Objective To understand the new characteristics of clinical symptoms of patients with mild COVID-19 during the prevalence of SARS-CoV-2 Omicron, and provide basis for better prevention and treatment of COVID-19.Methods A cross-sectional retrospective study was conducted with WeChat questionnaire among medical staff with COVID-19 recently, who come from the Third Affiliated Hospital of Chongqing Medical University and The Second Affiliated Hospital of Army Medical University.Results A total of 630 valid questionnaires was received. 99.2% of infected people had been vaccinated against COVID-19. 2.4% of infected persons developed pneumonia and 2.1% were hospitalized. The most common symptoms after infection were coughing (89.7%), fever (83.0%), fatigue (84.1%), headache and dizziness (75.7%), muscle soreness (72.7%), sore throat (62.1%), nasal congestion and runny nose (60.6%), expectoration (71.6%), anorexia (58.0%) and taste loss (40.2%). The incidence of gastrointestinal symptoms and cardiovascular symptoms was relatively low (17.8% and 31.0% respectively). The severity of self-reported symptoms of most infected persons was moderate or severe. The proportion of serious symptoms reported was coughing (23.8%), sore throat (27.0%), headache and dizziness (17.9%). The severity of symptoms reported by young group (<35 years old) was significantly higher than that of older group (>35 years old). Fever was the highest at 38 to 39 ℃ (52.4%). 77.0% of fever sustained for 1 to 3 days. At the time of investigation, the viral detection turned negative in 60.6% of infected people, and the time of turning negative was mostly 7 to 10 days. More than half of the infected persons still had different symptoms, among which cough (43.7%) and fatigue (23.8%) were the most common.Conclusions Most subjects with mild COVID-19 infection have obvious upper respiratory tract and systemic symptoms, the most prominent is the high incidence of cough, which has become a new feature of omicron infection. And most of the infected people have moderate to severe symptoms, and the younger ones have more severer symptoms.
With the wide application of deep learning technology in disease diagnosis, especially the outstanding performance of convolutional neural network (CNN) in computer vision and image processing, more and more studies have proposed to use this algorithm to achieve the classification of Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal cognition (CN). This article systematically reviews the application progress of several classic convolutional neural network models in brain image analysis and diagnosis at different stages of Alzheimer’s disease, and discusses the existing problems and gives the possible development directions in order to provide some references.
Objective To investigate effect of metabolic surgery on type 2 diabetes mellitus (T2DM) patients with body mass index (BMI) 27.5–32.5 kg/m2. Methods The clinical data of 43 T2DM patients with BMI 27.5–32.5 kg/m2 underwent metabolic surgery from October 2014 to October 2016 in the Third Xiangya Hospital of Central South University were analyzed retrospectively. The related indexes such as BMI, blood glucose level, blood lipid level were analyzed before and after metabolic surgery. Results All the patients underwent metabolic surgery successfully. Among them, 35 cases underwent laparoscopic gastric bypass surgery while 8 cases underwent laparoscopic sleeve gastrectomy without related complications after operation. Compared with preoperative indexes, the BMI, fasting blood glucose, HbA1c, triglyceride, and total cholesterol on the postoperative different time were all significantly decreased (P<0.05) except for the HbA1c on the postoperative 1-week, the high density lipoprotein level on the postoperative 12-month was significantly increased (P<0.05). The OGTT 30, 60, and 120 min blood glucose levels on the postoperative 1-week and 3-month, and 60 and 120 min blood glucose levels on the postoperative 6-month and 12-month were all significantly decreased (P<0.05). The OGTT-IRT 60 min insulin level on the postoperative 3-month and the 30 min insulin levels on the postoperative 6- and 12-month were all significantly increased (P<0.05). The levels of OGTT-CRT 30 and 60 min C peptide on the postoperative 6-month and the level of 30 min C peptide on the postoperative 12-month were all significantly increased (P<0.05). Conclusions Metabolic surgery is effective in treatment of T2DM patients with BMI 27.5–32.5 kg/m2, and levels of blood glucose and blood lipids can be improved significantly. Synthesis and release of insulin by islet cells can be ameliorated.
Objective To explore the therapeutic effect of mild hypothermia on the inflammatory response, organ function and outcome in perioperative patients with acute Stanford type A aortic dissection (AAAD). Methods From February 2017 to February 2018, 56 patients with AAAD admitted in our department were enrolled and randomly allocated into two groups including a control group and an experimental group. After deep hypothermia circulatory arrest during operation, in the control group (n=28), the patients were rewarmed to normal body temperatures (36 to 37 centigrade degree), and which would be maintained for 24 hours after operation. While in the experimental group (n=28), the patients were rewarmed to mild hypothermia (34 to 35 centigrade degree), and the rest steps were the same to the control group. The thoracic drainage volume and the incidence of shivering at the first 24 hours after operation, inflammatory indicators and organ function during perioperation, and outcomes were compared between the two groups. There were 20 males and 8 females at age of 51.5±8.7 years in the control group, 24 males and 4 females at age of 53.3±11.2 years in the experimental group.Results There was no obvious difference in the basic information and operation information in patients between the two groups. Compared to the control group, at the 24th hour after operation, the level of peripheral blood matrix metalloproteinases (MMPs) was lower than that in the experimental group (P=0.008). In the experimental group, after operation, the awakening time was much shorter (P=0.008), the incidence of bloodstream infection was much lower (P=0.019). While the incidence of delirium, acute kidney injury (AKI), hepatic insufficiency, mechanical ventilation duration, intensive care unit (ICU) stays, or hospital mortality rate showed no statistical difference. And at the first 24 hours after operation, there was no difference in the thoracic drainage volume between the two groups, and no patient suffered from shivering. Conclusion The mild hypothermia therapy is able to shorten the awakening time and reduce the incidence of bloodstream infection after operation in the patients with AAAD, and does not cause the increase of thoracic drainage volume or shivering.
