The peak period of cardiovascular disease (CVD) is around the time of awakening in the morning, which may be related to the surge of sympathetic activity at the end of nocturnal sleep. This paper chose 140 participants as study object, 70 of which had occurred CVD events while the rest hadn’t during a two-year follow-up period. A two-layer model was proposed to investigate whether hypnopompic heart rate variability (HRV) was informative to distinguish these two types of participants. In the proposed model, the extreme gradient boosting algorithm (XGBoost) was used to construct a classifier in the first layer. By evaluating the feature importance of the classifier, those features with larger importance were fed into the second layer to construct the final classifier. Three machine learning algorithms, i.e., XGBoost, random forest and support vector machine were employed and compared in the second layer to find out which one can achieve the highest performance. The results showed that, with the analysis of hypnopompic HRV, the XGBoost+XGBoost model achieved the best performance with an accuracy of 84.3%. Compared with conventional time-domain and frequency-domain features, those features derived from nonlinear dynamic analysis were more important to the model. Especially, modified permutation entropy at scale 1 and sample entropy at scale 3 were relatively important. This study might have significance for the prevention and diagnosis of CVD, as well as for the design of CVD-risk assessment system.
Objective To propose an innovative self-supervised learning method for vascular segmentation in computed tomography angiography (CTA) images by integrating feature reconstruction with masked autoencoding. Methods A 3D masked autoencoder-based framework was developed, where in 3D histogram of oriented gradients (HOG) was utilized for multi-scale vascular feature extraction. During pre-training, random masking was applied to local patches of CTA images, and the model was trained to jointly reconstruct original voxels and HOG features of masked regions. The pre-trained model was further fine-tuned on two annotated datasets for clinical-level vessel segmentation. Results Evaluated on two independent datasets (30 labeled CTA images each), our method achieved superior segmentation accuracy to the supervised neural network U-Net (nnU-Net) baseline, with Dice similarity coefficients of 91.2% vs. 89.7% (aorta) and 84.8% vs. 83.2% (coronary arteries). Conclusion The proposed self-supervised model significantly reduces manual annotation costs without compromising segmentation precision, showing substantial potential for enhancing clinical workflows in vascular disease management.
To solve the complex interaction problems of hepatitis disease classification, we proposed a lasso method (least absolute shrinkage and selection operator method) with feature interaction. First, lasso penalized function and hierarchical convex constraint were added to the interactive model which is newly defined. Then the model was solved with the convex optimal method combining Karush-Kuhn-Tucker (KKT) condition with generalized gradient descent. Finally, the sparse solution of the main effect features and interactive features were derived, and the classification model was implemented. The experiments were performed on two liver data sets and proved that features interaction contributed to the classification of liver diseases. The experimental results showed that the feature interaction lasso method was of strong explanatory ability, and its effectiveness and efficiency were superior to those of lasso, of all pair-wise lasso, support vector machine (SVM) method, K nearest neighbor (KNN) method, linear discriminant analysis (LDA) classification method, etc.
ObjectiveTo investigate the value of proton magnetic resonance spectroscopy (1H-MRS), gradient dual-echo, and triple-echo sequences in the quantitative evaluation of treatment effect of fatty liver at 3.0T MR.MethodsThirty patients with fatty liver diagnosed by CT or ultrasound who admitted in Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital between August 2017 and May 2018, were enrolled and undergone gradient dual-echo, triple-echo, and 1H-MRS examination before and 3 months after treatment. The fat index (FI) and relative lipid content (RLC) were measured. Fatty liver index (FLI) was calculated from blood biochemical indicators, waist circumference, and BMI at the same time. With the reference standard of FLI, the results before and after treatment measured from MRI were analyzed.ResultsThere were significantly differences of FLI, FIdual, FItriple, and RLC before and after treatment (t=5.281, P<0.001; Z=–3.651, P<0.001; Z=–3.630, P<0.001; Z=–4.762, P<0.001), all indexes decreased after treatment. FIdual and FItriple were positively correlated with FLI before (rs=0.413, P=0.023; rs=0.396, P=0.030) and after treatment (rs=0.395, P=0.031; rs=0.519, P=0.003), the highest correlation factor was FItriple to FLI after treatment. There were no significant correlation between RLC and FLI before and after treatment (P>0.05).ConclusionsIt is feasible to quantitatively evaluate the treatment effect of fatty liver by using 1H-MRS, gradient dual-echo, and triple-echo sequences. Gradient triple-echo sequences has better accuracy, which is technically easy to implement and more suitable for clinical development.
