Validation of a hand-held Ultrasound device in the evaluation of Aortic Stenosis

Validation of a hand-held Ultrasound device in the evaluation of Aortic Stenosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Validation of a hand-held Ultrasound device in the evaluation of Aortic Stenosis Jon Zubiaur, Adrián Margarida de Castro, Raquel Pérez-Barquín, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5153609/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Dec, 2024 Read the published version in The International Journal of Cardiovascular Imaging → Version 1 posted 7 You are reading this latest preprint version Abstract Purpose Hand-held ultrasound devices (HHUD) are increasingly used in routine clinical practice, though they lacked continuous (CW) Doppler capability until recently. There is limited evidence on the utility of HHUD in assessing aortic stenosis (AS) in real-world settings. Our goal is to validate a new HHUD with CW Doppler assessing AS hemodynamic severity. Methods An observational, single-center study was conducted with patients diagnosed with AS. Following a reference echocardiographic study in the cardiac imaging laboratory, a HHUD with CW Doppler (Kosmos, EchoNous™) was used by an operator with intermediate echocardiography experience (American Society of Echocardiography, level II). The focus was on measuring aortic transvalvular Doppler velocities. Agreement between the mean trans-aortic gradient (mAG) was assessed using the intraclass correlation coefficient (ICC) test. A total of 101 patients were included. Results The reference test obtained a mAG of 29 mmHg (19.8–42.2), while the HHUD test showed 27.2 mmHg (16.2–43.9). A strong correlation was observed (r = 0.89), with an ICC value of 0.87 and no significant bias (1.61 ± 0.9). The HHUD demonstrated excellent ability to identify severe AS (kappa = 0.81, 95% CI 0.68–0.94; global agreement 92.1%). Agreement was lower in patients with obesity, poor acoustic windows, or atrial fibrillation. Conclusions The HHUD showed good agreement with standard echocardiography in assessing AS. While it slightly underestimated mAG, it was accurate enough to reliably quantify AS severity. Echocardiography point of care ultrasound hand-held ultrasound aortic stenosis Figures Figure 1 Figure 2 Figure 3 Figure 4 1. INTRODUCTION Aortic stenosis (AS) is the most common valve disease requiring either surgical or percutaneous intervention in Europe and North America ( 1 ). The progressively increasing age of the population also explains the growing prevalence of this condition ( 2 ). Simultaneously, safe and less invasive procedures, such as transcatheter aortic valve replacement (TAVR), are now available and provide effective treatment ( 3 ). According to the most recent clinical practice guidelines, the evaluation of the hemodynamic severity of AS should be performed by echocardiography ( 4 – 6 ). Among the recommended parameters to assess are the mean aortic gradient, aortic valve area, peak aortic velocity, dimensionless index, and ventricular ejection fraction, which should guide the decision to intervene, along with consideration of the patient's symptoms and comorbidities. Recent technological advances have resulted in the development of handheld ultrasound devices (HHUD) with high-quality imaging. One of the main advantages of these devices is that they provide rapid and effective bedside assessments. Additionally, this technology is continuously improving and is currently relatively inexpensive. These features have made the HHUD a valuable tool for use both in the inpatient and outpatient hospital settings. As a result, research interest in this field has increased ( 7 , 8 ). Thus, some studies have attempted to assess AS using two-dimensional imaging and a semi-quantitative approach. These studies rely on indirect parameters such as the presence of valve calcium and the mobility of the aortic leaflets. Since these parameters essentially subjective, they are considered only as an option for initial screening ( 9 – 11 ). However, a complete assessment of AS requires a quantitative approach, specifically the measurement of aortic transvalvular velocity. For this, continuous wave (CW) Doppler is necessary. Until recently, this technology was not available in portable echocardiography devices but the Kosmos® (EchoNous) device, a HHUD with CW Doppler capability, now allows for the quantitative evaluation of AS by measuring aortic transvalvular velocities for the first time. Recently, Sachpekidis and colleagues studied the Kosmos device for the evaluation of AS in a controlled setting, reporting favorable results ( 8 ). In their study, an experienced operator conducted the HHUD examination, but he was not blinded to the previous findings obtained with a conventional device. Therefore, while this study serves as a validation of the device for quantificatifyng transaortic velocities with a CW Doppler-equipped HHUD, it differs from how this technique is typically used in daily clinical practice. In real-life settings, HHUD bedside studies are often performed by clinicians who are not necessarily experts in echocardiography, most of whom have only an intermediate level of experience in echocardiography (as defined by the American Society of Echocardiography (ASE) level II) ( 12 ). The objective of our study is to validate the ability of the Kosmos HHUD to quantify AS in a real-life setting, daily practice setting. To this end, we designed a study comparing the results of an HHUD examination performed by an operator with intermediate experienced (ASE level II), who was blinded to the reference standard echocardiographic assessment conducted by experienced operators (ASE level III) at the Echocardiography Laboratory using high-end equipment. 2. METHODS 2.1 Study design We conducted a prospective, observational, single-center study that included patients diagnosed with AS who had undergone a previous echocardiogram. The study was designed following the 2015 Standards for Reporting Diagnostic Accuracy (STARD) statement ( 13 ). Approval for the study was obtained from the Cantabria Institutional Review Board (approval number MTVAL1907). 2.2 Participants Patients were randomly recruited from the cardiac imaging laboratory at a tertiary referral center in the northern Spain between October 2022 and August 2023. They had been previously diagnosed with AS (any severity grade) via echocardiography, based on the definition of the 2021 European Society of Cardiology (ESC) guidelines ( 4 ). All patients were over 18 years of age and provided informed consent prior to participation. 2.3 Methods Immediately after undergoing a standard echocardiography study, a focused echocardiographic assessment of transaortic velocities using the Kosmos HHUD was performed. These assessments were conducted by two independent cardiologists, blinded to each other´s findings. Additionally, the cardiologist performing the HHUD study was blinded to the patient´s clinical history and previous echocardiograms. The cardiologist conducting the reference echocardiogram had expert-level (level III) training in echocardiography as per the 2019 ASE Advanced Training Statement on Echocardiography ( 12 ). To simulate a real-world clinical setting, the cardiologist performing the HHUD had intermediate-level training (ASE level II). Both echocardiographic studies were performed consecutively to ensure no significant clinical or hemodynamic changes occurred between them. Blood pressure and heart rate (HR) were measured before each test. The reference echocardiography system used was the Philips EPIQ CVx™ (Philips Healthcare, Amsterdam, The Netherlands), while the HHUD device was the Kosmos (EchoNous™) with CW Doppler capability ( Fig. 1 ). 2.4 Clinical definitions AS was defined according to the 2021 ESC guidelines and the 2021 practical guidelines from the British Society of Echocardiography ( 4 , 5 , 14 ). Severe aortic stenosis (SAS) was defined as a mean aortic gradient (mAG) of ≥ 40 mmHg. Moderate aortic stenosis (MAS) was defined as a mAG between 20 mmHg and 39 mmHg. Mild aortic stenosis (MiAS) was defined as a mAG of < 20 mmHg. Low-flow, low gradient AS was defined as mAG < 40mmHg, aortic valve area (AVA) ≤ 1.0 cm 2 and stroke volume index < 35ml/m 2 . Left ventricle ejection fraction (LVEF) was estimated using the Simpson biplane method, with impaired LVED defined as ≤ 40%. Body surface area (SA) was calculated using the DuBois formula. A suboptimal acoustic window was defined by the reference echocardiographer. Obesity was classified as a body mass index (BMI) ≥ 30 kg/m 2 . Information on previous lung disease, neurological disease, and atrial fibrillation (AF) was extracted from the patients' electronic medical records. We chose mAG as the main variable in our study due to its importance in determining AS severity. We also measured maximum aortic velocity (Vmax), aortic velocity-time integral (VTI), left ventricle outflow tract (LVOT) diameter and LVOT VTI, and estimated the VTI ratio and aortic valve area (AVA). All measurements and estimates were conducted according to international guidelines ( 4 , 14 ). The primary outcome variable was the value of the intraclass correlation (ICC) between the mAG values obtained from the two echocardiographic studies. We also analyzed the ICC for the other quantitative variables. 