Left ventricular diastolic dysfunction in uremia patients: the role of four-dimensional automatic left atrial quantification in prediction

Introduction

Chronic kidney disease (CKD) exhibits a disturbing upward trend in mortality rate, which is closely associated with the disease progression stage. As CKD progresses, particularly when it enters the end stage, namely the uremic stage, renal function gradually deteriorates and complications incrementally increase, thereby causing the mortality rate to ascend. In the background, cardiovascular complications play a vital role (1). Relevant studies have indicated that the severity of left ventricular diastolic dysfunction (LVDD) significantly increases along with the gradual advancement of CKD. Especially for patients with advanced CKD, the risk of LVDD increases by more than threefold (2). Left atrial function is correlated with LVDD, and they mutually interact. When LVDD occurs, the left atrium compensates for the elevated left atrial pressure resulting from restricted ventricular filling by augmenting myocardial work, which in turn exacerbates the filling pressure of the left ventricle, forming a vicious cycle (3,4).

Previous techniques for assessing the left atrium of uremic patients, such as two-dimensional (2D) echocardiography, 2D speckle tracking, and three-dimensional (3D) speckle tracking, are limited. They are readily influenced by the imaging plane and angle and are prone to speckle loss, which adversely affects the measurement accuracy. In contrast, the four-dimensional automated left atrial quantification (4D Auto LAQ) technology, based on full-volume imaging, acquires more precise left atrial volume parameters through 3D volume measurement for the assessment of left ventricular diastolic function, thereby facilitating a better evaluation of left ventricular diastolic function. Relevant studies have also indicated that the 4D Auto LAQ technology exhibits high sensitivity and specificity in the evaluation of LVDD (5).

The application range of 4D Auto LAQ technology in cardiovascular diseases is constantly expanding, and an increasing number of studies have begun to focus on its application value in vascular diseases, such as atrial fibrillation, metabolic syndrome, and coronary heart disease, among others (6,7). Nevertheless, studies on the diastolic function of uremic patients are relatively scarce. This research aimed to assess the left atrial function of uremic patients by means of 4D Auto LAQ technology and its application value in predicting LVDD, and to analyze the predictive indicators for risk stratification, so as to explore the differences in left atrial remodeling and functional maintenance between uremic patients with normal diastolic function and those with LVDD. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1022/rc).

Methods

Study population

We conducted a 3-year retrospective cohort study on 150 uremic patients who were treated at The Second Affiliated Hospital of Hainan Medical University from 2021 to 2023. The inclusion criteria were as follows: (I) age ranging from 20 to 60 years; (II) estimated glomerular filtration rate (eGFR) <15 mL/min/1.73 m², and structural or functional renal dysfunction persisting for more than 3 months. The exclusion criteria were as follows: (I) body mass index (BMI) ≥30.0 kg/m²; (II) previous history of cardiomyopathy, manifested as abnormal ventricular wall structure or motion; (III) congenital heart diseases, such as atrial septal defect, ventricular septal defect, and patent foramen ovale; (IV) the presence of hemodynamic abnormalities, such as moderate or severe valvular regurgitation; (V) post-transplant patients; (VI) ejection fraction <50%; (VII) non-sinus rhythm. Ultimately, a total of 108 uremic patients met the inclusion criteria, among whom 59 were dialysis patients. According to the American Society of Echocardiography/European Association of Cardiovascular Imaging (ASE/EACVI) guidelines (8), with the interventricular septal ratio of the early diastolic mitral inflow velocity and the early diastolic mitral annular tissue velocity (E/e’) >15 as the critical threshold for elevated left ventricular filling pressure, the patients were divided into A-group (E/e’ ≤15, n=58) and B-group (E/e’ >15, n=50). Additionally, 38 healthy volunteers were recruited as the control group (N-group, n=38). Who were matched with the case group in terms of age and BMI? All participants had normal results from routine physical examinations. The specific method design process is shown in Figure 1. This study was approved by the Ethics Committee of The Second Affiliated Hospital of Hainan Medical University (approval No. 2024-KCSN-16), and all participants provided informed consent. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Figure 1 Flowchart. A-group: the group of uremia patients with an E/e’ ≤15. B-group: the group of uremia patients with an E/e’ >15. N-group: the group of healthy volunteers. E/e’, ratio of the early diastolic mitral inflow velocity and the early diastolic mitral annular tissue velocity; LASSO, least absolute shrinkage and selection operator.

