Introduction
China is home to the largest population of uraemic patients globally, with an annual increase of approximately 100 000–200 000 new cases. Over the past decade, the prevalence of uraemia has decreased by nearly 30%, reflecting significant progress in healthcare, education and environmental policies in China.1 Effective prevention of complications in this extensive patient population is vital for preserving their quality of life. Uraemia, representing the terminal phase of all renal diseases, is commonly complicated by cardiovascular issues, which are the primary cause of mortality in these patients, responsible for more than 50% of deaths. These cardiovascular complications significantly diminish the quality of life for uraemic individuals. Chronic kidney disease heightens the risk of cardiovascular disease, resulting in irreversible myocardial damage and left atrial remodelling as renal insufficiency progresses to uraemia. These pathophysiological alterations negatively impact left atrial volume and function, which is crucial for maintaining cardiac performance. Studies, such as those by Kadappu et al., suggest that abnormalities in left atrial function can manifest even at the subclinical stage of cardiovascular diseases.2 Changes in left atrial volume and function can profoundly influence a patient's prognosis and quality of life.3 For example, left atrial enlargement is a recognized precursor to atrial fibrillation and thrombotic events. Additionally, robust evidence establishes a link between left atrial remodelling, atrial fibrillation and the risk of ischaemic stroke.4 Hence, early detection and evaluation of left atrial function in uraemic patients are invaluable for clinical outcomes and have the potential to guide therapeutic interventions.
Previous studies have investigated left atrial function in patients with renal insufficiency using various technologies, such as real-time three-dimensional echocardiography (RT-3DE), left atrial volume tracking (LAVT), two-dimensional speckle-tracking imaging (2D-STI), three-dimensional speckle-tracking imaging (3D-STI) and velocity vector imaging (VVI).5–7 However, each method has its limitations. RT-3DE often utilizes a left ventricular cone model to analyse the left atrium, but this approach is prone to errors. LAVT, operating on a two-dimensional (2D) plane, fails to fully capture the size and function of the left atrium. 2D-STI suffers from low spatial resolution and susceptibility to the loss of planar speckles, resulting in inaccurate measurements and an incomplete representation of three-dimensional (3D) atrial information. While 3D-STI overcomes the limitations of planar motion in 2D imaging, it is influenced by the image quality of one or more segments, leading to reduced temporal and spatial resolution. This can pose challenges in tracking the left atrium and may result in speckle loss issues.
In contrast, four-dimensional automatic left atrial quantification (4D auto LAQ) introduces a novel 3D-based ultrasound quantitative analysis method that assesses left atrial volume and longitudinal and circumferential atrial myocardial strain across the complete cardiac cycle.8,9 This study sought to assess alterations in left atrial volume and function in uraemic patients receiving haemodialysis through the utilization of 4D auto LAQ technology, aiming to offer pivotal insights for upcoming therapeutic approaches.
Materials and methods
Study population
Ninety-four patients diagnosed with uraemia at the Second Affiliated Hospital of Hainan Medical University, Hainan Province, China, were included in this retrospective cohort study. The detailed study design is illustrated in Figure 1. Patients were categorized into two groups based on their treatment modalities: the uraemia non-dialysis (U-ND) group and the uraemic haemodialysis (U-D) group. The U-ND group comprised 19 males and 15 females, aged between 30 and 73 years (mean ± SD, 49.41 ± 10.06 years). In contrast, the U-D group consisted of 45 males and 15 females, with ages ranging from 21 to 85 years (mean ± SD, 50.72 ± 14.01 years). Inclusion criteria: (i) Patients were clinically diagnosed with stage 5 chronic kidney disease or uraemia according to the 2012 Kidney Disease: Improving Global Outcomes (KDIGO) diagnostic criteria (GFR < 15 mL min−1·1.73 mm−2). The U-D group included patients who had undergone regular haemodialysis via an artificial arteriovenous fistula for more than 3 months, while the U-ND group comprised individuals who did not receive any replacement therapy such as haemodialysis, peritoneal dialysis and kidney transplantation. (ii) All enrolled participants exhibited LVE > 50% and were in sinus rhythm. Exclusion criteria include (i) myocardial involvement diseases: patients with conditions such as cardiomyopathy, myocarditis, coronary heart disease, myocardial infarction, connective tissue disease, etc.; (ii) congenital heart disease; (iii) valvular disease: patients with mild to severe valvular stenosis and regurgitation caused by rheumatic, congenital, senile, infectious and other reasons; (iv) patients with left ventricular ejection fraction (LVEF) < 50%; (v) non-sinus rhythm: patients with arrhythmia such as atrial fibrillation or flutter and ventricular fibrillation or flutter that prevent obtaining a normal left atrial volume curve and left atrial strain curve; (vi) patients experiencing complications of artificial arteriovenous fistula in the haemodialysis group including stenosis, infection, occlusion, thrombosis, etc.; (vii) patients undergoing peritoneal dialysis or kidney transplantation; and (viii) patients with poor image quality.