2.5 Statistical analysis Quantitative variables were expressed as median and interquartile range (IQR) (25th – 75th percentiles), while qualitative variables were expressed as frequencies (n, %). Differences between quantitative variables were assessed using the Mann-Whitney U test, and differences between qualitative variables were evaluated with the χ² test for. A p-value of less than 0.05 was considered statistically significant. We performed an ICC test between the quantitative variables. We performed a kappa test between the qualitative variables. We performed a Bland-Altman and a Passing Bablok analysis to graphically describe the outcomes of our data. Statistical analyses were carried out using STATA 16 software (StataCorp. 2019. Stata Statistical Software: Release 16 . College Station, TX: StataCorp LLC). 2.6 Sample size calculation We estimated the sample size with the formula provided by Bonett and Walter ( 15 , 16 ). We selected the most conservative sample size estimate, resulting in a calculated sample size of 101 patients. 3. RESULTS 3.1 Participants The enrolment period commenced in October 2022 and concluded in August 2023. In accordance with the estimated sample size calculation, 101 patients were recruited from a pool of 105 eligible patients. Four patients were excluded (One patient received an alternative diagnosis, 3 patients refused to participate) (Supplementary Fig. 1). The study patients were 78.7-year-old and 35.6% were female. The median BMI was 26.3 kg/m 2 , and the median SA was 1.8m 2 . A total of 22 patients (21.8%) were classified as obese. In 25 patients (23.8%) the acoustic window was considered as suboptimal. Twenty-four patients (23.8%) were in AF, 6 (5.9%) had a neurological disorder, 7 (6.9%) a respiratory disorder and 4 (4%) a chest malformation. Median “mean arterial tension” was 92 mmHg (interquartile range: 84.7–100 mmHg) and HR was 70 bpm (interquartile range: 62–75 bpm) when HHUD test was performed. There were no statistically significant differences in mean arterial tension (p = 0.871) and HR (p = 0.794) between the reference test and the HHUD test. The median left ventricle ejection fraction (LVEF) was 60% and 19 (18.8%) had impaired LVEF. These baseline characteristics are shown in Table 1 . Table 1 Main baseline clinical characteristics. Variables N = 101 Age (years) 78.7 (73–84) Female 36 (35.6%) Height (cm) 165 (156–171) Weight (kg) 73 (64–82) Body surface area by DuBois (m 2 ) 1.8 (1.7–1.9) Body mass index (kg/m 2 ) 26.3 (24.1–29.3) Obesity (BMI ≥ 30) 22 (21.8%) Systolic blood pressure (mmHg) 130 (117–150) Diastolic blood pressure (mmHg) 71 (65–80) Mean blood pressure (mmHg) 92 (84.7–100) Heart rate (beats per minute) 70 (62–75) Previous lung pathology 7 (6.9%) Previous neurological pathology 6 (5.9%) Thoracic malformations 4 (4%) Suboptimal echocardiographic window 25 (24.8%) Atrial Fibrillation 24 (23.8%) LVEF (%) 60 (50–65) LVEF ≤ 40% 19 (18.81%) Values are shown as “median (Interquartile range)” or “n (%)”. Abbreviations: BMI: Body mass index; LVEF: Left ventricular ejection fraction. The HHUD test, focused on the evaluation of aortic valve parameters, took a median time of 9 minutes (interquartile range: 7–11 minutes) to be performed. 3.2 Test results The reference test yielded a median mAG of 29 mmHg (interquartile range: 19.8–42.2 mmHg), whereas the HHUD test resulted in a median mAG of 27.2 mmHg (interquartile range: 16.2–43.9 mmHg). A strong agreement was observed between the HHUD and reference mAG measurements, as indicated by an ICC of 0.87 (95% CI 0.79–0.94). Linear regression analysis revealed a good correlation between the two methods (r = 0.89; 95% CI 0.85–0.94) (see Table 2 ). Table 2 Results of the measurements by the two echocardiographs and the agreement tests. Variables Reference Hand-Held device Test Aortic valve ICC Spearman Kappa Mean Aortic Gradient (mmHg) 29 (19.8–42.2) 27.2 (16.2–43.9) 0.87 0.89 Maximum Aortic Velocity (m/s) 343.5 (282.4–402.6) 309.4 (242.6–375.3) 0.71 0.79 Left ventricular outflow tract diameter (mm) 21.6 (19.9–22.9) 21.0 (18.9–22.4) 0.59 0.59 Aortic VTI (cm) 75.2 (59.3–99.2) 72.1 (54.9–88.8) 0.81 0.86 LVOT VTI (cm) 21 (17.1–24.6) 19.3 (16.4–22.9) 0.28 0.76 Left ventricular outflow tract area (cm 2 ) 3.7 (3.1–4.2) 3.5 (2.8–3.9) 0.58 0.59 Aortic valve area (cm 2 ) 0.9 (0.7–1.2) 0.9 (0.7–1.2) 0.46 0.63 Indexed aortic valve area (cm 2 /m 2 ) 0.5 (0.4–0.7) 0.5 (0.4–0.7) 0.43 0.59 VTI ratio 0.28 (0.19–0.47) 0.25 (0.21–0.36) 0.43 0.76 Aortic valve opening reduction 0.44 Mild 21 (20.1%) 25 (24.8%) Moderate 35 (34.6%) 34 (33.7%) Severe 45 (44.6%) 42 (41.6%) Aortic Valve Calcification 0.39 Mild 15 (14.9%) 22 (21.8%) Moderate 36 (35.6%) 26 (25.7%) Severe 50 (49.5%) 53 (52.5%) Bicuspid Aortic Valve 5 (4.9%) 3 (3%) -0.04 Values are shown as “median (Interquartile range)” or “n (%)”. Abbreviations: ICC: Intraclass correlation coefficient; LVOT: Left ventricle outflow tract; VTI: Velocity-time integral. Table 3 Classification of aortic stenosis severity by the two echocardiographs and agreement tests. Grade of Aortic Stenosis Reference Hand-Held device Kappa test Agreement Mild 29 (28.7%) 35 (34.6%) 0.73 88.1% Moderate 41 (40.6%) 37 (36.6%) 0.58 80.2% Severe 31 (30.7%) 29 (28.7%) 0.81 92.1% Global 0.7 80.2% LF/LG 22 (21.9%) 30 (29.7%) 0.23 70.3% LF/LG: Low flow / low gradient. The Bland & Altman analysis demonstrated that 4 cases (3.9%) exceeded the predefined limit, while 3 cases (2.9%) fell below the limit of agreement (LOA) (± 17.8 mmHg) (Fig. 2 ). The Passing-Bablok analysis revealed no deviation from linearity, with a constant difference of -3.21 mmHg (95% CI: 0.57–5.46) but no evidence of proportional difference (95% CI: 0.83–1.02) (Fig. 3 ). According to the severity classification of the AS, the reference test diagnosed 31 (30.7%) as SAS, 41 (40.6%) as MAS and 29 (28.7%) as MiAS. Conversely, the HHUD test diagnosed 29 (28.7%) as SAS, 37 (36.6%) as MAS and 35 (34.6%) as MiAS. Kappa analysis showed good agreement with a value of 0.7. Total agreement within each grade exceeded 80.2% ( Table 4 ) . Notably, the HHUD exhibited excellent agreement for classifying AS, particularly in the SAS grade, with a kappa value of 0.81 (95% CI 0.68–0.94) and a global agreement of 92.1%. The positive predictive value was 89.6%, while the negative predictive value was 93.1%. Sensitivity and specificity were reported at 83.8% and 95.7%, respectively. Table 4 Subgroup analyses of the mean aortic gradient according to different variables. Reference Hand-Held device Correlation ICC test Obesity Present 20.6 (16.4–28.7) 20.2 (11.5–27.9) 0.63 0.59 Absent 32 (20.7–46.8) 30.7 (16.7–46.9) 0.89 0.88 Suboptimal window Present 28.7 (22.2–41) 27.4 (16.2–39.9) 0.79 0.77 Absent 30.1 (17.2–42.4) 26.7 (16.4–45.2) 0.89 0.89 AF Present 31.9 (23.9–41.7) 28.85 (19.2–42.2) 0.75 0.73 Absent 28.9 (15.5–42.2) 26.3 (15.9–46.4) 0.9 0.89 Degree of aortic stenosis Severe 48.5 (44–59.3) 49.9 (42.8–62.3) 0.73 0.81 Moderate 29 (23.7–33.1) 26.3 (21.8–30.7) 0.52 0.43 Mild 14.2 (12.1–16.4) 11.5 (8.8–16.2) 0.35 0.31 LF/LG 26.6 (23.6–29.6) 25.6 (20.4–30.9) 0.69 0.63 Abbreviations: AF: Atrial fibrillation; ICC: Intraclass correlation coefficient; LF/LG: Low flow / low gradient. DATA AVAILABILITY STATEMENT The data underlying this article will be shared on reasonable request to the corresponding author. However, other measurements of the aortic valve demonstrated poorer agreement. The Vmax and VTI showed good agreement (ICC = 0.71 (95% CI: 0.6–0.81); r = 0.79 & (ICC = 0.81 (95% CI: 0.71–0.91); r = 0.86, respectively). In contrast, LVOT diameter and LVOT VTI had poorer agreement (ICC = 0.59 (95% CI: 0.5–0.7); r = 0.59 & (ICC = 0.28 (95% CI: 0.21–0.36); r = 0.76, respectively). Hence, the calculations derived from these measurements showed lower agreement than expected from mAG values. The result for AVA was an ICC of 0.47 (95% CI: 0.31–0.6) and for VTI ratio an ICC of 0.43 (0.27–0.59). (Table 2 ). To minimize the error derived from LVOT measurement, we also calculated a modified AVA of the HHUD device using the LVOT diameter measured by the reference test which increased the value of ICC from 0.47 to 0.51. Considering the lower agreement value of AVA, we compared the patients classified as low flow / low gradient AS. The reference device classified 22 patients (21.9%) as LFLG and the HHUD device 30 (29.7%) patients. The kappa value was 0.23 with a global agreement of 70.3%. However, mAG measurement in this group of patients showed good agreement (ICC: 0.63). 3.3 Subgroup analyses Subgroup analysis revealed a stronger correlation of the mAG value when obesity was absent (ICC: 0.88) compared to when it was present (ICC: 0.59). Similarly, absence of a suboptimal acoustic window (ICC: 0.89) and absence of AF (ICC: 0.89) were associated with higher correlation coefficients compared to their presence (ICC: 0.77 for suboptimal acoustic window; ICC: 0.73 for AF) ( Table 4 ) . 