Procedure of parameters acquisition

Echocardiographic images were acquired by experienced sonographers in accordance with the guidelines of ASE. Before the examination, patients were required to rest calmly for 10 minutes, and their brachial artery blood pressure was recorded. After connecting the electrocardiogram (ECG), patients were placed in the left lateral decubitus position and instructed to breathe smoothly. A GE Vivid E95 color Doppler ultrasound diagnostic instrument with an M5Sc probe (frequency 1.4–4.6 MHz; GE HealthCare, Chicago, IL, USA) was utilized to acquire conventional echocardiographic parameters in the parasternal long-axis view of the left ventricle and the apical four-chamber view. A 4Vc probe (frequency 1.5–4.0 MHz) was employed, with the volume frame rate adjusted to over 40% of the heart rate. Patients were instructed to hold their breath at the end of expiration. In the four-chamber view, real-time images of three consecutive cardiac cycles were continuously collected, and the images with clear left atrial endocardium were selected and imported into the EchoPAC203 workstation (HealthCare).

General data and conventional echocardiographic parameters

General parameters: the clinical data of all enrolled patients were retrieved from the electronic medical record systems of the participating hospitals, encompassing age, gender, height, weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), medication history, and underlying diseases. BMI and body surface area (BSA) were concurrently calculated. Furthermore, laboratory examinations were performed on the participants, comprising blood urea nitrogen (BUN), serum creatinine (SCr), N-terminal pro-brain natriuretic peptide (NT-proBNP), and eGFR, were conducted.

Conventional echocardiographic parameters: left ventricular ejection fraction (LVEF) was measured by Simpson’s biplane method (Simpson-EF); left atrial anteroposterior diameter (LAD), left ventricular end-diastolic diameter (LVDd), interventricular septal thickness (IVST), left ventricular posterior wall thickness (LVPWT), and LVEF were measured via Simpson’s biplane method. The peak velocities of early (E) and late (A) diastolic blood flow at the mitral valve orifice were measured by spectral Doppler in the apical four-chamber view, and the E/A ratio was computed. The early diastolic velocity (e’) of the interventricular septum was measured using tissue Doppler imaging, and the E/e ratio was calculated.

4D left atrial volume and left atrial strain parameters

The images were analyzed using the 4D Auto LAQ technology on the EchoPAC 203 workstation to obtain the left atrial volume and strain parameters (see Figure 2): left atrial minimum volume (LAVmin), left atrial maximum volume (LAVmax), left atrial pre-atrial contraction volume (LAVpreA), left atrial maximum volume index (LAVImax), left atrial ejection fraction (LAEF), left atrial emptying volume (LAEV), and left atrial passive ejection fraction (LAPEF) were calculated. LAPEF = (LAVmax − LAVpreA)/LAVmax, and left atrial active ejection fraction (LAAEF), LAAEF = (LAVpreA − LAVmin)/LAVpreA; the left atrial strain parameters: left atrial reservoir longitudinal strain (LASr), left atrial reservoir circumferential strain (LASr-c), left atrial conduit longitudinal strain (LAScd), left atrial conduit circumferential strain (LAScd-c), left atrial contraction longitudinal strain (LASct), and left atrial contraction circumferential strain (LASct-c).