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Research content
Instruments and methods
Echocardiographic evaluations were conducted using a Vivid E95 scanner (GE Ultrasound) with cardiac transducers (4Vc: 1.4–5.2 MHz; M5Sc: 1.4–4.6 MHz). The measurements were taken prior to any dialysis sessions. During the assessment, participants were positioned on their left side and instructed to breathe calmly, and an electrocardiogram (ECG) was acquired in a controlled, quiet setting. Standard physiological parameters such as systolic and diastolic blood pressure (SBP and DBP), heart rate (HR) and demographic variables, including age and gender, were recorded. Body mass index (BMI) and body surface area (BSA) in square metres were also calculated. Additionally, medical history details such as dialysis duration (dialysis vintage) and the presence of comorbidities like hypertension, diabetes and anaemia were documented. Usage of medications, including renin–angiotensin–aldosterone system inhibitors (RAAS), calcium channel blockers (CCB), alpha-receptor antagonists (α-RA) and beta-receptor blockers (β-Rb), was noted as well.
Conventional echocardiography acquisition
Echocardiographic examinations were conducted using established techniques. The parameters assessed included left atrial diameter (LAD), left ventricular end-diastolic diameter (LVDd), interventricular septal thickness (IVST), left ventricular posterior wall thickness (LVPWT) and left ventricular ejection fraction (LVEF), following the guidelines of the American Society of Echocardiography. Pulsed-wave Doppler ultrasound was utilized to capture transmitral inflow diastolic velocities (E and A waves) for E/A ratio calculations. Tissue Doppler imaging was employed to measure early diastolic velocity (e′), which is essential for deriving E/A and E/e′ ratios.
4D auto LAQ acquisition
All participants underwent a 3D echocardiographic examination using a GE 4Vc transducer for comprehensive 3D data collection. The imaging protocol was optimized to capture the complete volume data of the entire left atrium from the apical four-chamber view. Depth and angle adjustments were diligently made to achieve a frame rate exceeding 40% of the participant's HR. A full-volume image in the apical four-chamber view was captured and stored for subsequent analysis. Data sets that exhibited incomplete visualization of the left atrium, blurred endocardial borders or significant artefacts were excluded from the analysis. Data analysis was performed using GE EchoPAC 203 software. The archived 3D full-volume images were systematically reviewed, activating the analysis mode and selecting the volume and 4D Auto LAQ submodels. The sampling site was centred at the mitral orifice across three planes. The ‘review’ function was utilized to derive left atrial parameters, including volume and strain, evaluated by 4D auto LAQ (Figures 2 and 3). Parameters assessed with this technique encompassed left atrial maximum volume (LAVmax), left atrial pre-atrial contraction volume (LAVpreA), left atrial minimum volume (LAVmin), left atrial maximum volume index (LAVImax), left atrial emptying volume (LAEV), left atrial ejection fraction (LAEF), left atrial reservoir longitudinal strain (LASr), left atrial conduit longitudinal strain (LAScd), left atrial contraction longitudinal strain (LASct), left atrial reservoir circumferential strain (LASr-c), left atrial conduit circumferential strain (LAScd-c), left atrial contraction circumferential strain (LASct-c), left atrial active ejection fraction (LAAEF) and left atrial passive ejection fraction (LAPEF). The formulas for calculating these fractions are as follows: LAEF = (LAVmax − LAVmin)/LAVmax × 100%, LAAEF = (LAVpreA − LAVmin)/LAVpreA × 100% and LAPEF = (LAVmax − LAVpreA)/LAVmax × 100%. Positive strain values indicate an increase in the length of the left atrial wall during the reservoir phase, while negative strain values reflect the contraction of the atrial wall in subsequent phases.