4. Discussion To our knowledge, this study is the first to attempt to validate a new HHUD for the assessment of AS in a real-life scenario, encompassing a diverse range of patients with varying degrees of AS severity. The results of our study demonstrated a good correlation between the mAG values measured using this new HHUD, equipped with CW Doppler capability, and those obtained from a standard reference echocardiogram. Although there was a slight tendency for the HHUD to measure lower values, these differences were not clinically significant. Recently, Sachpekidis et al. published a study comparing this new HHUD to the reference echocardiography for evaluating AS in a controlled environment, with similarly positive results ( 8 ). They reported excellent agreement between the HHUD and the reference test for the measurement of the Vmax. However, both assessments in their study were performed by an expert echocardiographer who was not blinded to the results. In contrast, our study was specifically designed to replicate a typical daily clinical scenario. Our cohort consisted of elderly patients (78.7 years-old) with a high prevalence of obesity (26.3%), AF (23.8%), and 25% had a suboptimal acoustic window. We believe that the characteristics of our sample closely reflect the real-world population of AS patients commonly encountered in clinical practice. Additionally, in most clinical settings, HHUD assessments are performed by operators with varying levels of experience, typically ASE Level I or II. Therefore, we intentinoally designed our study to be conducted by a single operator with intermediate experience (ASE Level II), which we consider representative of most bedside HHUD evaluations. The HHUD results were then compared with gold standard studies performed by experienced echocardiographers (ASE Level III) using high-end ultrasound machines. Overall, our study demonstrated a lower level of agreement across various parameters when compared to the findings of Sachkepidis et al. This discrepancy can be attributed to several factors, particularly the fact that an experienced operator conducted both the standard and HHUD studies in their research, without being blinded to the results of the other technique. Nevertheless, the level of agreement observed in our study was sufficient for a reliable quantitative estimation of AS severity. Importantly, we found that the HHUD had an excellent accuracy in identifying patients with SAS by evaluating mAG, with a kappa of 0.81 and predictive values exceeding 90%. This is a notable finding, as it highlights the potential utility of the device, considering that handheld ultrasound devices are not intended to replace conventional evaluations in the cardiac imaging laboratory by expert echocardiographers using high-quality equipment. Instead, their role in daily clinical practice is to provide a rapid, initial assessment at the patient's bedside, as recommended by the European Association of Cardiovascular Imaging for focused cardiac ultrasound ( 17 ). While the assessment of AS is not currently included among the applications for focused ultrasound in acute settings, our findings could support the use of HHUDs with CW Doppler capability in this context in future guidelines. When the recommendations for focused cardiac ultrasound were developed, most HHUDs lacked high-quality color Doppler, and few had pulsed-wave (PW) Doppler. Thus, the absence of valvular disease quantification in those recommendations is understandable, primarily due to the technical limitations of the HHUDs available at that time. However, with the advent of new HHUDs featuring enhanced Doppler capabilities, a more comprehensive echocardiographic evaluation could be performed, especially after an initial assessment in emergency situations raises suspicion of AS. The results of our study, conducted in a setting resembling real clinical practice, suggest that performing an initial assessment with the HHUD is a feasible option. Potential scenarios where the portability of this device may be beneficial include the first evaluation of patients with suspected AS in an emergency setting, during on-call shifts, or for follow-up of AS patients in outpatient clinics. Besides, although a formal cost-effectiveness analysis has not been performed, the relatively lower cost of these devices could have a significant impact in rural or resource-limited settings. 4.1 Study limitations This is a single-center study with a somewhat limited sample-size. The HHUD examination was conducted by a single operator with moderate experience (Level II) while the reference test was performed by multiple experienced echocardiographers (Level III). This could be seen both as a limitation and a strength. While it makes the results more generalizable, it may have contributed to lower agreement levels. Additionally, the reduced agreement in LVOT and LVOT VTI measurements could lead to an overestimation in certain subgroups of severe AS patients, particularly those with discordant mAG and AVA (e.g., low-flow, low-gradient AS). Another limitation is that the operators were aware that the patients had some degree of AS, meaning the study was not fully blinded. Finally, we did not conduct a comprehensive analysis of interobserver and intraobserver variability between operators. 4.2 Future directions While we observed promising levels of agreement, these findings should be confirmed in a larger, multicenter, international study. Additionally, a full assessment of all recommended AS parameters is necessary to fully validate this device. Validation studies in specific settings (e.g., rural or low-resource environments) would also help evaluate the device’s portability and cost-effectiveness, particularly in scenarios where practitioners with minimal echocardiography training might benefit from using this technology. 4.3 Conclusion Based on the results of this study, this HHUD device with continuous Doppler capability appears to be a suitable option for bedside assessment of AS by a moderately experienced operator in a real-life clinical scenario. While the HHUD tended to slightly underestimate mAG values, it was still sufficiently accurate to correctly assess AS severity in the majority of patients. Declarations Central figure. Graphical abstract summarizing the design and results of the study. Upper figure showing a caption of continuous wave doppler corresponds to the hand-held device. Lower figure corresponds to the reference echocardiography device. Upper right figure corresponds to scatter graph showing the correlation between the mean aortic gradient and lower right figure corresponds to Bland-Altman agreement graph. Supplementary Fig. 1. Flow-chart of patient selection. 5. FUNDING This work was financially supported by a grant from Instituto de Investigación Sanitaria, IDIVAL. EchoNous™ did not contribute with any founding to this study. Author Contribution J.Z., A.M., R.P.B., M.L., L.R., G.M., and J.A. VdP. conceived the study's concept and protocol. J.Z. and J.A. VdP. drafted the main manuscript. All authors reviewed and approved the final manuscript. Data Availability The data underlying this article will be shared on reasonable request to the corresponding author. References Iung B, Delgado V, Rosenhek R, Price S, Prendergast B, Wendler O et al (2019) Contemporary Presentation and Management of Valvular Heart Disease. 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Statist Med 17(1):101–110 Neskovic AN, Skinner H, Price S, Via G, De Hert S, Stankovic I et al (2018) Focus cardiac ultrasound core curriculum and core syllabus of the European Association of Cardiovascular Imaging. Eur Heart J - Cardiovasc Imaging 19(5):475–481 Additional Declarations No competing interests reported. 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Zubiaur","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYBACxgYwIQEk+R8+AJI8fCRo4WE2AJFsxFsFVAzSyEBQC3N77+HPvDss5A1unz1W+TXHToaNgfnhoxv4LOg5l2DMe0bCcMO5vLTbstuSgQ5jMzbOwadlRo5BMm+bBOOGMwxmtyW3MQO18LBJE9JyGKjFHqSlWHJbPVFaDJuBWhI3nOExY/y47TARWnrOGDPOPSORPPMMW7I047bjPGzMBPxi2N5j/OHtjjrbvjPMBz/+3FZtz8/e/PAxXi0NSBxmHjCJRzkIyKO48gcB1aNgFIyCUTAyAQA2VURsYUGsVQAAAABJRU5ErkJggg==","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jon","middleName":"","lastName":"Zubiaur","suffix":""},{"id":367346485,"identity":"6ba8882c-b5d7-4a43-8383-ecfe53192d2d","order_by":1,"name":"Adrián Margarida de Castro","email":"","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Adrián","middleName":"Margarida","lastName":"de Castro","suffix":""},{"id":367346486,"identity":"8fd3329a-e90a-41fe-976e-3749847ae58c","order_by":2,"name":"Raquel Pérez-Barquín","email":"","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Raquel","middleName":"","lastName":"Pérez-Barquín","suffix":""},{"id":367346487,"identity":"0775f8d7-ec38-4086-9ee6-f60ff0b62419","order_by":3,"name":"Manuel Lozano González","email":"","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Manuel","middleName":"Lozano","lastName":"González","suffix":""},{"id":367346488,"identity":"105f405c-80cb-4ee4-b497-e85398a2f92c","order_by":4,"name":"Gonzalo Martin Gorria","email":"","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Gonzalo","middleName":"Martin","lastName":"Gorria","suffix":""},{"id":367346489,"identity":"bdd8a7de-e995-4a6f-847c-fcc574a7f061","order_by":5,"name":"Luis Javier Ruiz Guerrero","email":"","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"Javier Ruiz","lastName":"Guerrero","suffix":""},{"id":367346490,"identity":"d36f0071-b257-4439-bbdf-b76ef996137e","order_by":6,"name":"Andrea