Data privacy and smart home energy appliances: A stated choice experiment.

Data privacy in smart homes is receiving increasing attention due to the growing adoption of smart appliances. Adoption of smart appliances can bring benefits, including energy consumption reduction. This study investigates how people made the trade-offs between sharing privacy-sensitive data and the potential environmental and economic benefits of smart home energy appliances using discrete choice modeling. The findings reveal that the trade-off is mainly affected by four product attributes: the type of data that is processed, the reason why this data is processed, the data sharing frequency, and the financial benefit gained from the smart home appliances. Specifically, individuals tend to share less data daily for their daily routine convenience and demand a (theoretical) financial compensation for the data sharing. The results also show that privacy attitudes are not related to data sharing preferences, while socio-demographics, including gender, age, and income, are. The results emphasize the gap between people's attitudes and behaviors regarding data privacy. This research serves as a foundation for further investigations and can be used by smart appliance retailers, manufacturers, and governments for designing research and development focus and energy reduction incentives, respectively.

Role of Quantitation of Saline Bubble Studies in Patients with Liver Cirrhosis.

OBJECTIVE: Microbubble contrast echocardiography with a late positive signal enables the detection of intrapulmonary vascular dilation, including hepatopulmonary syndrome, in patients with end-stage liver disease. We assessed the relationship between the severity of bubble study and clinical outcome. METHODS: We retrospectively analyzed 163 consecutive patients with liver cirrhosis who underwent an echocardiogram with bubble study from 2018 to 2021. Patients who were diagnosed with a late positive signal were divided into three groups: grade 1 (1-9 bubbles), grade 2 (10-30 bubbles) and grade 3 (>30 bubbles). RESULTS: Fifty-six percent of the patients had a late positive bubble study (grade 1: 31%, grade 2: 23%, grade 3: 46%). Patients with grade 3 had a significantly higher international normalized ratio, model for end-stage liver disease score and Child-Pugh score and a lower peripheral oxygen saturation compared with patients with a negative study. In patients undergoing liver transplant (LT), survival rates were similar among the groups (3-mo: >87%, 1-y: >87%, 2-y: >83%). However, survival rate was lower in grade 3 patients without LT (3-mo: 81%, 1-y: 64%, 2-y: 39%). CONCLUSION: Patients with grade 3 had much worse mortality without LT compared with other groups. However, after LT, all grades had equal survival. Therefore, patients with grade 3 may be considered as higher priority for LT.

Usefulness of Integrating Heart Failure Risk Factors Into Impairment of Global Longitudinal Strain to Predict Anthracycline-Related Cardiac Dysfunction.

The prediction of cancer therapeutics-related cardiac dysfunction (CTRCD) is an essential aspect of care for individuals who receive potentially cardiotoxic oncologic treatments. Certain clinical risk factors have been described for incident CTRCD, and measurement of left ventricular (LV) longitudinal strain by speckle tracking 2-dimensional echocardiography (2DE) is the best-validated myocardial mechanical imaging assessment to detect subtle changes in LV function during cancer treatment. However, the direct integration of clinical and imaging risk factors to predict CTRCD has not yet been extensively examined. This was a retrospective study of 183 women with breast cancer aged 50.9 ± 10.8 years who received treatment with anthracyclines (doxorubicin dose of 422 ± 69 mg/m2, with 41.2% of subjects also receiving trastuzumab) and underwent 2DE at clinically determined intervals. CTRCD was diagnosed when LV ejection fraction dropped ≥10% to a subnormal (<53%) value by 2DE. Left ventricular global longitudinal strain (LV-GLS) was assessed offline. The risk prediction tool based only on clinical factors previously described by Ezaz et al was applied to our cohort and accurately stratified these subjects into low-, intermediate-, and high-risk groups, with incident CTRCD in 7.4%, 26.9%, and 54.6%, respectively (chi-square = 20.7, p <0.0001). We developed novel multivariate models to predict CTRCD using (1) demographic variables only (c = 0.8674), (2) echocardiographic (peak LV-GLS) variables only (c = 0.8440), or (3) a combination of demographic and echocardiographic variables, with the combined model exhibiting superior receiver-operating characteristics (c = 0.9629). In conclusion, estimation of CTRCD risk should integrate all available data, including both clinical variables and an imaging assessment.

Feasibility, accuracy, and reproducibility of real-time full-volume 3D transthoracic echocardiography to measure LV volumes and systolic function: a fully automated endocardial contouring algorithm in sinus rhythm and atrial fibrillation.

