Heart valve disease (HVD) is one of the common cardiovascular diseases. Heart sound is an important physiological signal for diagnosing HVDs. This paper proposed a model based on combination of basic component features and envelope autocorrelation features to detect early HVDs. Initially, heart sound signals lasting 5 minutes were denoised by empirical mode decomposition (EMD) algorithm and segmented. Then the basic component features and envelope autocorrelation features of heart sound segments were extracted to construct heart sound feature set. Then the max-relevance and min-redundancy (MRMR) algorithm was utilized to select the optimal mixed feature subset. Finally, decision tree, support vector machine (SVM) and k-nearest neighbor (KNN) classifiers were trained to detect the early HVDs from the normal heart sounds and obtained the best accuracy of 99.9% in clinical database. Normal valve, abnormal semilunar valve and abnormal atrioventricular valve heart sounds were classified and the best accuracy was 99.8%. Moreover, normal valve, single-valve abnormal and multi-valve abnormal heart sounds were classified and the best accuracy was 98.2%. In public database, this method also obtained the good overall accuracy. The result demonstrated this proposed method had important value for the clinical diagnosis of early HVDs.
Objective To analyze the causal relationship between gut microbiota and tic disorder based on Mendelian randomization (MR). Methods A total of 196 known microbiota (9 phyla, 16 classes, 20 orders, 32 families, and 119 genera) in the human intestinal microbiota dataset downloaded from the MiBioGen database were selected as the exposure factors, and the dataset of tic disorder (finn-b-KRA_PSY_TIC) containing 172 patients and 218620 controls was downloaded from the genome-wide association study database as the outcome variable. Inverse variance weighted was used as the main analysis method, and the causal relationship between gut microbiota and tic disorder was evaluated using odds ratio (OR) and its 95% confidence interval (CI). Horizontal pleiotropy was tested by MR-Egger intercept and MR-PRESSO global test, heterogeneity was assessed by Cochran’s Q test, and sensitivity analysis was performed by leave-one-out method. Results Inverse variance weighted results showed that the Family Rhodospirillaceae [OR=0.398, 95%CI (0.191, 0.831), P=0.014], Order Rhodospirillales [OR=0.349, 95%CI (0.164, 0.743), P=0.006], and Parasutterella [OR=0.392, 95%CI (0.171, 0.898), P=0.027] had negative causal relationships with tic disorder. The Genus Lachnospira [OR=8.784, 95%CI (1.160, 66.496), P=0.035] and Candidatus Soleaferrea [OR=2.572, 95%CI (1.161, 5.695), P=0.020] had positive causal relationships with tic disorder. In addition, MR-Egger intercept and MR-PRESSO global test showed no horizontal pleiotropy, Cochran’s Q test showed no heterogeneity, and leave-one-out sensitivity analysis showed the results were stable. Conclusions A causal relationship exists between gut microbiota and tic disorder. The Family Rhodospirillaceae, Order Rhodospirillales, and Parasutterella are associated with a decreased risk of tic disorder, while the Genus Lachnospira and Candidatus Soleaverea can increase the risk of tic disorder.
Impedance cardiography (ICG) is essential in evaluating cardiac function in patients with cardiovascular diseases. Aiming at the problem that the measurement of ICG signal is easily disturbed by motion artifacts, this paper introduces a de-noising method based on two-step spectral ensemble empirical mode decomposition (EEMD) and canonical correlation analysis (CCA). Firstly, the first spectral EEMD-CCA was performed between ICG and motion signals, and electrocardiogram (ECG) and motion signals, respectively. The component with the strongest correlation coefficient was set to zero to suppress the main motion artifacts. Secondly, the obtained ECG and ICG signals were subjected to a second spectral EEMD-CCA for further denoising. Lastly, the ICG signal is reconstructed using these share components. The experiment was tested on 30 subjects, and the results showed that the quality of the ICG signal is greatly improved after using the proposed denoising method, which could support the subsequent diagnosis and analysis of cardiovascular diseases.
Objective Secondary osteoporosis is very common in patients with primary osteoporosis. Diabetes is a known cause of secondary osteoporosis. While type I diabetes has been clearly linked with diabetic osteoporosis, the effect of type II diabetes on bone health is controversial.Methods In the present study, we investigated the associations between type II diabetes and osteoporosis as well as fractures at different skeletal sites in Women’s Health Initiative participants.Results Common risk factors such as age, race, BMI, HRT use, and the history of fractures were significantly associated with osteoporosis and fractures in this study population. Diabetic women appeared to have a decreased risk of osteoporosis although it no longer remained significant after adjusting for other risk factors (crude HR=0.78, 95%CI 0.61 to 0.99; adjusted HR=0.93, 95%CI 0.73 to 1.19). The impact of diabetes on fractures varied at different body sites. There was a significant increase of risk of hip fracture (HR=2.54, 95%CI 1.14 to 5.66), but not spine fracture (HR=1.71, 95%CI 0.81 to 3.60) and arm fracture (HR=0.92, 95%CI 0.48 to 1.76) among the women with diabetes. Although the overall risk of fractures in diabetic women did not differ significantly from non-diabetic women (HR=1.37, 95%CI 0.89 to 2.09), the difference had a two-fold increase and was statistically significant after 2,000 days (HR=2.01, 95%CI 1.21 to 3.35), indicating a different hazard at different stages of diabetes.Conclusion Our findings suggest that type II diabetes may not be clearly associated with osteoporosis, it increases a site-specific fracture risk at least in the hip. In addition, the overall fracture risk appears to increase in a time-dependent manner.