Figure 2 Schematic illustration of left atrial volume and strain parameters derived from 4D Auto LAQ analysis. (A) Left atrial circumferential strain with A-group. (B) Left atrial circumferential strain with B-group. A-group: the group of uremia patients with an E/e’ ≤15. B-group: the group of uremia patients with an E/e’ >15. 4D Auto LAQ, four-dimensional automated left atrial quantification; ED, end-diastolic; ES, end-systolic; LAEF, left atrial ejection fraction; LAEV, left atrial emptying volume; LAVmax, left atrial maximum volume; LAVmin, left atrial minimum volume; LAVpreA, left atrial pre-trial contraction volume; LAScd, left atrial conduit longitudinal strain; LAScd-c, left atrial conduit circumferential strain; LASct, left atrial contraction longitudinal strain; LASct-c, left atrial contraction circumferential strain; LASr, left atrial reservoir longitudinal strain; LASr-c, left atrial reservoir circumferential strain; PreA, pre-atrial contraction.

Statistics

Data processing was performed using SPSS software (IBM Corp., Armonk, NY, USA). Parameters with normal distribution were expressed as mean ± standard deviation. One-way analysis of variance (ANOVA) was employed for intergroup analysis among multiple groups; for two groups, if the parameters conformed to variance homogeneity, the least significant difference (LSD) test was utilized; otherwise, the Tamhane’s T2 test was adopted. Parameters with non-normal distribution were examined using the Kruskal-Wallis H test and presented as median (25%, 75%). Count data were expressed as cases (%) and compared between two groups using the χ² test. A P value <0.05 was regarded as statistically significant. Least absolute shrinkage and selection operator (LASSO)-Logistic regression analysis was initially employed to screen for characteristic variables. Subsequently, multivariate regression analysis was carried out to further sieve out key influential factors and establish a nomogram prediction model. The predictive capability of the model was comprehensively assessed by drawing receiver operating characteristic (ROC) curves, calibration curves, and clinical decision curve analysis (DCA).

Results

General data parameters

Among the three groups of participants, no significant statistical differences were observed in multiple indicators such as age and gender (all P>0.05). In contrast to the N-group, significant alterations were noted in the laboratory indicators of the uremia case group (P<0.05), whereas no statistically significant differences were found in the aforementioned indicators between the A-group and the B-group (P>0.05). The reverse was true for DBP—marked differences in DBP were identified among the three groups. The DBP of the A-group and the B-group was increased compared to the control group (P<0.05). The prevalence of hypertension in the A-group was higher than that in the B-group (P<0.05). For details, refer to Table 1.

Conventional echocardiographic parameters

Significant differences were observed in LAD, E/e’, and e among the three groups (all P<0.05). Compared with the N-group, LAD and E/e’ gradually increased while e gradually decreased in the A-group and B-group (P<0.05). The IVST, E/A, and LVPWT in the uremic case group were greater than those in the normal group (P<0.05), but there was no significant disparity between the A-group and B-group (P>0.05). LVDd in the B-group was larger than that in the N-group, and Simpson-EF in the B-group was smaller than that in the A-group and N-group, E of B-group was larger than that of A-group and N-group, and the with statistically significant differences (P<0.05). The detailed data are presented in Tables 1,2.

4D left atrial volume and left atrial strain parameters

The statistical results demonstrated that there were no significant differences in LAAEF and LASct-c among the three groups (P>0.05). Conversely, the differences in LAVmax, LAVmin, LAVpreA, LAVImax, and the absolute value of LAScd among the three groups were statistically significant. Upon further post-hoc pairwise comparisons, it was revealed that, in comparison to the N-group, LAVmax, LAVmin, LAVpreA, and LAVImax in the A- and B-groups increased gradually, whereas the absolute value of LAScd decreased gradually (P<0.05). When compared with the other two groups, the absolute values of LAEF, LAPEF, LASr, LASr-c, and the absolute value of LAScd-c in the B-group were significantly reduced (P<0.05), whereas there were no significant differences between the A- and N-groups (P>0.05).

Compared with N-group, LAEV in the uremic case group showed an increase (P<0.05), yet there were no significant differences between the A-group and B-group (P>0.05). The absolute value of LASct in B-group was marginally lower than that in the N-group and A-group. Moreover, only the difference between the A-group and B-group was statistically significant (P<0.05), although this difference was not substantial. The detailed data are presented in Table 2.