Teira Calderon","email":"","orcid":"","institution":"Hospital Universitari i Politècnic La Fe","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"Teira","lastName":"Calderon","suffix":""},{"id":367346491,"identity":"fd7125cd-fd3a-430a-bb30-6948a8f77756","order_by":7,"name":"Ignacio Santiago Setien","email":"","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ignacio","middleName":"Santiago","lastName":"Setien","suffix":""},{"id":367346492,"identity":"a8a9a207-f556-4554-a53f-facf17760785","order_by":8,"name":"David Serrano Lozano","email":"","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"Serrano","lastName":"Lozano","suffix":""},{"id":367346493,"identity":"d4294638-96b6-4e88-b6cc-ba85b526470c","order_by":9,"name":"Francisco González Vilchez","email":"","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Francisco","middleName":"González","lastName":"Vilchez","suffix":""},{"id":367346494,"identity":"1ceb7806-2078-469c-8e62-c4a0ff71afd7","order_by":10,"name":"Jose Antonio Vázquez de Prada","email":"","orcid":"","institution":"Marqués de Valdecilla University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jose","middleName":"Antonio Vázquez","lastName":"de Prada","suffix":""}],"badges":[],"createdAt":"2024-09-25 16:53:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5153609/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5153609/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10554-024-03320-7","type":"published","date":"2024-12-31T15:57:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68213953,"identity":"7d3ef7ac-37bc-421c-8780-4070d30397c2","added_by":"auto","created_at":"2024-11-04 18:34:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2713746,"visible":true,"origin":"","legend":"\u003cp\u003eImages of the measurement of mean aortic gradient by the hand-held ultrasound device (left image) and the reference echocardiograph (right image).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5153609/v1/808db0c5430764b4d4b1f718.png"},{"id":68214181,"identity":"b64ffa94-ec88-4f8c-8a23-11a839860755","added_by":"auto","created_at":"2024-11-04 18:42:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":36198,"visible":true,"origin":"","legend":"\u003cp\u003eScatter graph showing the correlation between the mean aortic gradient measured by reference echocardiograph (y axis) and the mean aortic gradient measured by the hand-held echocardiograph (x axis).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5153609/v1/d93c85950151575ec24c7f61.png"},{"id":68213956,"identity":"c46f5f0b-3fe6-42ba-8fd9-e853927ea0db","added_by":"auto","created_at":"2024-11-04 18:34:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":927887,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman agreement graph for mean aortic gradient measurements by the two echocardiographs.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5153609/v1/b26cb6bb8336be95c6dba75f.png"},{"id":68213955,"identity":"cafc52a9-ec93-4a16-b090-b96afaff45ad","added_by":"auto","created_at":"2024-11-04 18:34:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":79770,"visible":true,"origin":"","legend":"\u003cp\u003ePassing-Bablok regression line for mean aortic gradient measurements by the two echocardiographs.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5153609/v1/f888bd70eb211fc38729e8a5.png"},{"id":73093354,"identity":"34000fc7-8e02-4c0f-b205-e823cc175633","added_by":"auto","created_at":"2025-01-06 16:14:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4120809,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5153609/v1/0bc49bbf-6892-4da6-97b4-0efff5913bc7.pdf"},{"id":68213957,"identity":"1fb5d387-78e9-481e-a90c-9b0d746d6d10","added_by":"auto","created_at":"2024-11-04 18:34:59","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":627495,"visible":true,"origin":"","legend":"","description":"","filename":"Centralillustration.tif","url":"https://assets-eu.researchsquare.com/files/rs-5153609/v1/e8c1922ba10523c23323b0dc.tif"},{"id":68213958,"identity":"884f42c5-f41a-47e3-b4e1-6b00e1264100","added_by":"auto","created_at":"2024-11-04 18:34:59","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":339626,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYFIGURE1.tif","url":"https://assets-eu.researchsquare.com/files/rs-5153609/v1/0cb068fa26eff2e85c3cdd00.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Validation of a hand-held Ultrasound device in the evaluation of Aortic Stenosis","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eAortic stenosis (AS) is the most common valve disease requiring either surgical or percutaneous intervention in Europe and North America (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The progressively increasing age of the population also explains the growing prevalence of this condition (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Simultaneously, safe and less invasive procedures, such as transcatheter aortic valve replacement (TAVR), are now available and provide effective treatment (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). According to the most recent clinical practice guidelines, the evaluation of the hemodynamic severity of AS should be performed by echocardiography (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Among the recommended parameters to assess are the mean aortic gradient, aortic valve area, peak aortic velocity, dimensionless index, and ventricular ejection fraction, which should guide the decision to intervene, along with consideration of the patient's symptoms and comorbidities.\u003c/p\u003e \u003cp\u003eRecent technological advances have resulted in the development of handheld ultrasound devices (HHUD) with high-quality imaging. One of the main advantages of these devices is that they provide rapid and effective bedside assessments. Additionally, this technology is continuously improving and is currently relatively inexpensive. These features have made the HHUD a valuable tool for use both in the inpatient and outpatient hospital settings. As a result, research interest in this field has increased (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThus, some studies have attempted to assess AS using two-dimensional imaging and a semi-quantitative approach. These studies rely on indirect parameters such as the presence of valve calcium and the mobility of the aortic leaflets. Since these parameters essentially subjective, they are considered only as an option for initial screening (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, a complete assessment of AS requires a quantitative approach, specifically the measurement of aortic transvalvular velocity. For this, continuous wave (CW) Doppler is necessary. Until recently, this technology was not available in portable echocardiography devices but the Kosmos\u0026reg; (EchoNous) device, a HHUD with CW Doppler capability, now allows for the quantitative evaluation of AS by measuring aortic transvalvular velocities for the first time.\u003c/p\u003e \u003cp\u003eRecently, Sachpekidis and colleagues studied the Kosmos device for the evaluation of AS in a controlled setting, reporting favorable results (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In their study, an experienced operator conducted the HHUD examination, but he was not blinded to the previous findings obtained with a conventional device. Therefore, while this study serves as a validation of the device for quantificatifyng transaortic velocities with a CW Doppler-equipped HHUD, it differs from how this technique is typically used in daily clinical practice. In real-life settings, HHUD bedside studies are often performed by clinicians who are not necessarily experts in echocardiography, most of whom have only an intermediate level of experience in echocardiography (as defined by the American Society of Echocardiography (ASE) level II) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe objective of our study is to validate the ability of the Kosmos HHUD to quantify AS in a real-life setting, daily practice setting. To this end, we designed a study comparing the results of an HHUD examination performed by an operator with intermediate experienced (ASE level II), who was blinded to the reference standard echocardiographic assessment conducted by experienced operators (ASE level III) at the Echocardiography Laboratory using high-end equipment.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design\u003c/h2\u003e \u003cp\u003eWe conducted a prospective, observational, single-center study that included patients diagnosed with AS who had undergone a previous echocardiogram. The study was designed following the 2015 Standards for Reporting Diagnostic Accuracy (STARD) statement (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Approval for the study was obtained from the Cantabria Institutional Review Board (approval number MTVAL1907).