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Purpose The present study aimed to explore the predictive ability of an ultrasound linear regression equation in patients undergoing endovascular stent placement (ESP) to treat carotid artery stenosis-induced ischemic stroke. Methods Pearson's correlation coefficient of actual improvement rate (IR) and 10 preoperative ultrasound indices in the carotid arteries of 64 patients who underwent ESP were retrospectively analyzed. A predictive ultrasound model for the fitted IR after ESP was established. Results Of the 10 preoperative ultrasound indices, peak systolic velocity (PSV) at stenosis was strongly correlated with postoperative actual IR (r = 0.622; P less then 0.01). The unstable plaque index (UPI; r = 0.447), peak eccentricity ratio (r = 0.431), and plaque stiffness index (β; r = 0.512) moderately correlated with actual IR (P less then 0.01). Furthermore, the resistance index (r = 0.325) and the dilation coefficient (r = 0.311) weakly correlated with actual IR (P less then 0.05). There was no significant correlation between actual IR and the number of unstable plaques, area narrowing, pulsatility index, and compliance coefficient. In combination, morphological, hemodynamic, and physiological ultrasound indices can predict 62.39% of neurological deficits after ESP fitted IR = 0.9816 - 0.1293β + 0.0504UPI - 0.1137PSV. Conclusion Certain carotid ultrasound indices correlate with ESP outcomes. The multi-index predictive model can be used to evaluate the effects of ESP before surgery.Aims Curved M-mode images of global strain (GS) and strain rate (GSR) provide sufficiently detailed spatiotemporal information of deformation mechanics. This study investigated whether a deep convolutional neural network (CNN) could accurately classify these images in patients with atrial fibrillation (AF) who underwent radiofrequency catheter ablation (RFCA) with different outcomes. Methods and Results We retrospectively evaluated 606 consecutive patients who underwent RFCA for drug-refractory AF. Patients were divided into AF-free (n = 443) and AF-recurrent (n = 163) groups. Transthoracic echocardiography was performed within 24 h after RFCA. Left atrial curved M-mode speckle-tracking images were acquired from randomly selected 163 patients in AF-free group and 163 patients in AF-recurrent group as the dataset for deep CNN modeling. We used the ReLu activation function and repeatedly performed CNN model for 32 times to evaluate the stability of hyperparameters. Logistic regression models with the left atrial dimension, emptying fraction, and peak systolic GS as predictor variables were used for comparisons. Images from the apical 2-chamber (2-C) and 4-chamber (4-C) views had distinct features, leading to different CNN performance between settings; of them, the "4-C GS+4-C GSR" setting provided the highest performance index values. All four predictor variables used for logistic regression modeling were significant; however, none of them, individually or in any combined form, could outperform the optimal CNN model. Conclusion The novel approach using deep CNNs for learning features of left atrial curved M-mode speckle-tracking images seems to be optimal for classifying outcome status after AF ablation.Background The effect of sacubitril/valsartan on survival and hospitalization risk in older patients with heart failure has not been explored. We aimed to investigate the risk of hospitalization and mortality with the use of sacubitril/valsartan vs. enalapril in patients with heart failure. Methods This was a population-based cohort study using the Hong Kong-wide electronic healthcare database. Patients diagnosed with heart failure and newly prescribed sacubitril/valsartan or enalapril between July 2016 and June 2019 were included. The risk of primary composite outcome of cardiovascular mortality or heart failure-related hospitalization, all-cause hospitalization, heart failure-related hospitalization, cardiovascular mortality and all-cause mortality were compared using Cox regression with inverse probability treatment weighting. Additional analysis was conducted by age stratification. Results Of the 44,503 patients who received sacubitril/valsartan or enalapril, 3,237 new users (sacubitril/valsartan, n = 1,056; enalapril, n = 2,181) with a diagnosis of heart failure were identified. Compared with enalapril, sacubitril/valsartan users were associated with a lower risk of primary composite outcome [hazard ratio (HR) 0.58; 95% confidence interval (CI), 0.45-0.75], heart failure-related hospitalization (HR 0.59; 95% CI, 0.45-0.77), all-cause mortality (HR 0.51; 95% CI, 0.36-0.74) and borderline non-significant reductions in all-cause hospitalization (HR 0.85; 95% CI, 0.70-1.04) and cardiovascular mortality (HR 0.63; 95% CI, 0.39-1.02). The treatment effect of sacubitril/valsartan remains unaltered in the patient subgroup age ≥ 65 years (73%). Conclusions In real-world settings, sacubitril/valsartan was associated with improved survival and reduced heart failure-related hospitalization compared to enalapril in Asian patients with heart failure. The effectiveness remains consistent in the older population.The coronavirus disease 2019 (COVID-19) pandemic has become a global threat. Increases in cardiac biomarkers are common and are associated with adverse outcomes in patients with COVID-19. Although these increases are more likely to occur in cases with concomitant cardiac disease, the differences in cardiac biomarker levels between patients with and without cardiac disease and their associations with in-hospital mortality are largely unknown. A consecutive serial of laboratory-confirmed COVID-19 cases was retrospectively enrolled. read more Clinical characteristics, laboratory results, and outcome data were collected. The levels of cardiac biomarkers were evaluated and compared by stratifying patients according to concomitant cardiac conditions and clinical classifications. The prognostic efficacy of cardiac biomarker levels on admission was also assessed. Among the overall study population and survived patients, the cardiac biomarker levels at both the early and late stages in cardiac patients were significantly higher than those in non-cardiac patients.
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