Aiming at the problems of obscure clinical auscultation features of pulmonary hypertension associated with congenital heart disease and the complexity of existing machine-aided diagnostic algorithms, an algorithm based on the statistical characteristics of the high-frequency components of the second heart sound signal is proposed. Firstly, an endpoint detection adaptive segmentation method is employed to extract the second heart sounds. Subsequently, the high-frequency component of the heart sound is decomposed using the discrete wavelet transform. Statistical features including the Hurst exponent, Lempel-Ziv information and sample entropy are extracted from this component. Finally, the extracted features are utilized to train an extreme gradient boosting algorithm (XGBoost) classifier, which achieves an accuracy of 80.45% in triple classification. Notably, this method eliminates the need for a noise reduction algorithm, allows for swift feature extraction, and achieves effective multi-classification using only three features. It is promising for early screening of pulmonary hypertension associated with congenital heart disease.
ObjectivesTo investigate simple assess method of the degree of low transvalvular gradient aortic stenosis patients with impaired left ventricular function and to investigate aortic valve replacement indications, short and mid-term outcome of this kind of patients. MethodsWe retrospectively analyzed the clinical data of 21 low-gradient patients with impaired left ventricular function in our hospital from January 2011 through May 2014. There were 15 males and 6 females aged 41-66 (54.6± 10.7) years with mean aortic transvalvular gradient less than 40 mm Hg and left ventricular ejection fraction (LVEF) less than 50%. ResultsIn response to dobutamine echocardiography stress test, 20 patients underwent aortic valve replacement. The result of intraoperative pathology showed 11 patients were with bicuspid aortic valve malformation, 4 patients with degenerative changes, 4 patients with rheumatic disease. During the same period, 3 patients underwent atrial fibrillation ablation, 1 patient with ascending aorta replacement, 2 patients with coronary artery bypass grafting, 1 patient with mitral valvuloplasty. One patient died of multiple organ failure on the fourth day after operation. The remaining patients recovered. The patients were followed up for 3 to 37 months after operation. Heart function of majority improved to gradeⅠorⅡin 3 months after surgery. The result of echocardiogram showed prosthetic valve function was good and LVEF increased (preoperative 35.7%± 8.2% vs. postoperative 49.4%± 7.2%). One patient suffered sudden death of unknown cause in the 11th months after operation. ConclusionsFor patients whose dobutamine echocardiography stress test displayed with true severe aortic stenosis and left ventricular contractile reserve capacity, after aortic valve replacement and relief of the obstruction, the left ventricular afterload decreases significantly, the left ventricular function also improves, LVEF and the quality of life improve significantly after operation.
Objective To observe the midterm haemodynamic manifestation of the home made C-L pugestrut tilting disc mechanical valve in aortic valve replacement, and to evaluate its function. Methods Twenty patients underwent aortic valve replacement over 5 years were collected and divided into two groups, the C-L pugestrut group （n=10）：aortic valve was replaced by home-made C-L pugestrut tilting disc mechanical valve（21mm）; Medtronic-Hall group （n=10）：aortic valve was replaced by Medtronic-Hall mechanical valve （21mm）. The peak transprosthetic gradients （△P）, mean transprosthetic gradients （△Pm）and effective orifice area（EOA） at rest were compared between two groups. Results At rest, △P of the C-L pugestrut group and Medtronic-Hall group were 11.63±3.23mmHg vs. 9. 78±3. 35mmHg; △Pm of the C-L pugestrut group and Medtronic-Hall group were 6. 25±2. 32 mmHg vs. 5.85±2.32mmHg： EOA of the C-L pugestrut group and Medtronic-Hall group were 1.07±0.17 cm2 vs. 1.25±0.27 cm2. There was no statistically significance in △P, △Pm and EOA between two groups（P〉0.05）. Conclusions The midterm haemodynamic results of the home-made C-L pugestrut tilting disc mechanical valve show that it has comparable haemodynamic results to those of Medtronic-Hall mechanical valve ,and it has well-done function. The home-made C-L pugestrut valve is one of the reliable mechanical heart valves.