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Other examinations
One hour before dialysis, fasting venous blood samples were collected for routine biochemical assays, including measurements of creatinine, blood urea nitrogen (BUN), N-terminal pro-brain natriuretic peptide (NT-proBNP) and glomerular filtration rate (GFR).
Evaluation of intraobserver and interobserver variability
For the assessment of intraobserver and interobserver reliability, 30 subjects were randomly selected from the N, U-ND and U-D groups. Measurements were repeated by the same observer after several days to evaluate intraobserver variability. Interobserver variability was assessed by comparing the results of two independent observers who were blinded to the patient groups. Interclass correlation coefficients (ICCs) were used to determine consistency within and between observers. ICC values were categorized as ‘good’ if equal to or greater than 0.75, ‘moderate’ if between 0.41 and 0.74 and ‘poor’ if less than or equal to 0.40.
Statistical analyses
Continuous variables were presented as means ± standard deviations for normally distributed data and as medians with interquartile ranges [25th–75th percentile] for non-normally distributed data. One-way ANOVA was utilized to compare multiple groups for normally distributed variables. Fisher's least significant difference test or Tamhane's T2 was applied for multiple group comparisons with normally distributed data, whereas the Kruskal–Wallis H test was used for groups with non-normally distributed data. Categorical variables were expressed as frequencies and evaluated using the chi-square test or Fisher's exact test. The Pearson correlation coefficient was employed to examine the relationship between LAEF and left atrial strain parameters, assuming a normal distribution of both variables. All statistical analyses were performed using SPSS version 22.0 software, with a significance level set at P < 0.05.
Results
Baseline demographic and clinical data
Analysis of baseline demographic and clinical data showed no significant differences among the three groups in terms of gender, age, BMI, male gender prevalence, dialysis duration (dialysis vintage), the presence of hypertension, diabetes, anaemia, use of RAAS inhibitors, α-RA blockers, CCB, β-blockers and BSA. However, the U-D group had notably higher serum SCr levels and lower eGFR than both the U-ND and N groups (P < 0.05). Furthermore, patients with uraemia exhibited higher levels of BUN, SBP, DBP and NT-proBNP compared to the N group (P < 0.05). No significant differences in BUN, SBP, DBP and NT-proBNP levels were observed between the U-ND and U-D groups (P > 0.05) (Table 1).
Table 1 General basic information of healthy volunteers, uraemic undialysed patients and uraemic dialysis patients at the time of inclusion in the study
Parameter | N group ( |
U-ND group ( |
U-D group ( |
||
Age, years | 45.16 ± 10.76 | 49.41 ± 10.06 | 50.72 ± 14.01 | 4.990 | 0.082 |
Male gender, n (%) | 19 (59%) | 19 (56%) | 45 (75%) | 4.330 | 0.115 |
Dialysis vintage, months | — | — | 24(11,46) | — | — |
Hypertension, n (%) | — | 29 (85%) | 51 (85%) | 0.001 | 0.969 |
Diabetes, n (%) | — | 8 (24%) | 10 (17%) | 0.660 | 0.416 |
Anaemic, n (%) | — | 32 (80%) | 45 (75%) | 4.590 | 0.032 |
RAAS, n (%) | — | 11 (32%) | 24 (40%) | 0.543 | 0.461 |
α-RA, n (%) | — | 7 (21%) | 11 (18%) | 0.071 | 0.789 |
CCB, n (%) | — | 24 (70%) | 44 (73%) | 0.617 | 0.432 |
β-Rb, n (%) | — | 16 (47%) | 23 (38%) | 0.681 | 0.409 |
BMI, kg/m2 | 21.87 ± 2.58 | 22.21 ± 3.57 | 20.92 ± 3.05 | 2.200 | 0.115 |
BSA, m2 | 1.65 ± 0.17 | 1.67 ± 0.2 | 1.59 ± 0.14 | 2.890 | 0.059 |
BUN, mmol/L | 4.62 ± 1.19 | 27.29 ± 11.37a | 26.95 ± 9.47a,b | 74.670 | <0.001 |
SCr, μmol/L | 69.81 ± 13.41 | 889.82 ± 410.81a | 1152.33 ± 389.83a,b | 101.660 | <0.001 |
NT-proBNP, pg/mL | 43 (34, 55) | 2829 (972, 12 296)a | 14 003 (2338, 21 865)a | 71.060 | <0.001 |
GFR, mL/min | 107 (91, 150) | 6 (4, 7)a | 3 (3, 5)a,b | 81.030 | <0.001 |
SBP, mmHg | 117.57 ± 13.43 | 147.94 ± 17.64a | 142.53 ± 22.90a | 22.300 | <0.001 |
DBP, mmHg | 76 (68, 83) | 90 (82, 98)a | 85 (74, 96)a | 15.120 | 0.001 |
Conventional echocardiographic data
In patients with uraemia, a higher prevalence of left atrial enlargement and left ventricular hypertrophy was observed compared to the control group. Uraemic patients exhibited significantly increased values in LAD, IVS, LVPWT and the E/e′ ratio, while the e′ and E/A ratios were lower (P < 0.05). There were no significant differences in LAD, IVS, LVPWT, E/e′, e′ and E/A ratio between the U-ND and U-D groups. Left ventricular measurements were notably larger in the U-ND group than in the control group (P < 0.05). However, no significant differences were found in LVEF and peak transmitral flow velocity in early diastole (E) among the groups (Table 2).