LASSO-logistic regression model

The indicators that exhibited statistically significant differences between the A-group and the B-group, which were stratified according to E/e’ >15, were incorporated into the LASSO regression model, namely LAD, Simpson-EF, LAVmin, LAVmax, LAVpreA, LAVImax, LAEF, LASr, LAScd, LASct, LASr-c, LAScd-c, LAPEF, and hypertension, amounting to 14 indicators. The optimal λ value was determined through cross-validation (lambda.1se was selected as the optimal λ value), as depicted in Figure 3. The four predictors identified were subjected to further multivariate logistic regression analysis and modeling using the stepwise backward regression approach. The ultimate analysis results revealed that LASr [odds ratio (OR) =1.105; 95% confidence interval (CI): 1.028–1.188; P=0.007] and hypertension (OR =3.287; 95% CI: 1.139–9.481; P=0.028) were independent influencing factors for the event occurrence. The results are presented in Table 3.

Figure 3 Feature selection using the LASSO regression model. (A) The LASSO regression coefficient path graph of 14 variables. (B) The LASSO regression cross-validation curve, with lambda.lse adopted as the ultimate screening criterion. LASSO, least absolute shrinkage and selection operator.

The multivariate logistic regression model was visualized using a nomogram. The results are presented as follows in Figure 4: for each one-unit increase in LAVpreA, the score decreased by 6.5 points; for each one-unit increase in LASr, the score increased by 10 points; for each one-unit increase in LAPEF, the score increased by 4.7 points. Hypertensive patients (yes) obtained 23.9 points, whereas those without hypertension obtained 0 points. Based on the total score of all variables, the corresponding event occurrence risk was calculated via the nomogram.

Figure 4 Nomogram. LAPEF, left atrial passive ejection fraction; LASr, left atrial reservoir longitudinal strain; LAVpreA, left atrial pre-atrial contraction volume.

The efficacy of the nomogram model was assessed via ROC curves, calibration curves, and DCA. The results indicated that the comprehensive model exhibited the best performance in diagnosing LVDD in uremic patients [area under the curve (AUC) =0.811; 95% CI: 0.728–0.893]. The single indicator LASr also revealed application value (AUC =0.742; 95% CI: 0.649–0.834), as shown in Table 4. The calibration curve and Hosmer-Lemeshow test (χ²=5.230, P=0.733) demonstrated that the model had an excellent goodness of fit. The clinical decision curve indicated that the model had favorable clinical utility when the risk threshold was 9–93% (see Figures 5,6).

Figure 5 ROC curves. AUC, area under the curve; LAPEF, left atrial passive ejection fraction; LASr, left atrial reservoir longitudinal strain; LAVpreA, left atrial pre-atrial contraction volume; ROC, receiver operating characteristic.

Figure 6 Feature selection using LASSO regression model. (A) Calibration curves. (B) Decision curve analysis. LASSO, least absolute shrinkage and selection operator.

Repeatability and reproducibility

A total of 20 cases were randomly selected from each of the three groups of participants, and intra- and inter-observer consistency tests were conducted respectively. The analysis results suggested a favorable consistency performance. Specific conclusions are displayed in Table 5.

Discussion

Previous studies have indicated that LVDD constitutes a significant sign of cardiovascular system impairment in patients with CKD. It serves not only as a predictor of disease progression but also as a crucial factor influencing patient prognosis (9). The functional disorder is mainly characterized by the inability of the left ventricular myocardium to relax effectively or become abnormally stiff during diastole, thereby hindering the normal filling process of the ventricle during this phase, resulting in an abnormal increase in left ventricular end-diastolic pressure and subsequently triggering an elevation in pulmonary venous pressure. This sequence of pathophysiological changes ultimately intensifies the burden on the heart and promotes the occurrence of heart failure (10). It is noteworthy that a substantial decline in the eGFR particularly as patients advance to the end-stage kidney disease (ESKD) stage, is accompanied by increasingly pronounced clinical manifestations of LVDD (11,12). The results of this study demonstrate the following: (I) the volume of the left atrium gradually increases as the filling pressure of the left ventricle rises, suggesting a direct proportion between the left atrium and the filling pressure of the left ventricle. (II) LASr, LASr-c, LAScd, and LAScd-c decrease along with LVDD. (III) LAScd undergoes changes, which were even observed in the group with normal left ventricular filling pressure. (IV) LASr exhibits the best diagnostic efficacy in uremic patients with LVDD.