ObjectiveTo investigate the correlation between graft maturity and knee function after anterior cruciate ligament (ACL) reconstruction.MethodsA total of 50 patients who underwent ACL reconstruction with autologous tendons between August 2016 and August 2018 were included in the study. There were 28 males and 22 females, with an average age of 31.0 years (range, 18-50 years). At 6 months and 2 years after operation, the signal to noise quotient (SNQ) values of tibial and femoral ends of graft were measured by MRI, and the mean value was taken as the SNQ value of graft. The function of knee joint was evaluated by Tegner, Lysholm, and International Knee Documentation Committee (IKDC) scores. The differences in SNQ values between tibial and femoral ends were analyzed at 6 months and 2 years after operation. The correlation between SNQ value at 6 months after operation and knee function score at 2 years after operation was analyzed. According to SNQ value at 6 months after operation, the patients were divided into group A (SNQ value≥12) and group B (SNQ value<12) and the correlation between SNQ value and knee function score was further analyzed.ResultsAll incisions healed primarily without infection or injury of blood vessels and nerves. All patients were followed up 24-28 months (mean, 26.6 months). The IKDC, Lysholm, and Tegner scores at 6 months and 2 years after operation were significantly higher than those before operation (P<0.05), and all scores at 2 years after operation were also significantly higher than those at 6 months (P<0.05). The SNQ values at 6 months and 2 years after operation were 12.517±6.272 and 10.900±6.012, respectively, and the difference was significant (t=1.838, P=0.007). The SNQ values of graft at 6 months after operation were significantly different from those at 2 years after operation (P<0.05), and the SNQ values of tibial and femoral ends of graft at the same time point were significantly different (P<0.05). The SNQ value of 50 patients at 6 months after operation was negatively correlated with Lysholm, IKDC, and Tegner scores at 2 years after operation (r=–0.965, P=0.000; r=–0.896, P=0.000; r=–0.475, P=0.003). The patients were divided into groups A and B according to the SNQ value, each with 25 cases; the SNQ values of the two groups at 6 months after operation were negatively correlated with Lysholm, IKDC, and Tegner scores at 2 years after operation (P<0.05).ConclusionAfter ACL reconstruction, the knee function scores and graft maturity of patients gradually improved. The lower the SNQ value in the early stage, the higher the knee function score in the later stage. The SNQ value of MRI in the early stage after ACL reconstruction can predict the knee function in the later stage.
Working memory is an important foundation for advanced cognitive function. The paper combines the spatiotemporal advantages of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to explore the neurovascular coupling mechanism of working memory. In the data analysis, the convolution matrix of time series of different trials in EEG data and hemodynamic response function (HRF) and the blood oxygen change matrix of fNIRS are extracted as the coupling characteristics. Then, canonical correlation analysis (CCA) is used to calculate the cross correlation between the two modal features. The results show that CCA algorithm can extract the similar change trend of related components between trials, and fNIRS activation of frontal pole region and dorsolateral prefrontal lobe are correlated with the delta, theta, and alpha rhythms of EEG data. This study reveals the mechanism of neurovascular coupling of working memory, and provides a new method for fusion of EEG data and fNIRS data.
To assess the rel iabil ity of diabetic cutaneous ulcer surface area (DCUSA) measurement usingdigital planimetry method (A) and transparency tracing method (B). Methods Images of diabetic cutaneous ulcers from35 inpatients with diabetic skin ulcers from September 2005 to April 2007 were taken by a digital camera once a week or twice a week over a period of 12 weeks, resulting in 305 photographs; the ulcers were traced on a grid with acetate wound tracings, simultaneously. A total of 305 pairs of DCUSA which were calculated respectively throughout digital camera combined with Image J medical imaging software and transparency tracing with grid sheet by two independent observers sequentially were obtained. The intraclass correlation coefficients (ICCs, one-way random effect model) was used as an indicator of chancecorrected agreement to estimate the relative rel iabil ity for the interobserver data. Multiple l inear regression analysis was also used to measure the relationship of these two methods. Results DCUSA obtained from method A and obtained from method B was (4.84 ± 7.73) cm2 and (5.03 ± 7.89) cm2, respectively; no significant difference was found (P gt; 0.05). ICCs was high (ICCs=0.949 for method B and 0.965 for method A), indicating that the relative rel iabil ity for the interobserver was excellent. The method A were highly correlated with measurements obtained from method B (r = 0.957, P lt; 0.05). Conclusion The digital planimetry method described in this study represents a simple, practical, without any wound damage and contamination, and inexpensive technique to accurately evaluate the areas of diabetic cutaneous ulcers. The photographic technique combined with Image J medical imaging software should be considered for wound measurement.