Table 2 Parameters of conventional ultrasound measurements of healthy volunteers, uraemic undialysed patients and uraemic dialysis patients at the time of inclusion in the study
Parameter | N group ( |
U-ND group ( |
U-D group ( |
||
LAD, mm | 29.66 ± 3.23 | 36.00 ± 6.53a | 36.58 ± 6.82a | 14.91 | <0.001 |
IVS, mm | 8.56 ± 0.95 | 12.15 ± 1.76a | 12.82 ± 2.14a | 60.70 | <0.001 |
LVPWT, mm | 8.56 ± 1.19 | 12.03 ± 1.71a | 12.70 ± 2.11a | 56.69 | <0.001 |
LV, mm | 43.41 ± 3.51 | 47.88 ± 5.49a | 45.45 ± 6.56 | 5.13 | 0.007 |
E, cm/s | 72 (58, 81) | 73 (55, 92) | 70 (55, 96) | 0.76 | 0.881 |
E/e′ | 6.2 (4.8, 7.2) | 10.4 (6.7, 13.9)a | 10.8 (8.2, 15.6)a | 18.80 | <0.001 |
e′ | 12.0 (10.5, 14.0) | 6.7 (5.5, 9.0)a | 6.5 (5.0, 9.0)a | 55.20 | <0.001 |
E/A | 1.3 (0.9, 1.6) | 0.9 (0.7, 1.4)a | 0.7 (0.6, 1.7)a | 11.40 | <0.001 |
LVEF, % | 61 (65, 67) | 58 (63, 67) | 59 (64, 68) | 0.94 | 0.624 |
Left atrial volume and strain function parameters
Relative to the N group, LAVmin, LAVmax, LAVpre, LAVImax and LAEV were increased in uraemic patients (P < 0.05). Haemodialysis patients exhibited a decrease in these values when compared to non-dialysis patients, but this decrease was not statistically significant (P > 0.05). The absolute values of LAScd-c, LAScd and LAPEF were lower in the U-D group in comparison to both the N and U-ND groups (P < 0.05). Similarly, LASr was lower in uraemic patients than in the N group (P < 0.05). No significant differences were detected in the remaining variables among the groups (Table 3).