In patients with uremia, factors such as hypertension, water–sodium retention, inflammatory responses, toxin accumulation, and disorders of calcium-phosphorus metabolism significantly increase the cardiac burden. This leads to myocardial hypertrophy and fibrosis, subsequently reducing ventricular compliance and ultimately inducing LVDD, accompanied by an elevation in left ventricular filling pressure. Echocardiography evaluates left ventricular diastolic function by measuring parameters including the E wave, A wave, E/A ratio, and E/e’ ratio. Among these, the E/e’ ratio is widely recognized for its more accurate reflection of ventricular compliance (13). The ASE/EACVI guidelines recommend using the average E/e’ of the interventricular septum and the lateral wall as the core index for assessing left ventricular filling pressure (14). Notably, the guidelines clearly state that when the E/e’ >15 of the interventricular septum or the E/e’ >13 of the lateral wall, either parameter reaching the critical value independently can support the diagnosis. This criterion is consistent with previous relevant research findings (15). However, it should be emphasized that this assessment method may have certain biases in special clinical scenarios such as mitral annular calcification and severe arrhythmias. According to the ASE/EACVI guidelines, an E/e’ >15 of the interventricular septum is classified as the group with abnormal left ventricular diastolic function, 8≤ E/e’ ≤15 represents the critical group (the so-called gray zone) of left ventricular diastolic function, and E/e’ <8 is the group with normal diastolic function. In this study, the E/e’ ratio gradually increased among the three groups. Research has shown that an increase in the E/e’ ratio is not only directly associated with an elevation in left ventricular filling pressure but also serves as a sensitive marker of diastolic function impairment. As the left ventricular filling volume increases, that is, during the process of diastolic function changes, left atrial volume parameters (LAVmax, LAVmin, LAVpreA, LAVImax, LAD) increase significantly. In contrast, left ventricular structural parameters (LVDd, LVPWT, IVST) did not show statistically significant differences between group A and group B. This suggests that conventional ultrasound parameters are not sensitive enough to identify the stage of diastolic dysfunction in uremic patients in this study (16). Importantly, all left atrial parameters exhibited significant gradient changes among the three groups, further validating the correlation between left atrial enlargement and an increase in the E/e’ ratio in this study.

It is well recognized that the atrial myocardium is composed of superficial striated muscle fibers and deep circular or annular muscle fibers. Longitudinal strain measures the shortening in the long-axis direction of the cardiac chamber, whereas circumferential strain measures the contraction in the short-axis direction (17). In the conclusion of this study, LASr, LASr-c, LAScd, and LAScd-c in group B were significantly lower than those in groups A and N. This indicates that in uremic patients, the longitudinal and circumferential strains of the left atrial reserve function and channel function decline, suggesting that the deterioration of diastolic function and the impairment of atrial mechanical properties progress concurrently. Based on the data in this study, group N, with an E/e’ <8, is in the normal function stage, whereas group A, with 8≤ E/e’ ≤15, is in the gray zone of diastolic function. IVST, LVPWT, LAD, LAVmax, LAVmin, LAVpreA, and LAVImax showed statistical significance between the two groups. This is because group A consists of diagnosed uremic patients, resulting in significant myocardial hypertrophy and left atrial enlargement. Notably, only LAScd gradually increased among the three groups as diastolic function changed. This indicates that compared with other strain assessment parameters, LAScd undergoes changes in the “gray area” of diastolic function. This highlights the advantage of 4D Auto LAQ in early identification during diastolic function changes compared to conventional echocardiographic parameters. Among them, LAScd changes earlier than other strains, and its longitudinal strain index has a significantly higher diagnostic efficiency in the uremic population than that of circumferential strain (18), suggesting that the orientation of myocardial fibers may influence the sensitivity of strain measurement.