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Participants\u003c/h2\u003e \u003cp\u003ePatients were randomly recruited from the cardiac imaging laboratory at a tertiary referral center in the northern Spain between October 2022 and August 2023. They had been previously diagnosed with AS (any severity grade) via echocardiography, based on the definition of the 2021 European Society of Cardiology (ESC) guidelines (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). All patients were over 18 years of age and provided informed consent prior to participation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Methods\u003c/h2\u003e \u003cp\u003eImmediately after undergoing a standard echocardiography study, a focused echocardiographic assessment of transaortic velocities using the Kosmos HHUD was performed. These assessments were conducted by two independent cardiologists, blinded to each other\u0026acute;s findings. Additionally, the cardiologist performing the HHUD study was blinded to the patient\u0026acute;s clinical history and previous echocardiograms. The cardiologist conducting the reference echocardiogram had expert-level (level III) training in echocardiography as per the 2019 ASE Advanced Training Statement on Echocardiography (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). To simulate a real-world clinical setting, the cardiologist performing the HHUD had intermediate-level training (ASE level II). Both echocardiographic studies were performed consecutively to ensure no significant clinical or hemodynamic changes occurred between them. Blood pressure and heart rate (HR) were measured before each test.\u003c/p\u003e \u003cp\u003eThe reference echocardiography system used was the Philips EPIQ CVx\u0026trade; (Philips Healthcare, Amsterdam, The Netherlands), while the HHUD device was the Kosmos (EchoNous\u0026trade;) with CW Doppler capability \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Clinical definitions\u003c/h2\u003e \u003cp\u003eAS was defined according to the 2021 ESC guidelines and the 2021 practical guidelines from the British Society of Echocardiography (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Severe aortic stenosis (SAS) was defined as a mean aortic gradient (mAG) of \u0026ge;\u0026thinsp;40 mmHg. Moderate aortic stenosis (MAS) was defined as a mAG between 20 mmHg and 39 mmHg. Mild aortic stenosis (MiAS) was defined as a mAG of \u0026lt;\u0026thinsp;20 mmHg. Low-flow, low gradient AS was defined as mAG\u0026thinsp;\u0026lt;\u0026thinsp;40mmHg, aortic valve area (AVA)\u0026thinsp;\u0026le;\u0026thinsp;1.0 cm\u003csup\u003e2\u003c/sup\u003e and stroke volume index\u0026thinsp;\u0026lt;\u0026thinsp;35ml/m\u003csup\u003e2\u003c/sup\u003e. Left ventricle ejection fraction (LVEF) was estimated using the Simpson biplane method, with impaired LVED defined as \u0026le;\u0026thinsp;40%.\u003c/p\u003e \u003cp\u003eBody surface area (SA) was calculated using the DuBois formula. A suboptimal acoustic window was defined by the reference echocardiographer. Obesity was classified as a body mass index (BMI)\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e. Information on previous lung disease, neurological disease, and atrial fibrillation (AF) was extracted from the patients' electronic medical records.\u003c/p\u003e \u003cp\u003eWe chose mAG as the main variable in our study due to its importance in determining AS severity. We also measured maximum aortic velocity (Vmax), aortic velocity-time integral (VTI), left ventricle outflow tract (LVOT) diameter and LVOT VTI, and estimated the VTI ratio and aortic valve area (AVA). All measurements and estimates were conducted according to international guidelines (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The primary outcome variable was the value of the intraclass correlation (ICC) between the mAG values obtained from the two echocardiographic studies. We also analyzed the ICC for the other quantitative variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eQuantitative variables were expressed as median and interquartile range (IQR) (25th \u0026ndash; 75th percentiles), while qualitative variables were expressed as frequencies (n, %). Differences between quantitative variables were assessed using the Mann-Whitney U test, and differences between qualitative variables were evaluated with the χ\u0026sup2; test for. A p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eWe performed an ICC test between the quantitative variables. We performed a kappa test between the qualitative variables. We performed a Bland-Altman and a Passing Bablok analysis to graphically describe the outcomes of our data.\u003c/p\u003e \u003cp\u003eStatistical analyses were carried out using STATA 16 software (StataCorp. 2019. \u003cem\u003eStata Statistical Software: Release 16\u003c/em\u003e. College Station, TX: StataCorp LLC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Sample size calculation\u003c/h2\u003e \u003cp\u003eWe estimated the sample size with the formula provided by Bonett and Walter (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). We selected the most conservative sample size estimate, resulting in a calculated sample size of 101 patients.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Participants\u003c/h2\u003e \u003cp\u003eThe enrolment period commenced in October 2022 and concluded in August 2023. In accordance with the estimated sample size calculation, 101 patients were recruited from a pool of 105 eligible patients. Four patients were excluded (One patient received an alternative diagnosis, 3 patients refused to participate) \u003cb\u003e(Supplementary Fig.\u0026nbsp;1).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe study patients were 78.7-year-old and 35.6% were female. The median BMI was 26.3 kg/m\u003csup\u003e2\u003c/sup\u003e, and the median SA was 1.8m\u003csup\u003e2\u003c/sup\u003e. A total of 22 patients (21.8%) were classified as obese. In 25 patients (23.8%) the acoustic window was considered as suboptimal. Twenty-four patients (23.8%) were in AF, 6 (5.9%) had a neurological disorder, 7 (6.9%) a respiratory disorder and 4 (4%) a chest malformation. Median \u0026ldquo;mean arterial tension\u0026rdquo; was 92 mmHg (interquartile range: 84.7\u0026ndash;100 mmHg) and HR was 70 bpm (interquartile range: 62\u0026ndash;75 bpm) when HHUD test was performed. There were no statistically significant differences in mean arterial tension (p\u0026thinsp;=\u0026thinsp;0.871) and HR (p\u0026thinsp;=\u0026thinsp;0.794) between the reference test and the HHUD test. The median left ventricle ejection fraction (LVEF) was 60% and 19 (18.8%) had impaired LVEF. These baseline characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMain baseline clinical characteristics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;101\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.7 (73\u0026ndash;84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (35.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e165 (156\u0026ndash;171)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73 (64\u0026ndash;82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody surface area by DuBois (m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.8 (1.7\u0026ndash;1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.3 (24.1\u0026ndash;29.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (21.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130 (117\u0026ndash;150)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic blood pressure (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (65\u0026ndash;80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean blood pressure (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (84.7\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate (beats per minute)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (62\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious lung pathology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious neurological pathology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic malformations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuboptimal echocardiographic window\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial Fibrillation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 (50\u0026ndash;65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF\u0026thinsp;\u0026le;\u0026thinsp;40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (18.81%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eValues are shown as \u0026ldquo;median (Interquartile range)\u0026rdquo; or \u0026ldquo;n (%)\u0026rdquo;. Abbreviations: BMI: Body mass index; LVEF: Left ventricular ejection fraction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe HHUD test, focused on the evaluation of aortic valve parameters, took a median time of 9 minutes (interquartile range: 7\u0026ndash;11 minutes) to be performed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Test results\u003c/h2\u003e \u003cp\u003eThe reference test yielded a median mAG of 29 mmHg (interquartile range: 19.8\u0026ndash;42.2 mmHg), whereas the HHUD test resulted in a median mAG of 27.2 mmHg (interquartile range: 16.2\u0026ndash;43.9 mmHg). A strong agreement was observed between the HHUD and reference mAG measurements, as indicated by an ICC of 0.87 (95% CI 0.79\u0026ndash;0.94). Linear regression analysis revealed a good correlation between the two methods (r\u0026thinsp;=\u0026thinsp;0.89; 95% CI 0.85\u0026ndash;0.94) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the measurements by the two echocardiographs and the agreement tests.