We proposed a multi-resolution-wavelet-transform based method to extract brainstem auditory evoked potential (BAEP) from the background noise and then to identify its characteristics correctly. Firstly we discussed the mother wavelet and wavelet transform algorithm and proved that bi-orthogonal wavelet bior5.5 and stationary discrete wavelet transform (SWT) were more suitable for BAEP signals. The correlation analysis of D6 scale wavelet coefficients between single trails and the ensemble average of all trails showed that the trails with good correlation (> 0.4) had higher signal-to-noise ratio, so that we could get a clear BAEP from a few trails by an average and wavelet filter method. Finally, we used this method to select desirable trails, extracted BAEP from every 10 trails and calculated theⅠ-Ⅴinter-waves' latency. The results showed that this strategy of trail selection was efficient. This method can not only achieve better de-noising effect, but also greatly reduce the stimulation time needed as well.
摘要:目的: 研究尿微量白蛋白与冠心病的相关性。 方法 : 按冠状动脉造影诊断标准将116例患者分为冠心病组(82人) 与非冠心病组(34人),测定晨尿白蛋白/ 肌酐浓度值(ACR),比较两组患者尿ACR 并分析ACR与冠脉病变程度的相关性。 结果 : 冠心病组ACR显著高于非冠心病组的; ACR与冠脉计分呈显著的直线正相关。 结论 :冠心病患者ACR水平升高,微量白蛋白尿与冠状动脉病变范围和程度密切相关, 且对冠状动脉狭窄程度具有独立预测价值。Abstract: Objective: To investigate the relationship between microalbuminuria and coronary artery disease(CAD). Methods : According to the diagnostic standard of coronary artery angiography,116 patients were divided into CAD group (82 patients) and nonCAD group (34 patients). The albumin and creatinine concentrationratio ratio(ACR) in morning urine samples from patients of both groups was estimated and compared. The correlation of ACR to the extent of coronary lesions was analyzed. Results : ACR in the CAD group was significantly higher than that in nonCAD group. A distinctly linear positive correlation existed between ACR and the score of the coronary lesions. Conclusion : ACR increase in patients with CHD.Micoalbuminuria was associated with the severity of coronary lesions in patients with CHD and is an independent predictor of CAD.
Objective To investigate the pleural effusion lymphocyte subsets in patients with pneumonia complicated with pleural effusion and its relationship with the occurrence of critical illness. MethodsPatients with pneumonia complicated with pleural effusion (246 cases) admitted to our hospital from January 2020 to June 2022 were selected as the research subjects. According to the severity of pneumonia, they were divided into a critical group (n=150) and a non-critical group (n=96). After 1:1 matching by propensity score matching method, there were 60 cases in each group. The general data of the two groups were compared. CD3+, CD4+, CD8+, CD4+/CD8+ ratio were detected by flow cytometry. Multivariate logistic regression was used to analyze the risk factors of critical pneumonia, and a nomogram prediction model was constructed and evaluated. The relationship between PSI score and lymphocyte subsets in pleural effusion was analyzed by local weighted regression scatter smoothing (LOWESS). Results After matching, the differences between the two groups of patients in the course of disease, heat peak, heat course, atelectasis, peripheral white blood cell count (WBC), C-reactive protein (CRP), D-dimer (D-D), procalcitonin (PCT) and hemoglobin were statistically significant (P<0.05). Compared with the non-critical group, the proportion of CD3+, CD4+, CD4+/CD8+ cells in critical group was lower (P<0.05), and the proportion of CD8+ cells was higher (P<0.05). Combined atelectasis, increased course of disease, fever peak and fever course, increased WBC, CRP, D-D, CD8+ and PCT levels, and decreased CD3+, CD4+, CD4+/CD8+ and Hb levels were independent risk factors for the occurrence of critical pneumonia (P<0.05). The nomogram prediction model based on independent influencing factors had high discrimination, accuracy and clinical applicability. There was a certain nonlinear relationship between pneomonia severity index and CD3+, CD4+, CD8+ and CD4+/CD8+. Conclusions Lymphocyte subsets in pleural effusion are closely related to the severity of pneumonia complicated with pleural effusion. If CD3+, CD4+, CD8+ and CD4+/CD8+ are abnormal, attention should be paid to the occurrence of severe pneumonia.