Table 3 Parameters of left atrial volume and strain in healthy volunteers, uraemic non-dialysis patients and uraemic dialysis patients at the time of enrolment
Parameter | N group ( |
U-ND group ( |
U-D group ( |
||
LAVmin, mL | 17 (15, 21) | 31 (24, 37)a | 27 (21, 35)a | 30.57 | <0.001 |
LAVmax, mL | 38 (32, 47) | 63 (55, 73)a | 57 (46, 67)a | 37.07 | <0.001 |
LAVpreA, mL | 28 (25, 32) | 46 (40, 58)a | 44 (36, 60)a | 41.48 | <0.001 |
LAVImax, mL/m | 23 (19, 28) | 38 (33, 43)a | 37 (28, 45)a | 37.07 | <0.001 |
LAEV, mL | 20 (17, 26) | 33 (27, 37)a | 29 (20, 35)a | 23.65 | <0.001 |
LAEF, % | 55 (49, 57) | 50 (44, 57) | 53 (45, 58) | 2.69 | 0.260 |
LAAEF, mL | 35.98 ± 8.08 | 34.86 ± 10.03 | 37.79 ± 12.62 | 0.82 | 0.441 |
LAPEF, mL | 25.96 ± 8.84 | 24.25 ± 10.60 | 18.68 ± 11.00a,b | 6.01 | 0.003 |
LASr, % | 22.50 ± 6.21 | 18.56 ± 8.58a | 18.03 ± 7.59a | 4.81 | 0.010 |
LASct, % | −10.12 ± 4.40 | −8.76 ± 6.03 | −10.57 ± 6.66 | 0.99 | 0.373 |
LAScd, % | −12.87 ± 5.57 | −10.06 ± 6.70a | −7.43 ± 5.07a,b | 10.37 | <0.001 |
LASr-c, % | 31 (24, 35) | 30 (24, 34) | 28 (17, 36) | 1.38 | 0.501 |
LASct-c, % | −18 (−21, −12) | −16 (−19, −12) | −18 (−25, −10) | 0.80 | 0.670 |
LAScd-c, % | −12 (−16, −10) | −14 (−16, −10) | −8 (−14, −4)a,b | 16.47 | <0.001 |
Pearson correlation analysis between LAEF and left atrial strain parameters
Positive correlations were found between LAEF and LASr as well as LASr-c, while negative correlations were observed with LAScd, LASct, LAScd-c and LASct-c (Figure 4).
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Intraobserver and interobserver variability
Here, intraobserver and interobserver variability were assessed, with the findings demonstrated that the intra- and interobserver ICCs for LAVmin, LAVmax, LAVpreA, LAVImax, LAEV, LAEF, LASr, LAScd, LASct, LASr-c, LAScd-c and LASct-c were all greater than 0.75, indicating good uniformity (Table 4). These findings confirm the reliability and consistency of the observations in our study.
Table 4 Intraobserver and interobserver variability
Parameter | Intraobserver | Interobserver | ||||
ICC | 95% CI | ICC | 95% CI | |||
LAVmin, mL | 0.922 | 0.813–0.968 | <0.001 | 0.927 | 0.826–0.971 | <0.001 |
LAVmax, mL | 0.949 | 0.875–0.979 | <0.001 | 0.968 | 0.921–0.987 | <0.001 |
LAVpreA, mL | 0.936 | 0.846–0.974 | <0.001 | 0.929 | 0.829–0.971 | <0.001 |
LAVImax, mL/m | 0.928 | 0.829–0.971 | <0.001 | 0.926 | 0.907–0.985 | <0.001 |
LAEV, mL | 0.887 | 0.738–0.954 | <0.001 | 0.903 | 0.771–0.960 | <0.001 |
LAEF, % | 0.790 | 0.542–0.911 | <0.001 | 0.795 | 0.551–0.913 | <0.001 |
LASr, % | 0.944 | 0.864–0.978 | <0.001 | 0.782 | 0.528–0.908 | <0.001 |
LAScd, % | 0.790 | 0.543–0.911 | <0.001 | 0.752 | 0.474–0.894 | <0.001 |
LASct, % | 0.764 | 0.495–0.899 | <0.001 | 0.815 | 0.590–0.922 | <0.001 |
LASr-c, % | 0.858 | 0.667–0.941 | <0.001 | 0.843 | 0.645–0.935 | <0.001 |
LAScd-c, % | 0.755 | 0.479–0.895 | <0.001 | 0.837 | 0.643–0.932 | <0.001 |
LASct-c, % | 0.922 | 0.813–0.968 | <0.001 | 0.915 | 0.798–0.965 | <0.001 |
Discussion
This study employed 4D auto LAQ technology to evaluate subclinical changes in left atrial volume and function in patients with uraemia. The main findings were as follows: (i) Left atrial enlargement and LV hypertrophy represented the most common cardiac abnormalities in uraemic patients, as evidenced by significant increases in LAVmin, LAVmax, LAVpre, LAVImax and LAEV compared to the N group. (ii) The U-D group exhibited notably lower absolute values of LAScd-c, LAScd and LAPEF in comparison with the N and U-ND groups. (iii) LAEF exhibited a positive correlation with LASr and LASr-c and an inverse correlation with LAScd, LASct, LAScd-c and LASct-c. These results underscore the efficacy of 4D auto LAQ technology in detecting alterations in left atrial volume and function among patients with uraemia.
