzing left atrial size, left atrial ejection fraction and the difference in duration of pulmonary venous and mitral flow velocity at atrial contraction
.
J Am Coll Cardiol
.
1993
;
22
(
7
):
1972
82
.
9.
Tsang
TS
,
Barnes
ME
,
Gersh
BJ
,
Bailey
KR
,
Seward
JB
.
Left atrial volume as a morphophysiologic expression of left ventricular diastolic dysfunction and relation to cardiovascular risk burden
.
Am J Cardiol
.
2002
;
90
(
12
):
1284
9
.
10.
Møller
JE
,
Hillis
GS
,
Oh
JK
,
Seward
JB
,
Reeder
GS
,
Wright
RS
.
Left atrial volume a powerful predictor of survival after acute myocardial infarction
.
Circulation
.
2003
;
107
(
17
):
2207
12
.
11.
Patel
RK
,
Pennington
C
,
Stevens
KK
,
Taylor
A
,
Gillis
K
,
Rutherford
E
.
Effect of left atrial and ventricular abnormalities on renal transplant recipient outcome — a single-center study
.
Transpl Res
.
2014
;
3
:
20
.
12.
Patel
RK
,
Jardine
AGM
,
Mark
PB
,
Cunningham
AF
,
Steedman
T
,
Powell
JR
.
Association of left atrial volume with mortality among ESRD patients with left ventricular hypertrophy referred for kidney transplantation
.
Am J Kidney Dis
.
2010
;
55
:
1088
96
.
13.
Kainz
A
,
Goliasch
G
,
Wiesbauer
F
,
Binder
T
,
Maurer
G
,
Nesser
HJ
.
Left atrial diameter and survival among renal allograft recipients
.
Clin J Am Soc Nephrol
.
2013
;
8
:
2100
5
.
14.
Regele
F
,
Kainz
A
,
Kammer
M
,
Beer
A
,
Steringer-Mascherbauer
R
,
Binder
T
.
Regression of left atrial diameter after kidney transplantation is associated with prolonged survival: an observational study
.
Transpl Int
.
2018
;
31
(
9
):
999
1007
.
15.
Tsang
TS
,
Abhayaratna
WP
,
Barnes
ME
,
Miyasaka
Y
,
Gersh
BJ
,
Bailey
KR
.
Prediction of cardiovascular outcomes with left atrial size: is volume superior to area or diameter
.
J Am Coll Cardiol
.
2006
;
47
:
1018
23
.
16.
Ristow
B
,
Ali
S
,
Whooley
MA
,
Schiller
NB
.
Usefulness of left atrial volume index to predict heart failure hospitalization and mortality in ambulatory patients with coronary heart disease and comparison to left ventricular ejection fraction (from the heart and soul study)
.
Am J Cardiol
.
2008
;
102
:
70
6
.
17.
Dörr
K
,
Kammer
M
,
Reindl-Schwaighofer
R
,
Lorenz
M
,
Prikoszovich
T
,
Marculescu
R
.
Randomized trial of etelcalcetide for cardiac hypertrophy in hemodialysis
.
Circ Res
.
2021
;
128
:
1616
25
.
18.
Dörr
K
,
Kammer
M
,
Reindl-Schwaighofer
R
,
Lorenz
M
,
Loewe
C
,
Marculescu
R
.
Effect of etelcalcetide on cardiac hypertrophy in hemodialysis patients: a randomized controlled trial (ETECAR-HD)
.
Trials
.
2019
;
20
(
1
):
601
.
19.
Kim
SJ
,
Han
SH
,
Park
JT
,
Kim
JK
,
Oh
HJ
,
Yoo
DE
.
Left atrial volume is an independent predictor of mortality in CAPD patients
.
Nephrol Dial Transpl
.
2011
;
26
:
3732
9
.
20.
Koell
B
,
Zotter-Tufaro
C
,
Duca
F
,
Kammerlander
AA
,
Aschauer
S
,
Dalos
D
.
Fluid status and outcome in patients with heart failure and preserved ejection fraction
.
Int J Cardiol
.
2017
;
230
:
476
81
.
21.
Jaeger
JQ
,
Mehta
RL
.
Assessment of dry weight in hemodialysis: an overview
.
J Am Soc Nephrol
.
1999
;
10
:
392
403
.
22.
Jambrik
Z
,
Monti
SPE
,
Coppola
V
,
Agricola
E
,
Mottola
G
,
Miniati
M
.
Usefulness of ultrasound lung comets as a nonradiologic sign of extravascular lung water
.
Am J Cardiol
.
2004
;
93
(
10
):
1265
70
.
