The effect of micronutrients on pressure ulcer was reviewed.Nutritional treatment is helpful to prevent and cure the pressure ulcer.Especially micronutrients should be paid more attention to.

Objective:To investigate the effect of instantaneous flow rate on the consistency of diagnostic accuracy of severe degenerative mitral regurgitation (DMR) using proximal isovelocity surface area (PISA).Methods:From June 2019 to June 2021, 75 patients with DMR who underwent echocardiography in Department of Echocardiography of Zhongshan Hospital, Fudan University were prospectively enrolled. The instantaneous flow rate of DMR during the systolic phase was calculated using M-mode PISA(PISA M-mode), and a time-integrated curve was plotted. Regurgitant volume (RVol) and effective regurgitant orifice area (EROA) were calculated by traditional PISA (PISA max), pair PISA (PISA pair), and PISA M-mode, respectively. RVol acquired from cardiac magnetic resonance (CMR) volumetric method in 22 patients of the enrolled patients. The correlation and consistency of RVol acquired between the three PISA methods and CMR were compared. Agreement of diagnostic accuracy of severe mitral regurgitation (sMR) acquired between the three PISA methods and multi-parameter algorithm by American Society of Echocardiography (ASE) was analyzed using Cohen′s Kappa analysis. Results:The curve of instantaneous flow rate of DMR showed unimodal pattern with the peak at mid-late systolic phase. The correlation of RVol acquired between PISA methods and CMR was moderate for PISA max and PISA pair ( r=0.77, 0.80, both P<0.001), whereas PISA M-mode presented strong correlation with CMR ( r=0.87, P<0.001). RVol acquired from PISA max was larger than that of CMR[(69.1±37.1) ml vs (49.0±29.0)ml, P=0.002]. Both PISA max and PISA pair were shown moderate agreement of diagnostic accuracy of sMR with ASE multi-parameters algorithm (RVol: κ=0.496, 0.525, both P<0.001; EROA: κ=0.570, 0.578, both P<0.001), while PISA M-mode presented strong agreement (RVol: κ=0.867 and EROA: κ=0.802, both P<0.001). Conclusions:Based on the unimodal pattern of instantaneous flow rate in patients with DMR, PISA max may significantly overestimate RVol, exposing a significant proportion of patients with DMR to unnecessary MR surgery. PISA M-mode presents better correlation and consistency with CMR on the quantification of RVol compared with PISA max and PISA pair, and may improve the diagnostic accuracy of quantification of sMR using PISA.

The finite element method is a new method to study the mechanism of brain injury caused by blunt instruments. But it is not easy to be applied because of its technology barrier of time-consuming and strong professionalism. In this study, a rapid and quantitative evaluation method was investigated to analyze the craniocerebral injury induced by blunt sticks based on convolutional neural network and finite element method. The velocity curve of stick struck and the maximum principal strain of brain tissue (cerebrum, corpus callosum, cerebellum and brainstem) from the finite element simulation were used as the input and output parameters of the convolutional neural network The convolutional neural network was trained and optimized by using the 10-fold cross-validation method. The Mean Absolute Error (MAE), Mean Square Error (MSE), and Goodness of Fit ( R ²) of the finally selected convolutional neural network model for the prediction of the maximum principal strain of the cerebrum were 0.084, 0.014, and 0.92, respectively. The predicted results of the maximum principal strain of the corpus callosum were 0.062, 0.007, 0.90, respectively. The predicted results of the maximum principal strain of the cerebellum and brainstem were 0.075, 0.011, and 0.94, respectively. These results show that the research and development of the deep convolutional neural network can quickly and accurately assess the local brain injury caused by the sticks blow, and have important application value for understanding the quantitative evaluation and the brain injury caused by the sticks struck. At the same time, this technology improves the computational efficiency and can provide a basis reference for transforming the current acceleration-based brain injury research into a focus on local brain injury research.
Brain ; Brain Injuries ; Computer Simulation ; Finite Element Analysis ; Humans ; Neural Networks, Computer

Objective To evaluate the diagnostic value of myocardial work related parameters in coronary ischemia patients with coronary artery disease (CAD) coronary ischemia using non-invasive left ventricular pressure strain loop (PSL), taking fraction flow reservation (FFR) as the gold standard. Methods From December 2020 to December 2021, 53 clinically suspected CAD patients were prospectively enrolled. All patients underwent echocardiography, invasive coronary angiography and FFR measurement. According to the results of coronary angiography, patients were divided into myocardial ischemia group (n=24, FFR≤0.80) and non-myocardial ischemia group (n=29, FFR＞0.80). PSL was used for off-line analysis to obtain the global work index (GWI), global constructive work (GCW), global wasted work (GWW), global work efficiency (GWE) , global positive work( GPW) , and global systolic constructive work (GSCW) and other myocardial work parameters. The differences of parameter values between the two groups were compared. The diagnostic efficacy of work parameters in myocardial ischemia was analyzed by ROC curve. Results Compared with the non-myocardial ischemia group, GWI, GCW, GPW and GSCW were significantly decreased in the myocardial ischemia group at the 18-, 16-, and 12-segment levels (P＜0.001). The ROC curve showed that the AUC results of GWI, GCW, GPW, GSCW at the 18-segment level were 0.803(95%CI 0.679-0.927), 0.807(95%CI 0.687-0.928), 0.822(95%CI 0.708-0.936), 0.819(95%CI 0.703-0.935). The optimal cut-off value of GWI was 1 676.3 mmHg%, and the sensitivity, specificity and accuracy of predicting myocardial ischemia were 70.8%, 86.2% and 79.2%, respectively. The optimal cut-off value of GCW was 1 999.4 mmHg%, and the sensitivity, specificity and accuracy of predicting myocardial ischemia were 75.0%, 82.8% and 79.2%, respectively. Conclusions Analyzing myocardial work using PSL has good significance for screening suspected myocardial ischemia in CAD patients.