In patients with uraemia, irrespective of dialysis status, there were notable increases in SCr and BUN, accompanied by a decrease in GFR. This decline in renal function leads to an accumulation of metabolic wastes, including creatinine and urea nitrogen. Additionally, compared to the N group, patients exhibited increases in LAD, IVS, LVPWT, SBP and DBP. These changes may be linked to disruptions in the RAAS in uraemic conditions. Elevated levels of angiotensin II stimulate A-receptors, promoting the secretion of extracellular matrix and differentiation of mesenchymal fibroblasts,10 potentially leading to myocardial fibrosis and hypertrophy through autocrine, paracrine and cytosolic secretion mechanisms.11 Furthermore, high levels of aldosterone enhance sodium and water retention while promoting potassium excretion, subsequently raising blood volume, increasing cardiac volume load and fostering myocardial hypertrophy, resulting in elevated diastolic and systolic blood pressure.12 The observed reduction in the E/A ratio and e′ along with the elevation in E/e′ in uraemic patients, relative to the N group, suggests a decline in left ventricular diastolic function, increased preload and elevated filling pressures, ultimately resulting in elevated left atrial pressure. These findings corroborate the study's results and further illustrate the complex interplay between renal dysfunction and cardiovascular changes in uraemia.
This study found elevated values of LAEV, LAVImax, LAVpre, LAVmin and LAVmax in uraemic patients. Although the values in the U-D group were lower than those in the U-ND group, this discrepancy did not reach statistical significance. Additionally, the values of LASr, LAScd and LAPEF were decreased in uraemic patients compared to the N group, consistent with the observations of Calleja et al.,13 who reported increased left atrial volumes and diminished reservoir, conduit and contractile functions in end-stage renal disease patients. Notably, our study highlighted statistically significant decreases in reservoir strain and conduit strain. Similarly, Gan et al.14 observed similar trends in patients with chronic kidney disease progressing to end-stage renal failure, where those who reached end-stage exhibited decreased LASr and increased LAVImax. Uraemic patients may experience cardiomyocyte hypertrophy and fibrosis due to dysregulation in the RAAS, accompanied by water and sodium retention. Such pathological changes can lead to elevated left atrial filling pressures, resulting in increased left atrial volume and reduced compliance. Despite haemodialysis potentially reducing blood volume to alleviate cardiac preload and strain, our results suggested a decrease in left atrial volume without statistical significance, indicating altered left atrial function and potential impairment. Analysis of left atrial conduit function (represented by LAScd, LAScd-c and LAPEF) and reservoir function (represented by LASr) revealed a gradual decline in all three groups concerning LAPEF.7 However, no significant difference was observed in LASr between the U-ND and U-D groups. This lack of significance could be attributed primarily to the limited sample size that may not provide conclusive findings. Furthermore, the relatively short median duration of dialysis treatment in the U-N group (24 months) might have influenced the results. Lastly, our study suggested that changes in left atrial conduit strain preceded alterations in reserve function in uraemic patients, aligning with results reported by Thomas et al.15 The utilization of 4D auto LAQ technology effectively identified these abnormal changes, indicating that long-term haemodialysis may not necessarily enhance and might even compromise cardiac function in uraemic patients.
In this study, we observed a decrease in LASr in uraemic patients. LASr is indicative of left atrial compliance, reflecting the relaxation properties of the left atrium during early diastolic filling.16 An increase in left atrial volume, an indicator of left atrial remodelling, frequently coexists with conditions such as uraemia. Patients with uraemia experience atrial myofibrillation and structural remodelling of the left atrium, which contribute to diminished left atrial compliance, thereby reducing LASr.17
Previous investigations into left atrial volume and function in uraemic patients predominantly employed technologies like RT-3DE, 2D-STI and 3D-STI. These methods typically utilize left ventricular analysis techniques to assess left atrial parameters. While conventional echocardiography serves as the gold standard for assessing cardiac structure and function, its sensitivity is somewhat limited, often only revealing changes with significant cardiac implications.2 In contrast, studies by Takeuchi et al.18 and Yanbin et al.19 underscore the ability of 4D automated left atrial quantification (4D auto LAQ) technology to sensitively and promptly detect alterations in left atrial function, even in individuals with mild to moderate heart failure, offering a more precise assessment than traditional methods. This technology, specialized for left atrial assessments, excels in computing left atrial strain utilizing morphological data, providing thorough and precise evaluations of left atrial volume and functional shifts, surpassing other ultrasound techniques in predicting variations in left ventricular volume and function across diverse pathologies. Its application has expanded to appraising left atrial function in patients with hypertension and diabetes,11,12 underscoring its significant potential in clinical practice. Nonetheless, there is a noticeable dearth of studies utilizing 4D auto LAQ technology to scrutinize left atrial volume and function specifically in uraemic patients, highlighting an avenue deserving of further investigation.