ObjectiveTo investigate the perioperative hemodynamic changes of off-pump coronary artery bypass grafting (OPCABG) patients monitored by pulse recorded analysis method (MostCare/PRAM devices) and its relationship with the prognosis.MethodsA total of 89 patients who underwent OPCABG from October 2016 to January 2017 in Beiijng Anzhen Hospital were included, including 53 males and 36 females aged 60.50±8.40 years. The hemodynamic changes were recorded. The patients were divided into two groups (a major adverse cardiovascular events group and a stable group) according to whether major adverse cardiovascular events occurred or not. The difference of hemodynamic changes between the two groups was analysed.ResultsThe mean percentage increases of stroke volume (SV) in the passive leg raising (PLR) test before opening chest and after chest closure were 23.00%±3.20% and 29.40%±3.70%, respectively. Hemodynamic data were analysed seven times, namely, anaesthesia, opening chest, heparin administration, coronary artery bypass grafting, protamine administration, thoracic closure and after operation. SV was significantly decreased during above periods, while systemic vascular resistance index (SVRI) was significantlyincreased. Cardiac circle efficiency (CCE) and maximum pressure gradient (dP/dT) were decreased after anaesthesia, and decreased to the lowest value during the procedure of bypass grafting, and then they began to increase gradually after the manipulation of bypass grafting was finished. Stroke volume variation (SVV) and pulse pressure variation (PPV) were slightly decreased during anaesthesia, then increased significantly through the whole surgery. Major adverse cardiovascular events occurred in 9 patients and 4 of them died. The basic mean values of SVRI, SVV and PPV of patients in the major adverse cardiovascular events group before opening chest were significantly higher than those of patients in the stable group. There was no significant difference in the mean values of CCE, dP/dT or SV between the two groups. There was no significant correlation between the prognosis and the mean values of SVRI, SVV, PPV, CCE, dP/dT or SV.ConclusionThe hemodynamic indexes are not stable, thus, it is necessary to monitor the perioperative hemodynamic changes of OPCABG patients timely by MostCare/PRAM device and adjust treatment measures accordingly.
Objective To study the effect of local appl ication of different concentrations of nerve growth factor (NGF) on fracture heal ing, and to further search for the appropriate concentration gradient of NGF to promote fracture heal ing. Methods Seventy-five adult male Sprague Dawley rats, weighing (220.0 ± 2.5) g, were made the right tibia fracture model at 1 cm distal from the tibial tubercle and randomly divided into 5 groups (groups A, B, C, D, and E, n=15). Fractures were treated with 0.3 mL normal sal ine containing different concentration of NGF (0.006 48 × 10-2, 0.032 40 × 10-2, 0.162 00 ×10-2, and 0.810 00 × 10-2 μg/g) in groups A, B, C, and D, respectively, and the same amount of normal sal ine in group E. After2, 4, and 6 weeks, the specimens were harvested from 5 rats of each group to perform the biochemical test and histological observation. Before the rats were sacrificed, the arteriovenous blood was taken from the eye-ball to test the alkal ine phosphatase (ALP) activity. Results After 2, 4, and 6 weeks, the gross observation showed that the size and hardness of bone tissue and callus tissue growth gradually increased in groups A, B, C, and D, and group D was higher than groups A, B, C, and E. The X-ray films showed that the calcified area gradually increased in groups A, B, C, and D, and group D was higher than groups A, B, C, and E. The histological observation showed that the trabecular qual ity and maturity in group D were better than those in groups A, B, C, and E. Group D was significantly higher than groups A, B, C, and E (P lt; 0.05) in the gray values of callus tissue and the calcium content of callus tissue at 4 and 6 weeks, in the wet weight of callus tissue at 2 and 4 weeks, and in the ALP content of serum at 2 weeks. The trabecula surface index of osteoblast, the trabecular volume, and the trabecular width decreased as time in the order of groups A, B, C, and D, which were higher than those of group E; group D was the highest, showing significant differences when compared with the other groups (P lt; 0.05). Conclusion The local appl ication of NGF can promote fracture heal ing in rats. The high concentration gradient of NGF (0.810 00 × 10-2 μg/g) has an obvious promotion role on fracture heal ing.
For speech detection in Parkinson’s patients, we proposed a method based on time-frequency domain gradient statistics to analyze speech disorders of Parkinson’s patients. In this method, speech signal was first converted to time-frequency domain (time-frequency representation). In the process, the speech signal was divided into frames. Through calculation, each frame was Fourier transformed to obtain the energy spectrum, which was mapped to the image space for visualization. Secondly, deviations values of each energy data on time axis and frequency axis was counted. According to deviations values, the gradient statistical features were used to show the abrupt changes of energy value in different time-domains and frequency-domains. Finally, KNN classifier was applied to classify the extracted gradient statistical features. In this paper, experiments on different speech datasets of Parkinson’s patients showed that the gradient statistical features extracted in this paper had stronger clustering in classification. Compared with the classification results based on traditional features and deep learning features, the gradient statistical features extracted in this paper were better in classification accuracy, specificity and sensitivity. The experimental results show that the gradient statistical features proposed in this paper are feasible in speech classification diagnosis of Parkinson’s patients.