23.
Picano
E
,
Frassi
FMG
,
Agricola
E
,
Gligorova
S
,
Gargani
L
,
Mottola
G
.
Ultrasound lung comets: a clinically useful sign of extravascular lung water
.
J Am Soc Echocardiogr
.
2006
;
19
(
3
):
356
63
.
24.
Agricola
E
,
Bove
TPE
,
Oppizzi
M
,
Marino
G
,
Zangrillo
A
,
Margonato
A
.
Ultrasound comet-tail images”: a marker of pulmonary edema, A comparative study with wedge pressure and extravascular lung water
.
Chest
.
2005
;
127
(
5
):
1690
5
.
25.
Giannese
D
,
Puntoni
A
,
Cupisti
A
,
Morganti
R
,
Varricchio
E
,
D’Alessandro
C
.
Lung ultrasound and BNP to detect hidden pulmonary congestion in euvolemic hemodialysis patients: a single centre experience
.
BMC Nephrol
.
2021
;
22
:
36
.
26.
Lang
RM
,
Bierig
M
,
Devereux
RB
,
Flachskampf
FA
,
Foster
E
,
Pellikka
PA
.
Recommendations for chamber quantification: a report from the American society of echocardiography’s Guidelines and standards committee and the chamber quantification writing group, developed in conjunction with the European association of echocardiography, a branch of the European society of cardiology
.
J Am Soc Echocardiogr
.
2005
;
18
:
1440
63
.
27.
Bokhari
SR
,
Mansur
A
,
Khan Assir
MZ
,
Ittifaq
A
,
Sarwar
S
.
Echocardiographic evaluation of left atrial volume index in patients with chronic kidney disease
.
Saudi J Kidney Dis Transpl
.
2020
;
31
(
4
):
750
8
.
28.
Grabner
A
,
Amaral
AP
,
Schramm
K
,
Singh
S
,
Sloan
A
,
Yanucil
C
.
Activation of cardiac fibroblast growth factor receptor 4 causes left ventricular hypertrophy
.
Cell Metab
.
2015
;
22
(
6
):
1020
32
.
29.
Tripepi
G
,
Benedetto
FA
,
Mallamaci
F
,
Tripepi
R
,
Malatino
L
,
Zoccali
C
.
Left atrial volume in end-stage renal disease: a prospective cohort study
.
J Hypertens
.
2006
;
24
:
1173
80
.
30.
Tsioufis
C
,
Taxiarchou
E
,
Syrseloudis
D
,
Chatzis
D
,
Tsiachris
D
,
Chatzistamatiou
E
.
Left ventricular mass but not geometry determines left atrial size in the early stages of hypertension
.
J Hum Hypertens
.
2009
;
23
:
674
9
.
31.
Laukkanen
JA
,
Kurl
S
,
Eränen
J
,
Huttunen
M
,
Salonen
JT
.
Left atrium size and the risk of cardiovascular death in middle-aged men
.
Arch Intern Med
.
2005
;
165
:
1788
93
.
32.
Gerdts
E
,
Oikarinen
L
,
Palmieri
V
,
Otterstad
JE
,
Wachtell
K
,
Boman
K
.
Correlates of left atrial size in hypertensive patients with left ventricular hypertrophy: the Losartan Intervention for Endpoint Reduction in Hypertension (LIFE) Study
.
Hypertension
.
2002
;
39
:
739
43
.
33.
Gehlken
C
,
Screever
EM
,
Suthahar
N
,
van der Meer
P
,
Westenbrink
BD
,
Coster
JE
.
Left atrial volume and left ventricular mass indices in heart failure with preserved and reduced ejection fraction
.
ESC Hear Fail
.
2021
;
8
(
4
):
2458
66
.
34.
Ravera
M
,
Rosa
GM
,
Fontanive
P
,
Bussalino
E
,
Dorighi
U
,
Picciotto
D
.
Impaired left ventricular global longitudinal strain among patients with chronic kidney disease and end-stage renal disease and renal transplant recipients
.
Cardiorenal Med
.
2019
;
9
(
1
):
61
8
.
35.
Thomas
LAW
,
Abhayaratna
WP
.
Left atrial reverse remodeling: mechanisms, evaluation, and clinical significance
.
JACC Cardiovasc Imaging
.
2017
;
10
:
65
77
.
36.
Hatani
T
,
Kitai
T
,
Murai
R
,
Kim
K
,
Ehara
N
,
Kobori
A
.
Associations of residual left ventricular and left atrial remodeling with clinical outcomes in patients after aortic valve replacement for severe aortic stenosis
.