Several limitations of this study should be acknowledged: (i) The sample size was relatively small, potentially impacting the generalizability of the results, thus emphasizing the need for larger studies to validate these findings. (ii) The 4D auto LAQ technique demands high-quality imaging; suboptimal image quality can lead to an underestimation of left atrial strain. (iii) Given that the process of haemodialysis induces changes in blood volume in patients, such changes may act as a confounder and lead to systematic bias in the results as compared with the results in controls who did not undergo haemodialysis. To ensure the accuracy and reliability of our results, we performed testing before the initiation of dialysis therapy to minimize bias from dialysis-induced volume changes. (iv) The study did not consider the influence of long-term medication use and the high prevalence of comorbidities such as hypertension and anaemia, which might impact left atrial function. Addressing these limitations in future studies will be crucial for advancing our understanding of left atrial function in uraemia and refining the diagnostic and therapeutic approaches for these patients.
Conclusions
The findings of this study demonstrate that left atrial volume and function undergo alterations in patients with uraemia. Interestingly, haemodialysis does not seem to enhance left atrial function; instead, it might worsen the deterioration of left atrial conduit function. The 4D auto LAQ technology offers a novel and effective method for the quantitative assessment of left atrial volume and function in this patient population.
Conflict of interest
The authors claim that they have no competitive interests.
Funding
This work was supported by Joint Program on Health Science & Technology Innovation of Hainan Province (No. WSJK2024MS218), Hainan Provincial Natural Science Foundation of China (No. 822RC841) and Hainan Provincial Medical and Health Research Project of China (No. 21A200226).
Data availability statement
All data generated or analysed during this study are included. Further inquiries can be directed to the corresponding author.
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Abstract
Objective
This study aimed to evaluate the utility of left atrial volume and function in uraemic patients using four‐dimensional automatic left atrial quantification (4D auto LAQ) technology.
Methods
Thirty‐four undialysed uraemic patients (U‐ND group), 60 dialysed uraemic patients (U‐D group), and 32 healthy volunteers (N group) were enrolled in our current study. Conventional echocardiographic parameters were recorded, and left atrial volume and strain parameters were analysed to determine statistical differences among the three groups. The Pearson correlation coefficient was employed to assess the relationships between left atrial ejection fraction and left atrial strain parameters.
Results
Compared to the N group, uraemic patients often displayed left atrial enlargement and left ventricular hypertrophy. Significant increases were noted in left atrial diameter, interventricular septum thickness, left ventricular posterior wall thickness, E/e′, diastolic blood pressure, systolic blood pressure, left atrial minimum volume, left atrial maximum volume, left atrial pre‐atrial contraction volume, left atrial emptying volume and left atrial maximum volume index (P < 0.05). Conversely, the e′, E/A ratio and left atrial reservoir longitudinal strain were significantly decreased (P < 0.05). However, no statistically significant differences were observed in the aforementioned parameters between the U‐ND and U‐D groups. The absolute values of left atrial conduit longitudinal strain and left atrial conduit circumferential strain, as well as left atrial passive ejection fraction, were notably lower in the U‐D group compared to the N and U‐ND groups, with statistically significant differences identified among the three groups (P < 0.05).
Conclusions
Uraemic patients exhibit marked left atrial enlargement and left ventricular hypertrophy, coupled with altered atrial function, particularly ductal dysfunction in the U‐D group. The 4D auto LAQ technology proves advantageous in detecting these alterations, offering a promising tool for thorough cardiac assessment in this patient cohort.
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