Existing research has indicated that LAVImax ≥34 (mL/m²) serves as an independent risk factor for predicting patient mortality (19). Nevertheless, within the multivariate logistic regression model formulated in this study, the association between left atrial volume and the endpoint event did not attain statistical significance (P>0.05). In light of this finding, when conducting clinical assessments of uremic patients with abnormal left ventricular diastolic function, relying solely on the parameter of left atrial volume may introduce potential biases. Conversely, the multi-parameter combined prediction model developed in this research demonstrated excellent discriminatory power, with an AUC of 0.811, thus presenting a more favorable predictive efficacy compared to single ultrasound parameters. Moreover, this study revealed that in uremic patients, LASr and a history of hypertension are crucial and sensitive independent predictors of LVDD grading. ROC curve analysis further validated that, in comparison with traditional echocardiographic parameters, LASr demonstrates heightened sensitivity and discriminatory capabilities in detecting subclinical cardiac insufficiency and differentiating various LVDD grades. This outcome aligns with the research conclusions of Cameli et al. (20). Notably, traditional ultrasound structural parameters, such as LAD, typically mirror the long-term adaptive alterations of the cardiac structure. However, they lack dynamism and early-stage sensitivity. During the early phase of LVDD, the left atrium enhances its contraction compensatorily to maintain cardiac output, which is manifested as an elevation in LASr. As LVDD advances, the left atrium gradually loses its compensatory ability, and LASr decreases significantly. This dynamic process reflects the abnormalities of left ventricular diastolic function earlier and more sensitively than do traditional structural parameters (21). This conclusion is also congruent with the research findings of Morris et al. (22). The novelty of this study lies in the first application of 4D Auto LAQ technology to quantitatively analyze the dynamic changes in left atrial function among uremic patients. We discovered that LASr, LASr-c, LAScd, and LAScd-c exhibit a gradient-decreasing trend with the deterioration of diastolic function. When compared with traditional ultrasound indices, the prediction system based on the multi-parameter logistic regression model enhanced the diagnostic accuracy. Notably, LASr demonstrated the highest sensitivity during the progression of diastolic function and served as an independent and sensitive predictor. This offers a novel quantitative tool for the early identification of cardiovascular risk in patients with CKD, thus possessing significant clinical translational significance.

Limitations: (I) although the moderate sample size offered sufficient statistical power for the primary analysis, the single-center design might restrict the generalizability of the research findings. Future validations conducted in larger-scale and multi-center cohorts, encompassing more diverse ethnic groups, would enhance its clinical applicability. (II) The nature of retrospective data collection entails inherent limitations. Specifically, the absence of average e’ values at both the septal and lateral mitral annulus in accordance with the current guidelines of the ASE/EACVI precludes a comprehensive evaluation of local myocardial mechanics in uremic cardiomyopathy. It is imperative to undertake prospective studies adopting standardized protocols to bridge this technical gap. (III) The intrinsic heterogeneity of comorbid conditions and polypharmacy patterns introduced inevitable confounding factors.

Conclusions

The 4D Auto LAQ technique offers valuable insights into the assessment of LVDD in uremic patients, revealing significant impairment in left atrial conduit-phase strain within the clinically challenging “gray zone” of LVDD. Left atrial strain demonstrates superior sensitivity and specificity compared to conventional echocardiographic parameters for detecting early alterations in atrial function. Furthermore, the multivariable logistic regression model confirms its robust clinical utility in evaluating diastolic function, while its application in CKD populations underscores transformative potential for early cardiovascular risk stratification and intervention. Collectively, these findings establish a novel diagnostic framework for uremic cardiomyopathy.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1022/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1022/dss

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).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1022/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was approved by the Ethics Committee of The Second Affiliated Hospital of Hainan Medical University (approval No. 2024-KCSN-16), and all participants provided informed consent. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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