OBJECTIVES: To assess the feasibility, accuracy, and reproducibility of real-time full-volume 3-dimensional transthoracic echocardiography (3D RT-VTTE) to measure left ventricular (LV) volumes and ejection fraction (EF) using a fully automated endocardial contouring algorithm and to identify and automatically correct the contours to obtain accurate LV volumes in sinus rhythm and atrial fibrillation (AF). BACKGROUND: 3D transthoracic echocardiography is not used routinely to quantify LV volumes and EF. A fully automated workflow using RT-VTTE may improve clinical adoption. METHODS: RT-VTTE was performed and 3D EF and volumes obtained using an automated trabecular endocardial contouring algorithm; an automated correction was applied to track the compacted myocardium. Cardiac magnetic resonance (CMR) and 2-dimensional biplane Simpson method were the reference standard. RESULTS: Ninety-one patients (67 in normal sinus rhythm [NSR], 24 in AF) were included. Among all NSR patients, there was excellent correlation between RT-VTTE and CMR for end-diastolic volume (EDV), end-systolic volume (ESV), and EF (r = 0.90, 0.96, and 0.98, respectively; p < 0.001). In patients with EF ≥50% (n = 36), EDV and ESV were underestimated by 10.7 ± 17.5 ml (p = 0.001) and by 4.1 ± 6.1 ml (p < 0.001), respectively. In those with EF <50% (n = 31), EDV and ESV were underestimated by 25.7 ± 32.7 ml (p < 0.001) and by 16.2 ± 24.0 ml (p = 0.001). Automated contour correction to track the compacted myocardium eliminated mean volume differences between RT-VTTE and CMR. In patients with AF, LV volumes and EF were accurate by RT-VTTE (r = 0.94, 0.94, and 0.91 for EDV, ESV, and EF, respectively; p < 0.001). Automated 3D LV volumes and EF were highly reproducible. CONCLUSIONS: Rapid, accurate, and reproducible EF can be obtained by RT-VTTE in NSR and AF patients by using an automated trabecular edge contouring algorithm. Furthermore, automated contour correction to detect the compacted myocardium yields accurate and reproducible 3D LV volumes.

Automated quantification of mitral inflow and aortic outflow stroke volumes by three-dimensional real-time volume color-flow Doppler transthoracic echocardiography: comparison with pulsed-wave Doppler and cardiac magnetic resonance imaging.

BACKGROUND: The aim of this study was to compare the feasibility, accuracy, and reproducibility of automated quantification of mitral inflow and aortic stroke volumes (SVs) using real-time three-dimensional volume color-flow Doppler transthoracic echocardiography (RT-VCFD), with cardiac magnetic resonance (CMR) imaging as the reference method. METHODS: In 44 patients (86% of the screened patients) without valvular disease, RT-VCFD, CMR left ventricular short-axis cines and aortic phase-contrast flow measurement and two-dimensional (2D) transthoracic echocardiography (TTE) were performed. Dedicated software was used to automatically measure mitral inflow and aortic SVs with RT-VCFD. CMR total SV was calculated using planimetry of short-axis slices and aortic SV by phase-contrast imaging. SVs by 2D TTE were computed in the conventional manner. RESULTS: The mean age of the included patients was 40 ± 16 years, and the mean left ventricular ejection fraction was 61 ± 9%. Automated flow measurements were feasible in all study patients. Mitral inflow SV by 2D TTE and RT-VCFD were 85.0 ± 21.5 and 94.5 ± 22.0 mL, respectively, while total SV by CMR was 95.6 ± 22.7 mL (P < .001, analysis of variance). On post hoc analysis, mitral inflow SV by RT-VCFD was not different from the CMR value (P = .99), while SV on 2D TTE was underestimated (P = .001). The respective aortic SVs were 82.8 ± 22.3, 94.2 ± 22.3, and 93.4 ± 24.6 mL (P < .001). On post hoc analysis, aortic SV by RT-VCFD was not different from the CMR value (P = .99), while SV on 2D TTE was underestimated (P = .006). The interobserver variability for SV measurements was significantly worse for 2D TTE compared with RT-VCFD. CONCLUSIONS: RT-VCFD imaging with an automated quantification algorithm is feasible, accurate, and reproducible for the measurement of mitral inflow and aortic SVs and is superior to manual 2D TTE-based measurements. The rapid and automated measurements make this technique practical in the clinical setting to measure and report SVs routinely where the acoustic window will allow it, which was 86% in our study.