Normal brain aging and a serious of neurodegenerative diseases may lead to decline in memory, attention and executive ability and poorer quality of life. The mechanism of the decline is not clear now and is still a hot issue in the fields of neuroscience and medicine. A large number of researches showed that resting state functional brain networks based functional magnetic resonance imaging (fMRI) are sensitive and susceptive to the change of cognitive function. In this paper, the researches of brain functional connectivity based on resting fMRI in recent years were compared, and the results of subjects with different levels of cognitive decline including normal brain aging, mild cognitive impairment (MCI) and Alzheimer’s disease (AD) were reviewed. And the changes of brain functional networks under three different levels of cognitive decline are introduced in this paper, which will provide the basis for the detection of normal brain aging and clinical diseases.
The cognitive impairment of type 2 diabetes patients caused by long-term metabolic disorders has been the current focus of attention. In order to find the related electroencephalogram (EEG) characteristics to the mild cognitive impairment (MCI) of diabetes patients, this study analyses the EEG synchronization with the method of multi-channel synchronization analysis--S estimator based on phase synchronization. The results showed that the S estimator values in each frequency band of diabetes patients with MCI were almost lower than that of control group. Especially, the S estimator values decreased significantly in the delta and alpha band, which indicated the EEG synchronization decrease. The MoCA scores and S value had a significant positive correlation in alpha band.
Alzheimer's disease (AD) is a typical neurodegenerative disease, which is clinically manifested as amnesia, loss of language ability and self-care ability, and so on. So far, the cause of the disease has still been unclear and the course of the disease is irreversible, and there has been no cure for the disease yet. Hence, early prognosis of AD is important for the development of new drugs and measures to slow the progression of the disease. Mild cognitive impairment (MCI) is a state between AD and healthy controls (HC). Studies have shown that patients with MCI are more likely to develop AD than those without MCI. Therefore, accurate screening of MCI patients has become one of the research hotspots of early prognosis of AD. With the rapid development of neuroimaging techniques and deep learning, more and more researchers employ deep learning methods to analyze brain neuroimaging images, such as magnetic resonance imaging (MRI), for early prognosis of AD. Hence, in this paper, a three-dimensional multi-slice classifiers ensemble based on convolutional neural network (CNN) and ensemble learning for early prognosis of AD has been proposed. Compared with the CNN classification model based on a single slice, the proposed classifiers ensemble based on multiple two-dimensional slices from three dimensions could use more effective information contained in MRI to improve classification accuracy and stability in a parallel computing mode.
Objective To analyze the aortic development in patients with mild coarctation of the aorta (CoA) and ventricular septal defect (VSD) after isolated VSD repair and to explore the risk factors affecting postoperative aortic development. Methods A retrospective analysis was conducted on the clinical data of 4231 patients who underwent VSD repair at Guangdong Provincial People’s Hospital from January 2018 to August 2023. Patients with mild CoA were selected as the study subjects. Based on whether CoA progressed postoperatively, patients were divided into a progression group and a non-progression group. Univariate and multivariate analyses were performed, and a logistic regression model was established to analyze the factors affecting postoperative aortic development. Results A total of 231 patients were included, with 142 males and 89 females, and a median age of 223 (105, 635) days. Among the 231 patients, 30 showed varying degrees of mild CoA progression during postoperative follow-up, with an incidence rate of 13.0%. Multivariate logistic regression analysis revealed that higher preoperative pulmonary artery pressure [OR=2.053, 95%CI (1.095, 3.850), P=0.025] and larger VSD [OR=20.200, 95%CI (1.614, 254.440), P=0.020] were risk factors for postoperative CoA progression. Conclusion Most patients with mild CoA and VSD exhibited varying degrees of catch-up growth in the aorta postoperatively. Higher preoperative pulmonary artery pressure and larger VSD size are influencing factors for postoperative CoA progression, necessitating more cautious surgical strategies and closer follow-up for this subset of patients.
This study uses mind-control game training to intervene in patients with mild cognitive impairment to improve their cognitive function. In this study, electroencephalogram (EEG) data of 40 participants were collected before and after two training sessions. The continuous complexity of EEG signals was analyzed to assess the status of cognitive function and explore the effect of mind-control game training on the improvement of cognitive function. The results showed that after two training sessions, the continuous complexity of EEG signal of the subject increased (0.012 44 ± 0.000 29, P < 0.05) and amplitude of curve fluctuation decreased gradually, indicating that with increase of training times, the continuous complexity increased significantly, the cognitive function of brain improved significantly and state was stable. The results of this paper may show that mind-control game training can improve the status of the brain cognitive function, which may provide support and help for the future intervention of cognitive dysfunction.
We in the present research proposed a classification method that applied infomax independent component analysis (ICA) to respectively extract single modality features of structural magnetic resonance imaging (sMRI) and positron emission tomography (PET). And then we combined these two features by using a method of weight combination. We found that the present method was able to improve the accurate diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Compared AD to healthy controls (HC): the study achieved a classification accuracy of 93.75%, with a sensitivity of 100% and a specificity of 87.64%. Compared MCI to HC: classification accuracy was 89.35%, with a sensitivity of 81.85% and a specificity of 99.36%. The experimental results showed that the bi-modality method performed better than the individual modality in comparison to classification accuracy.