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHand-Held device\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic valve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eICC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpearman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKappa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Aortic Gradient (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (19.8\u0026ndash;42.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.2 (16.2\u0026ndash;43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum Aortic Velocity (m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e343.5 (282.4\u0026ndash;402.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e309.4 (242.6\u0026ndash;375.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft ventricular outflow tract diameter (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.6 (19.9\u0026ndash;22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.0 (18.9\u0026ndash;22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic VTI (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.2 (59.3\u0026ndash;99.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.1 (54.9\u0026ndash;88.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVOT VTI (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21 (17.1\u0026ndash;24.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.3 (16.4\u0026ndash;22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft ventricular outflow tract area (cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.7 (3.1\u0026ndash;4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (2.8\u0026ndash;3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic valve area (cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.9 (0.7\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.7\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndexed aortic valve area (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.5 (0.4\u0026ndash;0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (0.4\u0026ndash;0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVTI ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.28 (0.19\u0026ndash;0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25 (0.21\u0026ndash;0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic valve opening reduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21 (20.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35 (34.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (33.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45 (44.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (41.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic Valve Calcification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (14.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (21.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36 (35.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (25.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50 (49.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (52.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBicuspid Aortic Valve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eValues are shown as \u0026ldquo;median (Interquartile range)\u0026rdquo; or \u0026ldquo;n (%)\u0026rdquo;. Abbreviations: ICC: Intraclass correlation coefficient; LVOT: Left ventricle outflow tract; VTI: Velocity-time integral.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification of aortic stenosis severity by the two echocardiographs and agreement tests.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade of Aortic Stenosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHand-Held device\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKappa test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAgreement\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (28.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35 (34.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41 (40.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37 (36.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31 (30.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29 (28.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLF/LG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (29.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eLF/LG: Low flow / low gradient.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe Bland \u0026amp; Altman analysis demonstrated that 4 cases (3.9%) exceeded the predefined limit, while 3 cases (2.9%) fell below the limit of agreement (LOA) (\u0026plusmn;\u0026thinsp;17.8 mmHg) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The Passing-Bablok analysis revealed no deviation from linearity, with a constant difference of -3.21 mmHg (95% CI: 0.57\u0026ndash;5.46) but no evidence of proportional difference (95% CI: 0.83\u0026ndash;1.02) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). According to the severity classification of the AS, the reference test diagnosed 31 (30.7%) as SAS, 41 (40.6%) as MAS and 29 (28.7%) as MiAS. Conversely, the HHUD test diagnosed 29 (28.7%) as SAS, 37 (36.6%) as MAS and 35 (34.6%) as MiAS. Kappa analysis showed good agreement with a value of 0.7. Total agreement within each grade exceeded 80.2% \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Notably, the HHUD exhibited excellent agreement for classifying AS, particularly in the SAS grade, with a kappa value of 0.81 (95% CI 0.68\u0026ndash;0.94) and a global agreement of 92.1%. The positive predictive value was 89.6%, while the negative predictive value was 93.1%. Sensitivity and specificity were reported at 83.8% and 95.7%, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSubgroup analyses of the mean aortic gradient according to different variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHand-Held device\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCorrelation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eICC test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.6 (16.4\u0026ndash;28.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.2 (11.5\u0026ndash;27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32 (20.7\u0026ndash;46.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.7 (16.7\u0026ndash;46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuboptimal window\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.7 (22.2\u0026ndash;41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.4 (16.2\u0026ndash;39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.1 (17.2\u0026ndash;42.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.7 (16.4\u0026ndash;45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.9 (23.9\u0026ndash;41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.85 (19.2\u0026ndash;42.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.9 (15.5\u0026ndash;42.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.3 (15.9\u0026ndash;46.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDegree of aortic stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48.5 (44\u0026ndash;59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.9 (42.8\u0026ndash;62.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (23.7\u0026ndash;33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.3 (21.8\u0026ndash;30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.2 (12.1\u0026ndash;16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.5 (8.8\u0026ndash;16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLF/LG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.6 (23.6\u0026ndash;29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.6 (20.4\u0026ndash;30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: AF: Atrial fibrillation; ICC: Intraclass correlation coefficient; LF/LG: Low flow / low gradient.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eDATA AVAILABILITY STATEMENT\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eThe data underlying this article will be shared on reasonable request to the corresponding author.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHowever, other measurements of the aortic valve demonstrated poorer agreement. The Vmax and VTI showed good agreement (ICC\u0026thinsp;=\u0026thinsp;0.71 (95% CI: 0.6\u0026ndash;0.81); r\u0026thinsp;=\u0026thinsp;0.79 \u0026amp; (ICC\u0026thinsp;=\u0026thinsp;0.81 (95% CI: 0.71\u0026ndash;0.91); r\u0026thinsp;=\u0026thinsp;0.86, respectively). In contrast, LVOT diameter and LVOT VTI had poorer agreement (ICC\u0026thinsp;=\u0026thinsp;0.59 (95% CI: 0.5\u0026ndash;0.7); r\u0026thinsp;=\u0026thinsp;0.59 \u0026amp; (ICC\u0026thinsp;=\u0026thinsp;0.28 (95% CI: 0.21\u0026ndash;0.36); r\u0026thinsp;=\u0026thinsp;0.76, respectively). Hence, the calculations derived from these measurements showed lower agreement than expected from mAG values. The result for AVA was an ICC of 0.47 (95% CI: 0.31\u0026ndash;0.6) and for VTI ratio an ICC of 0.43 (0.27\u0026ndash;0.59). (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). To minimize the error derived from LVOT measurement, we also calculated a modified AVA of the HHUD device using the LVOT diameter measured by the reference test which increased the value of ICC from 0.47 to 0.51. Considering the lower agreement value of AVA, we compared the patients classified as low flow / low gradient AS. The reference device classified 22 patients (21.9%) as LFLG and the HHUD device 30 (29.7%) patients. The kappa value was 0.23 with a global agreement of 70.3%. However, mAG measurement in this group of patients showed good agreement (ICC: 0.63).