J Cardiol
.
2016
;
68
:
241
7
.
37.
Kühl
HP
,
Franke
A
,
Puschmann
D
,
Schöndube
FA
,
Hoffmann
R
,
Hanrath
P
.
Regression of left ventricular mass one year after aortic valve replacement for pure severe aortic stenosis
.
Am J Cardiol
.
2002
;
89
:
408
13
.
38.
Fagard
RH
,
Celis
H
,
Thijs
L
,
Wouters
S
.
Regression of left ventricular mass by antihypertensive treatment a meta-analysis of randomized comparative studies
.
Hypertension
.
2009
;
54
(
5
):
1084
91
.
39.
Mattioli
AV
,
Bonatti
S
,
Monopoli
D
,
Zennaro
M
,
Mattioli
G
.
Influence of regression of left ventricular hypertrophy on left atrial size and function in patients with moderate hypertension
.
Blood Press
.
2005
;
5
(
5
):
273
8
.
40.
Yildirim
U
,
Akcay
M
,
Coksevim
M
,
Turkmen
E
,
Gulel
O
.
Comparison of left atrial deformation parameters between renal transplant and hemodialysis patients
.
Cardiovasc Ultrasound
.
2022
;
20
:
5
.
41.
Zapolski
T
,
Furmaga
J
,
Wysokiński
AP
,
Wysocka
A
,
Rudzki
S
,
Jaroszyński
A
.
The atrial uremic cardiomyopathy regression in patients after kidney transplantation - the prospective echocardiographic study
.
BMC Nephrol
.
2019
;
20
:
152
.
42.
Tamez
H
,
Zoccali
C
,
Packham
D
,
Wenger
J
,
Bhan
I
,
Appelbaum
E
.
Vitamin D reduces left atrial volume in patients with left ventricular hypertrophy and chronic kidney disease
.
Am Heart J
.
2012
;
164
:
902
9.e2
.
43.
Thadhani
R
,
Appelbaum
ESS
,
Pritchett
Y
,
Chang
Y
,
Wenger
J
,
Tamez
H
.
Vitamin D therapy and cardiac structure and function in patients with chronic kidney disease: the PRIMO randomized controlled trial
.
J Am Med Assoc
.
2012
;
307
(
7
):
674
84
.
44.
Slatopolsky
E
,
Brown
ADA
,
Dusso
A
.
Pathogenesis of secondary hyperparathyroidism
.
Kidney Int
.
1999
;
56
:
14
9
.
45.
Cunningham
J
,
Floege
J
,
London
G
,
Rodriguez
M
,
Shanahan
CM
.
Clinical outcomes in secondary hyperparathyroidism and the potential role of calcimimetics
.
NDT Plus
.
2008
1
Suppl 1
29
35
.
46.
Brown
AJ
,
Dusso
AS
,
Slatopolsky
E
.
Vitamin D analogues for secondary hyperparathyroidism
.
Nephrol Dial Transpl
.
2002
17
Suppl 10
10
9
.
47.
Mizobuchi
M
,
Hatamura
I
,
Ogata
H
,
Saji
F
,
Uda
S
,
Shiizaki
K
.
Calcimimetic compound upregulates decreased calcium-sensing receptor expression level in parathyroid glands of rats with chronic renal insufficiency
.
J Am Soc Nephrol
.
2004
;
15
(
10
):
2579
87
.
48.
Lopez
TBD
,
Banerjee
D
.
Management of fluid overload in hemodialysis patients
.
Kidney Int
.
2021
;
100
(
6
):
1170
3
.
49.
Whitlock
M
,
Garg
A
,
Gelow
J
,
Jacobson
TBC
,
Broberg
C
.
Comparison of left and right atrial volume by echocardiography versus cardiac magnetic resonance imaging using the area-length method
.
Am J Cardiol
.
2010
;
106
:
1345
50
.
50.
Habibi
M
,
Samiei
S
,
Venkatesh
BA
,
Opdahl
A
,
Helle-Valle
TM
,
Zareian
M
.
Cardiac magnetic resonance-measured left atrial volume and function and incident atrial fibrillation: results from MESA (Multi-Ethnic study of atherosclerosis)
.
Circ Cardiovasc Imaging
.
2016
;
8
:
e004299
.
51.
Maceira
AM
,
Cosín-Sales
J
,
Roughton
M
,
Prasad
SK
,
Pennell
DJ
.
Reference left atrial dimensions and volumes by steady state free precession cardiovascular magnetic resonance
.
J Cardiovasc Magn Reson
.
2010
;
12
(
1
):
65
.