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Subgroup analyses\u003c/h2\u003e \u003cp\u003eSubgroup analysis revealed a stronger correlation of the mAG value when obesity was absent (ICC: 0.88) compared to when it was present (ICC: 0.59). Similarly, absence of a suboptimal acoustic window (ICC: 0.89) and absence of AF (ICC: 0.89) were associated with higher correlation coefficients compared to their presence (ICC: 0.77 for suboptimal acoustic window; ICC: 0.73 for AF) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":" \u003cp\u003eTo our knowledge, this study is the first to attempt to validate a new HHUD for the assessment of AS in a real-life scenario, encompassing a diverse range of patients with varying degrees of AS severity. The results of our study demonstrated a good correlation between the mAG values measured using this new HHUD, equipped with CW Doppler capability, and those obtained from a standard reference echocardiogram. Although there was a slight tendency for the HHUD to measure lower values, these differences were not clinically significant.\u003c/p\u003e \u003cp\u003eRecently, Sachpekidis et al. published a study comparing this new HHUD to the reference echocardiography for evaluating AS in a controlled environment, with similarly positive results (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). They reported excellent agreement between the HHUD and the reference test for the measurement of the Vmax. However, both assessments in their study were performed by an expert echocardiographer who was not blinded to the results.\u003c/p\u003e \u003cp\u003eIn contrast, our study was specifically designed to replicate a typical daily clinical scenario. Our cohort consisted of elderly patients (78.7 years-old) with a high prevalence of obesity (26.3%), AF (23.8%), and 25% had a suboptimal acoustic window. We believe that the characteristics of our sample closely reflect the real-world population of AS patients commonly encountered in clinical practice. Additionally, in most clinical settings, HHUD assessments are performed by operators with varying levels of experience, typically ASE Level I or II. Therefore, we intentinoally designed our study to be conducted by a single operator with intermediate experience (ASE Level II), which we consider representative of most bedside HHUD evaluations. The HHUD results were then compared with gold standard studies performed by experienced echocardiographers (ASE Level III) using high-end ultrasound machines.\u003c/p\u003e \u003cp\u003eOverall, our study demonstrated a lower level of agreement across various parameters when compared to the findings of Sachkepidis et al. This discrepancy can be attributed to several factors, particularly the fact that an experienced operator conducted both the standard and HHUD studies in their research, without being blinded to the results of the other technique. Nevertheless, the level of agreement observed in our study was sufficient for a reliable quantitative estimation of AS severity.\u003c/p\u003e \u003cp\u003eImportantly, we found that the HHUD had an excellent accuracy in identifying patients with SAS by evaluating mAG, with a kappa of 0.81 and predictive values exceeding 90%. This is a notable finding, as it highlights the potential utility of the device, considering that handheld ultrasound devices are not intended to replace conventional evaluations in the cardiac imaging laboratory by expert echocardiographers using high-quality equipment. Instead, their role in daily clinical practice is to provide a rapid, initial assessment at the patient's bedside, as recommended by the European Association of Cardiovascular Imaging for focused cardiac ultrasound (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). While the assessment of AS is not currently included among the applications for focused ultrasound in acute settings, our findings could support the use of HHUDs with CW Doppler capability in this context in future guidelines. When the recommendations for focused cardiac ultrasound were developed, most HHUDs lacked high-quality color Doppler, and few had pulsed-wave (PW) Doppler. Thus, the absence of valvular disease quantification in those recommendations is understandable, primarily due to the technical limitations of the HHUDs available at that time. However, with the advent of new HHUDs featuring enhanced Doppler capabilities, a more comprehensive echocardiographic evaluation could be performed, especially after an initial assessment in emergency situations raises suspicion of AS.\u003c/p\u003e \u003cp\u003eThe results of our study, conducted in a setting resembling real clinical practice, suggest that performing an initial assessment with the HHUD is a feasible option. Potential scenarios where the portability of this device may be beneficial include the first evaluation of patients with suspected AS in an emergency setting, during on-call shifts, or for follow-up of AS patients in outpatient clinics. Besides, although a formal cost-effectiveness analysis has not been performed, the relatively lower cost of these devices could have a significant impact in rural or resource-limited settings.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Study limitations\u003c/h2\u003e \u003cp\u003eThis is a single-center study with a somewhat limited sample-size. The HHUD examination was conducted by a single operator with moderate experience (Level II) while the reference test was performed by multiple experienced echocardiographers (Level III). This could be seen both as a limitation and a strength. While it makes the results more generalizable, it may have contributed to lower agreement levels. Additionally, the reduced agreement in LVOT and LVOT VTI measurements could lead to an overestimation in certain subgroups of severe AS patients, particularly those with discordant mAG and AVA (e.g., low-flow, low-gradient AS). Another limitation is that the operators were aware that the patients had some degree of AS, meaning the study was not fully blinded. Finally, we did not conduct a comprehensive analysis of interobserver and intraobserver variability between operators.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Future directions\u003c/h2\u003e \u003cp\u003eWhile we observed promising levels of agreement, these findings should be confirmed in a larger, multicenter, international study. Additionally, a full assessment of all recommended AS parameters is necessary to fully validate this device. Validation studies in specific settings (e.g., rural or low-resource environments) would also help evaluate the device\u0026rsquo;s portability and cost-effectiveness, particularly in scenarios where practitioners with minimal echocardiography training might benefit from using this technology.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Conclusion\u003c/h2\u003e \u003cp\u003eBased on the results of this study, this HHUD device with continuous Doppler capability appears to be a suitable option for bedside assessment of AS by a moderately experienced operator in a real-life clinical scenario. While the HHUD tended to slightly underestimate mAG values, it was still sufficiently accurate to correctly assess AS severity in the majority of patients.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCentral figure.\u003c/h2\u003e \u003cp\u003eGraphical abstract summarizing the design and results of the study. Upper figure showing a caption of continuous wave doppler corresponds to the hand-held device. Lower figure corresponds to the reference echocardiography device. Upper right figure corresponds to scatter graph showing the correlation between the mean aortic gradient and lower right figure corresponds to Bland-Altman agreement graph.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSupplementary Fig.\u0026nbsp;1.\u003c/strong\u003e \u003cp\u003eFlow-chart of patient selection.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003e5. FUNDING\u003c/h2\u003e \u003cp\u003eThis work was financially supported by a grant from Instituto de Investigaci\u0026oacute;n Sanitaria, IDIVAL. EchoNous\u0026trade; did not contribute with any founding to this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.Z., A.M., R.P.B., M.L., L.R., G.M., and J.A. VdP. conceived the study's concept and protocol. J.Z. and J.A. VdP. drafted the main manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data underlying this article will be shared on reasonable request to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIung B, Delgado V, Rosenhek R, Price S, Prendergast B, Wendler O et al (2019) Contemporary Presentation and Management of Valvular Heart Disease. Circulation 140(14):1156\u0026ndash;1169\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ed\u0026rsquo;Arcy JL, Coffey S, Loudon MA, Kennedy A, Pearson-Stuttard J, Birks J et al (2016) Large-scale community echocardiographic screening reveals a major burden of undiagnosed valvular heart disease in older people: the OxVALVE Population Cohort Study. Eur Heart J 37(47):3515\u0026ndash;3522\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReardon MJ, Van Mieghem NM, Popma JJ, Kleiman NS, S\u0026oslash;ndergaard L, Mumtaz M et al \u003cdiv class=\"ExternalRefDOI\"\u003ehttps://doi.org/10.1056\u003c/div\u003e/NEJMoa1700456. Massachusetts Medical Society; 2017 [cited 2021 Dec 25]. Surgical or Transcatheter Aortic-Valve Replacement in Intermediate-Risk Patients. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nejm.org/doi/10.1056/NEJMoa1700456\u003c/span\u003e\u003cspan address=\"https://www.nejm.org/doi/10.1056/NEJMoa1700456\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVahanian A, Beyersdorf F, Praz F, Milojevic M, Baldus S, Bauersachs J et al (2022) 2021 ESC/EACTS Guidelines for the management of valvular heart disease: Developed by the Task Force for the management of valvular heart disease of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J 43(7):561\u0026ndash;632\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRing L, Shah BN, Bhattacharyya S, Harkness A, Belham M, Oxborough D et al (2021) Echocardiographic assessment of aortic stenosis: a practical guideline from the British Society of Echocardiography. Echo Res Pract 8(1):G19\u0026ndash;59\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaumgartner H, Hung J, Bermejo J, Chambers JB, Edvardsen T, Goldstein S et al (2017) Recommendations on the Echocardiographic Assessment of Aortic Valve Stenosis: A Focused Update from the European Association of Cardiovascular Imaging and the American Society of Echocardiography. J Am Soc Echocardiogr 30(4):372\u0026ndash;392\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaribeau Y, Sharkey A, Chaudhary O, Krumm S, Fatima H, Mahmood F et al (2020) Handheld Point-of-Care Ultrasound Probes: The New Generation of POCUS. J Cardiothorac Vasc Anesth 34(11):3139\u0026ndash;3145\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSachpekidis V, Papadopoulou SL, Kantartzi V, Styliadis I, Nihoyannopoulos P (2022) A Novel Handheld Echocardiography Device with Continuous-Wave Doppler Capability: Implications for the Evaluation of Aortic Stenosis Severity. J Am Soc Echocardiogr 35(12):1273\u0026ndash;1280\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliams C, Mateescu A, Rees E, Truman K, Elliott C, Bahlay B et al (2019) Point-of-care echocardiographic screening for left-sided valve heart disease: high yield and affordable cost in an elderly cohort recruited in primary practice. Echo Res Pract 6(3):71\u0026ndash;79\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChugh Y, Lohese O, Sorajja P, Garberich R, Stanberry L, Cavalcante J et al (2022) Adoptability and accuracy of point-of-care ultrasound in screening for valvular heart disease in the primary care setting. J Clin Ultrasound 50(2):265\u0026ndash;270\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMj\u0026oslash;lstad OC, Andersen GN, Dalen H, Graven T, Skjetne K, Kleinau JO et al (2013) Feasibility and reliability of point-of-care pocket-size echocardiography performed by medical residents. Eur Heart J Cardiovasc Imaging 14(12):1195\u0026ndash;1202\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWiegers SE, Ryan T, Arrighi JA, Brown SM, Canaday B, Damp JB et al (2019) 2019 ACC/AHA/ASE Advanced Training Statement on Echocardiography (Revision of the 2003 ACC/AHA Clinical Competence Statement on Echocardiography): A Report of the ACC Competency Management Committee. J Am Coll Cardiol 74(3):377\u0026ndash;402\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L et al (2015) STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ 351:h5527\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDweck MR, Loganath K, Bing R, Treibel TA, McCann GP, Newby DE et al (2023) Multi-modality imaging in aortic stenosis: an EACVI clinical consensus document. Eur Heart J Cardiovasc Imaging 24(11):1430\u0026ndash;1443\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonett DG (2002) Sample size requirements for estimating intraclass correlations with desired precision. Statist Med 21(9):1331\u0026ndash;1335\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalter SD, Eliasziw M, Donner A (1998) Sample size and optimal designs for reliability studies. Statist Med 17(1):101\u0026ndash;110\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeskovic AN, Skinner H, Price S, Via G, De Hert S, Stankovic I et al (2018) Focus cardiac ultrasound core curriculum and core syllabus of the European Association of Cardiovascular Imaging. Eur Heart J - Cardiovasc Imaging 19(5):475\u0026ndash;481\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-international-journal-of-cardiovascular-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caim","sideBox":"Learn more about [The International Journal of Cardiovascular Imaging](https://www.springer.com/journal/10554)","snPcode":"10554","submissionUrl":"https://submission.nature.com/new-submission/10554/3","title":"The International Journal of Cardiovascular Imaging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Echocardiography, point of care ultrasound, hand-held ultrasound, aortic stenosis","lastPublishedDoi":"10.21203/rs.3.rs-5153609/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5153609/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eHand-held ultrasound devices (HHUD) are increasingly used in routine clinical practice, though they lacked continuous (CW) Doppler capability until recently. There is limited evidence on the utility of HHUD in assessing aortic stenosis (AS) in real-world settings. Our goal is to validate a new HHUD with CW Doppler assessing AS hemodynamic severity.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eAn observational, single-center study was conducted with patients diagnosed with AS. Following a reference echocardiographic study in the cardiac imaging laboratory, a HHUD with CW Doppler (Kosmos, EchoNous\u0026trade;) was used by an operator with intermediate echocardiography experience (American Society of Echocardiography, level II). The focus was on measuring aortic transvalvular Doppler velocities. Agreement between the mean trans-aortic gradient (mAG) was assessed using the intraclass correlation coefficient (ICC) test. A total of 101 patients were included.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe reference test obtained a mAG of 29 mmHg (19.8\u0026ndash;42.2), while the HHUD test showed 27.2 mmHg (16.2\u0026ndash;43.9). A strong correlation was observed (r\u0026thinsp;=\u0026thinsp;0.89), with an ICC value of 0.87 and no significant bias (1.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9). The HHUD demonstrated excellent ability to identify severe AS (kappa\u0026thinsp;=\u0026thinsp;0.81, 95% CI 0.68\u0026ndash;0.94; global agreement 92.1%). Agreement was lower in patients with obesity, poor acoustic windows, or atrial fibrillation.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe HHUD showed good agreement with standard echocardiography in assessing AS. While it slightly underestimated mAG, it was accurate enough to reliably quantify AS severity.\u003c/p\u003e","manuscriptTitle":"Validation of a hand-held Ultrasound device in the evaluation of Aortic Stenosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-04 18:34:55","doi":"10.21203/rs.3.rs-5153609/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-17T16:25:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-17T09:28:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"310848692423039774095264124830159515791","date":"2024-10-05T11:04:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-28T08:50:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-26T03:17:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-26T03:17:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"The International Journal of Cardiovascular Imaging","date":"2024-09-25T16:43:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"the-international-journal-of-cardiovascular-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caim","sideBox":"Learn more about [The International Journal of Cardiovascular Imaging](https://www.springer.com/journal/10554)","snPcode":"10554","submissionUrl":"https://submission.nature.com/new-submission/10554/3","title":"The International Journal of Cardiovascular Imaging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"94965731-c4c3-4964-b79f-7300f493985b","owner":[],"postedDate":"November 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-06T16:02:00+00:00","versionOfRecord":{"articleIdentity":"rs-5153609","link":"https://doi.org/10.1007/s10554-024-03320-7","journal":{"identity":"the-international-journal-of-cardiovascular-imaging","isVorOnly":false,"title":"The International Journal of Cardiovascular Imaging"},"publishedOn":"2024-12-31 15:57:32","publishedOnDateReadable":"December 31st, 2024"},"versionCreatedAt":"2024-11-04 18:34:55","video":"","vorDoi":"10.1007/s10554-024-03320-7","vorDoiUrl":"https://doi.org/10.1007/s10554-024-03320-7","workflowStages":[]},"version":"v1","identity":"rs-5153609","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5153609","identity":"rs-5153609","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}